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Spatial Modelling of the Haida Gwaii Ecosystem : Contributions to Haida Gwaii Marine Spatial Planning Pitcher, Tony J.; Kumar, Rajeev; Lam, Mimi E.; Surma, Szymon; Varkey, Divya 2016

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	ISSN 1198-6727 Fisheries Centre Research Reports 2016   Volume 24   Number  1   Spatial Modelling of the Haida Gwaii Ecosystem: Contributions to  Haida Gwaii  Marine Spatial Planning      Institute for the Oceans and Fisheries,  University of British Columbia, Canada SPATIAL	MODELLING	IN	HAIDA	GWAII		 2		 	HAIDA	GWAII	ECOSYSTEM	MODEL			 3	Spatial	Modelling	of	the	Haida	Gwaii	Ecosystem:		Contributions	to	Haida	Gwaii		Marine	Spatial	Planning			Tony	J.	Pitcher,	Rajeev	Kumar,	Mimi	E.	Lam,		Szymon	Surma	and	Divya	Varkey		Institute	for	the	Oceans	and	Fisheries,	UBC			Coastal	section	of	Haida	Gwaii	waters	from	Google	Earth		Please	cite	as:			Pitcher,	T.J.,	 Kumar,	R.,	 Lam,	M.E.,	 Surma,	 S.	 and	Varkey,	D.	 (2016)	 Spatial	Modelling	of	 the	Haida	Gwaii	Ecosystem:	Contributions	to	Haida	Gwaii	Marine	Spatial	Planning.	Fisheries	Centre	Research	Reports	24	(1):	79pp.	SPATIAL	MODELLING	IN	HAIDA	GWAII		 4	Spatial	Modelling	of	the	Haida	Gwaii	Ecosystem:		Contributions	to	Haida	Gwaii	Marine	Spatial	Planning	by	Tony	J.	Pitcher,	Rajeev	Kumar,	Mimi	E.	Lam,		Szymon	Surma	and	Divya	Varkey		Contents		 Executive	Summary	................................................................................................................................	1		 Introduction		..............................................................................................................................................	2		 	 The	Haida	Gwaii	marine	ecosystem,	fisheries	and	ecosystem	model	..................	2		 	 Ecosim	and	Ecospace	models	................................................................................................	2		 Methods	 	................................................................................................................................................	3		 	 General	introduction	to	Ecopath	with	Ecosim	(EwE)	.................................................	3		 	 	 Ecopath:	the	static	snapshot	of	the	ecosystem	..................................................	3		 	 	 Ecosim:	a	temporal	dynamic	approach	.................................................................	3		 	 	 Ecospace:	dynamic	spatial	modelling	....................................................................	4		 	 The	published	EwE	model	for	Northern	British	Columbia	.......................................	4		 	 Adapting	the	NBC	EwE	model	to	Haida	Gwaii	................................................................	5		 	 	 Haida	Fisheries	................................................................................................................	6		 	 	 Ecopath	parameters	......................................................................................................	6		 	 	 Ecosim	parameters	........................................................................................................	6		 	 Spatializing	the	model	for	Ecospace	...................................................................................	6		 	 Scenarios	for	Ecospace	simulations	....................................................................................	9		 Results	 	.............................................................................................................................................	11		 	 Ecospace	MPA	scenarios:	impacts	on	groups	..............................................................	11		 Discussion	 	.............................................................................................................................................	17		 	 Review	of	Previous	Research	using	Ecospace	.............................................................	17		 	 Ecospace	MPA	scenarios	for	Haida	Gwaii	......................................................................	18		 	 Problems	with	salmon	in	this	modelling	.......................................................................	21		 	 Problems	with	herring	in	this	model	...............................................................................	22		 Conclusions	.............................................................................................................................................	22		 Acknowledgements	..............................................................................................................................	23		 Literature	Cited	.....................................................................................................................................	23		 Appendix	A:	EwE	model	equations	...............................................................................................	26		 Appendix	B:	EwE	model	parameters	...........................................................................................	28			 Appendix	C:	Habitat	capacity	and	fishing	intensity	maps		..................................................	40		 Appendix	D:	All	results	tables	.........................................................................................................	52		 		 ©		Institute	for	the	Oceans	and	Fisheries,	University	of	British	Columbia	2016	Fisheries	Centre	Research	Reports	are	Open	Access	publications	Please	cite	as:		Pitcher,	T.J.,	Kumar,	R.,	Lam,	M.E.,	Surma,	S.	and	Varkey,	D.	(2016)	Spatial	Modelling	of	the	Haida	Gwaii	Ecosystem:	Contributions	to	Haida	Gwaii	Marine	Spatial	Planning.	Fisheries	Centre	Research	Reports	24	(1):	79pp.		HAIDA	GWAII	ECOSYSTEM	MODEL			 1	Executive	Summary		Zoning	 of	 marine	 space	 is	 increasingly	 used	 to	 reconcile	 conflicting	 socio-economic	 and	conservation	goals	for	marine	resources:	marine	spatial	planning	entails	appraisal	of	the	outcomes	of	ecosystem-based	 trade-offs	by	stakeholders.	This	 report	gives	 the	results	of	a	pilot	 study	using	state-of-the-art,	spatial	ecosystem	modelling	of	potential	marine	protected	areas	in	the	Haida	Gwaii	marine	 ecosystem.	 It	 aims	 to	 inform	 any	marine	 spatial	 planning	 process	 of	 the	 likely	 ecological	consequences	 of	 alternative	 spatial	 management	 scenarios.	 A	 published	 ecosystem	 model	 of	northern	BC	has	been	adapted	 to	Haida	Gwaii,	 augmented	and	 spatialized.	Novel	habitat	 capacity	maps	and	fishery	zones	have	been	employed	in	the	modelling	framework	for	the	first	time.		Marine	Protected	Areas	(MPAs)	from	Marxan	analyses	carried	out	by	the	British	Columbia	Marine	Conservation	Analysis	(BCMCA)	were	run	in	Ecospace	to	examine	their	effects	on	the	Haida	Gwaii	marine	ecosystem.	Seven	scenarios	were	analyzed	for	two	sizes	of	MPAs	(28%	and	9%	of	the	area):	1.	Complete	closure	of	all	MPAs	to	fishing;	2.	Exclusion	of	all	non-Haida	fisheries	from	the	MPAs;	3.	Exclusion	 of	 bottom	 trawling	 from	 the	 MPAs;	 4.	 Doubling	 of	 fishing	 pressure	 in	 the	 entire	ecosystem;	5.	Doubling	of	fishing	pressure	outside	no-take	MPAs;	6.	Increased	herring	catches;	and	7.	Closure	of	all	 fisheries	 in	 the	ecosystem.	Outcomes	(biomasses	and	catches)	were	evaluated	 for	three	spatial	zones:	(1)	the	entire	marine	ecosystem;	(2)	inside	MPAs;	and	(3)	the	‘spillover’	zones	immediately	adjacent	to	the	MPAs.	Model	 results	 show	 that	 smaller	MPAs	 covering	 9%	 of	 the	 area	may	 provide	 half	 of	 the	 benefits	(increased	biomass,	catches,	spillover	and	biodiversity)	of	larger	MPAs	with	only	slightly	less	catch.	Spillover	catches	in	the	zones	immediately	surrounding	the	MPAs	partially	compensated	the	loss	of	catches	 from	 the	 closed	 areas,	 especially	 for	 the	 smaller	 MPAs.	 Food	 web	 interactions	 added	complexity	 to	 this	 finding,	 especially	 in	 the	 larger	 MPAs,	 as	 trophic	 cascades	 established	 in	 the	closed	areas	cause	top	predators	to	increase	and	prey	groups	to	decline.		Doubling	 the	 existing	 fishing	 would	 cause	 major	 depletions	 in	 the	 Haida	 Gwaii	 ecosystem	 (only	partially	 offset	 by	 large	 MPAs),	 while	 complete	 closure	 to	 all	 fisheries	 and	 to	 trawling	 would	enhance	 rebuilding,	 but	 reduce	 catches.	While	 these	 extreme	 scenarios	 are	 unrealistic,	 trade-offs	resulting	from	intermediate	policy	options	could	be	explored	in	more	detail.	For	example,	localized	MPAs	might	increase	biomasses	without	large	reductions	in	catch,	and	generate	catches	in	spillover	zones	 that	 could	 be	 targeted	 by	 fisheries	 and	 thus	 lower	 fishing	 costs.	 Minor	 differences	 among	different	areas	around	Haida	Gwaii	were	observed	within	the	MPAs	from	the	Marxan	MaPP	designs,	but	 siting	 of	 more	 realistically	 located	 MPAs	 could	 be	 investigated	 using	 this	 model	 to	 balance	conservation	with	socio-economic	goals	through	participatory	consultations.		The	model	was	used	to	assess	benefits	of	large	and	small	MPA	options	identified	in	Marxan	analyses	by	the	Marine	Planning	Partnership	consisting	of	the	Haida	Nation	and	BC.		A	notable	feature	of	this	method	 is	 the	 explicit	 visualization	 of	 impacts	 of	 different	 spatial	 management	 scenarios,	 which	should	facilitate	multi-stakeholder	discussions	in	setting	viable	policy.	The	spatial	dynamics	of	three	salmon	groups	in	the	model	remained	unrealistic	despite	several	attempts	at	improvement	from	a	preliminary	 study	 and	 hence	 have	 been	 excluded	 from	 the	 results.	 A	 more	 refined	 model	 could	examine	the	actual	spatial	management	options	determined	by	a	BC	marine	spatial	planning	process	and	recently	published	by	the	Haida	Nation	and	the	BC	Government.			 March	2016	SPATIAL	MODELLING	IN	HAIDA	GWAII		 2	Introduction		Zoning	of	marine	space	is	increasingly	being	used	as	a	management	and	policy	strategy	to	reconcile	conflicting	 local	 stakeholder	 uses	 and	 conservation	 of	marine	 resources.	 Marine	 spatial	 planning	entails	 the	appraisal	of	a	 range	of	ecosystem-based	 trade-offs	by	different	stakeholders	 (Jentoft	&	Knol	 2012).	 Scientific	 estimates	 of	 the	 magnitude	 of	 these	 trade-offs	 can	 facilitate	 assent	 and	agreement	 among	 stakeholders.	 Thus,	 marine	 spatial	 planning	 based	 on	 science	 can	 inform	management	 and	 policy	 decisions	 involving	 trade-offs	 in	 resource	 use	 and	 allocation	 and	biodiversity	 protection.	 This	 report	 documents	 the	 results	 of	 a	 pilot	 study	 using	 state-of-the-art,	spatially-explicit	ecosystem-based	modelling	of	the	Haida	Gwaii	(HG)	ecosystem.	This	research	was	commissioned	to	inform	the	local	multi-stakeholder	marine	spatial	planning	process	and	to	support	the	Haida	Gwaii	Marine	Advisory	Committee’s	work	 in	evaluating	 the	consequences	of	alternative	spatial	management	scenarios	for	important	constituents	of	the	Haida	Gwaii	marine	ecosystem.		The	Haida	Gwaii	marine	ecosystem,	fisheries	and	ecosystem	model	Haida	 Gwaii	 boasts	 a	 highly	 productive	 and	 diverse	 marine	 ecosystem,	 comprised	 of	 intertidal	zones,	kelp	forests,	shallow	banks,	and	a	continental	shelf	break.	The	marine	productivity	is	largely	due	 to	 oceanographic	 features,	 such	 as	 the	Haida	Eddies	 (created	by	 the	 splitting	 of	 the	westerly	North	Pacific	Current	 into	northerly	and	southerly	branches	off	 the	west	coast	of	 the	 islands)	and	the	Hecate	Strait	Front	(generated	by	the	meeting	of	opposing	tidal	flows	from	Dixon	Entrance	and	Queen	Charlotte	Sound).	The	ecological	diversity	results	mainly	from	the	diversity	of	its	bathymetric	features	(e.g.,	the	shelf	break,	banks,	reefs,	estuaries,	and	fjords),	produced	by	a	combination	of	past	tectonic	and	glacial	action.	Despite	its	isolation,	this	ecosystem	has	long	been	affected	by	extractive	human	activities,	such	as	the	maritime	fur	trade	and	commercial	whaling	(Surma	and	Pitcher	2015).	These	activities	have	depleted	many	ecologically	 important	species,	 including	sea	otters	and	 large	whales,	from	the	waters	of	Haida	Gwaii.	Its	waters	are	still	home	to	many	commercially	important	and	charismatic	species,	however,	supporting	commercial,	Haida,	and	recreational	fisheries,	as	well	as	a	growing	marine	ecotourism	industry.	Our	Haida	Gwaii	marine	ecosystem	model	is	an	adaptation	of	an	existing	Northern	British	Columbia	(NBC)	model	 (Ainsworth	2006),	built	using	 the	Ecopath	with	Ecosim	(EwE)	modelling	 framework	(Christensen	et	al.	2005).	Several	advantages	accrue	 from	adapting	an	existing	model,	 rather	 than	building	 a	 new	 one:	 (1)	 as	 the	 NBC	model	 includes	 the	 Haida	 Gwaii	 ecosystem	within	 its	model	boundaries,	 it	 already	 includes	 the	 key	 functional	 groups	 (assemblages	 of	 ecologically	 similar	organisms)	in	the	ecosystem;	(2)	functional	groups	in	the	NBC	model	have	been	refined	over	several	model	 iterations;	 (3)	key	parameters	 in	 the	NBC	model	have	been	 fitted	 to	over	50	years	of	 time	series	survey	data.	Given	 the	 time	constraints	of	 this	pilot	project,	 functional	groups	and	 fisheries	were	 modified	 to	 ensure	 that	 the	 model	 simulates	 the	 dynamics	 of	 the	 Haida	 Gwaii	 ecosystem	reasonably	well,	but	further	model	refinements	are	needed.	The	model	adaptation	is	fully	detailed	in	the	Methods	Section.		Ecosim	and	Ecospace	models	In	Ecopath	with	Ecosim	(EwE),	the	static	Ecopath	model	provides	a	snapshot	of	the	ecosystem	at	a	single	 point	 in	 time	 basedon	 the	mass-balance	 principle.	 Each	 functional	 group	 is	 parameterized	using	biomass	(in	tonnes	km-2),	production,	consumption	and	diet	composition.	The	mass-balance	model	is	then	used	to	initiate	a	dynamic	simulation,	Ecosim,	that	tracks	biomass	changes	in	the	food	web	with	time:	the	final	ecosystem	model	parameters	are	estimated	when	model	biomass	changes	are	fitted	to	survey	and	fisheries	time	series	data.	Ecosim	has	been	widely	used	to	track	changes	in	the	biomass	pools	of	the	ecosystem	groups.	Less	widely	used	is	Ecospace,	the	spatial	component	of	HAIDA	GWAII	ECOSYSTEM	MODEL			 3	the	EwE	modelling	framework,	which	enables	us	to	account	for	the	spatial	heterogeneity	of	marine	ecosystems	 and	 their	 embedded	 fisheries.	 Ecospace	 operates	 by	 running	 time-dynamic	 Ecosim	simulations	 of	 the	 food	 web	 in	 each	 grid	 cell	 of	 a	 map	 representing	 the	 entire	 ecosystem.	 The	identity	 of	 all	 functional	 groups	 occurring	 in	 each	 grid	 cell	 is	 specified	 based	 on	 the	 known	distribution	of	 the	 species	 included	 in	 the	model.	Each	cell	 is	 connected	 to	 its	 four	neighbours	by	biomass	 flows	 determined	 by	 the	 dispersal	 rates	 and	 habitat	 requirements	 of	 relevant	 functional	groups.	 Ecospace	 has	 been	 employed	 in	 siting	 and	 evaluating	Marine	 Protected	 Areas	 (MPAs)	 in	other	locations	(see	review	in	Discussion	section).	In	this	project,	we	take	advantage	of	a	new	facility	recently	introduced	to	Ecospace	(EwE	6.2):	the	ability	 to	 use	 overlapping	 habitat	 suitability	 maps	 for	 each	 species	 or	 functional	 group	 in	 the	ecosystem	model.	In	the	older	EwE	5,	modelled	habitats	in	Ecospace	could	not	overlap,	which	would	have	 made	 this	 Haida	 Gwaii	 work	 difficult	 to	 implement.	 We	 use	 Ecospace	 to	 explore	 the	consequences	of	 some	possible	 future	 scenarios	 for	 spatial	management	of	organisms	 in	 the	 food	web	and	the	main	Haida	Gwaii	fisheries.	We	employ	two	candidate	Marine	Protected	Area	scenarios	from	recent	work	by	Marxan	analysts	 from	the	Marine	Planning	Partnership	 for	 the	North	Pacific	Coast	(BCMCA	2012).	In	this	report,	several	levels	and	types	of	spatial	management	of	the	MPAs	are	explored	and	some	potential	consequences	presented.			Methods	General	introduction	to	Ecopath	with	Ecosim	(EwE)	Ecopath	 with	 Ecosim	 (EwE)	 is	 a	 leading	 fisheries	 ecosystem	 modelling	 suite,	 listed	 by	 the	 USA	National	 Oceanic	 and	 Atmospheric	 Administration	 (NOAA)	 as	 one	 of	 the	 top	 ten	 scientific	breakthroughs	of	the	century	(NOAA	2007).	The	modelling	software	works	on	the	principle	of	food	web	 interactions	 constrained	 by	 a	mass-balance	 approach.	 EwE	has	 three	 components—Ecopath,	Ecosim	and	Ecospace—that	model	the	static,	dynamic,	and	spatial	behaviour,	respectively,	of	a	given	ecosystem.		Ecopath:	 the	 static	 snapshot	 of	 the	 ecosystem.	 The	 core	 idea	 of	 Ecopath,	 first	 conceptualized	 by	Polovina	(1984),	has	been	improved	over	the	years	(Christensen	and	Pauly	1992;	Christensen	and	Walters	2004;	Christensen	et	al.	2005).	All	producers	and	consumers	in	an	ecosystem	are	classified	in	functional	groups	that	represent	similar	ecological	roles	or	require	separate	management	results:	among	marine	mammals	 and	 fish,	 species	 are	 the	 norm.	 The	mass-balance	 approach	 of	 Ecopath	ensures	that	production	of	biomass	within	a	functional	group	equals	the	loss	of	biomass	caused	by	fisheries	 and	 predators,	 net	 migration	 and	 unexplained	 mortality:	 consumption	 within	 a	 group	equals	the	sum	of	production,	energy	expenditure	in	respiration	and	unassimilated	food.	Modellers	start	with	the	following	information	for	each	group:	biomass	(B),	production	to	biomass	ratio	(P/B),	consumption	 over	 biomass	 (Q/B)	 and	 the	 diet	 (trophic	 interactions	 in	 quantitative	 terms).	 Mass	balance	 is	achieved	by	matrix	 inversion.	Multiple	age	groups	within	a	population	can	be	modelled	with	a	‘multi	stanza’	facility	(Christensen	and	Walters	2004)	but	in	this	model	the	implementation	of	the	 age-structure	 facility	 is	 limited	 to	 a	 couple	 of	 species	 only	 such	 as	 Pacific	 hake	 and	 Pacific	halibut.	The	above	two	balanced	equations	are	mathematically	formulated	in	Appendix	A.			Ecosim:	 a	 temporal	 dynamic	 approach.	 Once	 the	 Ecopath	model	 is	 built,	modellers	 often	wish	 to	explore	the	effect	of	perturbations	 in	a	balanced	aquatic	system.	To	answer	this	question,	Ecosim,	developed	by	Walters	 et	 al.	 (1999),	models	 changes	 in	 biomass	 in	 response	 to	 changes	 in	 fishing	mortality	and	top-down	or	bottom-up	drivers	(e.g.,	Surma	and	Pitcher	2015).	The	core	differential	SPATIAL	MODELLING	IN	HAIDA	GWAII		 4	equation	by	which	Ecosim	works	 is	 provided	 in	Appendix	A.	The	key	parameter	 affecting	Ecosim	simulation	 dynamics	 is	 the	 vulnerability	 parameter	 (transfer	 rate)	 derived	 from	 foraging	 arena	theory	 (Walters	 et	 al.	 1997).	 The	 vulnerability	 parameter	 emulates	 how	 prey	 biomass	 in	 the	ecosystem	moves	 between	 states	 of	 not	 being	 available	 to	 the	 predator,	 for	 example,	 hiding	 in	 a	refuge,	 and	 being	 vulnerable	 to	 being	 eaten,	 for	 example,	 out	 foraging	 itself.	 This	 transfer	 rate	between	the	vulnerable	and	invulnerable	pools	of	prey	biomass	governs	whether	the	predator-prey	relationship	emulates	a	‘top	down’	(high	transfer	rate)	or	‘bottom	up’	(low	transfer	rate)	process.	In	fitting	 an	 Ecosim	 model	 to	 historical	 time	 series	 of	 biomass	 and	 catch	 data,	 the	 vulnerability	parameters	are	tuned	such	that	the	model	predictions	reflect	the	same	trends	as	the	historical	time	series.	In	our	case,	such	fitting	was	performed	for	the	NBC	model,	but	has	not	yet	been	repeated	for	our	adapted	HG	model.	(This	work	is	in	progress	in	2016)	Ecospace:	dynamic	spatial	modelling.	In	Ecospace,	the	dynamic	food	web	simulations	of	Ecosim	run	in	parallel	in	linked	square	map	grid	cells.	In	most	Ecospace	models,	the	cells	are	at	least	25	km2	in	size,	although	smaller	cells	have	been	used.	Areas	of	land	are	mapped	onto	a	grid	of	the	model	cells,	and	 sea	 cells	 can	 be	 allocated	 to	 different	 depth	 zones.	 Biomass	 in	 each	 functional	 group	 in	 the	model	transfers	between	cells	according	to	a	set	of	dispersal	rules,	with	relative	movement	speeds	depending	on	 food	availability	and	predation	 risk.	Directional	 and	 seasonal	migration	 can	also	be	modelled.	 Fisheries	 in	 the	 model	 occur	 in	 regions	 where	 catch	 rates	 for	 the	 target	 species	 are	maximised	 and	 can	 be	 excluded	 from	 defined	 regions	 of	 cells,	 emulating	 spatial	 management.	Exclusion	of	all	of	the	fisheries	in	the	model	represents	a	no-take	MPA.		Unlike	Atlantis,	Ecospace	does	not	include	a	three-dimensional	depth	component	of	the	ecosystem	food	web	within	each	cell:	vertical	migration	of	plankton,	 for	example,	 is	not	explicitly	 included	in	the	model,	 but	 it	may	 be	 implicit	 in	 diet	 composition	matrix).	 Ecospace	 has	 been	 utilized	 for	 the	planning	 and	evaluation	of	MPAs,	 including	 a	previous	 application	 in	Haida	Gwaii	 (Salomon	et	 al.	2002,	 Ainsworth	 2006),	 Hong	 Kong	 (Pitcher	 et	 al.	 2002),	 the	 Faroe	 Islands	 (Zeller	 and	 Reinert	2004),	the	Northern	Adriatic	(Fouzai	et	al.	2012),	the	Central	Pacific	(Martell	et	al.	2005),	and	Raja	Ampat,	 Indonesian	 West	 Papua	 (Varkey	 et	 al.	 2012).	 Atlantis	 and	 Ecosim	 provide	 generally	comparable	 results	when	 used	 to	 compare	 alternative	management	 policy	 scenarios	 (New	 South	Wales:	Forrest	et	al.	2015).	Two	new	facilities	 in	 the	Ecospace	 framework	have	been	used	 for	 the	first	 time	 in	 this	 project:	 1.	maps	of	 habitat	 capacity	 (suitability)	 for	 each	 functional	 group	 in	 the	system,	which	can	now	overlap	as	required;	and	2.	fisheries	constrained	to	defined	regions	of	cells,	emulating	licence	provisions	(Steenbeek	et	al.	2016).	The	published	EwE	model	for	Northern	British	Columbia	The	first	EwE	model	of	the	Northern	BC	(NBC)	ecosystem	was	built	by	Beattie	(2001).	It	was	revised	to	employ	local	ecological	knowledge	(LEK)	in	a	comprehensive	historical	reconstruction	study	by	Ainsworth	 (2006)	 and	 colleagues	 (Ainsworth	 and	 Pitcher	 2005,	 Ainsworth	 et	 al.	 2008).	 The	NBC	model	 covers	 an	 area	 extending	 from	 the	northern	 tip	of	Vancouver	 Island	 to	 the	 southern	 tip	of	Alaska	and	so	it	thus	includes	the	Haida	Gwaii	ecosystem	within	its	boundaries	and	so	serves	as	a	useful	starting	point	for	the	adapted	Haida	Gwaii	model	(HG	model).	The	NBC	model	includes	53	functional	groups,	representing	over	150	species	from	the	Northern	BC	ecosystem	 (Ainsworth	 et	 al	 2002).	 Important	 commercial	 fish	 species	 modelled	 include:	 Pacific	halibut	 (Hippoglossus	 stenolepis),	 Pacific	 herring	 (Clupea	 pallasii),	 Pacific	 cod	 (Gadus	macrocephalus),	 sablefish	 (Anoplopoma	 fimbria),	 Pacific	 salmon,	 and	 rockfish.	 Salmon	 are	categorised	 as	 either	 transient	 –	 sockeye	 (Oncorhynchus	 nerka),	 chum	 (O.	 keta)	 and	 pink	 (O.	gorbuscha)	–	and	“resident”	–	coho	(O.	kisutch)	and	chinook	(O.	tshawytscha),	although	coho	are	not	generally	present	during	winter.	 	Rockfish	species	are	divided	 into	 three	groups	based	on	habitat	HAIDA	GWAII	ECOSYSTEM	MODEL			 5	and	 feeding	 behaviour:	 inshore,	 piscivorous,	 and	 planktivorous.	 Inshore	 rockfish	 include	 copper	(Sebastes	caurinus),	quillback	(S.	maliger),	tiger	(S.	nigrocinctus),	China	(S.	nebulosus)	and	yelloweye	rockfish	 (S.	 ruberrimus).	 Piscivorous	 rockfish	 include	 species	 that	 feed	 mainly	 on	 fish	 and	 large	invertebrates:	 rougheye	 (S.	 aleutianus),	 shortraker	 (S.	 borealis),	 black	 (S.	 melanops),	 blue	 (S.	mystinus),	 chillipepper	 	 (S.	goodei)	and	dusky	rockfish	 (S.	ciliatus).	Planktivorous	 rockfish	 include:	yellowmouth	(S.	reedi),	widow	(S.	entomelas),	yellowtail	 (S.	flavidus),	canary	(S.	pinniger),	bocaccio	(S.	 paucispinis)	 and	 others.	 Pacific	 Ocean	 perch	 (S.	 alutus),	 a	 pelagic	 rockfish,	 was	 assigned	 to	 a	separate	group	due	to	its	distinctive	ecological	and	fisheries	role.		The	juveniles	and	adults	of	all	the	important	species	have	 juvenile	and	adult	dynamics	using	a	forerunner	of	the	multi-stanza	facility	termed	 a	 ‘split	 pool’.	 Shallow	 water	 benthic	 fish	 and	 forage	 fish	 are	 two	 functional	 groups	 that	aggregate	 several	 species	 that	 serve	as	prey	 to	 important	 fish	groups	 in	 the	model.	Commercially	important	 invertebrates	 are	modelled	 in	 three	 separate	 groups	 (commercial	 shrimp,	 large	 crabs,	epifaunal	 invertebrates)	 and	 others	 are	 aggregated	 into	 a	 few	 large	 groups	 (small	 crabs,	 infaunal	carnivorous	 invertebrates,	 infaunal	 invertebrate	 detritivores).	 Lower	 trophic	 level	 representation	includes	 three	 zooplankton	 groups	 (carnivorous	 jellyfish,	 euphausiids,	 and	 copepods),	 and	 two	groups	of	producers	(phytoplankton	and	macrophytes).		Fisheries	 in	 the	NBC	model	 are	differentiated	based	on	gear	and	 target	 species:	 groundfish	 trawl,	sablefish	 trap,	 herring	 gillnet,	 groundfish	 hook-and-line,	 halibut	 hook-and-line,	 salmon	 gillnet,	salmon	 seine,	 salmon	 troll,	 salmon	 troll	 freezer,	 longline,	 herring	 seine,	 crab	 trap,	 shrimp/prawn	trap,	 shrimp	 trawl,	 eulachon,	 other	 invertebrates,	 and	 recreational.	 Most	 of	 the	 fisheries	 (except	groundfish	trawling	and	recreational	fisheries)	target	two	to	three	functional	groups	in	the	model.	The	groundfish	trawl	mainly	targets	rockfish,	flatfish	(Pleuronectiformes),	Pacific	Ocean	perch,	and	Pacific	 cod,	 but	 it	 also	 lands	 skates	 (Rajidae),	 lingcod	 (Ophiodon	 elongatus),	 pollock	 (Gadus	chalcogrammus),	 dogfish	 (Squalus	 suckleyi),	 etc.;	 the	 fishery	 also	 discards	 several	 species.	 Shrimp	trawl	 fisheries	 discard	 flatfish,	 ratfish	 (Hydrolagus	 colliei),	 eulachon	 (Thaleichthys	 pacificus),	 and	corals	and	sponges,	as	well	as	small	amounts	of	other	species.	Shrimp	trawl	fisheries	discard	flatfish,	ratfish	 (Hydrolagus	 colliei),	 eulachon	 (Thaleichthys	 pacificus),	 and	 corals	 and	 sponges,	 as	 well	 as	small	 amounts	 of	 other	 species.	 Recreational	 fisheries	 for	 salmon,	 rockfish,	 halibut,	 and	invertebrates	 are	 grouped	 together;	 investigating	 species-specific	 recreational	 fisheries	 policy	would	require	splitting	the	fisheries	by	target	species.			Parameterization	of	 the	NBC	model	 is	based	on	numerous	 sources	of	 information	 (approximately	300	papers/	studies/	reports/	records),	exemplifying	a	powerful	integration	of	scientific	work.	The	model	was	also	fitted	to	50	years	of	historical	biomass	time	series	to	strengthen	its	validity	as	a	tool	for	 management	 scenario	 analyses.	 Readers	 are	 encouraged	 to	 consult	 Ainsworth	 (2006)	 for	detailed	information	on	functional	groups	and	model	parameters.			Adapting	the	NBC	EwE	model	to	Haida	Gwaii	The	original	NBC	model	was	developed	in	an	older	version	of	EwE,	version	5.	In	EwE	version	6,	the	software	and	its	capabilities	have	been	improved	significantly.	These	new	facilities	have	been	used	to	 adapt	 the	 NBC	model	 to	 Haida	 Gwaii.	 Only	 the	 major	 changes	 made	 to	 build	 the	 adapted	 HG	model	 are	 described	 here.	More	 recent	 changes	 to	 this	model	 are	 described	 in	 a	 separate	 report	(Kumar	et	al.	2016).	Juvenile	 and	 adult	 categories	 of	 the	 same	 functional	 group	 are	modelled	 using	 ‘split	 pools’	 in	 the	NBC	model	(EwE	5),	but	in	EwE	6,	they	are	modelled	using	a	 ‘multi-stanza’	approach,	wherein	the	juvenile	and	adult	components	are	linked	within	a	stable	age	structure.	The	split	pools	in	the	NBC	model	for	several	functional	groups	would	not	import	correctly	into	EwE	6,	since	this	functionality	is	no	longer	available.	The	NBC	model	had	22	split	pool	groups,	representing	juveniles	and	adults	of	SPATIAL	MODELLING	IN	HAIDA	GWAII		 6	11	 functional	 groups.	 Remodelling	 all	 11	 functional	 groups	 into	 age-structure	 based	multi-stanza	groups	was	not	possible	within	the	time	constraints	of	this	project	(but	is	in	progress	in2016).	In	the	adapted	 HG	 model,	 2	 groups	 (Pacific	 herring,	 Clupea	 pallasi,	 and	 Pacific	 halibut,	 Hippoglossus	stenolepis)	were	modelled	within	 the	multi-stanza	 approach,	while	 the	 remaining	18	 juvenile	 and	adult	 split	 pools	 were	 collapsed	 into	 one	 age	 group	 each.	 Marine	 mammal	 groups	 were	disaggregated	 to	 include	 explicit	 groups	 for	 all	 baleen	whales,	 as	 well	 as	 four	 groups	 of	 toothed	whales	and	separate	representation	for	seals	and	sea	lions.	The	existing	shark	and	skate	group	was	also	 split	 into	 four	new	groups.	Given	 the	 improved	 representation	of	 cetaceans	 in	 the	model,	 an	earlier	 version	 of	 this	model	was	 used	 to	 explore	 the	 ecosystem	 impacts	 of	 the	 recovery	 of	 large	whales	to	historical,	unexploited	levels	in	the	model	area	(Surma	and	Pitcher	2015).		Pacific	herring	is	an	important	species	of	management	concern,	owing	to	its	present	depletion	level,	former	stock	collapses,	service	role	as	a	forage	species	in	the	ecosystem,	and	cultural	importance	for	the	 Haida.	 Most	 herring	 fisheries	 in	 the	 model	 area	 have	 been	 closed,	 and	 although	 estimated	biomass	is	“stable	over	the	past	few	years”,	species	recovery	has	been	poor	(Cleary	and	Schweigert	2012).			Pacific	Hake	(Merluccius	productus)	was	not	included	in	the	original	NBC	model,	but	because	of	its	increasing	presence	 in	BC	waters,	we	added	 it	 as	a	new	 functional	group	 in	our	HG	model.	 In	 the	Haida	Gwaii	 ecosystem,	 hake	 is	 an	 important	 predator	 of	 herring	 (Schweigert	 et	 al.	 2010).	 	 After	merging	 the	 split	 pools,	 adding	 multi-stanzas	 for	 herring	 and	 halibut,	 and	 including	 hake	 and	expanded	marine	mammal	 and	 shark	 groups,	 the	 HG	model	 used	 in	 this	work	 had	 56	 functional	groups.		Haida	Fisheries.	Four	specific	traditional	Haida	fisheries	were	added	to	the	existing	fleets	in	the	NBC	model:	salmon,	herring,	clam,	and	seaweed.	Although	other	fisheries	occur,	these	were	identified	to	be	of	specific	 interest	 for	the	MPA	policy	options	to	be	investigated.	Estimates	for	salmon,	herring	(harvested	mainly	as	spawn-on-kelp)	and	seaweed	are	basedon	HOTT	 information.	Clam	 landings	are	included	in	the	commercial	razor	clam	fishery.	Haida	landings	are	small	relative	to	commercial	fisheries,	except	for	razor	clam	fisheries	(Russ	Jones,	pers.	comm.).		Ecopath	parameters.	The	changes	made	to	the	groups	in	the	HG	model	(merging	split	pools,	adding	new	 groups)	 necessitated	 modifications	 to	 the	 diet	 matrix.	 For	 the	 merged	 split-pools,	 the	 diets	were	rescaled	such	that	the	merged	groups	together	created	the	same	level	of	predatory	pressure	on	their	prey	as	it	was	before	merging;	similarly,	the	merged	groups	together	contributed	the	same	amount	to	the	predator	diet	as	before	merging.	The	rationale	behind	the	new	marine	mammal	and	shark	 group	 parameters	 is	 described	 in	 Surma	 and	 Pitcher	 (2015)	 and	 Kumar	 et	 al.	 (2016).	 The	altered	 diet	 matrix	 is	 presented	 in	 Appendix	 B,	 along	 with	 the	 mass-balance,	 predator-prey	vulnerability,	 and	 fisheries	 model	 parameters.	 Production	 over	 biomass	 (P/B)	 and	 consumption	over	biomass	(Q/B)	of	each	merged	group	were	scaled	based	on	the	biomass	of	juveniles	and	adults	in	 the	 split-pools.	Biomass	 in	a	merged	group	 is	 the	 total	biomass	of	 their	 respective	age	 stanzas.	Since	a	biomass	estimate	 for	hake	within	 the	HG	region	was	not	available,	we	made	the	 following	assumptions	for	calculation	of	hake	biomass:	• Based	 on	 the	 hake	 distribution	map	 obtained	 from	 Stewart	 and	 Hamel	 2010	 (Figure	 2),	 we	assumed	that	hake	distribution	ranged	from	latitudes	55°	N	to	35.5°	N.	• We	assumed	that	90%	of	hake	are	found	within	this	zone.	• We	assumed	that	the	distribution	is	concentrated	roughly	around	45° N	and	the	concentration	decreases	northwards	and	southwards.	HAIDA	GWAII	ECOSYSTEM	MODEL			 7	• We	 assume	 that	 the	 concentration	 is	 similar	 to	 a	 standard	 normal	 distribution	 with	 mean	around	45°	N.	• Based	on	the	assumption	of	normal	distribution,	the	area	under	the	curve	is	calculated	for	the	model	area,	expressed	as	a	 fraction	of	the	standard	normal	distribution.	We	assumed	that	the	same	fraction	of	the	total	Pacific	hake	biomass	would	be	present	in	the	HG	region.	• Since	hake	reside	in	BC	for	only	6	months,	the	value	calculated	in	the	above	step	was	halved	to	obtain	the	final	estimate	(0.8	t.km-2)		Ecosim	parameters.	The	vulnerability	parameters	govern	the	top-down	versus	bottom-up	predator-prey	 control	 in	 Ecosim	 food	 web	 dynamics;	 thus	 it	 plays	 a	 major	 role	 in	 the	 Ecosim	 fitting	procedure.	Since	we	merged	several	stanzas	in	the	HG	model	and	split	several	functional	groups,	it	was	not	appropriate	to	directly	transfer	the	tuned	vulnerabilities	from	the	source	NBC	model.	As	an	alternative	approach,	for	this	work	we	scaled	the	predator	vulnerabilities	to	the	trophic	level	of	prey	groups	 in	 the	 HG	model	 as	 an	 approximation	 (Cheung	 et	 al.	 2002,	 Ainsworth	 and	 Pitcher	 2004,	Ainsworth	et	al.	2008).		Spatializing	the	model	for	Ecospace	Figure	1.	Drawing	the	Ecospace	map	of	Haida	Gwaii.	A.	GIS	map	of	Haida	Gwaii	and	surrounding	ocean	with	a	4-km	grid	overlaid	(from	the	HOTT).	B.	Semi-transparent	overlay	of	GIS	map	(in	A)	on	Ecospace	map	(in	C),	both	with	4-km	grids.	C.	Final	Ecospace	map	of	Haida	Gwaii	coastline	and	depth,	drawn	on	a	4-km	grid.	After	some	pilot	work	with	an	8-km	grid	of	cells,	we	used	a	4-km	grid	to	create	the	basic	Ecospace	map	from	a	Geographic	 Information	System	(GIS)	map	supplied	by	Chris	MacDougall	of	 the	Haida	Oceans	 Technical	 Team	 (HOTT).	 Use	 of	 a	 semi-transparent	 GIS	 overlay	 (Figure	 1A)	 of	 the	 same	geographical	projection	employed	in	EwE	facilitated	drawing	the	model	map	(Figure	1B).	The	actual	model	 map	 of	 Haida	 Gwaii	 was	 adapted	 to	 the	 constraint	 that	 land	 areas	 should	 not	 include	‘trapped’	 cells	of	ocean	with	no	outlet	or	 ‘border’	 to	other	ocean	areas,	 as	 then	model	biomass	 in	Ecospace	 would	 not	 be	 able	 to	 transfer	 in	 and	 out.	 The	 final	 Ecospace	 map,	 which	 covers	approximately	81,000	km2	of	ocean	(or	a	total	of	93,100	km2	in	the	model	area)	is	shown	in	Figure	1C.	SPATIAL	MODELLING	IN	HAIDA	GWAII		 8	This	 project	 uses	 a	 new	 facility	 in	 Ecospace,	 wherein	 a	 GIS-like	 layer	 for	 each	 species	 group	determines	 its	 relative	abundance	 (biomass)	 in	 the	 food	web	operating	 in	each	spatial	 cell.	These	Ecospace	‘habitat	capacity	maps’	in	EwE	6	(Steenbeek	and	Christensen	2009;	Steenbeek	et	al.	2016)	replace	 the	 non-overlapping	 habitats	 of	 previous	 versions.	 We	 used	 information	 from	 HOTT,	relative	 abundance	 layers	 used	 in	 the	MaPP	Marxan	 analysis,	 and	mapped	 information	 from	 the	Haida	traditional	ecological	knowledge	(TEK)	report	(Council	of	 the	Haida	Nation	2011).	For	each	functional	group,	the	habitat	capacity	for	each	cell	on	the	map	was	scaled	between	bad	(0)	and	good	(1)	habitats;	this	EwE	6	feature	allows	sophisticated	Ecospace	maps.	Movement	between	cells	was	based	on	species	dispersal	rates	and	quality	of	adjacent	habitats.	For	this	pilot	project,	we	modified	the	mapped	information	in	consultation	with	HOTT	in	cases	that	looked	anomalous.			Figure	2	depicts	three	examples	of	habitat	capacity	maps;	the	full	set	is	given	in	Appendix	C.	These	maps	went	 through	 three	stages	of	 refinement	by	 the	model	 team	and	experts	 in	 the	Haida	Gwaii	region:	doubtless	they	could	be	refined	further.	Preliminary	work	revealed	that	salmon	groups	were	unusually	 sensitive	 to	MPAs:	parameters	were	adjusted	 to	 reduce	 this	problem,	but	 the	 issue	still	needs	 more	 attention	 if	 salmon	 spatial	 dynamics	 are	 to	 be	 resolved.	 Our	 solution	 has	 been	 to	eliminate	salmon	dynamics	from	the	results	of	this	project	(see	discussion	section).			Figure	 2.	Three	examples	of	Ecospace	habitat	capacity	maps	(red	 is	 the	highest	relative	habitat	suitability;	white	is	no	suitability):	A.	Coho	salmon,	from	HOTT	map,	June	to	November;	B.	Inshore	rockfish,	from	expert	knowledge;	and	C.	Seabirds,	from	HOTT	and	BC	MaPP.	HAIDA	GWAII	ECOSYSTEM	MODEL			 9		In	 EwE	 6,	 “travel	 cost”	maps	 can	 be	 specified	 for	 individual	 fisheries,	 providing	maps	 of	 relative	potential	fishing	intensity.	We	emulated	fishing	effort	distribution	in	Ecospace	by	setting	the	spatial	‘cost	of	fishing’	parameter	to	a	very	large	value	for	areas	outside	officially	licenced	or	known	active	fishing	areas.	Fishing	effort	distribution	was	obtained	 in	some	cases	 from	catch	maps	supplied	by	HOTT,	many	of	which	are	based	on	DFO	data.	When	 the	dynamic	model	 runs,	 fishery	 catches	are	determined	by	the	fishing	gear	(target	species	and	bycatch)	and	relative	biomass	abundance	of	the	target	 species	moderated	 by	 the	 relevant	 potential	 fishing	 intensity	maps.	 Figure	 3	 depicts	 three	examples	of	potential	fishery	intensity	maps;	the	full	set	is	provided	in	Appendix	C.			Scenarios	for	Ecospace	simulations	Two	MPA	size	options	were	run	in	Ecospace	to	test	the	ecological	effects	of	small	MPAs	(low-target	Marxan,	 9%	of	 the	 area)	 and	 large	MPAs	 (high-target	Marxan,	 28%	of	 the	 area)	 in	 the	waters	 off	Haida	Gwaii.	The	two	MPA	options	were	based	on	high-clumping	Marxan	analyses	run	by	the	British	Columbia	Marine	Conservation	Analysis	(BCMCA	2012).	Ecospace	MPAs	were	mapped	onto	our	grid	using		shapefiles	generated	by	Marxan	(Figure	4);		4km	spillover	zones	were	drawn	around	the	MPA	boundaries	(see	Figure	5).	For	ease	of	analysis,	the	Ecospace	MPAs	were	divided	into	four	regions:	west	coast,	east	coast,	north	coast,	and	mainland	(Figure	4).								Figure	3.	Three	examples	of	Ecospace	potential	fishery	 intensity	maps	(red	is	the	highest	relative	potential	fishing	 intensity;	white	 is	 no	 fishing):	 A.	 Halibut	 hook	 and	 line	 fishery,	 interpolated	 from	 an	 International	Halibut	Commission	map;	B.	Sablefish	trap	fishery;	and	C.	Prawn	trap	fishery,	both	B	and	C	from	HOTT	and	a	DFO	catch	map.		SPATIAL	MODELLING	IN	HAIDA	GWAII		 10		Within	 each	MPA	option,	 the	 effects	 of	 seven	 scenarios	 ,	 planned	 after	 discussion	with	 the	Haida	Oceans	Technical	Team,	were	run	in	the	spatial	model:			1.	complete	closure	of	all	MPAs	to	fishing;		2.	exclusion	of	all	non-Haida	fisheries	from	the	MPAs;		3.	exclusion	of	groundfish	trawling	from	the	MPAs;		4.	doubling	the	fishing	pressure	in	the	entire	ecosystem;		5.	doubling	the	fishing	pressure	outside	the	no-take	MPAs;		6.	increasing	herring	catches	fivefold;	and		7.	closure	of	all	fisheries	in	the	entire	ecosystem.			In	 both	MPA	 size	 options,	 all	 seven	marine	 spatial	 planning	 scenarios	were	 analyzed	 in	 terms	 of	functional	group	biomasses	and	catches,	evaluated	inside	of	three	spatial	zones:	1.	the	entire	Haida	Gwaii	marine	ecosystem;	2.	the	MPAs;	and	3.	the	spillover	zones	immediately	adjacent	to	the	MPAs	(see	Figure	5).	Figure	4.	Ecospace	MPAs	generated	from	the	two	high-clumping	MPA	options	from	MaPP	Marxan	analyses:	A.	High-target	MPAs	for	larger	closed	area	(28%).	B.	Low-target	MPAs	for	smaller	closed	area	(9%).	Within	each	option,	the	MPAs	cluster	into	four	regions,	indicated	by	the	coloured	hashed	areas	(see	Figure	5).	HAIDA	GWAII	ECOSYSTEM	MODEL			 11	The	 Haida	 Gwaii	Ecospace	 simulation	model	 was	 run	 for	 25	years	for	each	scenario.	Biomass	 and	 catch	 by	functional	 group	 and	fleet	 on	 the	 25th	 year	were	 taken	 as	 results.	The	 scenario	 results	were	 expressed	 as	percentage	 changes,	positive	 or	 negative,	compared	 to	 the	baseline	 ‘status	 quo’	simulation.	 Only	functional	 groups	 with	the	 largest	 changes	 are	shown	 in	 the	 results	graphs.	Catches,	 discards	 of	non-target	 species,	 and	biomass	 overall,	 inside	the	 MPAs,	 and	 in	 the	spillover	 zones	 (Figure	5)	were	 also	 pooled	 in	order	 to	 examine	 the	overall	 effects	 of	 the	MPA	policies.				Results	Ecospace	MPA	scenarios:	impacts	on	functional	groups	In	our	model,	 the	spatial	dynamics	of	 the	 three	salmon	groups	 in	response	 to	 the	MPAs	remained	unrealistic	despite	several	attempts	at	improvement	froma	preliminary	study,	and	hence	all	salmon	have	been	excluded	from	the	results.	This	situation	is	explained	in	detail	in	the	discussion	section.	We	express	all	results	for	the	25-year	simulations	as	a	percentage	of	the	baseline	(no	policy	change)	values.	Figures	6-13	show	the	seven	Ecospace	scenario	results	obtained	 for	 the	 two	MPA	options,	large	and	small	MPAs.	Only	functional	groups	with	changes	larger	than	5%,	positive	or	negative,	are	shown,	 sorted	by	 their	 relative	 changes	 in	biomass	or	 catch	 in	 the	whole	Haida	Gwaii	 ecosystem.	Results	 are	 displayed	 for	 three	 spatial	 zones:	 (1)	 the	 overall	 Haida	 Gwaii	 marine	 ecosystem	 –	designated	 ‘all’	 in	 the	 figures;	 (2)	 the	MPAs;	and	(3)	 the	spillover	zones	 (see	Figure	5). Complete	results	of	the	Ecospace	scenarios	for	all	of	the	model	functional	groups	are	provided	in	Appendix	D. Figure	 5.	 	 Spatial	 zones	 in	 Ecospace	 scenarios	 for	 the	 two	 high-clumping	Marxan	 MPA	 options:	 A.	 Large	 (‘high-target’)	 MPAs;	 B.	 Small	 (‘low-target’)	MPAs.	MPA	regions	 include:	west	 coast,	north	 coast,	 east	 coast	and	mainland,	each	 region	 represented	 by	 different	 colours.	 The	 4km	 wide	 spillover	 zones			around	the	rim	of	each	MPA	are	highlighted.	SPATIAL	MODELLING	IN	HAIDA	GWAII		 12		Figure	 6.	 Changes	 in	biomass	 and	 catch	 in	response	 to	 complete	closure	 of	 all	 fisheries	inside	 small	 MPAs	 (pink	bars)	and	large	MPAs	(red	bars).	 Columns	 show	changes	 within	 different	spatial	 zones:	 the	 whole	Haida	 Gwaii	 marine	ecosystem	(left);	the	MPAs	(centre);	 and	 spillover	zones	 (right).	 Bars	represent	 percentage	changes	 after	 a	 25-year	simulation	with	respect	 to	a	 baseline	 scenario.	 For	clarity,	only	changes	larger	than	 +/-	 5%	 are	 shown,	sorted	 by	 their	 relative	changes	 in	 biomass	density	in	the	Haida	Gwaii	ecosystem.		Scenario	1.	Complete	closure	of	all	MPAs	to	fishing:	The	greatest	impact	of	the	no-take	MPAs	was	on	the	 biomass	 of	 rockfish,	 lingcod	 and	 hake	 groups	 in	 both	 the	 small	MPAs	 (about	 10%)	 and	 large	MPAs	 (by	 about	 30%	 -	 see	 Figure	 6).	 Pacific	 Ocean	 Perch	 showed	 a	 small	 overall	 decrease	 but	increased	 inside	the	MPAs,	although	results	 for	spillover	zones	were	equivocal.	The	main	biomass	increases	 inside	 the	MPAs	 and	 spillover	 zones	were	 echoed	within	 the	 entire	 ecosystem	 and	 this	translated	into	significantly	higher	spillover	catches,	but	not	in	the	rest	of	the	ecosystem.	Biomass	of	all	other	fish	groups	in	the	small	MPAs	increased	about	10%	inside	the	MPAs	and	about	5%	in	the	entire	 modelled	 area,	 while	 in	 the	 large	 MPAs,	 biomasses	 increased	 up	 to	 30%	 and	 15%,	respectively.	 For	 both	 MPA	 sizes,	 there	 was	 a	 notable	 concentration	 of	 biomass	 in	 the	 spillover	zones,	resulting	in	increased	catches	of	crabs,	rockfish	and	Pacific	Ocean	perch	of	over	20%	in	the	small	MPAs	and	over	50%	in	the	large	MPAs.	Overall,	catches	decreased	slightly,	except	for	crabs.	Figure	 7.	 MPA-wise	 changes	 in	 biomass	 in	response	to	complete	closure	of	fisheries	inside	small	 (pink	 bars)	 and	 large	 (red	 bars)	 MPAs.	Bars	 represent	 percentage	 changes	 after	 a	 25-year	 simulation	 with	 respect	 to	 a	 baseline	scenario.	 For	 clarity,	 only	 changes	 larger	 than	+/-	 5%	 are	 shown,	 sorted	 by	 their	 relative	changes	in	biomass	density.	We	further	explored	the	biomass	and	catch	results	 among	 the	 four	 regions	 of	 MPAs	(Figure	 7).	 Trends	 in	 the	 fish	 group	responses	were	similar	in	the	different	MPA	regions,	 but	 their	 magnitudes	 were	significantly	greater	in	HG_West	and	for	the	large	 MPAs	 option	 compared	 with	HG_North,	HG_East	and	Mainland.	For	both	HAIDA	GWAII	ECOSYSTEM	MODEL			 13	MPA	 sizes,	 HG_West	 showed	 more	 pronounced	 biomass	 increases	 and	 decreases.	 Herring	 and	shrimp	 declined	 here	 while	 most	 other	 biomass	 changes	 were	 positive.	 Sablefish	 biomass	 was	higher	 in	all	regions	except	HG_East,	resulting	 in	higher	biomass	 in	 the	respective	spillover	zones.	Catch	 results	 by	 region	 show	 significant	 concentrations	 in	HG_West	 and	HG_East	 spillover	 zones,	though	all	four	regions	had	increased	spillover	catches	(see	Appendix	D).		Figure	 8.	 Modelled	changes	 in	 biomass	 and	catch	 in	 response	 to	allowing	 only	 the	 four	traditional	 Haida	fisheries	 (salmon,	herring,	 clam,	 and	seaweed)	 to	 operate	inside	small	MPAs	 (pink	bars)	 and	 large	 MPAs	(red	 bars).	 Bars	represent	 percentage	changes	 after	 a	 25-year	simulation	 with	 respect	to	 a	 baseline	 scenario.	For	clarity,	only	changes	larger	 than	 +/-	 5%	 are	shown,	 sorted	 by	 their	relative	 changes	 in	biomass	 density	 in	 the	Haida	Gwaii	ecosystem.			Scenario	 2.	 Exclusion	 of	 all	 non-Haida	 fisheries	 from	 MPAs:	 The	 scenario	 allowing	 only	 the	 four	traditional	Haida	fisheries	(salmon,	herring,	clam,	and	seaweed)	 inside	the	MPAs	(Figure	8)	yields	results	very	similar	to	the	scenario	excluding	all	fisheries	from	the	MPAs	(Figure	6),	suggesting	that	these	 Haida	 fisheries	 have	 low	 impact	 on	 the	 biomasses	 and	 catches	 of	 the	 functional	 groups	modelled.	 This	 result	 confirms	 the	 view	 that	 Haida	 landings	 (termed	 FSC	 by	 DFO)	 have	 small	ecosystem	impacts	relative	to	commercial	 fisheries.	The	Haida	commercial	razor	clam	fishery	was	not	 explicitly	 considered,	 as	 the	 epifaunal	 invertebrates	 functional	 group	 in	our	 ecosystem	model	was	not	disaggregated	for	razor	clams:	this	could	be	done	in	a	revised	model	Scenario	 3.	 Exclusion	 of	 groundfish	 (bottom)	 trawling	 from	MPAs:	When	 groundfish	 trawling	 was	excluded	 from	 the	 MPAs	 (Figure	 9),	 rockfish	 and	 lingcod	 biomasses	 increased	 by	 2-4%	 (small	MPAs)	 to	5-8%	(large	MPAs)	 in	biomass.	Overall	catches	were	reduced	by	similar	amounts.	Large	decreases	 in	 catches	 inside	 the	MPAs	 reflect	 the	 targeting	 of	 these	 species	 by	 trawls,	 as	 do	 large	increases	in	spillover	catches	as	these	species	recover	inside	the	MPAs.					SPATIAL	MODELLING	IN	HAIDA	GWAII		 14	Figure	 9.	 Changes	 in	biomass	and	 catch	 in	 response	 to	 a	complete	 trawling	 closure	inside	small	MPAs	(pink	bars)	and	 large	 MPAs	 (red	 bars).	Bars	 represent	 percentage	changes	 after	 a	 25-year	simulation	 with	 respect	 to	 a	baseline	 scenario.	 For	 clarity,	only	 changes	 larger	 than	 +/-	5%	are	shown,	sorted	by	their	relative	 changes	 in	 biomass	density	 in	 the	 Haida	 Gwaii	ecosystem.			Scenario	 4.	 Doubling	 fishing	 pressure	 	 in	 the	entire	ecosystem:	Doubling	the	fishing	pressure	on	 the	 entire	 modelled	 area	 for	 25	 years	(Figure	10)	left	the	Haida	Gwaii	ecosystem	in	a	much	 simplified	 condition,	 with	 meager	biomasses	 of	 sablefish,	 rockfish,	 dogfish,	Pacific	 Ocean	 perch,	 hake	 and	 lingcod,	 which	would	 be	 insufficient	 to	 support	 commercial	fisheries.	Consequently,	 these	commercial	 fish	species	exert	less	predatory	pressure	on	lower	trophic	levels	in	the	model,	and	so	prey	species	such	as	shallow-water	benthic	fish,	large	crabs,	shrimp,	 herring,	 and	 squid	 increase	 and	eventually	 dominate	 the	 ecosystem.	 As	 there	are	no	MPAs	operating	in	this	scenario,	results	for	 the	 three	 zones	 are	 identical.	 This	 is	 an	example	of	a	fishing-induced	trophic	cascade.		Figure	 10.	 Changes	 in	 biomass	 and	 catch	 in	response	to	heavy	fishing	(twice	the	present	 level)	in	 the	 entire	 modelled	 HG	 area.	 Bars	 represent	percentage	 changes	 in	 small	 (pink	bars)	 and	 large	(red	 bars)	 MPAs	 after	 a	 25-year	 simulation	 with	respect	 to	 a	 baseline	 scenario.	 For	 clarity,	 only	changes	 larger	 than	 +/-	 5%	 are	 shown,	 sorted	 by	their	 relative	 changes	 in	 biomass	 density	 in	 the	Haida	 Gwaii	 ecosystem.	 As	 there	 are	 no	 MPAs	operating	 in	 this	 scenario,	 results	 for	 the	 three	zones	are	identical.				HAIDA	GWAII	ECOSYSTEM	MODEL			 15	Scenario	5.	Doubling	 fishing	pressure	outside	no-take	MPAs:	When	 fishing	was	 doubled	 in	 all	 areas	except	for	the	no-take	MPAs	(Figure	11),	all	three	spatial	zones	in	the	model	were	similarly	affected,	as	evident	in	the	similar	patterns	in	biomass	and	catch	changes.	Removing	all	fishing	pressure	inside	the	MPAs	while	doubling	 it	 in	 the	remaining	areas	did	not	boost	 the	biomasses	of	 the	commercial	species.	This	is	similar	to	the	scenario	doubling	the	fishing	in	all	areas,	except	that	within	the	MPAs,	the	 losses	were	 less	 pronounced	 and	 low	 trophic	 levels	 groups	 like	 herring	 and	 crabs	 increased	through	 predator	 release	 and	 trophic	 cascades.	 In	 the	 small	 MPAs,	 the	 biomasses	 of	 predatory	commercial	 species	were	 larger	and	 those	of	prey	 species	were	 slightly	 smaller	 than	when	heavy	fishing	 was	 allowed	 in	 the	 entire	 modelled	 area.	 Both	 large	 and	 small	 MPAs	 harboured	 similar	biomasses	 of	 predatory	 commercial	 species	 and	 lower	 biomasses	 of	 prey	 specie,	 but	 spillover	catches	suggested	more	protection	against	depletion	being	afforded	by	the	large	MPAs.		Although,	as	might	 be	 expected,	 the	MPAs	provided	 some	mitigation	 of	 the	 heavy	 fishing	pressure,	 The	model	shows	that	the	heavy	fishing	levels	examined	here	are	not	sustainable,	as	(1)	the	overall	decline	in	the	biomasses	of	predatory	commercial	species	was	similar	irrespective	of	whether	the	MPAs	were	implemented	or	not;	and	(2)	even	our	 large	MPAs	did	not	provide	protection	sufficient	 to	prevent	the	declines.		 	Figure	 11.	 Changes	 in	biomass	 and	 catch	 in	response	 to	 fishing	closures	 inside	 the	 small	(pink	 bars)	 and	 large	(red	 bars)	 MPAs,	 but	allowing	 heavy	 fishing	(twice	 the	 present	 level)	elsewhere.	 Bars	represent	 percentage	changes	 after	 a	 25-year	simulation	 with	 respect	to	 a	 baseline	 scenario.	For	 clarity,	 only	 changes	larger	 than	 +/-	 5%	 are	shown,	 sorted	 by	 their	relative	 changes	 in	biomass	 density	 in	 the	Haida	Gwaii	ecosystem			.		Scenario	6.	Increasing	herring	catches	fivefold:	Increasing	herring	fisheries	by	a	factor	of	five	(Figure	12)	caused	a	decline	in	adult	and	juvenile	herring	biomass	densities	by	20-30%	(small	MPAs)	or	45-55%	 (large	MPAs).	 As	 herring	 is	 an	 important	 consumer	 of	 euphausids,	 its	 decline	 increased	 the	availability	of	euphausids	to	other	species	in	the	ecosystem.	Consequently,	the	biomasses	of	Pacific	Ocean	 perch,	 pollock	 and	 sablefish	 increased	 due	 to	 the	 release	 of	 predation	 predation	 on	euphausids.	A	decline	in	lingcod	biomass	was	also	observed,	likely	due	to	the	increased	biomasses	of	its	predators,	halibut	and	arrowtooth	flounder	(‘turbot’,	Atheresthes	stomias).	Herring	decline	also	caused	a	small	decline	in	its	predators,	seals	and	sea	lions	(see	Appendix	D).	These	pinnipeds	also	prey	on	halibut,	 shallow	water	benthic	 fish	 and	 lingcod,	which	also	declined	under	 lower	herring	abundance	 and	 increased	 predatory	 pressure	 from	 the	 pinnipeds.	 Very	 similar	 changes	 are	 seen	SPATIAL	MODELLING	IN	HAIDA	GWAII		 16	inside	the	MPAs	and	spillover	zones,	since	no	additional	protection	from	MPAs	is	modelled	in	this	scenario.	Figure	 12.	 Changes	 in	biomass	 and	 catch	 in	response	 to	 heavy	 fishing	on	 herring	 in	 the	 entire	modelled	 HG	 area.	 Bars	represent	 percentage	changes	 in	 small	 (pink)	and	 large	 (red)	 MPA	scenarios	 after	 a	 25-year	simulation	with	respect	to	a	 baseline	 scenario.	 For	clarity,	 only	 changes	larger	 than	 +/-	 5%	 are	shown,	 sorted	 by	 their	relative	 changes	 in	biomass	 density	 in	 the	Haida	Gwaii	ecosystem.				Scenario	 7.	 Closure	 of	 all	 fisheries	 in	 the	 entire	 ecosystem:	Closing	 all	 fisheries	 in	 the	 entire	 Haida	Gwaii	modelled	area	(Figure	13)	gave	results	converse	to	 the	doubling	of	 fishing	pressure	(Figure	10).	The	biomasses	of	predatory	commercial	groups	(mainly	 lingcod,	dogfish,	Pacific	Ocean	perch,	rockfish,	and	hake)	increased,	while	prey	groups	(forage	fish,	herring,	flatfish,	shallow	water	benthic	fish,	and	commercial	shrimp)	decreased	due	to	cascading	effects	of	 increasing	predator	biomasses	increasing.	Figure	 13.	 Changes	 in	 biomass	 and	 catch	 in	response	to	a	complete	fishing	closure	in	the	entire	modelled	 HG	 area.	 Bars	 represent	 percentage	changes	 in	 small	 and	 large	 MPAs	 after	 a	 25-year	simulation	with	respect	to	a	baseline	scenario.	For	clarity,	only	changes	larger	than	+/-	5%	are	shown,	sorted	by	their	relative	changes	in	biomass	density	in	the	Haida	Gwaii	ecosystem.	As	there	are	no	MPAs	operating	 in	 this	 scenario,	 results	 for	 the	 three	zones	are	identical.						HAIDA	GWAII	ECOSYSTEM	MODEL			 17	Discussion	This	project	reports	two	main	outcomes:	1.	It	has	adapted	the	published	dynamic	simulation	model	of	the	Northern	British	Columbia	food	web	(Ecopath	with	Ecosim,	EwE)	to	the	Haida	Gwaii	marine	ecosystem	and	created	a	spatial	model	with	habitats,	 fisheries	and	management	areas	(Ecospace);	and	 2,	 It	 has	 demonstrated	 the	 potential	 for	 the	model	 to	 explore	 options	 among	marine	 spatial	management	scenarios	including	MPAs.		Review	of	Previous	Research	using	Ecospace	Ever	 since	Walters	 et	 al.	 (1999)	 published	 their	 seminal	 paper	 on	 the	 theory	 and	 applications	 of	Ecospace,	 this	 spatial	 component	 of	 the	 EwE	 package	 has	 played	 a	 major	 role	 in	 the	 ecological	design	of	MPAs.	Walters	et	al.	(1999)	first	analyzed	the	ecological	effects	of	a	no-take	zone	defined	by	oil	fields	off	the	coast	of	Brunei,	applying	Ecospace	to	successfully	predict	the	spatial	distribution	of	 model	 functional	 groups	 and	 account	 for	 patterns	 in	 predation	 and	 fishing	 pressure.	 Their	analysis	also	showed	that	 the	efficacy	of	small	MPAs	as	conservation	measures	may	be	drastically	reduced	by	the	buildup	of	fishing	effort	immediately	outside	the	MPAs	due	to	the	effects	of	spillover	and	 trophic	 cascades,	 specifically,	 the	 movement	 of	 predatory	 fish	 out	 of	 the	 MPAs	 along	 an	increasing	gradient	of	prey	abundance.	Walters	et	al.	(1999)	further	predicted	that	Ecospace	would	become	a	powerful	tool	for	designing	policy	experiments	involving	MPAs.	Pitcher	et	al.	 (2002)	utilized	Ecospace	 to	evaluate	 the	conservation	effects	of	proposed	MPAs	and	artificial	 reefs	 off	 Hong	 Kong.	 Their	 results	 showed	 that	MPAs	 had	 a	 clear	 positive	 effect	 on	 the	biomass	and	catches	of	large	reef	fish,	but	a	much	less	marked	effect	on	their	smaller	counterparts.	Pitcher	et	al.	(2002)	also	found	that	MPA	effectiveness	increased	with	size	but	this	relationship	was	complicated	by	 trophic	cascades.	Salomon	et	al.	 (2002)	used	Ecospace	 to	study	alternative	zoning	options	 for	 the	 (then	 proposed)	 Gwaii	 Haanas	 National	 Marine	 Conservation	 Area	 Reserve	(GHNMCAR).	They	determined	that	buffer	zones	where	some	fishing	is	permitted	may	alleviate	the	ecological	problems	first	noted	by	Walters	et	al.	 (1999),	as	well	as	socioeconomic	tensions	caused	by	MPAs,	 but	 only	 if	 these	 zones	 are	placed	on	 the	 outer	 boundaries	 of	 the	MPAs.	 Salomon	 et	 al.	(2002)	 also	 found	 that	 a	 no-take	MPA	with	 such	 a	 buffer	 zone	 provides	 the	 greatest	 increase	 in	biomass	of	all	MPA	variants.	However,	they	noted	that	the	efficacy	of	MPAs	is	limited	when	applied	to	wide-ranging	species.	Therefore,	multiple	indicator	species	must	be	used	to	gauge	their	success,	and	MPAs	must	be	deployed	as	part	of	a	suite	of	conservation	measures.	Zeller	and	Reinert	(2004)	utilized	Ecospace	to	evaluate	fisheries	policy	options	in	the	Faroe	Islands.	They	 found	 that	closed	areas	 increased	 the	biomass	of	 large	demersal	 fish	and	Greenland	halibut,	but	were	concerned	that	uncertainty	in	the	fisheries-based	model	input	data	may	have	affected	the	results.	 Martell	 et	 al.	 (2005)	 studied	 the	 effects	 of	 hypothetical	 MPAs	 on	 the	 tropical	 pelagic	ecosystem	of	 the	 Central	North	 Pacific	 using	 Ecospace.	 They	 concluded	 that	 only	 large	MPAs	 can	properly	 rebuild	and	protect	pelagic	 fish	populations	due	 to	 the	effects	of	 shifts	 in	phytoplankton	and	zooplankton	abundance	caused	by	ocean	currents,	as	well	as	the	high	dispersal	rates	of	pelagic	fish.	 Martell	 et	 al.	 (2005)	 withheld	 judgment	 on	 whether	 open-ocean	 MPAs	 are	 practical	conservation	tools,	but	affirmed	that	MPAs	should	be	designed	for	use	as	experiments	 in	adaptive	management.	 Cheung	 and	Pitcher	 (2005)	 explored	 the	 spatial	 arrangement	 of	MPAs	 in	 the	 South	China	 Sea,	 finding	 that	 large	 closures,	more	 than	 25%	of	 the	 area,	 could	 quickly	 turn	 around	 the	massive	 depletion	 in	 that	 productive	 shallow	 tropical	 region.	 Sayer	 et	 al.	 (2005)	 examined	MPAs	and	artificial	reefs	off	west	Scotland	for	their	potential	to	restore	benefits	from	former	small-scale	local	fisheries.	SPATIAL	MODELLING	IN	HAIDA	GWAII		 18	Ainsworth	(2006)	constructed	the	first	Ecospace	model	of	central	and	northern	British	Columbia	to	evaluate	various	conservation	scenarios	for	the	GHNMCAR,	including	seasonal	area	closures	as	well	as	 the	 exclusion	of	bottom	 trawling	or	 all	 commercial	 fisheries.	Ainsworth	 (2006)	 concluded	 that	long	closures	and	the	exclusion	of	commercial	fisheries	produced	the	best	results	in	terms	of	area-wide	catches	and	MPA	biomass.	He	also	noted	that	any	form	of	MPA,	particularly	no-take,	improved	area-wide	catches,	with	the	MPA	hosting	more	long-lived	species	and	longer	food	chains	but	lower	total	biomass	than	surrounding	waters.	Christensen	et	al.	(2009)	brought	attention	to	the	fact	that	while	 Ecospace	 was	 designed	 for	 analyzing	 MPA	 scenarios,	 it	 has	 rarely	 been	 used	 for	 spatial	optimization	 exercises	 applied	 to	MPA	 design.	 They	 described	 two	 alternative	MPA	 optimization	approaches	in	Ecospace:	the	Ecoseed	approach	and	a	Marxan-like	Monte	Carlo	routine.	Their	test	of	both	approaches	on	a	hypothetical	MPA	in	the	South	China	Sea	showed	that	MPAs	can	be	sited	in	a	manner	 that	 accommodates	 socioeconomic	 issues	 without	 compromising	 conservation	 goals.	However,	they	noted	a	trade-off	between	socioeconomic	factors	and	the	inclusion	of	cells	with	high	conservation	value	in	the	MPA,	and	recognized	that	some	impacts	on	endangered	species	may	not	have	been	reflected	in	the	model.		Varkey	et	al.	(2012)	utilized	Ecospace	to	analyze	the	benefits	to	reef	fish	provided	by	MPAs	in	Raja	Ampat,	Indonesia.	They	determined	that	rapid	recovery	of	reef	fish	populations,	especially	for	large	species,	only	occurred	in	no-take	scenarios,	although	some	recovery	was	produced	by	the	exclusion	of	commercial	fisheries.	Varkey	et	al.	(2012)	also	observed	trophic	cascades	in	MPAs	resulting	from	the	 protection	 of	 large	 predators,	 and	 noted	 trade-offs	 between	 increased	 catch	 and	 spillover	 in	partially	 fished	 MPAs	 and	 stock	 rebuilding	 in	 no-take	 situations.	 As	 with	 Salomon	 et	 al.	 (2002),	Zeller	and	Reinert	 (2004)	and	Martell	et	al.	 (2005),	Varkey	et	al.	 found	 that	 the	dispersal	 rates	of	particular	 species	 are	 crucial	 to	 the	 efficacy	 of	 their	 conservation	 in	 MPAs.	 Fouzai	 et	 al.	 (2012)	employed	 Ecospace	 to	 evaluate	 various	 fisheries	 policy	 options	 in	 the	 North-Central	 Adriatic,	including	MPAs	(no-take	and	no-trawl),	seasonal	closures,	and	effort	reductions.	They	found	that	all	three	 categories	 of	 conservation	 measures	 increased	 the	 biomasses	 of	 many	 fished	 species,	particularly	large	demersal	fish	and	predators.	Fouzai	et	al.	(2012)	also	observed	that	while	stable	or	 increasing	 trends	 in	 catches	 occurred	 for	 some	 fleets,	 the	 general	 pattern	was	 one	 of	 decline,	pointing	yet	again	to	a	trade-off	between	the	fulfillment	of	socioeconomic	and	conservation	goals.	Ecospace	MPA	scenarios	for	Haida	Gwaii	The	model	showed	that	establishing	MPAs	increased	the	biomasses	of	top	exploited	species,	notably	piscivorous,	 planktivorous	 and	 inshore	 rockfish,	 hake,	 dogfish,	 and	 Pacific	 Ocean	 perch.	 Biomass	changes	in	shallow	water	benthic	fish,	herring,	crabs	and	squids	were	a	result	of	trophic	interactions	in	 the	 ecosystem.	 For	 example,	 all	 three	 rockfish	 groups	 showed	 improvement	 in	 biomass	 in	response	to	complete	fisheries	exclusion	from	the	MPAs,	while	only	piscivorous	and	planktivorous	rockfish	 improved	 when	 bottom	 trawling	 was	 excluded.	 No	 changes	 were	 observed	 in	 inshore	rockfish	 in	 the	 latter	 case	 simply	because	 the	main	 gear	used	 for	 these	 fish	 is	 hook	and	 line.	The	higher	abundance	of	inshore	rockfish,	a	predator	on	shallow	water	benthic	fish,	caused	the	latter	to	decline	 when	 all	 fisheries	 were	 excluded.	 Likewise,	 squid	 declined	 in	 both	 scenarios	 because	 of	increased	abundance	of	their	predators,	piscivorous	and	planktivorous	rockfish.	In	interpreting	the	results	 for	 hake	 it	 is	 essential	 to	 keep	 in	mind	 that	 only	 a	 portion	 of	 the	 Pacific	 hake	 population	migrates	seasonally	 into	 the	Haida	Gwaii	waters,	so	 the	changes	predicted	by	the	Ecospace	model	are	not	applicable	to	the	entire	Pacific	hake	population.	The	 differences	 observed	 among	 the	 four	 MPA	 regions	 mainly	 due	 to	 variability	 in	 how	 habitat	capacity	for	the	functional	groups	and	sailing	cost	layers	for	the	fishing	fleets	overlay	each	other.	For	example,	 herring	 habitat	 capacity	 covers	 only	 a	 small	 portion	 of	 the	 HG-West	 MPA;	 increased	predation	pressure	from	dogfish,	inshore	rockfish,	and	hake	caused	declines	in	the	already	sparsely	HAIDA	GWAII	ECOSYSTEM	MODEL			 19	distributed	 adult	 and	 juvenile	 herring	 biomass	 in	 this	 region.	 High	 habitat	 capacity	 areas	 for	sablefish	are	on	 the	west	 coast	of	Haida	Gwaii	and	 in	 the	northern	part	of	 the	mainland,	 so	 these	areas	showed	the	strongest	responses	for	sablefish.		Unidirectional	responses	suggest	that	our	pilot	ecosystem	model	had	predictable	behaviour	and	no	inherent	 instabilities,	 with	 exception	 of	 salmon	 discussed	 below.	 Four	 general	 patterns	 were	apparent	in	the	results	across	the	seven	Ecospace	MPA	scenarios:		1. For	 both	 large	 and	 small	 MPAs,	 biomass	 and	 catch	 responses	 were	 similar	 in	 direction,	 but	differed	in	magnitude:	 large	MPAs	showed	bigger	changes	from	the	baseline	scenario,	because	the	large	MPAs	covered	~28%	of	the	total	modelled	area,	while	small	MPAs	covered	just	~9%.	This	nearly	three-fold	area	reduction	of	small	MPAs	was	responsible	for	their	reduced	biomass	and	catch	responses.	Trade-offs	between	the	size	and	 location	of	MPAs	to	enhance	production	without	putting	the	ecosystem	in	danger	could	be	a	potential	topic	for	further	research.	2. Increased	biomass	inside	MPAs	was	mirrored	in	the	adjacent	4km	spillover	zones,	as	the	higher	density	of	mobile,	species	in	the	MPAs	subsequently	dispersed	into	the	adjoining	areas.		3. For	most	 species,	 higher	biomasses	 and	 catches	were	observed	 in	 the	 spillover	 zones,	 though	the	higher	biomass	also	concentrated	fishing	pressure	there,	limiting	biomass	increases.	4. Higher	catches	in	spillover	zones	partially	compensated	for	the	loss	of	catch	under	the	no-take	scenarios	 for	most	species.	Except	 for	sablefish,	 the	overall	 loss	of	 catch	 for	 the	major	species	was	less	than	10%	when	no	fishing	was	allowed	inside	the	MPAs.			These	points	were	further	explored	by	examining	the	total	changes	in	biomass,	catch	and	by-catch	of	 exploited	 species	 (Figure	 14).	 The	model	 suggests	 we	may	 see	 larger	 increases	 in	 biomass	 in	larger	 MPAs,	 but	 only	 very	 small	 reductions	 in	 fishery	 catches,	 especially	 for	 small	 MPAs.	Surprisingly,	very	small	catch	losses	mean	that	the	trade-off	between	improvements	in	biomass	and	loss	of	catch	 looks	slightly	more	acceptable	 for	small	MPAs.	Moreover,	both	 large	and	small	MPAs	reduce	bycatch	in	all	three	scenarios,	partly	because	of	the	cessation	of	trawling	inside	the	MPAs.	No	trawling	in	the	MPAs	brings	many	of	the	benefits	of	biomass	increase	and	but	only	a	small	reduction	in	bycatch.	When	only	 traditional	Haida	 fisheries	 (‘FSC’)	 are	 allowed	 in	 the	MPAs,	 the	outcome	 is	almost	 the	 same	as	 in	 the	 fully	no-take	MPAs	 scenario,	 suggesting	 that	 traditional	Haida	 fisheries	have	smaller	ecosystem	impacts	than	commercial	fisheries.		Figure	 14.	 Model	 forecasts	 of	MPA	 scenarios	 in	 the	 HG	 spatial	ecosystem	 model:	 percentage	changes	 relative	 to	 baseline	levels.	Δ	Biomass	%	=	Percentage	change	 in	 total	 biomass	 of	harvested	 organisms;	Δ	 Catch	%	=	 Percentage	 change	 in	 total	catch;	Δ	Bycatch	%	=	Percentage	change	 in	 total	 bycatch.	 Three	spatial	 management	 scenarios:	no-take	MPAs	=	no	fishing	 inside	the	 MPAs;	 no-trawl	 MPAs	 =	 no	bottom	 trawling	 inside	 MPAs;	FSC	 in	 MPAs	 =	 only	 traditional	Haida	 fisheries	 inside	 the	 MPAs.		Large	 MPAs	 (~28%	 of	 area);	small	MPAs	(~9%	or	HG	area).			SPATIAL	MODELLING	IN	HAIDA	GWAII		 20	Figure	 15	 summarizes	 the	 results	 of	 the	 three	 extreme	 scenarios	 from	 the	 spatial	 modelling.	 As	expected,	halting	all	fishing	brings	a	recovery	of	many	exploited	populations	biomass,	with	overall	biomass	 increasing	almost	50%	with	no	 catch	or	bycatch.	This	 scenario	 is	 clearly	unrealistic	 as	 it	imposes	 extreme	 costs	on	all	 fisheries,	 and	 is	mainly	useful	 in	 tuning	 the	model	 to	 show	 realistic	recovery	 rates	 and	 levels.	 Equally	 unrealistic	 is	 the	 scenario	 doubling	 all	 fishing	 rates	 for	 the	 16	fisheries	 in	the	model.	This	 increased	catch	but	resulted	 in	an	almost	30%	loss	of	biomass,	a	70%	increase	in	bycatch,	and	a	reduction	in	biodiversity	as	some	organisms	were	almost	wiped	out.	The	third	 scenario	 shows	 that	 no-take	 MPAs	 help	 a	 little	 in	 reducing	 the	 costs	 of	 the	 heavy	 fishing	scenario,	 but	 neither	 large	 nor	 small	MPAs	 help	 enough	 to	make	 this	 heavy	 fishing	 policy	 option	viable.	Figure	 15.	 Model	forecasts	 of	 some	extreme	 scenarios	 in	the	 HG	 spatial	ecosystem	 model:	percentage	 changes	relative	 to	 baseline	levels.	 	 Δ	 Biomass	 %	 =	Percentage	 change	 in	total	 biomass	 of	harvested	 organisms;	Δ	Catch	 %	 =	 Percentage	change	 in	 total	 catch;	Δ	Bycatch	%	=	Percentage	change	 in	 total	 by-catch.	 Three	 spatial	management	 scenarios;	all	 no-take	 =	 no	 fishing	anywhere	 in	 the	region;	2x	 fishing	=	doubled	 fishing	rates	 for	 the	16	 fisheries	 in	 the	model	everywhere,	no	MPAs;	2x	 fishing	+	MPAs	=	double	 fishing	 rates	with	no-take	MPAs.	Forecasts	are	given	 for	 two	MPA	sizes;	MPAs	designed	by	Marxan	to	cover	28%	of	the	area	(large	MPAs)	and	for	9%	of	the	area	(small	MPAs).			Increased	 catches	 in	 the	 4km	 spillover	 zones	 around	 the	 margins	 of	 all	 the	 MPAs	 are	 shown	 in	Figure	 16.	 For	 the	 no-take	 MPAs,	 spillover	 catch	 for	 small	 MPAs	 is	 about	 50%	 higher	 than	 the	average	 catch	 over	 the	 entire	 model	 area,	 and	 more	 than	 double	 for	 the	 larger	 MPAs	 scenario.	Increased	spillover	catch	is	also	seen	in	the	scenario	with	no	trawling	inside	the	MPAs,	although	the	gains	are	slightly	smaller.	The	HG	model	gives	similar	spillover	findings	for	two	other	scenarios	(not	shown):	where	only	 traditional	Haida	 fisheries	are	allowed	 inside	 the	MPAs	and	 for	heavy	 fishing	with	MPAs.		Figure	 16.	 	Catches	 in	 the	combined	spillover	 regions	 around	 large	 and	small	 MPAs	 forecast	 by	 the	 Haida	Gwaii	 spatial	 ecosystem	 model	compared	 with	 average	 catches	 in	the	 entire	 region.	 Two	 spatial	management	 scenarios:	 No-take	MPAs	 =	 no	 fishing	 inside	 the	 MPAs;	No-trawl	MPAs	=	no	bottom	trawling	inside	the	MPAs.		HAIDA	GWAII	ECOSYSTEM	MODEL			 21	Figure	 17.	 Total	 biomass	 density	 of	exploited	 organisms	 inside	 MPAs,	inside	 spillover	 zones	 around	 the	MPAs,	compared	to	the	average	over	the	 entire	 region.	 Values	 were	forecast	 by	 the	 Haida	 Gwaii	 spatial	ecosystem	 model.	 Two	 spatial	management	 scenarios:	 No-take	MPAs	 =	 no	 fishing	 inside	 the	 MPAs;	2x	 fishing	 +	MPAs	 =	 doubled	 fishing	rates	for	the	16	fisheries	in	the	model	with	 no-take	 MPAs.	 Forecasts	 large	MPAs	 (designed	 by	Marxan	 to	 cover	28%	of	the	HG	area)	and	small	MPAs	(9%	of	the	HGV	area).			Figure	 17	 indicates	 that	 increased	 biomass	 of	 exploited	 organisms	 is	 the	 reason	 for	 the	 model	forecasting	higher	catches	inside	the	spillover	zone:	recovered	abundance	inside	the	no-take	MPAs	‘spills	over’	into	the	rest	of	the	ecosystem.	Biomass	inside	the	4km	spillover	zones	is	50%	above	the	average	for	the	entire	model	area.	The	spatial	model	shows	that	similar	advantages	occur	when	only	Haida	FSC	fisheries	are	allowed	inside	the	MPAs,	and	to	a	lesser	degree,	for	no-trawl	MPAs.		Figure	17	 also	 shows	 that	 the	 MPAs	 still	 provide	 spillover	 benefit	 under	 the	 heavy	 fishing	 scenario,	 as	shown	 in	 the	 right	 hand	 panels,	 although	 overall	 biomass	 is	 reduced	 under	 this	 scenario,	 as	indicated	 in	 Figure	15.	 	 Interestingly,	 the	model	 suggests	 that	 small	MPAs	 can	produce	 almost	 as	much	biomass	in	MPAs	and	spillover	zones	as	the	large	MPAs.	The	 sophistication	 of	 the	 EwE	 ecosystem	 simulation	 software,	 particularly	 its	 spatially-explicit	modelling	component,	Ecospace,	is	very	useful	for	modelling	policy	scenarios	in	an	area	like	Haida	Gwaii,	 where	 a	 great	 deal	 of	 local	 information	 is	 available	 on	 species	 and	 fisheries	 distributions.	However,	 the	predictions	of	Ecospace	are	highly	 influenced	by	 the	map	specifications,	and	careful	thought	 is	required	when	directly	using	maps	developed	in	previous	studies.	Previously,	Ecospace	responses	 were	 highly	 sensitive	 to	 dispersal	 rates—this	 was	 partly	 due	 to	 the	 limited	 facility	 in	specifying	functional	group	habitats	and	fisheries	distributions.	With	the	newer	version	of	Ecospace,	our	 judgement	 is	 that	 the	 preliminary	 model	 predictions	 are	 more	 robust	 and	 less	 sensitive	 to	dispersal	rates.	However,	 our	 modelling	 results	 need	 tempering	 with	 the	 realisation	 that,	 although	 we	 have	 put	effort	 into	updating	and	adapting	 the	ecosystem	model	 for	 the	Haida	Gwaii	ocean	area,	 the	model	still	requires	considerable	improvements	before	we	can	increase	our	confidence	in	the	results.	For	example,	salmon,	herring	and	sea	otter	diets	need	 improving,	and	the	 latter	requires	considerable	refinement	of	macrophytes	(kelp)	and	invertebrate	groups	in	the	model,	such	as	clams,	urchins	and	abalone.	 Moreover,	 the	 age	 structure	 of	 organisms	 in	 our	 model	 is	 weak:	 many	 groups	 such	 as	halibut	and	herring	require	more	realistic	age-class	structure	 than	has	been	built	 so	 far	using	 the	‘multi-stanza’	 EwE	 facility	 and	 other	 fish	 groups	 (e.g.,	 lingcod)	 are	 missing	 such	 representation	altogether.	 Improvements	 are	 currently	being	made	 to	modelled	herring	age	 structure,	 as	well	 as	herring	and	sea	otter	diets.	Problems	with	salmon	in	this	modelling	Salmon	life	histories	need	to	be	better	emulated	in	the	model,	partly	because	the	ecology	of	juvenile	habitats	and	food	web	interactions	are	not	explicitly	included,	and	partly	because	their	movements	are	 often	 driven	 by	 migration	 requirements	 as	 much	 as	 by	 feeding	 opportunities.	 The	 three	SPATIAL	MODELLING	IN	HAIDA	GWAII		 22	functional	groups	of	salmon	in	the	model,	transient	(sockeye,	chum,	pink),	chinook	and	coho	salmon	did	not	respond	spatially	 in	a	convincing	fashion,	unlike	most	other	groups	of	 fish.	The	simulation	responses	of	salmon	to	changes	in	fishing	pressures	in	Ecosim,	where	biomasses	can	be	driven	by	abundance	 or	 catch	 data,	 is	 acceptable	 despite	 the	 complicated	 ecology	 of	 salmon	 life	 histories.	However,	 the	 spatial	 responses	 of	 salmon	 in	 Ecospace	 are	 far	 less	 satisfactory.	 For	 example	 a	dramatic	 increase	 in	 salmon	 is	 not	 realistic	 just	 because	 there	 are	more	 euphausids	 to	 be	 eaten.	Most	salmon	are	migrating	through	Haida	Gwaii	from	other	areas	and	are	unlikely	to	respond	in	this	way	to	changes	in	local	food	availability.	The	number	of	salmon	in	the	ecosystem	is	determined	by	their	 freshwater	 spawning	 habitats	 on	 annual	 cycles	 (2-5	 years)	 and	won't	 increase	 because	 of	 a	short-term	increase	in	local	marine	food	availability.	Indeed,	the	salmon	in	our	model	feed	mostly	in	the	northern	Gulf	of	Alaska,	and	hence	would	probably	be	driven	by	oceanographic	dynamics	and	freshwater	 spawning	 habitats	 there,	 rather	 than	 conditions	 near	 Haida	 Gwaii.	 Furthermore,	transient	salmon	(chum,	pink,	sockeye)	in	the	Haida	Gwaii	region	are	unlikely	to	decrease	much	due	to	increased	predation	in	Haida	Gwaii	because	most	move	rapidly	through	the	area,	spending	only	a	limited	 time	 in	 the	 area	 during	migration,	 possibly	 a	 few	weeks	 in	 the	 spring	 during	 northward	migration	of	smolts	and	then	a	few	weeks	in	the	fall	as	migrating	adults.	Coho	and	chinook	salmon	are	represented	separately	in	our	model,	but	their	parameters,	even	after	considerable	adjustment,	appear	 to	 allow	 for	 too	 much	 increase	 in	 relation	 to	 the	 local	 food	 web.	 Ideally	 chum	 and	 pink	salmon	 should	 also	 be	 included	 explicitly	 as	 they	 are	 the	 main	 spawners	 in	 Haida	 Gwaii	 and	archaeological	data	from	Gwaii	Haanas	suggest	this	has	been	case	1000s	of	years.		Problems	with	herring	in	this	modelling	Since	the	herring	fishery	targets	spawning	aggregations,	considered	to	be	a	risky	operation	world-wide	(Sadovy	and	Dornier	2005),	a	 facility	to	emulate	seasonal	migration	 in	the	habitat	maps	and	seasonal	fishery	targets	 is	a	desirable	feature	to	be	built	 into	the	EwE	model	software	framework.	New	software	to	implement	this	seasonal	migration	has	been	developed	by	the	EwE	consortium	and	is	under	evaluation	in	2016.		Conclusions	The	 overarching	 conclusion	 of	 this	 pilot	 spatial	 modelling	 project	 on	 the	 Haida	 Gwaii	 marine	ecosystem	is	that	quite	modestly	sized	MPAs	can	achieve	conservation	goals	without	compromising	fishery	catch	yields.	Of	the	two	Marxan	MPA	options	investigated,	the	large	MPAs	representing	28%	of	 the	 total	 ocean	 area	 offer	 more	 benefits	 (increased	 biomasses,	 catches,	 spillover	 catches	 and	biodiversity)	than	small	MPAs	covering	9%	of	the	area.	Small	MPAs,	nevertheless,	still	provide	one	third	to	one	half	of	the	high-target	benefits.	Spillover	catches	in	the	zones	immediately	surrounding	the	MPAs	partially	compensated	for	the	loss	of	catches	from	the	closed	areas.	Food	web	interactions	add	 some	 complexity	 to	 this	 general	 finding,	 especially	 in	 the	 larger	 MPAs,	 as	 trophic	 cascades	become	established	in	closed	areas,	such	that	as	top	predators	increase,	prey	groups	tend	to	decline	and	lower	trophic	level	groups	may	increase	as	the	cascade	alternates	down	the	trophic	levels.		In	 this	 short	 pilot	 project,	 although	 the	 earlier	 NBC	 ecosystem	 model	 has	 been	 enhanced	 to	represent	Haida	Gwaii,	results	have	pinpointed	a	number	of	deficiencies	that	need	to	be	tackled	to	improve	 parameters	 for	 some	 predators,	 salmon,	 herring,	 invertebrates	 and	 fishery	 locations.	Nevertheless,	 as	 we	 have	 looked	 at	 changes	 proportional	 to	 the	 baseline,	 comparisons	 among	different	spatial	management	scenarios	are	likely	to	be	valid.		HAIDA	GWAII	ECOSYSTEM	MODEL			 23	The	spatial	modelling	results	suggest	that	improvements	to	biomass	of	commercial	fish	species	can	be	 obtained	with	 both	 the	 low-	 and	 high-target	MPAs.	 Closing	MPAs	 to	 trawling	 or	 all	 but	Haida	fisheries	yielded	benefits	almost	as	high	as	no-take	MPAs,	with	catch	losses	resulting	from	each	of	these	 options	 being	noticeably	moderated	by	 spillover	 effects.	Our	modelling	 results	 also	 suggest	that	doubling	current	fishing	pressure,	whether	everywhere	or	outside	no-take	MPAs,	would	cause	major	 depletions	 in	 the	 Haida	 Gwaii	 ecosystem,	 while	 complete	 closure	 to	 all	 fisheries	 and	 to	groundfish	 trawling	would	 enhance	 the	 pace	 of	 rebuilding,	 but	 at	 the	 cost	 of	 noticeable	 losses	 in	catch.	 These	 extreme	 scenarios	 are	 unrealistic	 policies,	 but	 the	 trade-offs	 resulting	 from	intermediate	scenarios	could	be	explored	in	more	detail	with	stakeholder	input.		Minor	 regional	 differences	were	 observed	within	 the	MPAs:	 siting	 of	 actual	MPAs	would	 balance	conservation	goals	with	socio-economic	goals	through	participatory	consultations.	An	intermediate	policy	 option	 might	 be	 to	 set	 up	 localized	 MPAs	 in	 a	 region	 which	 increased	 biomass	 without	reducing	fishery	catch	yields	dramatically,	particularly	in	relation	to	catches	in	the	spillover	zones,	which	 could	 be	 targeted	 by	 fisheries	 and	 thus	 lower	 fishing	 costs.	 This	 pilot	 study	 suggests	 that	spatially	explicit	modelling	results	are	able	 to	 inform	the	selection	of	MPA	siting	and	size	 to	meet	and	 balance	 conflicting	 policy	 objectives.	 A	 particular	 feature	 of	 this	 method	 is	 the	 explicit	visualization	of	 impacts	of	different	marine	spatial	management	scenarios,	which	should	 facilitate	multi-stakeholder	discussions	to	set	viable	policy.		In	this	pilot	project,	we	were	able	to	make	a	significant	innovation	in	Ecospace	modelling	by	using	GIS	maps	 to	 generate	habitat	 capacity	maps	 for	 the	 first	 time.	The	HOTT	 supplied	much	valuable	information	from	the	GIS	layers	used	in	the	MaPP	Marxan	analysis.	But	many	of	the	habitat	capacity	maps	 need	 to	 be	 improved:	 we	 had	 to	make	 a	 lot	 of	 inferences	 to	 cover	 obvious	 anomalies	 and	inadequacies	in	this	pilot	version.	Although	we	have	already	used	published	Haida	TEK	in	this	work,	some	of	 these	species	and	fishery	maps	could	be	greatly	 improved	through	 interviews	with	Haida	Gwaii	fishers	and	other	inhabitants.	For	simplicity,	in	this	report	we	used	two	Marxan	MPA	options,	but	an	improved	model	could	be	used	to	examine	actual	spatial	management	options	put	forward	by	Haida	Gwaii	marine	planners	under	the	MaPP	process	and	now	published	by	the	Haida	Nation	and	the	BC	Government	(MaPP	2015).	Moreover,	Ecospace	can	be	used	to	search	 for	 improved	spatial	arrangements	 of	 MPAs,	 providing	 an	 independent	 mapping	 framework	 to	 Marxan.	 An	 improved	model	might	 also	 be	 used	 to	 examine	 in	 detail	 the	 consequences	 of	 climate	 change	 in	 this	 ocean	area.		Acknowledgements	We	would	 like	 to	 thank	Mr	 Jeroen	 Steenbeek,	 and	Dr	 Cameron	Ainsworth	 for	 suggestions	 on	 the	modelling	 methods	 and	 Russ	 Jones	 for	 comments	 on	 the	 draft	 report.	 We	 thank	 HOTT	 team	members	Chris	McDougall,	Jason	Thompson	and	Russ	Jones	for	providing	data,	maps	and	advice	on	the	Haida	Gwaii	ecosystem,	its	habitats	and	fisheries.	This	work	was	funded	by	a	grant	from	HOTT	and	the	Council	of	the	Haida	Nation.		Literature	Cited	Ainsworth,	 C.H.	 (2006)	 Strategic	Marine	Ecosystem	Restoration	 in	Northern	British	 Columbia.	Unpublished	Ph.D.	dissertation:	University	of	British	Columbia.	Ainsworth,	 C.	 and	 Pitcher,	 T.J.	 (2004)	 Estimating	 the	 effects	 of	 predator-prey	 vulnerability	 settings	 on	Ecosim’s	 dynamic	 forecasts.	 In	 T.J.	 Pitcher	 (Ed.)	 Back	 to	 the	 Future:	 Advances	 in	 Methodology	 for	Modeling	 and	Evaluating	 Past	 Ecosystems	 as	 Future	 Policy	Goals.	 Fisheries	 Centre	Research	Reports	12(1):	45-47.		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This can be mathematically re-expressed as: !! ∗ ! ! ! = !! + !! ∗ ! ! !!!!! ∗ !"!" + !! + !"! + !! ∗ ! ! ! ∗ ! − !!!                  Equation 1 where,  subscript i and j represent prey and predator respectively;  Bi and Bj are biomasses of prey (i) and predator (j), respectively; P/Bi is the production/biomass ratio;  Yi is the total fishery catch rate of group (i); Q/Bj is the consumption/biomass ratio; DCij is the fraction of prey (i) in the average diet of predator (j); Ei is the net migration rate (emigration – immigration); and BAi is the biomass accumulation rate for group (i). EEi is the ecotrophic efficiency; the fraction of group mortality explained in the model   The second assumption in Ecopath is that consumption within a group equals the sum of production, respiration and unassimilated food, as in eq 2.  ( ) ( ) ( ) ( ) ( ) GSBQBPTMQGSBPBBQB ⋅+⋅−−⋅−+⋅=⋅ 11/                                     Equation 2  where, GS is the proportion of food unassimilated; and TM is the trophic mode expressing the degree of heterotrophy; 0 and 1 represent autotrophs and heterotrophs, respectively.  Intermediate values represent facultative consumers.  In Ecosim, time dynamic changes in biomass are modelled as  ( ) iiiiinjijnjjiii BeFMIQQgdtdB⋅++−+−= ∑∑== 11	 																																																					Equation 3  where,  dBi/dt represents biomass growth rate of group (i) during the interval dt; gi represents the net growth efficiency (production/consumption ratio); Ii is the immigration rate; Mi and Fi are natural and fishing mortality rates of group (i), respectively; ei is emigration rate; and APPENDIX	A		 27	Qji is consumption rate of predator (j) on prey (i) according to the assumptions of foraging arena theory  Further the calculation of consumption rate is as follows: 푄푖푗 = 푎푖푗푣푖푗퐵푖퐵푗푇푖푇푗푆푖푗푀푖푗/퐷푗푣푖푗!푣푖푗푇푖푀푖푗!푎푖푗푀푖푗퐵푗푆푖푗푇푗/퐷푗                               Equation 4  where, aij is the rate of effective search for i by j,  vij is the is the predator-prey vulnerability parameter for moving from available to unavailable states, Ti represents prey relative feeding time,  Tj the predator relative feeding time,  Sij the user-defined seasonal or long term forcing effects,  Mij the mediation forcing effects, and  Dj represents effects of handling time as a limit to consumption rate.   	EWE	MODEL	PARAMETERS			 28	Appendix	B.		EwE	model	parameters		Ecopath	Basic	Input	parameters		 	Group	name Trophic	levelB(t/km²) P/B	(/year) Q/B	(/year) EE P/Q	(/year)1 Sea	Otters 3.613 0.000 0.130 101.500 0.010 0.0012 Gray	whales 3.025 0.030 0.060 5.300 0.085 0.0113 Humpback	whales 3.652 0.185 0.060 4.600 0.000 0.0134 Minke	whales 3.634 0.030 0.090 6.300 0.057 0.0145 Blue	whales 3.200 0.006 0.040 3.500 0.001 0.0116 Fin	whales 3.295 0.035 0.050 4.100 0.000 0.0127 Sei	whales 3.241 0.000 0.060 5.200 0.005 0.0128 Sperm	whales 4.135 0.010 0.050 5.100 0.000 0.0109 Resident	orcas 4.625 0.003 0.090 7.700 0.000 0.01210 Transient	orcas 5.051 0.002 0.090 7.700 0.000 0.01211 Small	odontocetes 4.081 0.100 0.170 16.000 0.059 0.01112 Seals 4.162 0.125 0.171 15.100 0.115 0.01113 Sea	lions 4.116 0.125 0.171 15.100 0.082 0.01114 Seabirds 3.612 0.007 0.100 105.200 0.026 0.00115 Transient	salmon 3.116 0.208 2.480 8.330 0.818 0.29816 Coho	salmon 3.713 0.024 2.760 13.800 0.580 0.20017 Chinook	salmon 3.636 0.034 2.760 13.800 0.716 0.20018 Small	squid 2.862 1.090 6.023 34.675 1.000 0.17419 Large	squid 3.119 0.765 6.023 34.675 0.953 0.17420 Ratfish 3.390 0.517 0.099 1.400 0.633 0.07121 Dogfish 3.556 0.909 0.099 2.719 0.909 0.03622 Pollock 3.294 0.491 0.478 2.280 0.993 0.20923 Forage	fish 2.960 8.478 1.432 8.395 0.998 0.17124 Hake 3.551 0.820 0.550 2.750 1.000 0.20025 Eulachon 3.059 1.660 1.432 8.395 0.888 0.17126 Juvenile	herring 3.020 0.895 1.000 11.516 0.864 0.08727 Adult	herring 3.180 2.600 0.800 5.840 0.963 0.13728 POP 3.179 0.623 0.197 2.246 0.974 0.08729 Inshore	rockfish 3.495 0.100 0.190 5.688 0.950 0.03330 Piscivorous	rockfish 3.303 0.660 0.060 1.267 0.962 0.04731 Planktivorous	rockfish 3.359 1.343 0.100 2.248 0.976 0.04432 Arrowtooth	flounder 3.566 1.748 0.234 2.007 0.994 0.11633 Flatfish 3.193 0.495 1.465 5.187 0.698 0.28234 Juvenile	halibut 3.801 0.356 0.500 2.434 0.976 0.20535 Adult	halibut 3.857 0.900 0.400 1.095 0.546 0.36536 Pacific	cod 3.372 0.252 1.553 5.236 0.972 0.29737 Sablefish 3.487 0.388 0.375 4.733 0.876 0.07938 Lingcod 4.043 0.070 0.977 3.300 0.964 0.29639 Shallowwater	benthic	fish 3.441 0.509 1.500 5.256 0.988 0.28540 Small	demersal	elasmobranchs 3.566 0.300 0.320 1.240 0.903 0.25841 Large	demersal	sharks 3.769 0.025 0.130 1.240 0.049 0.10542 Salmon	sharks 4.227 0.020 0.200 1.200 0.000 0.16743 Blue	sharks 3.930 0.020 0.170 0.800 0.000 0.21344 Large	crabs 2.857 0.456 1.500 5.000 0.921 0.30045 Small	crabs 3.054 0.650 3.500 14.000 0.734 0.25046 Commercial	shrimp 2.660 0.200 11.475 45.900 0.414 0.25047 Epifaunal	invertebrates 2.060 13.448 1.448 16.089 0.838 0.09048 Infaunal	carnivorous	invertebrates 2.060 13.245 2.000 22.222 0.200 0.09049 Infaunal	detritivorous	invertebrates 2.000 34.305 1.349 14.989 0.747 0.09050 Carnivorous	jellyfish 2.163 3.000 18.000 60.000 0.691 0.30051 Euphausiids 2.200 10.000 6.600 24.820 0.898 0.26652 Copepods 2.000 5.250 27.000 90.000 0.816 0.30053 Corals	and	sponges 2.000 1.929 0.010 2.000 0.104 0.00554 Macrophytes 1.000 5.280 5.256 0.000 0.00855 Phytoplankton 1.000 15.406 178.502 0.000 0.24456 Detritus 1.000 10.000 0.452APPENDIX	B			 29	Diet	matrix		Prey	\	predator 1 2 3 4 5 6 7 8 9 10 111 Sea	Otters 0.0002 Gray	whales 0.0123 Humpback	whales 0.0004 Minke	whales 0.0125 Blue	whales 0.0006 Fin	whales 0.0007 Sei	whales 0.0008 Sperm	whales 0.0009 Resident	orcas10 Transient	orcas11 Small	odontocetes 0.07512 Seals 0.10013 Sea	lions 0.05114 Seabirds 0.00015 Transient	salmon 0.010 0.01016 Coho	salmon 0.010 0.00317 Chinook	salmon 0.380 0.00518 Small	squid 0.040 0.055 0.18019 Large	squid 0.050 0.376 0.09220 Ratfish 0.00121 Dogfish 0.005 0.00822 Pollock 0.100 0.013 0.02523 Forage	fish 0.225 0.233 0.005 0.075 0.055 0.25524 Hake 0.008 0.005 0.02025 Eulachon 0.022 0.018 0.04226 Juvenile	herring 0.025 0.018 0.05027 Adult	herring 0.200 0.100 0.038 0.25028 POP 0.00229 Inshore	rockfish30 Piscivorous	rockfish 0.020 0.00131 Planktivorous	rockfish 0.020 0.00532 Arrowtooth	flounder 0.001 0.00533 Flatfish 0.001 0.00334 Juvenile	halibut 0.00335 Adult	halibut 0.001 0.00536 Pacific	cod 0.02537 Sablefish 0.005 0.01038 Lingcod 0.002 0.00139 Shallowwater	benthic	fish 0.100 0.00240 Small	demersal	elasmobranchs 0.008 0.00141 Large	demersal	sharks 0.00242 Salmon	sharks43 Blue	sharks44 Large	crabs 0.01045 Small	crabs 0.20046 Commercial	shrimp47 Epifaunal	invertebrates 0.500 0.05048 Infaunal	carnivorous	invertebrates 0.07549 Infaunal	detritivorous	invertebrates 0.35050 Carnivorous	jellyfish51 Euphausiids 0.025 0.428 0.333 0.475 0.525 0.20052 Copepods 0.020 0.113 0.22553 Corals	and	sponges54 Macrophytes55 Phytoplankton56 Detritus57 Import 0.500 0.100 0.300 0.500 0.250 0.500 0.500 0.600 0.750EWE	MODEL	PARAMETERS			 30		Prey	\	predator 12 13 14 15 16 17 18 19 20 21 221 Sea	Otters2 Gray	whales3 Humpback	whales4 Minke	whales5 Blue	whales6 Fin	whales7 Sei	whales8 Sperm	whales9 Resident	orcas10 Transient	orcas11 Small	odontocetes12 Seals13 Sea	lions14 Seabirds15 Transient	salmon 0.010 0.100 0.020 0.01016 Coho	salmon 0.001 0.003 0.00117 Chinook	salmon 0.004 0.005 0.00318 Small	squid 0.100 0.090 0.050 0.200 0.174 0.066 0.00619 Large	squid 0.030 0.057 0.045 0.190 0.100 0.123 0.00620 Ratfish 0.00621 Dogfish 0.010 0.00122 Pollock 0.001 0.025 0.02823 Forage	fish 0.300 0.375 0.270 0.167 0.433 0.081 0.150 0.278 0.060 0.12524 Hake 0.020 0.020 0.010 0.01925 Eulachon 0.030 0.035 0.079 0.033 0.067 0.014 0.025 0.056 0.015 0.01926 Juvenile	herring 0.070 0.025 0.050 0.01527 Adult	herring 0.140 0.100 0.060 0.040 0.050 0.01828 POP 0.001 0.005 0.00429 Inshore	rockfish 0.001 0.00130 Piscivorous	rockfish 0.001 0.00331 Planktivorous	rockfish 0.002 0.006 0.00132 Arrowtooth	flounder 0.025 0.030 0.01533 Flatfish 0.030 0.030 0.04034 Juvenile	halibut 0.010 0.01035 Adult	halibut 0.040 0.03036 Pacific	cod 0.061 0.020 0.010 0.01037 Sablefish 0.005 0.00938 Lingcod 0.005 0.00339 Shallowwater	benthic	fish 0.103 0.020 0.06240 Small	demersal	elasmobranchs 0.001 0.00241 Large	demersal	sharks42 Salmon	sharks43 Blue	sharks44 Large	crabs 0.004 0.03745 Small	crabs 0.041 0.02646 Commercial	shrimp47 Epifaunal	invertebrates 0.002 0.002 0.041 0.183 0.052 0.05348 Infaunal	carnivorous	invertebrates 0.200 0.019 0.01349 Infaunal	detritivorous	invertebrates 0.080 0.00850 Carnivorous	jellyfish 0.036 0.100 0.060 0.060 0.02951 Euphausiids 0.112 0.150 0.360 0.450 0.380 0.107 0.203 0.139 0.36052 Copepods 0.156 0.150 0.149 0.041 0.142 0.37153 Corals	and	sponges54 Macrophytes55 Phytoplankton56 Detritus 0.041 0.316 0.344 0.08057 Import 0.600APPENDIX	B			 31		Prey	\	predator 23 24 25 26 27 28 29 30 31 32 331 Sea	Otters2 Gray	whales3 Humpback	whales4 Minke	whales5 Blue	whales6 Fin	whales7 Sei	whales8 Sperm	whales9 Resident	orcas10 Transient	orcas11 Small	odontocetes12 Seals13 Sea	lions14 Seabirds15 Transient	salmon16 Coho	salmon17 Chinook	salmon18 Small	squid 0.020 0.010 0.069 0.086 0.15119 Large	squid 0.010 0.079 0.086 0.15120 Ratfish21 Dogfish22 Pollock 0.005 0.02223 Forage	fish 0.100 0.060 0.020 0.024 0.108 0.09124 Hake 0.015 0.00625 Eulachon 0.001 0.012 0.005 0.005 0.047 0.01826 Juvenile	herring 0.080 0.100 0.010 0.01527 Adult	herring 0.120 0.020 0.030 0.04528 POP 0.020 0.00229 Inshore	rockfish 0.000 0.00130 Piscivorous	rockfish 0.001 0.000 0.00031 Planktivorous	rockfish 0.00232 Arrowtooth	flounder 0.00133 Flatfish 0.01334 Juvenile	halibut35 Adult	halibut36 Pacific	cod 0.00337 Sablefish38 Lingcod 0.002 0.00239 Shallowwater	benthic	fish 0.045 0.05040 Small	demersal	elasmobranchs 0.02041 Large	demersal	sharks42 Salmon	sharks43 Blue	sharks44 Large	crabs 0.005 0.01345 Small	crabs 0.107 0.130 0.013 0.05646 Commercial	shrimp 0.155 0.095 0.002 0.05747 Epifaunal	invertebrates 0.100 0.100 0.050 0.260 0.029 0.04848 Infaunal	carnivorous	invertebrates 0.354 0.33349 Infaunal	detritivorous	invertebrates 0.148 0.45050 Carnivorous	jellyfish 0.270 0.200 0.037 0.00551 Euphausiids 0.200 0.403 0.100 0.100 0.900 0.794 0.152 0.091 0.563 0.106 0.00252 Copepods 0.300 0.100 0.600 0.900 0.100 0.185 0.005 0.19053 Corals	and	sponges54 Macrophytes55 Phytoplankton56 Detritus 0.130 0.110 0.17157 ImportEWE	MODEL	PARAMETERS			 32		Prey	\	predator 34 35 36 37 38 39 40 41 42 43 441 Sea	Otters2 Gray	whales3 Humpback	whales4 Minke	whales5 Blue	whales6 Fin	whales7 Sei	whales8 Sperm	whales9 Resident	orcas10 Transient	orcas11 Small	odontocetes12 Seals 0.03413 Sea	lions 0.03414 Seabirds 0.00115 Transient	salmon 0.125 0.01316 Coho	salmon 0.015 0.00317 Chinook	salmon 0.015 0.00318 Small	squid 0.032 0.064 0.018 0.001 0.050 0.003 0.12519 Large	squid 0.032 0.064 0.018 0.001 0.200 0.004 0.05020 Ratfish 0.010 0.070 0.01021 Dogfish 0.030 0.002 0.00022 Pollock 0.005 0.011 0.010 0.001 0.00023 Forage	fish 0.055 0.014 0.194 0.182 0.140 0.198 0.050 0.035 0.01324 Hake 0.026 0.002 0.01325 Eulachon 0.011 0.003 0.039 0.039 0.063 0.040 0.010 0.001 0.00026 Juvenile	herring 0.050 0.015 0.130 0.00127 Adult	herring 0.020 0.011 0.010 0.011 0.003 0.00628 POP 0.003 0.005 0.000 0.01229 Inshore	rockfish 0.006 0.00130 Piscivorous	rockfish 0.001 0.001 0.001 0.00031 Planktivorous	rockfish 0.006 0.003 0.011 0.010 0.001 0.00032 Arrowtooth	flounder 0.010 0.090 0.030 0.010 0.011 0.050 0.00233 Flatfish 0.020 0.103 0.005 0.093 0.028 0.020 0.001 0.000 0.01034 Juvenile	halibut 0.060 0.010 0.003 0.099 0.01035 Adult	halibut 0.028 0.04036 Pacific	cod 0.008 0.050 0.010 0.003 0.089 0.010 0.001 0.00037 Sablefish 0.002 0.016 0.050 0.028 0.00038 Lingcod 0.005 0.007 0.010 0.000 0.01039 Shallowwater	benthic	fish 0.055 0.060 0.010 0.028 0.01040 Small	demersal	elasmobranchs 0.020 0.005 0.020 0.00041 Large	demersal	sharks42 Salmon	sharks43 Blue	sharks44 Large	crabs 0.240 0.155 0.250 0.06145 Small	crabs 0.300 0.145 0.014 0.006 0.076 0.181 0.125 0.10046 Commercial	shrimp 0.060 0.080 0.081 0.004 0.125 0.01547 Epifaunal	invertebrates 0.050 0.100 0.143 0.015 0.066 0.037 0.150 0.061 0.39548 Infaunal	carnivorous	invertebrates 0.075 0.333 0.150 0.10549 Infaunal	detritivorous	invertebrates 0.184 0.096 0.050 0.07550 Carnivorous	jellyfish 0.19051 Euphausiids 0.058 0.386 0.025 0.02452 Copepods 0.029 0.04853 Corals	and	sponges54 Macrophytes55 Phytoplankton56 Detritus 0.075 0.097 0.114 0.011 0.036 0.027 0.025 0.220 0.000 0.30057 Import 0.750 0.750APPENDIX	B			 33			 	Prey	\	predator 45 46 47 48 49 50 51 52 531 Sea	Otters2 Gray	whales3 Humpback	whales4 Minke	whales5 Blue	whales6 Fin	whales7 Sei	whales8 Sperm	whales9 Resident	orcas10 Transient	orcas11 Small	odontocetes12 Seals13 Sea	lions14 Seabirds15 Transient	salmon16 Coho	salmon17 Chinook	salmon18 Small	squid19 Large	squid20 Ratfish21 Dogfish22 Pollock23 Forage	fish24 Hake25 Eulachon26 Juvenile	herring27 Adult	herring28 POP29 Inshore	rockfish30 Piscivorous	rockfish31 Planktivorous	rockfish32 Arrowtooth	flounder33 Flatfish34 Juvenile	halibut35 Adult	halibut36 Pacific	cod37 Sablefish38 Lingcod39 Shallowwater	benthic	fish40 Small	demersal	elasmobranchs41 Large	demersal	sharks42 Salmon	sharks43 Blue	sharks44 Large	crabs45 Small	crabs46 Commercial	shrimp47 Epifaunal	invertebrates 0.60048 Infaunal	carnivorous	invertebrates 0.30049 Infaunal	detritivorous	invertebrates 0.100 0.100 0.060 0.06050 Carnivorous	jellyfish 0.06051 Euphausiids 0.300 0.01052 Copepods 0.200 0.081 0.20053 Corals	and	sponges54 Macrophytes 0.00155 Phytoplankton 0.800 1.00056 Detritus 0.400 0.939 0.940 1.000 0.849 1.00057 ImportEWE	MODEL	PARAMETERS			 34	Ecosim	Vulnerability	ParametersPrey	\	predator 1 2 3 4 5 6 7 8 9 10 11Sea	Otters 4.000Gray	whales 4.000Humpback	whales 4.000Minke	whales 4.000Blue	whales 4.000Fin	whales 4.000Sei	whales 4.000Sperm	whales 4.000Resident	orcasTransient	orcasSmall	odontocetes 4.000Seals 4.000Sea	lions 4.000Seabirds 4.000Transient	salmon 4.000 4.000Coho	salmon 4.000 4.000Chinook	salmon 4.000 4.000Small	squid 4.200 4.000 4.000Large	squid 4.200 4.000 4.000Ratfish 4.000Dogfish 4.000 4.000Pollock 3.500 4.000Forage	fish 3.500 3.500 3.500 3.500 3.500 4.000Hake 3.500 4.000 4.000Eulachon 3.500 3.500 4.000Juvenile	herring 3.500 3.500 4.000Adult	herring 3.500 3.500 3.500 4.000POP 4.000Inshore	rockfishPiscivorous	rockfish 4.000 4.000Planktivorous	rockfish 4.000 4.000Arrowtooth	flounder 4.000 4.000Flatfish 4.000 4.000Juvenile	halibut 4.000Adult	halibut 4.000 4.000Pacific	cod 4.000Sablefish 4.000 4.000Lingcod 4.000 4.000Shallowwater	benthic	fish 4.200 4.000Small	demersal	elasmobranchs 4.000 4.000Large	demersal	sharks 4.000Salmon	sharksBlue	sharksLarge	crabs 4.200Small	crabs 4.200Commercial	shrimpEpifaunal	invertebrates 4.200 3.100Infaunal	carnivorous	invertebrates 3.100Infaunal	detritivorous	invertebrates 3.100Carnivorous	jellyfishEuphausiids 3.100 3.500 3.500 3.500 3.500 3.500Copepods 3.500 3.500 3.500Corals	and	spongesMacrophytesPhytoplanktonDetritusAPPENDIX	B			 35	Prey	\	predator 12 13 14 15 16 17 18 19 20 21 22Sea	OttersGray	whalesHumpback	whalesMinke	whalesBlue	whalesFin	whalesSei	whalesSperm	whalesResident	orcasTransient	orcasSmall	odontocetesSealsSea	lionsSeabirdsTransient	salmon 4.100 4.100 4.200 4.100Coho	salmon 4.100 4.100 4.100Chinook	salmon 4.100 4.100 4.100Small	squid 4.100 4.100 4.200 3.200 4.100 3.600Large	squid 4.100 4.100 4.200 3.200 4.100 3.600Ratfish 4.100Dogfish 4.100 4.100Pollock 4.100 4.100Forage	fish 4.100 4.100 4.200 2.800 3.200 3.700 4.100 3.600Hake 4.100 4.100 4.100 3.600Eulachon 4.100 4.100 4.200 2.800 3.200 3.700 4.100 3.600Juvenile	herring 4.100 4.100 4.200 4.100Adult	herring 4.100 4.100 4.200 4.100POP 4.100 4.100 4.100Inshore	rockfish 4.100 4.100Piscivorous	rockfish 4.100 4.100Planktivorous	rockfish 4.100 4.100 4.100Arrowtooth	flounder 4.100 4.100 4.100Flatfish 4.100 4.100 4.100Juvenile	halibut 4.100 4.100Adult	halibut 4.100 4.100Pacific	cod 4.100 4.100 4.100Sablefish 4.100 4.100Lingcod 4.100 4.100Shallowwater	benthic	fish 4.100 4.100 4.100Small	demersal	elasmobranchs 4.100 4.100Large	demersal	sharksSalmon	sharksBlue	sharksLarge	crabs 4.100 4.100Small	crabs 4.200 4.100Commercial	shrimpEpifaunal	invertebrates 4.100 4.100 4.200 3.700 4.100 3.600Infaunal	carnivorous	invertebrates 3.700 4.100 3.600Infaunal	detritivorous	invertebrates 3.700 4.100Carnivorous	jellyfish 4.200 2.800 3.200 4.100Euphausiids 4.200 2.800 3.200 3.700 4.100 3.600Copepods 4.200 2.800 3.200 4.100 3.600Corals	and	spongesMacrophytesPhytoplanktonDetritus 4.200 2.800 3.200 4.100EWE	MODEL	PARAMETERS			 36	 Prey	\	predator 23 24 25 26 27 28 29 30 31 32 33Sea	OttersGray	whalesHumpback	whalesMinke	whalesBlue	whalesFin	whalesSei	whalesSperm	whalesResident	orcasTransient	orcasSmall	odontocetesSealsSea	lionsSeabirdsTransient	salmonCoho	salmonChinook	salmonSmall	squid 3.900 3.400 3.600 3.700 4.100Large	squid 3.400 3.600 3.700 4.100RatfishDogfishPollock 3.900 1.010Forage	fish 3.900 3.900 3.600 3.700 4.100 3.400Hake 3.900 3.600Eulachon 3.900 3.900 3.600 3.700 4.100 3.400Juvenile	herring 3.900 3.900 3.700 4.100Adult	herring 3.900 3.900 3.700 4.100POP 3.600 4.100Inshore	rockfish 3.900 4.100Piscivorous	rockfish 3.900 3.600 4.100Planktivorous	rockfish 4.100Arrowtooth	flounder 4.100Flatfish 4.100Juvenile	halibutAdult	halibutPacific	cod 4.100SablefishLingcod 4.100 3.400Shallowwater	benthic	fish 3.900 4.100Small	demersal	elasmobranchs 3.600Large	demersal	sharksSalmon	sharksBlue	sharksLarge	crabs 3.900 4.100Small	crabs 3.900 3.600 4.100 3.400Commercial	shrimp 3.900 3.900 3.600 4.100Epifaunal	invertebrates 3.000 3.100 3.900 3.600 4.100 3.400Infaunal	carnivorous	invertebrates 3.900 3.400Infaunal	detritivorous	invertebrates 3.600 3.400Carnivorous	jellyfish 3.000 3.100 3.600 3.700Euphausiids 3.000 3.900 3.100 3.400 3.900 3.600 3.700 4.100 3.400Copepods 3.000 3.900 3.100 3.400 3.600 3.700Corals	and	spongesMacrophytesPhytoplanktonDetritus 3.000 3.600 4.100APPENDIX	B			 37	Prey	\	predator 34 35 36 37 38 39 40 41 42 43 44Sea	OttersGray	whalesHumpback	whalesMinke	whalesBlue	whalesFin	whalesSei	whalesSperm	whalesResident	orcasTransient	orcasSmall	odontocetesSeals 4.300Sea	lions 4.300Seabirds 4.300Transient	salmon 4.300 4.300Coho	salmon 4.300 4.300Chinook	salmon 4.300 4.300Small	squid 4.500 4.600 3.900 4.100 4.300 4.300 4.300Large	squid 4.500 4.600 3.900 4.100 4.300 4.300 4.300Ratfish 4.300 4.300Dogfish 4.300 4.300 4.300Pollock 3.900 5.000 4.300 4.300 4.300Forage	fish 4.500 4.600 3.700 3.900 5.000 4.100 4.300 4.300 4.300Hake 5.000 4.300 4.300Eulachon 4.500 4.600 3.700 3.900 5.000 4.100 4.300 4.300 4.300Juvenile	herring 4.500 3.700 5.000 4.300Adult	herring 4.600 3.700 3.900 5.000 4.300 4.300POP 4.500 4.600 3.900 5.000Inshore	rockfish 5.000 4.300Piscivorous	rockfish 5.000 4.300 4.300 4.300Planktivorous	rockfish 4.600 3.900 5.000 4.300 4.300 4.300Arrowtooth	flounder 4.500 4.600 3.700 3.900 5.000 4.300 4.300Flatfish 4.500 4.600 3.900 5.000 4.300 4.300 4.300 2.800Juvenile	halibut 4.600 3.700 3.900 5.000 4.300Adult	halibut 5.000 4.300Pacific	cod 4.500 4.600 3.700 3.900 5.000 4.300 4.300 4.300Sablefish 3.700 3.900 4.300 4.300 4.300Lingcod 4.600 3.700 5.000 4.100 4.300Shallowwater	benthic	fish 4.500 3.700 4.100 4.300 4.300Small	demersal	elasmobranchs 4.600 3.700 4.300 4.300Large	demersal	sharksSalmon	sharksBlue	sharksLarge	crabs 4.500 4.600 4.300 4.300Small	crabs 4.500 4.600 3.700 3.900 5.000 4.100 4.300Commercial	shrimp 4.500 3.900 5.000 4.100 4.300 2.800Epifaunal	invertebrates 4.500 4.600 3.700 3.900 5.000 4.100 4.300 4.300 2.800Infaunal	carnivorous	invertebrates 3.700 4.100 4.300 2.800Infaunal	detritivorous	invertebrates 3.700 4.100 4.300 2.800Carnivorous	jellyfish 3.900Euphausiids 3.700 3.900 4.100 4.300Copepods 3.700 4.100Corals	and	spongesMacrophytesPhytoplanktonDetritus 4.500 4.600 3.700 3.900 5.000 4.100 4.300 4.300 4.300 2.800EWE	MODEL	PARAMETERS			 38		 	Prey	\	predator 45 46 47 48 49 50 51 52 53Sea	OttersGray	whalesHumpback	whalesMinke	whalesBlue	whalesFin	whalesSei	whalesSperm	whalesResident	orcasTransient	orcasSmall	odontocetesSealsSea	lionsSeabirdsTransient	salmonCoho	salmonChinook	salmonSmall	squidLarge	squidRatfishDogfishPollockForage	fishHakeEulachonJuvenile	herringAdult	herringPOPInshore	rockfishPiscivorous	rockfishPlanktivorous	rockfishArrowtooth	flounderFlatfishJuvenile	halibutAdult	halibutPacific	codSablefishLingcodShallowwater	benthic	fishSmall	demersal	elasmobranchsLarge	demersal	sharksSalmon	sharksBlue	sharksLarge	crabsSmall	crabsCommercial	shrimpEpifaunal	invertebratesInfaunal	carnivorous	invertebrates 3.100Infaunal	detritivorous	invertebrates 3.000 2.400 1.300 1.300Carnivorous	jellyfish 1.500Euphausiids 2.400 1.500Copepods 2.400 1.500 1.600Corals	and	spongesMacrophytes 1.300Phytoplankton 1.600 1.200Detritus 2.400 1.300 1.300 1.200 1.500 1.200APPENDIX	B			 39	Fisheries 																	Gear/Species 15 16 17 21 22 24 27 28 29 30 31 32 33 34 35 36 37 38 40 44 46 47 54Ground-fish	trawl 0.001 0.007 0.060 0.000 0.023 0.077 0.067 0.058 0.000 0.000 0.051 0.000 0.019 0.029 0.000Sable 0.038Herring	gillnet 0.155Ground	H+L 0.003 0.002Salmon	gillnet 0.075 0.020 0.015Crab	trap 0.026Shrimp	/	prawn	trap 0.004Other	Inv. 0.078Halibut	H+L 0.004 0.028 0.031 0.003 0.002Salmon	troll 0.003 0.001 0.000Salmon	seine 0.067 0.000Salmon	troll	freezer 0.010 0.001 0.001Herring	seine 0.087Shrimp	trawl 0.033Longline 0.030Recrea-tional 0.001 0.002 0.009 0.003 0.002 0.001 0.016 0.003 0.001 0.000 0.000Hake 0.252HG	salmon 0.000 0.000HG	herring	SOK 0.000HG_Clam 0.003HG	Seaweed 0.000HABITAT	AND	FISHERY	MAPS		 40	Appendix	C.	Habitat	Capacity	and	Fishery	Intensity	Maps	 This first section presents the habitat capacity maps set up for 43 of the model groups.    APPENDIX	C			 41	     HABITAT	AND	FISHERY	MAPS		 42	      APPENDIX	C			 43	     HABITAT	AND	FISHERY	MAPS		 44	      APPENDIX	C			 45	      HABITAT	AND	FISHERY	MAPS		 46	       APPENDIX	C			 47	       HABITAT	AND	FISHERY	MAPS		 48	The next section presents fishery intensity maps; the inverse of the sailing costs entered in the model.     APPENDIX	C			 49	          HABITAT	AND	FISHERY	MAPS		 50	      APPENDIX	C			 51	The final section presents the fishery intensity maps for the Haida Fisheries in the model        RESULTS	TABLES		52	Appendix	D:	All	Results	Tables														A. Ecospace	results	(Small	MPAs)							Biomass	Scenario	1:	No	fishing	in	MPA	 no fishing in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup Name Group name Group name Group name Group name Group nameSea Otters 0% 0% -1% 0% 0% -1% -1% 0% 0% 0% 0% 0%Gray whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Humpback whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Minke whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Blue whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Fin whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sei whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sperm whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Resident orcas 1% 1% 1% 3% 2% 3% 1% 3% 2% 2% 2% 2%Transient orcas 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Small odontocetes -1% -1% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Seals 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sea lions 0% 0% 3% 1% -1% 0% 2% 0% -1% 0% 0% 0%Seabirds 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Transient salmon 2% 0% 14% 7% 3% 10% 8% 4% 1% 5% 9% 5%Coho salmon 4% 1% 28% 15% 17% 21% 19% 9% 11% 13% 18% 11%Chinook salmon 2% -1% 11% 8% 11% 14% 6% 5% 6% 8% 10% 6%Small squid 0% 0% -1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Large squid 0% 0% -4% -2% -1% -2% -2% -1% -1% -2% -2% -1%Ratfish 0% 0% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Dogfish 1% 0% 5% 4% 1% 4% 2% 3% 0% 2% 4% 2%Pollock 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Forage fish 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Hake 2% 1% 3% 2% 4% 4% 2% 2% 3% 3% 3% 3%Eulachon 0% 0% 0% 0% 0% 1% 0% 0% 0% 0% 0% 0%Juvenile herring 0% -1% -7% 1% 1% 0% -1% 0% 0% 0% 0% 0%Adult herring 0% -1% -5% 1% 2% 1% -1% 0% 1% 0% 1% 0%POP -1% -4% 39% 6% 7% 5% 23% 3% 3% 2% 8% 3%Inshore rockfish 6% 3% 14% 18% 11% 30% 8% 13% 8% 21% 18% 12%Piscivorous rockfish 2% 0% 8% 8% 2% 6% 4% 6% 1% 5% 6% 4%Planktivorous rockfish 3% 1% 10% 10% 4% 13% 5% 7% 2% 10% 9% 6%Arrowtooth flounder 0% -1% 12% 1% 2% 2% 7% 0% 1% 1% 3% 1%Flatfish 0% -1% 0% 1% 3% 2% -2% 0% 1% 1% 2% 1%Juvenile halibut 0% -1% 5% 2% 1% 3% 5% 2% 0% 1% 2% 1%Adult halibut 0% -1% 6% 2% 2% 3% 4% 1% 1% 1% 2% 1%Pacific cod -1% -2% 6% 4% 6% 5% 1% 1% 3% 2% 5% 2%Sablefish 1% -1% 9% -1% 5% 8% 5% -2% 3% 5% 6% 3%Lingcod 2% 0% 53% 10% 5% 8% 33% 7% 2% 4% 15% 7%Shallowwater benthic fish 0% 1% -21% -1% 0% -2% -16% -1% 0% -2% -3% -1%Small demersal elasmobranchs 0% 0% 8% 2% 2% 1% 6% 1% 1% 1% 2% 1%Large demersal sharks 0% 0% 1% 0% 0% 0% 1% 0% 0% 0% 0% 0%Salmon sharks 0% 0% 6% 3% -3% 2% 5% 3% -2% 2% 2% 1%Blue sharks 0% 0% 1% 1% 0% 0% 1% 1% 0% 0% 1% 0%Large crabs 0% 0% -5% -2% 2% -1% -3% -2% 1% -1% 0% 0%Small crabs 0% 0% 0% 0% 0% -1% 0% 0% 0% 0% 0% 0%Commercial shrimp 0% 0% -10% -1% 0% 1% -7% -1% -1% -1% 1% -1%Epifaunal invertebrates 0% 0% 0% 1% 0% 0% 0% 0% 0% 0% 0% 0%Infaunal carnivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Infaunal detritivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Carnivorous jellyfish 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Euphausiids 0% 0% -1% -1% 0% -1% 0% 0% 0% 0% -1% 0%Copepods 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Corals and sponges 0% 0% 0% 0% 0% 1% 0% 0% 0% 0% 0% 0%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Detritus 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Total 0% 0% 1% 0% 0% 0% 0% 0% 0% 0% 1% 0%	 	 APPENDIX	D					53	Scenario	2:	Only	Haida	fisheries	in	MPAs Group name Group Name only haida fisheries in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group name Group nameSea Otters 0% 0% -1% 0% 0% -1% -1% 0% 0% 0% 0% 0%Gray whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Humpback whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Minke whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Blue whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Fin whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sei whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sperm whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Resident orcas 1% 1% 1% 3% 2% 3% 1% 3% 2% 2% 2% 2%Transient orcas 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Small odontocetes -1% -1% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Seals 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sea lions 0% 0% 3% 1% -1% 0% 2% 0% -1% 0% 0% 0%Seabirds 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Transient salmon 2% 0% 14% 7% 3% 10% 8% 4% 1% 5% 9% 5%Coho salmon 4% 1% 27% 15% 17% 21% 18% 9% 11% 13% 18% 11%Chinook salmon 2% -1% 11% 8% 11% 14% 6% 5% 6% 8% 10% 6%Small squid 0% 0% -1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Large squid 0% 0% -4% -2% -1% -2% -2% -1% -1% -2% -2% -1%Ratfish 0% 0% 1% 0% 0% 1% 1% 0% 0% 0% 0% 0%Dogfish 1% 0% 5% 4% 1% 4% 2% 3% 0% 2% 4% 2%Pollock 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Forage fish 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Hake 2% 1% 3% 2% 4% 4% 2% 2% 3% 3% 3% 3%Eulachon 0% 0% 0% 0% 0% 1% 0% 0% 0% 0% 0% 0%Juvenile herring 0% -1% -7% 1% 1% 0% -1% 0% 0% 0% 0% 0%Adult herring 0% -1% -5% 1% 2% 1% -1% 0% 1% 0% 1% 0%POP -1% -4% 39% 6% 7% 5% 23% 3% 3% 2% 8% 3%Inshore rockfish 6% 3% 14% 18% 11% 30% 8% 13% 8% 21% 18% 12%Piscivorous rockfish 2% 0% 8% 8% 2% 6% 4% 6% 1% 5% 6% 4%Planktivorous rockfish 3% 1% 10% 10% 4% 13% 5% 7% 2% 10% 9% 6%Arrowtooth flounder 0% -1% 12% 1% 2% 2% 7% 0% 1% 1% 3% 1%Flatfish 0% -1% 0% 1% 3% 2% -2% 0% 1% 1% 2% 1%Juvenile halibut 0% -1% 5% 2% 1% 3% 5% 2% 0% 1% 2% 1%Adult halibut 0% -1% 6% 2% 2% 3% 4% 1% 1% 1% 2% 1%Pacific cod -1% -2% 6% 4% 6% 5% 1% 1% 3% 2% 5% 2%Sablefish 1% -1% 9% -1% 5% 8% 5% -2% 3% 5% 6% 3%Lingcod 2% 0% 53% 10% 5% 8% 33% 7% 2% 4% 15% 7%Shallowwater benthic fish 0% 1% -21% -1% 0% -2% -16% -1% 0% -2% -3% -1%Small demersal elasmobranchs 0% 0% 8% 2% 2% 1% 6% 1% 1% -84% 2% -30%Large demersal sharks 0% 0% 1% 0% 0% 0% 1% 0% 0% 180% 0% 62%Salmon sharks 0% 0% 6% 3% -3% 2% 5% 3% -2% 9064% 2% 1948%Blue sharks 0% 0% 1% 1% 0% 0% 1% 1% 0% 6399% 1% 1560%Large crabs 0% 0% -5% -2% 2% -1% -3% -2% 1% -42% 0% -11%Small crabs 0% 0% 0% 0% 0% -1% 0% 0% 0% 1% 0% 0%Commercial shrimp 0% 0% -10% -1% 0% 1% -7% -1% -1% -19% 1% -11%Epifaunal invertebrates 0% 0% 0% 1% 0% 0% 0% 0% 0% -14% 0% -3%Infaunal carnivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% -9% 0% -2%Infaunal detritivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% -8% 0% -2%Carnivorous jellyfish 0% 0% 0% 0% 0% 0% 0% 0% 0% -24% 0% -8%Euphausiids 0% 0% -1% -1% 0% -1% 0% 0% 0% -12% -1% -4%Copepods 0% 0% 0% 0% 0% 0% 0% 0% 0% -15% 0% -4%Corals and sponges 0% 0% 0% 0% 0% 1% 0% 0% 0% -2% 0% 0%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 33% 0% 6%Phytoplankton 0% 0% 0% 0% 0% 0% 0% 0% 0% -11% 0% -3%Detritus 0% 0% 0% 0% 0% 0% 0% 0% 0% -10% 0% -3%Total 0% 0% 1% 0% 0% 0% 0% 0% 0% -6% 1% -2%RESULTS	TABLES		54	Scenario	3:	No	ground	fish	trawl	in	MPA Scenario	4:	Heavy	fishing	2-times	everywhere	Group name no groundfish trawl in mpaGroup Name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group name Group name Group nameSea Otters 0% 0% -1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Gray whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Humpback whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Minke whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Blue whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Fin whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sei whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sperm whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Resident orcas 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Transient orcas 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Small odontocetes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Seals 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sea lions 0% 0% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Seabirds 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Transient salmon 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Coho salmon 0% 0% -3% 0% 0% -1% -3% 0% 0% 0% -1% 0%Chinook salmon 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0% 0%Small squid 0% 0% -1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Large squid 0% 0% -3% -1% -1% -2% -1% -1% 0% -1% -2% -1%Ratfish 0% 0% 2% 1% 0% 1% 1% 0% 0% 0% 1% 0%Dogfish 0% 0% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Pollock 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Forage fish 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Hake 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Eulachon 0% 0% 1% 0% 0% 0% 1% 0% 0% 0% 0% 0%Juvenile herring 0% 0% -4% -1% 0% -1% 0% 0% 0% -1% -1% 0%Adult herring 0% 0% -3% -1% 0% -1% 0% 0% 0% -1% -1% 0%POP -1% -4% 41% 6% 7% 6% 24% 4% 3% 3% 8% 4%Inshore rockfish 0% 0% -3% -1% 1% 0% -2% -1% 1% 0% -1% -1%Piscivorous rockfish 1% 0% 6% 6% 2% 5% 3% 4% 1% 4% 5% 3%Planktivorous rockfish 3% 1% 10% 10% 4% 13% 6% 7% 2% 10% 9% 6%Arrowtooth flounder 0% -1% 15% 2% 2% 2% 9% 1% 1% 1% 4% 1%Flatfish 0% -1% 6% 2% 3% 3% 2% 0% 1% 1% 3% 1%Juvenile halibut 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Adult halibut 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Pacific cod 0% -2% 11% 5% 5% 5% 5% 2% 2% 2% 6% 2%Sablefish 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Lingcod 2% -1% 44% 7% 5% 6% 27% 4% 1% 3% 12% 5%Shallowwater benthic fish 1% 1% -13% 0% 0% 0% -10% 0% 0% 0% -2% -1%Small demersal elasmobranchs 0% 0% 9% 2% 1% 1% 7% 1% 1% 1% 2% 1%Large demersal sharks 0% 0% 1% 0% 0% 0% 1% 0% 0% 0% 0% 0%Salmon sharks 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Blue sharks 0% 0% -1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Large crabs 0% 0% -3% -1% 0% 0% -2% 0% 0% 0% -1% 0%Small crabs 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Commercial shrimp 0% 0% -3% -1% 0% 0% -2% 0% 0% 0% 0% 0%Epifaunal invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Infaunal carnivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Infaunal detritivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Carnivorous jellyfish 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Euphausiids 0% 0% -1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Copepods 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Corals and sponges 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Detritus 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Total 0% 0% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0%	 	 APPENDIX	D					55	 Group name Group Name Group name heavy fishing 2timesGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group nameSea Otters 15% 15% 10% 9% 21% 24% 8% 10% 21% 24% 15% 16%Gray whales 0% 0% 0% -1% -1% -1% 0% -1% -1% -1% 0% 0%Humpback whales 7% 7% 5% 15% 7% 6% 5% 14% 7% 6% 8% 8%Minke whales 9% 9% 7% 16% 9% 9% 7% 16% 9% 9% 11% 10%Blue whales 0% 0% 2% -3% 1% -1% 2% -3% 0% -1% 0% 0%Fin whales 1% 1% 2% 0% 1% 0% 2% 0% 1% 0% 1% 1%Sei whales -2% -2% 0% -5% -2% -4% 0% -5% -2% -4% -2% -2%Sperm whales 2% 2% 0% 4% 2% 6% 0% 4% 3% 6% 2% 2%Resident orcas -41% -40% -15% -55% -45% -57% -14% -55% -47% -56% -44% -46%Transient orcas 0% 0% -1% 1% -1% 1% -1% 1% -1% 1% 0% 0%Small odontocetes 12% 11% -2% 23% 8% 11% -1% 22% 9% 11% 13% 13%Seals 28% 27% 6% 41% 22% 28% 7% 41% 23% 28% 29% 29%Sea lions -19% -19% -34% -16% -21% -16% -33% -16% -20% -16% -19% -18%Seabirds 5% 5% 0% 10% 5% 6% 0% 10% 5% 6% 6% 6%Transient salmon -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100%Coho salmon -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100%Chinook salmon -99% -99% -98% -98% -99% -99% -98% -98% -99% -99% -99% -99%Small squid -9% -8% -8% -19% -11% -10% -9% -17% -10% -11% -13% -12%Large squid 18% 17% 25% 23% 25% 26% 20% 22% 24% 26% 25% 23%Ratfish -4% -4% 3% 1% -9% -9% 3% 1% -10% -10% -3% -5%Dogfish -54% -54% -48% -58% -58% -61% -48% -58% -59% -61% -55% -56%Pollock -1% -1% 3% -3% -2% -4% 3% -3% -2% -4% -1% -1%Forage fish 0% 0% 1% 1% 0% -5% 1% 1% -1% -5% 0% -1%Hake -97% -97% -96% -97% -97% -98% -96% -97% -97% -98% -97% -97%Eulachon 1% 1% -2% 2% 2% 0% -1% 2% 2% 1% 1% 2%Juvenile herring 22% 21% 228% 52% 18% 3% 193% 53% 18% 2% 26% 23%Adult herring 22% 21% 234% 54% 19% 2% 201% 52% 16% 2% 27% 23%POP -81% -81% -69% -78% -87% -84% -70% -78% -87% -84% -81% -82%Inshore rockfish -55% -52% -41% -66% -74% -83% -40% -65% -75% -83% -62% -64%Piscivorous rockfish -40% -40% -36% -43% -40% -55% -36% -42% -41% -56% -40% -42%Planktivorous rockfish -51% -51% -44% -55% -53% -65% -44% -55% -53% -65% -50% -52%Arrowtooth flounder -28% -29% -18% -22% -36% -31% -17% -23% -35% -32% -27% -29%Flatfish 19% 18% 47% 32% 15% 14% 47% 31% 14% 14% 21% 19%Juvenile halibut -33% -34% -25% -23% -37% -32% -26% -24% -37% -33% -31% -32%Adult halibut -37% -38% -27% -28% -41% -37% -27% -29% -41% -38% -36% -37%Pacific cod -9% -9% -47% 2% -5% -6% -47% 0% -5% -5% -10% -8%Sablefish -48% -48% -38% -33% -53% -58% -38% -36% -55% -59% -48% -50%Lingcod -98% -98% -97% -98% -99% -99% -97% -98% -99% -99% -99% -99%Shallowwater benthic fish 91% 87% 256% 137% 72% 85% 257% 128% 71% 83% 111% 96%Small demersal elasmobranchs -62% -63% -53% -58% -66% -64% -54% -59% -66% -64% -61% -62%Large demersal sharks 1% 1% -10% 1% 0% 5% -10% 1% 1% 5% 2% 2%Salmon sharks -85% -84% -78% -89% -90% -91% -77% -89% -90% -91% -87% -87%Blue sharks -21% -21% -26% -30% -17% -16% -25% -29% -16% -16% -23% -22%Large crabs 111% 108% 62% 155% 95% 142% 62% 151% 99% 139% 116% 117%Small crabs -5% -4% -6% -11% -4% -4% -3% -11% -4% -4% -6% -6%Commercial shrimp 23% 22% 1575% 50% 29% 19% 1154% 41% 27% 19% 27% 25%Epifaunal invertebrates 0% 0% 2% 1% 0% 0% 1% 1% 0% 0% 1% 0%Infaunal carnivorous invertebrates 0% 0% -1% 1% 0% -1% -1% 0% 0% -1% 0% 0%Infaunal detritivorous invertebrates 0% 0% 0% 1% 0% -1% 0% 0% 0% -1% 0% 0%Carnivorous jellyfish 1% 1% 1% 2% 0% 1% 0% 1% 1% 1% 1% 1%Euphausiids 0% 0% 4% -6% -1% -1% 4% -4% -1% -1% -1% -1%Copepods -1% -1% -2% -1% -3% -2% -2% -2% -2% -2% -2% -2%Corals and sponges -1% -1% -1% -1% -1% -2% -1% -1% -1% -2% -1% -1%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton 0% 0% 0% 2% 0% 0% 0% 1% 0% 0% 1% 0%Detritus 0% 0% 0% 1% 0% 0% 0% 1% 0% 0% 0% 0%Total -2% -2% -4% 0% -3% -3% -3% -1% -2% -3% -3% -2%RESULTS	TABLES		56	Scenario	5:	Heavy	fishing	2-times,	but	not	in	MPAs	 Group name Group Name Group name Group name heavy fishing but not in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group nameSea Otters 15% 15% 6% 9% 21% 23% 5% 9% 21% 23% 14% 15%Gray whales 0% 0% 0% -1% -1% -1% 0% -1% -1% -1% 0% 0%Humpback whales 7% 7% 5% 15% 7% 7% 5% 14% 7% 7% 8% 8%Minke whales 9% 9% 6% 16% 9% 9% 6% 16% 9% 9% 10% 10%Blue whales 0% 0% 2% -3% 1% -1% 1% -3% 0% -1% 0% 0%Fin whales 1% 1% 2% 0% 1% 0% 2% 0% 1% 0% 1% 1%Sei whales -2% -2% 0% -5% -2% -4% 0% -5% -2% -4% -2% -2%Sperm whales 2% 2% 0% 3% 2% 6% 0% 4% 3% 6% 2% 2%Resident orcas -40% -39% -15% -54% -45% -57% -14% -54% -47% -56% -44% -45%Transient orcas 0% 0% -1% 1% -2% 1% -1% 1% -1% 0% 0% 0%Small odontocetes 11% 11% -2% 23% 8% 11% -1% 22% 8% 11% 13% 13%Seals 27% 27% 4% 42% 22% 29% 6% 41% 23% 29% 30% 29%Sea lions -19% -20% -33% -16% -21% -16% -32% -16% -20% -16% -19% -18%Seabirds 5% 5% -1% 10% 5% 6% 0% 10% 5% 6% 6% 6%Transient salmon -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100%Coho salmon -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100%Chinook salmon -98% -98% -92% -97% -99% -99% -93% -97% -99% -99% -97% -98%Small squid -9% -8% -8% -18% -11% -11% -8% -17% -10% -11% -13% -12%Large squid 18% 17% 18% 21% 24% 24% 16% 20% 23% 25% 22% 21%Ratfish -5% -5% 5% 1% -8% -8% 4% 0% -10% -10% -2% -4%Dogfish -53% -53% -43% -54% -57% -58% -45% -55% -58% -59% -52% -54%Pollock -1% -1% 3% -3% -1% -4% 2% -3% -2% -4% -1% -1%Forage fish 0% 0% 1% 2% 0% -5% 1% 2% -1% -5% 0% 0%Hake -97% -97% -95% -97% -97% -97% -95% -97% -97% -97% -97% -97%Eulachon 2% 2% -2% 2% 2% 0% -1% 2% 2% 1% 1% 2%Juvenile herring 21% 19% 189% 59% 24% 6% 178% 56% 22% 3% 31% 25%Adult herring 21% 18% 199% 64% 24% 7% 187% 57% 19% 4% 33% 26%POP -81% -82% -25% -73% -86% -81% -44% -75% -86% -83% -75% -79%Inshore rockfish -49% -49% -22% -48% -67% -64% -29% -52% -70% -72% -46% -54%Piscivorous rockfish -38% -39% -25% -32% -38% -49% -29% -34% -40% -51% -31% -36%Planktivorous rockfish -47% -49% -31% -45% -49% -55% -37% -47% -51% -58% -40% -45%Arrowtooth flounder -29% -30% 3% -19% -34% -29% -5% -22% -34% -31% -21% -27%Flatfish 17% 16% 55% 36% 21% 20% 47% 31% 16% 16% 27% 21%Juvenile halibut -32% -33% -14% -18% -34% -28% -15% -19% -36% -31% -27% -30%Adult halibut -36% -37% -15% -22% -38% -32% -19% -25% -39% -35% -31% -34%Pacific cod -9% -12% -36% 16% 7% 6% -42% 6% 1% 0% 2% -3%Sablefish -46% -47% -22% -30% -46% -50% -30% -35% -51% -54% -39% -46%Lingcod -98% -98% -89% -97% -98% -99% -91% -97% -99% -99% -97% -98%Shallowwater benthic fish 89% 87% 178% 128% 71% 82% 200% 121% 70% 81% 99% 91%Small demersal elasmobranchs -62% -62% -46% -56% -65% -63% -48% -57% -65% -63% -59% -61%Large demersal sharks 1% 1% -9% 1% 0% 5% -9% 0% 1% 5% 2% 2%Salmon sharks -85% -84% -78% -89% -90% -91% -76% -89% -90% -91% -87% -87%Blue sharks -21% -20% -26% -29% -17% -16% -25% -29% -16% -16% -23% -22%Large crabs 107% 104% 46% 143% 101% 140% 50% 139% 102% 135% 114% 115%Small crabs -5% -4% -6% -11% -4% -4% -3% -11% -5% -5% -6% -6%Commercial shrimp 23% 21% 1341% 49% 30% 24% 1039% 39% 26% 19% 30% 24%Epifaunal invertebrates 0% 0% 1% 2% 0% 1% 1% 1% 0% 1% 1% 1%Infaunal carnivorous invertebrates 0% 0% -1% 1% 0% -1% -1% 1% 0% -1% 0% 0%Infaunal detritivorous invertebrates 0% 0% 0% 1% 0% -1% 0% 1% 0% -1% 0% 0%Carnivorous jellyfish 1% 1% 0% 2% 1% 1% 0% 1% 1% 1% 1% 1%Euphausiids 0% 0% 2% -7% -1% -2% 3% -5% -1% -2% -2% -2%Copepods -1% -1% -2% -1% -3% -2% -1% -2% -2% -2% -2% -2%Corals and sponges -1% -1% -1% -2% -1% 0% -1% -1% -1% -2% -1% -1%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton 0% 0% 0% 2% 0% 0% 0% 1% 0% 0% 1% 1%Detritus 0% 0% 0% 2% 0% 0% 0% 1% 0% 0% 1% 0%Total -2% -2% -3% 0% -2% -3% -3% 0% -2% -3% -2% -2%	 	 APPENDIX	D					57	Scenario	6:	Herring	fisheries	5-times	everywhere	 Group name Group Name Group name Group name Group name herring fisheries 5timesGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup nameSea Otters 1% 1% 0% 2% 1% 4% 0% 2% 7% -20% 1% 1%Gray whales 0% 0% 0% 0% 0% -1% 0% 0% 0% -1% 0% 0%Humpback whales -8% -8% -1% -11% -9% -14% -1% -11% -10% -13% -9% -10%Minke whales -7% -7% 0% -9% -7% -12% 0% -9% -7% -12% -7% -8%Blue whales 5% 4% 0% 11% 5% 12% 0% 11% 6% 12% 6% 6%Fin whales 4% 4% 0% 7% 4% 7% 0% 7% 5% 7% 5% 5%Sei whales 5% 4% 0% 9% 6% 12% 0% 9% 7% 11% 6% 6%Sperm whales 2% 1% 0% 4% 2% 6% 0% 4% 3% 5% 2% 2%Resident orcas 14% 14% 2% 21% 14% 26% 2% 21% 16% 25% 16% 17%Transient orcas -16% -15% -1% -16% -18% -26% -1% -16% -20% -25% -17% -18%Small odontocetes -41% -41% -6% -42% -39% -45% -6% -42% -41% -45% -42% -42%Seals -30% -29% -4% -31% -28% -32% -4% -31% -29% -32% -30% -30%Sea lions -18% -18% 3% -19% -18% -24% 3% -19% -19% -23% -19% -19%Seabirds -8% -8% 0% -9% -8% -11% 0% -9% -9% -11% -8% -9%Transient salmon 21% 21% 14% 25% 22% 29% 14% 25% 23% 28% 21% 22%Coho salmon 26% 26% 19% 24% 29% 29% 19% 24% 30% 29% 26% 27%Chinook salmon 23% 23% 4% 20% 24% 33% 4% 20% 26% 31% 22% 23%Small squid 7% 7% 0% 10% 10% 14% 0% 9% 11% 15% 9% 10%Large squid 4% 4% -1% 5% 5% 8% -1% 5% 6% 8% 5% 5%Ratfish 3% 3% 0% 3% 3% 5% 0% 3% 3% 5% 3% 3%Dogfish 2% 2% 1% 4% 3% 4% 1% 4% 3% 4% 3% 3%Pollock 14% 14% 3% 20% 16% 27% 3% 20% 18% 26% 14% 16%Forage fish -1% 0% 0% -2% 0% -1% 0% -2% 0% -1% -1% -1%Hake 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0% 0%Eulachon -5% -4% -1% -7% -3% -7% -1% -7% -2% -11% -5% -5%Juvenile herring -13% -13% 23% -12% -15% -9% 14% -13% -14% -9% -11% -12%Adult herring -26% -27% 11% -25% -27% -23% 3% -25% -27% -24% -24% -25%POP 17% 17% 6% 17% 17% 21% 6% 17% 18% 21% 18% 18%Inshore rockfish 0% 0% 0% 0% 1% 1% 0% 0% 3% -1% 0% 0%Piscivorous rockfish 1% 1% 1% 1% 1% 1% 1% 1% 0% 2% 1% 1%Planktivorous rockfish 2% 2% 1% 4% 2% 6% 1% 4% 2% 7% 3% 3%Arrowtooth flounder 5% 5% 1% 4% 5% 7% 1% 4% 6% 7% 5% 5%Flatfish -2% -2% 0% -3% -1% -1% 0% -3% -1% -2% -2% -2%Juvenile halibut 4% 4% 1% 4% 3% 5% 1% 4% 3% 4% 4% 4%Adult halibut 8% 7% 3% 8% 6% 10% 2% 8% 7% 9% 8% 8%Pacific cod 23% 23% 5% 29% 18% 40% 5% 29% 20% 36% 24% 25%Sablefish 12% 12% 3% 16% 13% 17% 3% 15% 13% 18% 12% 13%Lingcod -8% -8% 3% -11% -7% -9% 3% -11% -8% -10% -7% -8%Shallowwater benthic fish 3% 3% -2% 2% 1% 8% -2% 2% 2% 5% 3% 3%Small demersal elasmobranchs 1% 1% 2% 1% 2% 1% 2% 1% 2% 1% 1% 1%Large demersal sharks 2% 2% 1% 2% 2% 2% 1% 3% 2% 3% 2% 2%Salmon sharks 26% 26% 17% 33% 27% 29% 17% 33% 27% 29% 27% 27%Blue sharks 14% 13% 4% 16% 13% 19% 4% 16% 14% 20% 15% 15%Large crabs -8% -8% -1% -10% -8% -10% -1% -10% -8% -12% -8% -9%Small crabs -2% -2% 0% -1% -2% -3% 0% -1% 0% -5% -2% -2%Commercial shrimp 8% 8% -1% 11% 10% 5% 0% 10% 14% 6% 8% 8%Epifaunal invertebrates 0% 0% 0% 0% -1% -1% 0% -1% 0% -3% 0% -1%Infaunal carnivorous invertebrates -1% -1% 0% -1% -1% -1% 0% -1% 0% -4% -1% -1%Infaunal detritivorous invertebrates -1% -1% 0% -1% -1% -1% 0% -1% -1% -1% -1% -1%Carnivorous jellyfish -1% -1% 0% -1% -1% -1% 0% -1% 0% -1% -1% -1%Euphausiids 4% 4% 0% 5% 5% 6% 0% 5% 6% 6% 4% 5%Copepods -1% -1% 0% -2% -2% -2% 0% -2% -2% -3% -1% -2%Corals and sponges 0% 0% 0% 0% 0% 0% 0% 0% -1% 0% 0% 0%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 2% -3% 0% 0%Phytoplankton -1% -1% 0% -1% -1% -1% 0% -1% -1% -1% -1% -1%Detritus -1% -1% 0% -1% -1% -1% 0% -1% -1% -1% -1% -1%Total 0% 0% 0% -1% -1% 0% 0% -1% 0% -1% 0% 0%RESULTS	TABLES		58	Scenario	7:	No	fishing	anywhere	 Group name Group Name Group name Group name Group name Group name no fishing anywhereGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverSea Otters -5% -4% -3% -1% -8% -9% -3% -1% -9% -9% -5% -5%Gray whales 1% 1% 0% 1% 1% 1% 0% 1% 1% 1% 1% 1%Humpback whales -11% -10% -3% -15% -11% -14% -3% -15% -12% -14% -12% -12%Minke whales -13% -12% -5% -16% -13% -17% -5% -16% -14% -17% -14% -14%Blue whales 1% 1% -2% 6% 0% 5% -2% 6% 1% 5% 1% 2%Fin whales 0% 0% -2% 2% -1% 1% -2% 2% -1% 1% 0% 0%Sei whales 5% 4% 1% 11% 5% 10% 1% 11% 6% 10% 6% 6%Sperm whales 1% 1% 3% 3% 2% -1% 2% 2% 1% -1% 2% 2%Resident orcas 216% 208% 26% 239% 251% 411% 27% 241% 281% 412% 238% 253%Transient orcas 9% 9% 2% 8% 14% 11% 2% 8% 14% 11% 9% 10%Small odontocetes -17% -17% 18% -21% -14% -21% 17% -21% -16% -21% -18% -18%Seals -22% -21% 20% -24% -19% -25% 18% -24% -20% -25% -22% -22%Sea lions 64% 64% 109% 61% 71% 52% 108% 60% 66% 53% 64% 62%Seabirds -5% -5% 6% -8% -6% -9% 6% -8% -6% -9% -6% -6%Transient salmon 132% 129% 282% 74% 63% 55% 284% 74% 56% 53% 150% 133%Coho salmon 130% 128% 137% 104% 179% 159% 139% 102% 171% 160% 137% 139%Chinook salmon 48% 48% 22% 27% 71% 68% 23% 27% 70% 72% 46% 50%Small squid 12% 11% 3% 20% 16% 18% 5% 19% 16% 19% 15% 16%Large squid -21% -19% -24% -23% -29% -33% -19% -21% -27% -33% -27% -26%Ratfish -5% -5% -5% -10% -2% -5% -5% -10% -2% -5% -5% -5%Dogfish 106% 105% 73% 122% 124% 148% 72% 122% 129% 148% 111% 115%Pollock -3% -3% -3% -3% -4% -5% -2% -3% -4% -5% -3% -4%Forage fish -6% -5% -3% -13% -8% -9% -3% -13% -8% -9% -7% -7%Hake 189% 188% 177% 199% 183% 205% 175% 200% 187% 205% 192% 193%Eulachon 9% 9% 8% 7% 8% 13% 8% 7% 9% 12% 9% 9%Juvenile herring -43% -42% -85% -50% -46% -39% -83% -50% -44% -38% -45% -44%Adult herring -32% -32% -83% -42% -34% -26% -80% -41% -32% -26% -34% -33%POP 214% 210% 140% 176% 324% 237% 144% 179% 305% 240% 219% 229%Inshore rockfish 79% 74% 46% 88% 132% 147% 44% 85% 134% 153% 95% 100%Piscivorous rockfish 57% 56% 43% 61% 56% 109% 43% 59% 58% 110% 57% 61%Planktivorous rockfish 86% 85% 66% 91% 92% 144% 66% 90% 94% 145% 87% 91%Arrowtooth flounder 21% 21% 23% 20% 26% 19% 22% 20% 24% 19% 21% 21%Flatfish -28% -28% -46% -38% -24% -25% -45% -38% -24% -25% -30% -29%Juvenile halibut -15% -15% -7% -20% -9% -21% -7% -20% -10% -20% -16% -16%Adult halibut -4% -4% -1% -9% 2% -7% 0% -9% 0% -7% -4% -4%Pacific cod -19% -20% 49% -31% -23% -33% 50% -30% -26% -33% -16% -21%Sablefish 44% 44% 31% 13% 50% 58% 31% 17% 56% 61% 42% 47%Lingcod 377% 373% 545% 323% 393% 401% 510% 325% 396% 406% 395% 385%Shallowwater benthic fish -75% -75% -90% -85% -67% -81% -90% -85% -68% -80% -78% -76%Small demersal elasmobranchs 78% 78% 88% 78% 85% 70% 87% 78% 83% 70% 77% 77%Large demersal sharks 16% 16% 22% 20% 15% 15% 21% 19% 14% 15% 17% 16%Salmon sharks 1086% 1076% 527% 1131% 1342% 1413% 529% 1130% 1361% 1422% 1104% 1149%Blue sharks 53% 52% 53% 64% 48% 59% 52% 63% 48% 58% 57% 57%Large crabs -41% -41% -34% -47% -40% -46% -33% -46% -40% -47% -42% -43%Small crabs 13% 12% 3% 15% 17% 12% 1% 16% 18% 12% 13% 14%Commercial shrimp -33% -33% -89% -37% -39% -34% -88% -37% -38% -35% -35% -36%Epifaunal invertebrates 0% 0% 1% 0% 0% 0% 1% -1% 0% 0% 0% 0%Infaunal carnivorous invertebrates 0% 0% 2% -2% 0% 0% 1% -1% -1% 0% 0% 0%Infaunal detritivorous invertebrates 0% 0% 0% -2% 0% 0% 0% -1% 0% 0% 0% 0%Carnivorous jellyfish 0% 0% 3% -1% 0% 0% 2% -1% 0% 0% 0% 0%Euphausiids 3% 3% -5% 8% 4% 5% -3% 7% 5% 5% 4% 4%Copepods 2% 1% 2% 0% 3% 4% 2% 0% 3% 4% 2% 2%Corals and sponges 1% 1% 1% 1% 1% 2% 1% 1% 1% 2% 1% 1%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton -1% -1% 0% -2% -1% -1% 0% -2% -1% -1% -1% -1%Detritus -1% -1% 0% -2% -1% -1% 0% -2% -1% -1% -1% -1%Total 4% 4% 8% 3% 5% 5% 6% 3% 4% 5% 5% 4%	 	 APPENDIX	D					59	Catch	Scenario	1:	No	fishing	in	MPAs	  no fishing in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup Name Group name Group name Group name Group name Group nameSeals -2% 14% -100% -100% -100% -100% 24% 20% 17% 22% -100% 20%Sea lions -2% 13% -100% -100% -100% -100% 26% 20% 16% 22% -100% 20%Transient salmon 0% 13% -100% -100% -100% -100% 34% 24% 17% 28% -100% 25%Coho salmon 2% 15% -100% -100% -100% -100% 47% 30% 31% 37% -100% 33%Chinook salmon 0% 14% -100% -100% -100% -100% 32% 25% 26% 30% -100% 27%Large squid 2% 15% -100% -100% -100% -100% 19% 16% 18% 17% -100% 17%Ratfish 0% 15% -100% -100% -100% -100% 23% 18% 18% 19% -100% 19%Dogfish -1% 14% -100% -100% -100% -100% 22% 21% 16% 21% -100% 20%Pollock 0% 16% -100% -100% -100% -100% 22% 19% 19% 20% -100% 19%Forage fish 0% 15% -100% -100% -100% -100% 23% 18% 18% 20% -100% 19%Hake 0% 15% -100% -100% -100% -100% 17% 16% 19% 19% -100% 18%Eulachon 3% 17% -100% -100% -100% -100% 18% 16% 16% 16% -100% 16%Adult herring 0% 13% -100% -100% -100% -100% 19% 17% 16% 15% -100% 16%POP -2% 11% -100% -100% -100% -100% 52% 22% 22% 22% -100% 22%Inshore rockfish 1% 22% -100% -100% -100% -100% 41% 40% 28% 48% -100% 39%Piscivorous rockfish -3% 17% -100% -100% -100% -100% 28% 28% 20% 26% -100% 25%Planktivorous rockfish -2% 18% -100% -100% -100% -100% 29% 30% 21% 32% -100% 28%Arrowtooth flounder -1% 14% -100% -100% -100% -100% 32% 19% 19% 20% -100% 20%Flatfish 1% 14% -100% -100% -100% -100% 21% 17% 20% 20% -100% 19%Juvenile halibut -1% 13% -100% -100% -100% -100% 30% 19% 17% 19% -100% 18%Adult halibut 0% 13% -100% -100% -100% -100% 27% 19% 17% 20% -100% 19%Pacific cod 0% 13% -100% -100% -100% -100% 23% 19% 22% 22% -100% 21%Sablefish -1% 12% -100% -100% -100% -100% 26% 11% 21% 26% -100% 23%Lingcod 0% 14% -100% -100% -100% -100% 68% 26% 20% 25% -100% 25%Shallowwater benthic fish 2% 17% -100% -100% -100% -100% -3% 16% 16% 14% -100% 15%Small demersal elasmobranchs -1% 15% -100% -100% -100% -100% 31% 20% 19% 21% -100% 20%Large demersal sharks 1% 15% -100% -100% -100% -100% 24% 18% 18% 20% -100% 19%Large crabs 3% 15% -100% -100% -100% -100% 8% 13% 17% 12% -100% 16%Small crabs 0% 15% -100% -100% -100% -100% 23% 18% 18% 19% -100% 19%Commercial shrimp -3% 15% -100% -100% -100% -100% 8% 15% 16% 16% -100% 16%Epifaunal invertebrates -1% 13% -100% -100% -100% -100% 13% 14% 13% 14% -100% 14%Infaunal detritivorous invertebrates 1% 15% -100% -100% -100% -100% 23% 18% 18% 20% -100% 19%Carnivorous jellyfish 0% 14% -100% -100% -100% -100% 23% 19% 17% 21% -100% 20%Corals and sponges 3% 17% -100% -100% -100% -100% 23% 17% 19% 17% -100% 19%Macrophytes 3% 23% -100% -100% -100% -100% 23% 23% 23% 23% -100% 23%RESULTS	TABLES		60	Scenario	2:	Only	Haida	fisheries	in	MPAs	 Group name Group Name only haida fisheries in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group name Group nameSeals -2% 14% -100% -100% -100% -100% 24% 20% 17% 22% -100% 20%Sea lions -2% 13% -100% -100% -100% -100% 26% 20% 16% 22% -100% 20%Transient salmon 0% 13% -100% -100% -100% -100% 34% 24% 17% 28% -100% 25%Coho salmon 2% 15% -99% -99% -99% -100% 47% 30% 30% 37% -99% 33%Chinook salmon 0% 14% -100% -100% -100% -100% 32% 25% 26% 30% -100% 27%Large squid 2% 15% -100% -100% -100% -100% 19% 16% 18% 17% -100% 17%Ratfish 0% 15% -100% -100% -100% -100% 23% 18% 18% 19% -100% 19%Dogfish -1% 14% -100% -100% -100% -100% 22% 21% 16% 21% -100% 20%Pollock 0% 16% -100% -100% -100% -100% 22% 19% 19% 20% -100% 19%Forage fish 0% 15% -100% -100% -100% -100% 23% 18% 18% 20% -100% 19%Hake 0% 15% -100% -100% -100% -100% 17% 16% 19% 19% -100% 18%Eulachon 3% 17% -100% -100% -100% -100% 18% 16% 16% 16% -100% 16%Adult herring 0% 13% -100% -100% -100% -100% 19% 17% 16% 15% -100% 16%POP -2% 11% -100% -100% -100% -100% 52% 22% 22% 22% -100% 22%Inshore rockfish 1% 22% -100% -100% -100% -100% 41% 40% 28% 48% -100% 39%Piscivorous rockfish -3% 17% -100% -100% -100% -100% 28% 28% 20% 26% -100% 25%Planktivorous rockfish -2% 18% -100% -100% -100% -100% 29% 30% 21% 32% -100% 28%Arrowtooth flounder -1% 14% -100% -100% -100% -100% 32% 19% 19% 20% -100% 20%Flatfish 1% 14% -100% -100% -100% -100% 21% 17% 20% 20% -100% 19%Juvenile halibut -1% 13% -100% -100% -100% -100% 30% 19% 17% 19% -100% 18%Adult halibut 0% 13% -100% -100% -100% -100% 27% 19% 17% 20% -100% 19%Pacific cod 0% 13% -100% -100% -100% -100% 23% 19% 22% 22% -100% 21%Sablefish -1% 12% -100% -100% -100% -100% 26% 11% 21% 26% -100% 23%Lingcod 0% 14% -100% -100% -100% -100% 68% 26% 20% 25% -100% 25%Shallowwater benthic fish 2% 17% -100% -100% -100% -100% -3% 16% 16% 14% -100% 15%Small demersal elasmobranchs -1% 15% -100% -100% -100% -100% 31% 20% 19% -97% -100% -28%Large demersal sharks 1% 15% -100% -100% -100% -100% 24% 18% 18% 20451% -100% 7753%Large crabs 3% 15% -100% -100% -100% -100% 8% 13% 17% -74% -100% 2%Small crabs 0% 15% -100% -100% -100% -100% 23% 18% 18% -53% -100% -5%Commercial shrimp -3% 15% -100% -100% -100% -100% 8% 15% 16% -71% -100% -50%Epifaunal invertebrates -1% 13% -97% -97% -96% -98% 13% 13% 13% -79% -97% -9%Infaunal detritivorous invertebrates 1% 15% -100% -100% -100% -100% 23% 18% 18% -56% -100% -9%Carnivorous jellyfish 0% 14% -100% -100% -100% -100% 23% 19% 17% -63% -100% -17%Corals and sponges 3% 17% -100% -100% -100% -100% 23% 17% 19% -47% -100% 17%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% -27% 0% -4%	 	 APPENDIX	D					61	Scenario	3:	No	ground	fish	trawl	in	MPAs	  Group name no groundfish trawl in mpaGroup Name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group name Group name Group nameSeals 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sea lions 0% 0% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Transient salmon 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Coho salmon 0% 0% -3% 0% 0% -1% -3% 0% 0% 0% 0% 0%Chinook salmon 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Large squid 2% 15% -100% -100% -100% -100% 19% 17% 18% 18% -100% 18%Ratfish 0% 14% -99% -94% -94% -80% 24% 18% 17% 16% -90% 17%Dogfish 0% 2% -14% -16% -23% -16% 4% 3% 4% 4% -17% 4%Pollock 0% 15% -100% -99% -99% -95% 23% 19% 18% 19% -98% 19%Forage fish 0% 15% -100% -100% -100% -100% 23% 19% 18% 20% -100% 19%Hake 0% 0% -1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Eulachon 0% 0% -2% -1% -1% 0% 2% 0% 0% 0% -1% 0%Adult herring 0% 0% 0% -1% -1% -2% 3% 0% 0% -1% -1% -1%POP -2% 11% -100% -100% -100% -100% 54% 23% 22% 22% -100% 23%Inshore rockfish 0% 1% -6% -4% -4% -3% -1% 0% 1% 1% -4% 1%Piscivorous rockfish -2% 14% -82% -82% -86% -79% 24% 23% 17% 21% -82% 21%Planktivorous rockfish -2% 18% -99% -99% -99% -98% 29% 30% 21% 32% -99% 28%Arrowtooth flounder -1% 14% -100% -98% -98% -96% 34% 20% 18% 20% -98% 20%Flatfish 1% 13% -100% -98% -98% -93% 26% 18% 19% 19% -96% 19%Juvenile halibut 0% 1% -30% -7% -7% -6% 8% 1% 1% 1% -7% 1%Adult halibut 0% 0% -16% -5% -5% -4% 4% 1% 1% 1% -4% 1%Pacific cod 0% 12% -99% -95% -94% -93% 28% 19% 20% 20% -94% 20%Sablefish 0% 1% -7% -17% -7% -6% 2% 2% 2% 2% -7% 2%Lingcod 0% 12% -90% -87% -87% -83% 58% 21% 17% 19% -86% 21%Shallowwater benthic fish 1% 1% -39% -3% -5% -3% -5% 2% 0% 0% -4% 0%Small demersal elasmobranchs -1% 15% -100% -99% -99% -97% 33% 20% 19% 20% -98% 20%Large demersal sharks 1% 15% -100% -100% -100% -100% 24% 19% 18% 20% -100% 19%Large crabs 0% 0% -7% -2% -1% -2% -4% 0% 0% 0% -2% 0%Small crabs 0% 15% -100% -100% -100% -100% 23% 19% 18% 19% -100% 19%Commercial shrimp 0% 0% -3% 0% -1% -1% -2% 0% 0% -1% -1% 0%Epifaunal invertebrates 0% 0% -4% -2% -2% -2% 0% 0% 0% 0% -2% 0%Infaunal detritivorous invertebrates 1% 15% -100% -100% -100% -100% 23% 18% 18% 20% -100% 19%Carnivorous jellyfish 0% 4% -22% -24% -28% -20% 4% 4% 5% 4% -23% 4%Corals and sponges -1% 7% -81% -62% -54% -42% 19% 8% 11% 8% -70% 13%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%RESULTS	TABLES		62	Scenario	4:	Heavy	fishing	2-times	everywhere	 Group name Group Name Group name heavy fishing 2timesGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group nameSeals 138% 134% 195% 187% 125% 153% 190% 181% 120% 147% 153% 145%Sea lions 54% 51% 82% 69% 49% 66% 81% 66% 46% 62% 63% 58%Transient salmon -100% -100% -99% -100% -100% -100% -99% -100% -100% -100% -100% -100%Coho salmon -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100%Chinook salmon -98% -98% -97% -96% -99% -99% -97% -96% -99% -99% -98% -98%Large squid 150% 149% 169% 167% 153% 136% 159% 166% 156% 137% 152% 152%Ratfish 91% 92% 111% 118% 85% 71% 108% 116% 86% 71% 91% 89%Dogfish -12% -11% 19% -18% -19% -30% 18% -18% -22% -30% -11% -15%Pollock 101% 101% 111% 108% 100% 79% 108% 108% 103% 80% 100% 99%Forage fish 102% 103% 107% 118% 104% 77% 106% 117% 105% 78% 100% 99%Hake -94% -94% -89% -95% -95% -96% -90% -95% -95% -96% -94% -95%Eulachon 110% 108% 80% 119% 111% 118% 81% 117% 112% 113% 115% 113%Adult herring 125% 121% 1497% 252% 120% 76% 1257% 253% 115% 76% 139% 131%POP -64% -64% -36% -52% -75% -70% -39% -53% -73% -71% -63% -66%Inshore rockfish -37% -36% 31% -32% -50% -68% 32% -32% -53% -69% -35% -43%Piscivorous rockfish 18% 19% 33% 19% 20% -18% 31% 20% 20% -18% 17% 12%Planktivorous rockfish -5% -4% 14% -7% -6% -36% 12% -6% -7% -36% -4% -9%Arrowtooth flounder 43% 43% 68% 66% 27% 27% 71% 64% 31% 27% 44% 40%Flatfish 141% 141% 199% 184% 134% 114% 196% 180% 137% 115% 141% 139%Juvenile halibut 34% 32% 56% 74% 22% 36% 54% 73% 22% 33% 39% 35%Adult halibut 28% 27% 50% 60% 20% 30% 45% 58% 19% 27% 32% 29%Pacific cod 91% 92% 6% 121% 93% 77% 3% 118% 96% 78% 86% 90%Sablefish -13% -13% 48% 62% -16% -31% 45% 43% -25% -33% -7% -17%Lingcod -97% -97% -95% -97% -97% -99% -94% -97% -98% -99% -97% -98%Shallowwater benthic fish 258% 253% 670% 367% 240% 272% 700% 340% 238% 277% 276% 271%Small demersal elasmobranchs -24% -24% -5% -11% -29% -32% -6% -12% -28% -33% -24% -25%Large demersal sharks 108% 110% 80% 117% 105% 96% 78% 118% 110% 96% 103% 106%Large crabs 311% 307% 164% 527% 268% 471% 164% 472% 276% 454% 325% 319%Small crabs 95% 96% 94% 89% 99% 78% 95% 91% 103% 79% 89% 92%Commercial shrimp 138% 137% 3288% 172% 146% 132% 3170% 155% 150% 139% 137% 142%Epifaunal invertebrates 101% 101% 110% 104% 99% 101% 108% 103% 98% 101% 102% 100%Infaunal detritivorous invertebrates 103% 104% 102% 118% 103% 85% 100% 117% 105% 86% 100% 100%Carnivorous jellyfish 99% 98% 162% 110% 96% 96% 160% 106% 91% 93% 104% 99%Corals and sponges 100% 99% 94% 119% 101% 106% 92% 111% 110% 101% 102% 103%Macrophytes 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%	 	 APPENDIX	D					63	Scenario	5:	Heavy	fishing	2-times,	but	not	in	MPAs	  Group name Group Name Group name Group name heavy fishing but not in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group nameSeals 128% 163% -100% -100% -100% -100% 258% 244% 148% 198% -100% 191%Sea lions 49% 70% -100% -100% -100% -100% 129% 103% 64% 95% -100% 88%Transient salmon -99% -99% -100% -100% -100% -100% -98% -99% -100% -100% -100% -99%Coho salmon -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100%Chinook salmon -97% -97% -100% -100% -100% -100% -77% -92% -99% -98% -100% -95%Large squid 152% 184% -100% -100% -100% -100% 219% 214% 204% 184% -100% 200%Ratfish 90% 117% -100% -100% -100% -100% 171% 159% 121% 107% -100% 128%Dogfish -11% 2% -100% -100% -100% -100% 55% 6% -8% -12% -100% 7%Pollock 99% 131% -100% -100% -100% -100% 166% 151% 143% 119% -100% 142%Forage fish 103% 134% -100% -100% -100% -100% 167% 162% 144% 116% -100% 143%Hake -94% -93% -100% -100% -100% -100% -86% -93% -93% -94% -100% -93%Eulachon 116% 143% -100% -100% -100% -100% 112% 152% 148% 149% -100% 149%Adult herring 123% 147% -100% -100% -100% -100% 1446% 338% 165% 113% -100% 183%POP -64% -60% -100% -100% -100% -100% 52% -35% -66% -61% -100% -53%Inshore rockfish -31% -17% -100% -100% -100% -100% 126% 25% -32% -35% -100% 0%Piscivorous rockfish 17% 40% -100% -100% -100% -100% 87% 69% 47% 10% -100% 52%Planktivorous rockfish -3% 16% -100% -100% -100% -100% 65% 37% 17% -5% -100% 29%Arrowtooth flounder 39% 59% -100% -100% -100% -100% 156% 101% 58% 56% -100% 73%Flatfish 139% 169% -100% -100% -100% -100% 287% 234% 188% 163% -100% 190%Juvenile halibut 33% 50% -100% -100% -100% -100% 138% 119% 44% 66% -100% 66%Adult halibut 28% 44% -100% -100% -100% -100% 111% 100% 43% 59% -100% 58%Pacific cod 89% 110% -100% -100% -100% -100% 45% 176% 149% 126% -100% 142%Sablefish -11% 0% -100% -100% -100% -100% 110% 64% -2% -5% -100% 13%Lingcod -96% -96% -100% -100% -100% -100% -76% -93% -97% -98% -100% -95%Shallowwater benthic fish 262% 311% -100% -100% -100% -100% 674% 407% 293% 335% -100% 329%Small demersal elasmobranchs -24% -12% -100% -100% -100% -100% 39% 11% -12% -17% -100% -7%Large demersal sharks 109% 138% -100% -100% -100% -100% 132% 159% 150% 138% -100% 147%Large crabs 313% 359% -100% -100% -100% -100% 175% 535% 351% 533% -100% 394%Small crabs 94% 123% -100% -100% -100% -100% 153% 131% 142% 116% -100% 131%Commercial shrimp 130% 173% -100% -100% -100% -100% 3347% 195% 191% 180% -100% 183%Epifaunal invertebrates 99% 127% -100% -100% -100% -100% 135% 131% 126% 128% -100% 128%Infaunal detritivorous invertebrates 104% 133% -100% -100% -100% -100% 159% 161% 145% 125% -100% 142%Carnivorous jellyfish 96% 123% -100% -100% -100% -100% 225% 150% 119% 132% -100% 137%Corals and sponges 106% 132% -100% -100% -100% -100% 149% 147% 152% 137% -100% 149%Macrophytes -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100%RESULTS	TABLES		64	Scenario	6:	Herring	fisheries	5-times	everywhere	 Group name Group Name Group name Group name Group name herring fisheries 5timesGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup nameSeals -28% -28% -10% -28% -27% -28% -10% -28% -27% -28% -28% -28%Sea lions -17% -17% -4% -17% -17% -19% -4% -17% -17% -19% -17% -18%Transient salmon 23% 23% 7% 29% 24% 36% 7% 29% 26% 35% 23% 25%Coho salmon 31% 31% 12% 28% 32% 37% 12% 28% 34% 36% 32% 32%Chinook salmon 28% 27% -2% 24% 26% 40% -2% 24% 29% 37% 28% 28%Large squid 7% 7% -5% 7% 5% 12% -5% 7% 7% 11% 7% 8%Ratfish 4% 4% -4% 5% 3% 7% -4% 5% 4% 7% 4% 4%Dogfish 3% 3% -2% 5% 3% 7% -1% 5% 3% 6% 3% 4%Pollock 18% 18% -1% 21% 16% 31% -1% 22% 19% 29% 17% 19%Forage fish 0% 0% -5% -1% 0% 2% -5% 0% 0% 2% -1% 0%Hake 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0% 0%Eulachon -4% -4% -6% -5% -1% -7% -7% -6% 3% -13% -4% -4%Adult herring 181% 178% 471% 188% 173% 209% 411% 185% 175% 207% 193% 191%POP 19% 19% 1% 19% 18% 25% 2% 19% 19% 24% 20% 21%Inshore rockfish 0% 0% -1% 0% -1% 2% -1% 0% 2% 0% 0% 1%Piscivorous rockfish -1% -1% -3% 2% -1% 4% -3% 2% -1% 5% -1% 0%Planktivorous rockfish 1% 1% -3% 5% 1% 9% -3% 5% 1% 10% 1% 2%Arrowtooth flounder 6% 6% -3% 6% 5% 10% -3% 6% 7% 9% 6% 7%Flatfish 0% 0% -5% -2% -1% 2% -5% -1% 0% 0% 0% 0%Juvenile halibut 3% 3% -3% 4% 2% 7% -3% 4% 3% 6% 4% 4%Adult halibut 8% 7% -2% 8% 5% 12% -2% 8% 6% 11% 9% 8%Pacific cod 26% 25% 1% 31% 18% 43% 1% 31% 21% 38% 26% 27%Sablefish 17% 17% -4% 20% 16% 22% -4% 18% 17% 23% 15% 17%Lingcod -8% -8% -2% -10% -7% -7% -2% -10% -8% -8% -7% -8%Shallowwater benthic fish 5% 5% -7% 3% 4% 7% -7% 3% 8% 5% 6% 6%Small demersal elasmobranchs 3% 3% -2% 2% 3% 4% -2% 2% 3% 4% 3% 3%Large demersal sharks 4% 4% -4% 4% 2% 6% -3% 4% 3% 6% 4% 4%Large crabs -8% -8% 6% -13% -7% -12% 6% -12% -8% -15% -8% -9%Small crabs -1% -1% -4% 0% -2% 0% -4% 0% 1% -3% -1% -1%Commercial shrimp 7% 8% -8% 15% 14% 3% -7% 13% 22% 5% 5% 8%Epifaunal invertebrates -1% -1% 1% 0% -1% -1% 1% -1% 2% -7% -1% -1%Infaunal detritivorous invertebrates 0% 0% -5% 0% -1% 2% -5% 0% 0% 2% 0% 0%Carnivorous jellyfish 1% 1% -6% 2% 1% 4% -6% 2% 2% 4% 2% 2%Corals and sponges -3% -2% -5% 0% -1% 1% -5% -2% -2% 1% -3% -3%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 3% -11% 0% 0%	 	 APPENDIX	D					65	Scenario	7:	No	fishing	anywhere		[no	catch]   RESULTS	TABLES		66	B.	Ecospace	results	(Large		MPAs)	Biomass	Scenario	1:	No	fishing	in	MPA	 no fishing in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup Name Group name Group name Group name Group name Group nameSea Otters 1% 1% -2% 0% 1% -1% -1% 0% 2% 0% 0% 1%Gray whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Humpback whales 0% 0% -1% -1% 0% 0% -1% -1% 0% 0% 0% 0%Minke whales 0% 0% -1% -1% 0% 0% -1% -1% 0% 0% -1% 0%Blue whales 0% 0% -1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Fin whales 0% 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0%Sei whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sperm whales 0% 0% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Resident orcas 6% 3% 6% 6% 13% 13% 5% 4% 11% 11% 9% 8%Transient orcas 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Small odontocetes -1% -1% 1% 0% 0% 0% 0% -1% -1% 0% 0% -1%Seals 1% 0% 2% 2% 1% 1% 1% 1% 0% 0% 1% 1%Sea lions 0% -1% 10% 4% -1% 1% 8% 3% -2% 0% 2% 1%Seabirds 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Transient salmon 9% 1% 30% 21% 6% 16% 18% 11% -2% 8% 21% 9%Coho salmon 17% -3% 61% 30% 65% 54% 28% 9% 25% 32% 48% 21%Chinook salmon 5% -8% 21% 14% 27% 29% 8% 1% 7% 14% 22% 7%Small squid 1% 1% 0% 1% 0% 0% 1% 1% 0% 0% 0% 1%Large squid 0% 2% -7% -5% 0% -3% -3% -2% 2% -1% -3% -1%Ratfish -1% -2% 1% -1% 0% 0% 0% -2% -1% -1% 0% -1%Dogfish 3% -1% 9% 13% 1% 6% 6% 7% -3% 3% 8% 4%Pollock 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0% 0%Forage fish -1% -1% -1% -1% -2% -1% -1% -1% -2% -1% -1% -1%Hake 5% 3% 13% 10% 5% 6% 12% 7% 2% 5% 8% 6%Eulachon 0% 0% 1% 1% 0% 1% 1% 1% 0% 1% 1% 0%Juvenile herring -1% -1% -16% -2% 3% -1% -10% -2% 1% -2% -1% -1%Adult herring -1% -2% -14% 0% 3% 1% -10% -1% 0% -1% 1% -1%POP -5% -20% 45% 22% -1% 2% 12% 7% -17% -5% 14% -2%Inshore rockfish 19% 5% 25% 53% 29% 70% 11% 35% 10% 47% 42% 25%Piscivorous rockfish 6% 0% 12% 23% 1% 13% 7% 15% -2% 10% 12% 6%Planktivorous rockfish 8% 0% 17% 32% 2% 14% 10% 20% -3% 9% 16% 8%Arrowtooth flounder -4% -9% 12% 3% -3% -2% -1% -1% -8% -4% 2% -4%Flatfish -2% -4% -5% -2% 5% 0% -7% -5% 0% -2% 1% -2%Juvenile halibut 1% -3% 11% 5% 4% 6% 7% 1% 0% 2% 5% 2%Adult halibut 1% -3% 10% 6% 5% 6% 6% 1% 1% 3% 6% 2%Pacific cod 0% -7% 26% 9% 10% 1% 13% -1% -1% -4% 10% -1%Sablefish 1% -6% 17% -6% 9% 9% 12% -7% 2% 2% 9% 2%Lingcod 15% -5% 114% 40% 6% 19% 50% 24% -7% 9% 39% 14%Shallowwater benthic fish 2% 7% -43% -4% 2% -3% -26% 1% 5% 0% -5% 1%Small demersal elasmobranchs -4% -6% 11% -1% -3% -3% 4% -3% -5% -4% -2% -3%Large demersal sharks 0% 0% 3% 1% 0% 0% 2% 1% 0% 0% 0% 0%Salmon sharks 14% 9% 30% 28% 2% 14% 27% 25% 0% 12% 19% 16%Blue sharks 2% 2% 4% 4% 1% 2% 4% 4% 1% 2% 3% 2%Large crabs 1% 3% -10% -2% 5% -6% -5% 1% 3% -4% -1% 0%Small crabs 0% -1% 1% -1% -1% -1% 0% -1% -1% 0% 0% -1%Commercial shrimp 0% 1% -30% -3% 0% 2% -12% -2% 0% -1% 1% -1%Epifaunal invertebrates 0% 0% 0% 1% 0% 1% 0% 0% 0% 0% 0% 0%Infaunal carnivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Infaunal detritivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Carnivorous jellyfish 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Euphausiids 0% 1% -1% -1% 0% -1% 0% 0% 0% 0% -1% 0%Copepods 0% 0% 1% 1% 0% 1% 0% 0% 0% 0% 1% 0%Corals and sponges 0% 0% 0% 0% 1% 0% 0% 0% 0% -1% 0% 0%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Detritus 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Total 0% 0% 2% 1% 0% 0% 1% 0% 0% 0% 1% 0%	 	 APPENDIX	D					67	Scenario	2:	Only	Haida	fisheries	in	MPA	 Group name Group Name only haida fisheries in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group name Group nameSea Otters 1% 1% -2% 0% 1% -1% -1% 0% 2% 0% 0% 1%Gray whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Humpback whales 0% 0% -1% -1% 0% 0% -1% -1% 0% 0% 0% 0%Minke whales 0% 0% -1% -1% 0% 0% -1% -1% 0% 0% -1% 0%Blue whales 0% 0% -1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Fin whales 0% 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0%Sei whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sperm whales 0% 0% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Resident orcas 6% 3% 6% 6% 13% 13% 5% 4% 11% 11% 9% 8%Transient orcas 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Small odontocetes -1% -1% 1% 0% 0% 0% 0% -1% -1% 0% 0% -1%Seals 1% 0% 2% 2% 1% 1% 1% 1% 0% 0% 1% 1%Sea lions 0% -1% 10% 4% -1% 1% 8% 3% -2% 0% 2% 1%Seabirds 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Transient salmon 9% 1% 30% 21% 6% 16% 18% 11% -2% 8% 21% 9%Coho salmon 17% -3% 61% 29% 65% 53% 28% 9% 25% 32% 47% 21%Chinook salmon 5% -8% 21% 14% 27% 29% 8% 1% 7% 14% 22% 7%Small squid 1% 1% 0% 1% 0% 0% 1% 1% 0% 0% 0% 1%Large squid 0% 2% -7% -5% 0% -3% -3% -2% 2% -1% -3% -1%Ratfish -1% -2% 1% -1% 0% 0% 0% -2% -1% -1% 0% -1%Dogfish 3% -1% 9% 13% 1% 6% 6% 7% -3% 3% 8% 4%Pollock 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0% 0%Forage fish -1% -1% -1% -1% -2% -1% -1% -1% -2% -1% -1% -1%Hake 5% 3% 13% 10% 5% 6% 12% 7% 2% 5% 8% 6%Eulachon 0% 0% 1% 1% 0% 1% 1% 1% 0% 1% 1% 0%Juvenile herring -1% -1% -16% -2% 3% -1% -10% -2% 1% -2% -1% -1%Adult herring -1% -2% -14% 0% 3% 1% -10% -1% 0% -1% 1% -1%POP -5% -20% 45% 22% -1% 2% 12% 7% -17% -5% 14% -2%Inshore rockfish 19% 5% 25% 53% 29% 70% 11% 35% 10% 47% 42% 25%Piscivorous rockfish 6% 0% 12% 23% 1% 13% 7% 15% -2% 10% 12% 6%Planktivorous rockfish 8% 0% 17% 32% 2% 14% 10% 20% -3% 9% 16% 8%Arrowtooth flounder -4% -9% 12% 3% -3% -2% -1% -1% -8% -4% 2% -4%Flatfish -2% -4% -5% -2% 5% 0% -7% -5% 0% -2% 1% -2%Juvenile halibut 1% -3% 11% 5% 4% 6% 7% 1% 0% 2% 5% 2%Adult halibut 1% -3% 10% 6% 5% 6% 6% 1% 1% 3% 6% 2%Pacific cod 0% -7% 26% 9% 10% 1% 13% -1% -1% -4% 10% -1%Sablefish 1% -6% 17% -6% 9% 9% 12% -7% 2% 2% 9% 2%Lingcod 15% -5% 114% 40% 6% 19% 50% 24% -7% 9% 39% 14%Shallowwater benthic fish 2% 7% -43% -4% 2% -3% -26% 1% 5% 0% -5% 1%Small demersal elasmobranchs -4% -6% 11% -1% -3% -3% 4% -3% -5% -4% -2% -3%Large demersal sharks 0% 0% 3% 1% 0% 0% 2% 1% 0% 0% 0% 0%Salmon sharks 13% 9% 30% 28% 2% 14% 27% 24% 0% 12% 19% 16%Blue sharks 2% 2% 4% 4% 1% 2% 4% 4% 1% 2% 3% 2%Large crabs 1% 3% -10% -2% 5% -6% -5% 1% 3% -4% -1% 0%Small crabs 0% -1% 1% -1% -1% -1% 0% -1% -1% 0% 0% -1%Commercial shrimp 0% 1% -30% -3% 0% 2% -12% -2% 0% -1% 1% -1%Epifaunal invertebrates 0% 0% 0% 1% 0% 1% 0% 0% 0% 0% 0% 0%Infaunal carnivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Infaunal detritivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Carnivorous jellyfish 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Euphausiids 0% 1% -1% -1% 0% -1% 0% 0% 0% 0% -1% 0%Copepods 0% 0% 1% 1% 0% 1% 0% 0% 0% 0% 1% 0%Corals and sponges 0% 0% 0% 0% 1% 0% 0% 0% 0% -1% 0% 0%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Detritus 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Total 0% 0% 2% 1% 0% 0% 1% 0% 0% 0% 1% 0%RESULTS	TABLES		68	Scenario	3:	No	ground	fish	trawl	in	MPAs	 Group name no groundfish trawl in mpaGroup Name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group name Group name Group nameSea Otters 0% 1% -1% 0% 0% 0% 0% 0% 1% 0% 0% 1%Gray whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Humpback whales 0% 0% 0% -1% 0% 0% 0% 0% 0% 0% 0% 0%Minke whales 0% 0% -1% -1% 0% 0% 0% 0% 1% 0% 0% 0%Blue whales 0% 0% -1% -1% 0% 0% 0% -1% 0% 0% 0% 0%Fin whales 0% 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0%Sei whales 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Sperm whales 0% 0% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0%Resident orcas 0% 0% 0% 0% 1% 1% 0% 0% 1% 1% 0% 0%Transient orcas 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Small odontocetes 1% 1% 0% 1% 1% 0% 0% 1% 1% 0% 0% 1%Seals 2% 2% 2% 2% 1% 1% 1% 2% 1% 1% 1% 1%Sea lions 0% 0% 2% 1% 0% 0% 1% 1% 0% 0% 0% 0%Seabirds 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Transient salmon 0% 0% -1% -1% 0% 0% -1% -1% 0% 0% -1% 0%Coho salmon 0% 0% -6% -1% 0% 0% -4% -1% 1% 0% -1% 0%Chinook salmon 0% 0% -2% -1% 0% 0% -2% -1% 0% 0% -1% 0%Small squid 0% 0% -1% 0% 0% 0% 0% 1% 0% 0% 0% 0%Large squid 0% 1% -6% -4% 1% -2% -3% -2% 2% 0% -3% 0%Ratfish 0% -1% 3% 2% -1% 0% 2% 1% -2% -1% 1% 0%Dogfish 0% -1% 1% 1% 0% 0% 1% 0% -1% -1% 1% 0%Pollock 0% 0% 1% 0% 0% -1% 1% 0% -1% -1% 0% 0%Forage fish 0% 0% 1% -1% -1% -1% 0% -1% -1% -1% 0% 0%Hake 0% 0% -1% -1% 0% 0% -1% -1% 0% 0% -1% 0%Eulachon 0% 0% 1% 0% 0% 1% 1% 0% 0% 1% 0% 0%Juvenile herring 0% 1% -6% -3% 0% -2% -3% -1% 1% -1% -2% 0%Adult herring 0% 2% -5% -2% 1% -1% -3% -1% 1% -1% -1% 0%POP -4% -19% 50% 25% 0% 5% 13% 9% -17% -3% 17% -1%Inshore rockfish -1% 0% -7% -3% 3% 2% -3% -2% 4% 2% -2% 0%Piscivorous rockfish 5% 0% 10% 19% 1% 9% 6% 12% -2% 6% 10% 5%Planktivorous rockfish 9% 0% 18% 32% 2% 14% 11% 21% -3% 8% 16% 8%Arrowtooth flounder -2% -8% 20% 7% -2% 1% 3% 2% -7% -2% 6% -1%Flatfish -1% -4% 10% 3% 6% 2% 4% -2% 0% -1% 4% -1%Juvenile halibut 1% 1% -1% 0% 1% 0% -1% 0% 1% 0% 0% 1%Adult halibut 0% 0% 0% 0% 1% 0% 0% 0% 1% 0% 1% 0%Pacific cod 3% -5% 46% 13% 9% 5% 29% 2% -2% -1% 16% 3%Sablefish 0% 0% 0% 0% 0% 0% 0% -1% 0% 0% 0% 0%Lingcod 7% -8% 89% 26% 1% 5% 38% 14% -10% -1% 25% 6%Shallowwater benthic fish 3% 6% -29% -1% 2% 1% -16% 3% 4% 2% -2% 2%Small demersal elasmobranchs -3% -5% 14% 0% -3% -2% 7% -2% -5% -3% 0% -3%Large demersal sharks 0% 0% 2% 1% 0% 0% 2% 1% -1% 0% 0% 0%Salmon sharks -1% -1% -1% -1% -1% -1% -1% -1% -1% -1% -1% -1%Blue sharks 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0% 0%Large crabs 1% 2% -6% 1% 1% 0% -1% 2% 2% 0% 0% 1%Small crabs 0% 0% 0% -1% -1% -1% 0% -1% -1% -1% 0% 0%Commercial shrimp 1% 1% -11% -1% 0% 0% -2% 0% 1% 0% 0% 0%Epifaunal invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Infaunal carnivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Infaunal detritivorous invertebrates 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Carnivorous jellyfish 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Euphausiids 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0% 0%Copepods 0% 0% 1% 1% 0% 0% 0% 0% 0% 0% 0% 0%Corals and sponges 0% 0% 0% 0% 0% 0% 0% 0% 0% -1% 0% 0%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Detritus 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Total 0% 0% 1% 1% 0% 0% 1% 0% 0% 0% 1% 0%	 	 APPENDIX	D					69	Scenario	4:	Heavy	fishing	2-times	everywhere	 Group name Group Name Group name heavy fishing 2timesGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group nameSea Otters 15% 15% 9% 12% 19% 25% 7% 14% 21% 25% 15% 17%Gray whales 0% -1% 0% -1% -1% -1% 0% -1% -1% -1% 0% 0%Humpback whales 7% 7% 7% 14% 7% 6% 7% 12% 7% 6% 8% 8%Minke whales 9% 9% 8% 15% 9% 8% 9% 14% 9% 8% 10% 10%Blue whales 0% 0% 1% -3% 0% -1% 1% -2% 0% -1% 0% 0%Fin whales 1% 1% 2% 0% 1% 0% 1% 1% 1% 0% 1% 1%Sei whales -2% -1% 0% -5% -2% -4% -1% -4% -2% -4% -2% -2%Sperm whales 2% 2% 0% 4% 2% 6% 0% 4% 3% 6% 2% 2%Resident orcas -41% -39% -17% -54% -46% -54% -17% -54% -47% -53% -43% -44%Transient orcas 0% 0% -1% 1% -1% 0% -1% 1% -1% 1% 0% 0%Small odontocetes 12% 10% 5% 22% 9% 10% 9% 19% 9% 10% 13% 12%Seals 28% 26% 15% 40% 24% 27% 19% 37% 24% 27% 29% 28%Sea lions -19% -19% -33% -17% -20% -16% -32% -17% -20% -16% -19% -19%Seabirds 5% 5% 1% 9% 5% 6% 2% 8% 5% 6% 6% 6%Transient salmon -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100%Coho salmon -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100%Chinook salmon -99% -99% -99% -98% -99% -100% -99% -98% -99% -100% -99% -99%Small squid -9% -6% -11% -18% -10% -11% -13% -15% -8% -10% -13% -11%Large squid 18% 15% 26% 23% 23% 26% 22% 23% 21% 24% 25% 23%Ratfish -4% -5% 3% 1% -9% -10% 3% 0% -9% -11% -4% -5%Dogfish -54% -53% -50% -58% -58% -61% -50% -57% -59% -61% -56% -56%Pollock -1% -1% 3% -3% -2% -4% 2% -2% -2% -4% -1% -1%Forage fish 0% 0% 1% 1% 0% -5% 2% 1% -1% -5% 0% 0%Hake -97% -97% -96% -97% -97% -98% -96% -97% -97% -98% -97% -97%Eulachon 1% 1% 1% 2% 2% 1% 2% 1% 2% 2% 2% 2%Juvenile herring 22% 14% 162% 52% 21% 3% 137% 43% 17% 0% 27% 21%Adult herring 22% 14% 163% 50% 20% 0% 139% 40% 16% 0% 27% 22%POP -81% -82% -71% -78% -86% -83% -73% -79% -84% -84% -81% -81%Inshore rockfish -55% -48% -43% -66% -74% -85% -43% -66% -74% -84% -63% -66%Piscivorous rockfish -40% -40% -36% -41% -41% -56% -37% -39% -42% -56% -41% -42%Planktivorous rockfish -51% -52% -45% -55% -53% -66% -45% -52% -54% -66% -51% -52%Arrowtooth flounder -28% -31% -18% -23% -34% -31% -16% -25% -34% -32% -26% -28%Flatfish 19% 16% 51% 30% 15% 15% 57% 25% 14% 14% 21% 19%Juvenile halibut -33% -35% -24% -25% -36% -34% -24% -27% -36% -35% -32% -33%Adult halibut -37% -38% -27% -29% -40% -39% -27% -31% -41% -39% -36% -37%Pacific cod -9% -8% -45% -1% -4% -4% -41% -4% -3% -5% -11% -8%Sablefish -48% -48% -39% -33% -54% -59% -38% -36% -55% -60% -49% -50%Lingcod -98% -99% -97% -98% -98% -99% -97% -99% -98% -99% -98% -98%Shallowwater benthic fish 91% 78% 260% 122% 73% 85% 277% 103% 69% 81% 107% 92%Small demersal elasmobranchs -62% -63% -54% -59% -65% -64% -54% -60% -65% -64% -62% -63%Large demersal sharks 1% 1% -10% 1% 0% 6% -9% 2% 1% 5% 2% 2%Salmon sharks -85% -83% -79% -89% -90% -91% -78% -89% -90% -91% -87% -87%Blue sharks -21% -19% -27% -29% -17% -15% -28% -28% -16% -15% -23% -21%Large crabs 111% 106% 66% 145% 98% 148% 82% 133% 93% 137% 120% 113%Small crabs -5% -4% -6% -10% -4% -4% -5% -10% -4% -4% -6% -6%Commercial shrimp 23% 21% 1264% 44% 25% 20% 468% 32% 21% 19% 25% 23%Epifaunal invertebrates 0% 0% 2% 1% 0% 0% 2% 0% 0% 0% 1% 0%Infaunal carnivorous invertebrates 0% 0% -1% 0% 0% -1% 0% 0% 0% -1% 0% 0%Infaunal detritivorous invertebrates 0% 0% 0% 0% 0% -1% 0% 0% 0% -1% 0% 0%Carnivorous jellyfish 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1%Euphausiids 0% 0% 1% -4% -1% -1% 0% -1% 0% -1% -1% -1%Copepods -1% -1% -1% -1% -2% -1% -1% -2% -2% -2% -2% -1%Corals and sponges -1% -1% -1% -1% -1% -2% -1% -1% -1% -2% -1% -1%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton 0% 0% 0% 1% 0% 0% 0% 1% 0% 0% 1% 0%Detritus 0% 0% 0% 1% 0% 0% 0% 1% 0% 0% 0% 0%Total -2% -2% -4% -1% -2% -3% -3% -1% -2% -3% -2% -2%RESULTS	TABLES		70	Scenario	5:	Heavy	fishing	2-times,	but	not	in	MPAs	 Group name Group Name Group name Group name heavy fishing but not in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group nameSea Otters 14% 16% 2% 9% 20% 22% 4% 12% 22% 23% 12% 17%Gray whales 0% -1% 0% 0% -1% -1% 0% -1% -1% -1% 0% 0%Humpback whales 6% 5% 4% 12% 7% 7% 5% 10% 7% 6% 8% 7%Minke whales 8% 7% 5% 14% 9% 9% 6% 12% 9% 9% 9% 9%Blue whales 0% 0% 0% -4% 1% -2% 0% -3% 1% -1% -1% -1%Fin whales 1% 1% 1% -1% 2% 0% 1% 0% 1% 0% 0% 1%Sei whales -2% -1% -1% -5% -2% -4% -1% -5% -2% -3% -3% -2%Sperm whales 2% 2% 0% 3% 3% 7% 0% 3% 3% 7% 2% 2%Resident orcas -38% -37% -12% -51% -42% -52% -13% -51% -44% -51% -40% -42%Transient orcas 0% 0% -1% 0% -2% 0% -1% 0% -1% 0% 0% 0%Small odontocetes 9% 6% 4% 20% 7% 11% 7% 16% 7% 10% 12% 10%Seals 27% 24% 11% 40% 24% 29% 15% 36% 23% 28% 30% 28%Sea lions -20% -21% -31% -16% -21% -16% -30% -18% -21% -16% -19% -19%Seabirds 5% 4% 0% 8% 5% 6% 1% 7% 5% 6% 6% 5%Transient salmon -97% -98% -96% -96% -98% -98% -97% -97% -99% -99% -97% -98%Coho salmon -96% -98% -74% -94% -92% -99% -95% -97% -97% -99% -94% -97%Chinook salmon -85% -92% -36% -80% -77% -96% -67% -87% -88% -97% -76% -87%Small squid -8% -5% -9% -16% -11% -11% -10% -13% -7% -10% -12% -10%Large squid 18% 17% 13% 15% 23% 23% 16% 19% 23% 23% 19% 21%Ratfish -7% -9% 5% -1% -10% -10% 4% -4% -12% -12% -4% -7%Dogfish -49% -52% -39% -43% -55% -54% -43% -48% -58% -56% -46% -51%Pollock -2% -2% 1% -2% -2% -4% 1% -2% -3% -4% -1% -2%Forage fish 0% 0% 2% 2% -2% -5% 2% 1% -2% -5% 0% -1%Hake -95% -95% -92% -94% -95% -96% -93% -95% -95% -96% -94% -95%Eulachon 2% 2% 1% 3% 1% 3% 3% 3% 2% 3% 2% 2%Juvenile herring 18% 5% 104% 61% 29% 7% 102% 42% 14% 0% 32% 19%Adult herring 18% 3% 112% 67% 27% 7% 105% 42% 12% 0% 35% 20%POP -74% -84% -13% -52% -81% -77% -58% -65% -87% -80% -62% -74%Inshore rockfish -33% -41% -4% 5% -48% -45% -25% -20% -64% -58% -20% -43%Piscivorous rockfish -29% -38% -15% -4% -39% -42% -25% -15% -43% -45% -23% -32%Planktivorous rockfish -38% -49% -19% -13% -50% -54% -31% -25% -56% -58% -30% -41%Arrowtooth flounder -32% -42% 5% -18% -36% -30% -20% -27% -43% -35% -21% -32%Flatfish 13% 4% 48% 29% 25% 15% 42% 14% 12% 8% 25% 13%Juvenile halibut -22% -30% 19% -1% -23% -15% 6% -13% -28% -21% -13% -21%Adult halibut -27% -34% 9% -6% -26% -19% -2% -17% -32% -26% -17% -25%Pacific cod -4% -18% 6% 33% 22% 6% -12% 3% -4% -8% 18% -4%Sablefish -41% -48% -8% -31% -41% -46% -18% -37% -49% -53% -32% -42%Lingcod -88% -94% -27% -81% -97% -98% -72% -86% -97% -98% -80% -91%Shallowwater benthic fish 83% 83% 107% 93% 70% 79% 186% 90% 72% 78% 82% 84%Small demersal elasmobranchs -65% -67% -44% -60% -67% -65% -51% -63% -68% -66% -63% -65%Large demersal sharks 0% 0% -7% 0% 0% 5% -7% 0% 0% 4% 1% 1%Salmon sharks -84% -82% -77% -88% -89% -90% -77% -88% -89% -90% -86% -87%Blue sharks -19% -17% -26% -27% -15% -15% -26% -26% -14% -14% -21% -20%Large crabs 92% 88% 30% 106% 100% 120% 54% 104% 84% 110% 100% 94%Small crabs -5% -4% -5% -10% -5% -5% -5% -10% -4% -4% -6% -6%Commercial shrimp 23% 20% 919% 37% 26% 25% 383% 28% 21% 17% 28% 21%Epifaunal invertebrates 0% 0% 1% 2% 1% 1% 1% 1% 0% 1% 1% 1%Infaunal carnivorous invertebrates 0% 0% 0% 1% 0% -1% 0% 0% 0% -1% 0% 0%Infaunal detritivorous invertebrates 0% 0% 0% 1% 0% -1% 0% 0% 0% -1% 0% 0%Carnivorous jellyfish 1% 0% 1% 2% 1% 1% 1% 1% 1% 1% 1% 1%Euphausiids 0% 1% 0% -7% -1% -2% -1% -3% 0% -1% -3% -1%Copepods -1% -1% 0% 0% -2% -2% 0% -1% -2% -1% -1% -1%Corals and sponges -1% -2% 0% -2% 0% -1% -1% -2% -1% -4% 0% -1%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton 0% 0% 0% 2% 0% 1% 0% 1% 0% 0% 1% 0%Detritus 0% 0% 0% 1% 0% 0% 0% 1% 0% 0% 1% 0%Total -2% -2% -2% 1% -1% -2% -2% -1% -2% -3% -1% -2%	 	 APPENDIX	D					71	Scenario	6:	Herring	fisheries	5-times	everywhere	 Group name Group Name Group name Group name Group name herring fisheries 5timesGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup nameSea Otters 2% 2% 1% 3% 2% 6% 1% 3% 2% 5% 2% 2%Gray whales 0% 0% 0% 0% 0% -1% 0% 0% 0% -1% 0% 0%Humpback whales -11% -10% -2% -15% -11% -18% -2% -15% -12% -17% -12% -13%Minke whales -7% -7% -1% -10% -7% -12% -1% -10% -8% -12% -8% -9%Blue whales 7% 6% 1% 17% 8% 18% 2% 16% 9% 17% 9% 9%Fin whales 7% 6% 1% 12% 7% 13% 2% 12% 7% 12% 8% 8%Sei whales 8% 7% 1% 15% 10% 18% 1% 15% 11% 18% 9% 10%Sperm whales 3% 2% 0% 6% 4% 9% 1% 5% 4% 9% 3% 3%Resident orcas 25% 24% 5% 36% 26% 46% 6% 35% 27% 43% 29% 29%Transient orcas -20% -19% -2% -21% -23% -34% -2% -22% -25% -34% -22% -23%Small odontocetes -55% -54% -17% -57% -53% -60% -20% -58% -53% -59% -56% -56%Seals -41% -40% -12% -43% -39% -45% -15% -44% -39% -44% -42% -42%Sea lions -24% -24% 3% -25% -23% -31% 1% -26% -24% -31% -25% -25%Seabirds -11% -10% -1% -13% -12% -16% -2% -14% -12% -15% -12% -12%Transient salmon 34% 34% 23% 41% 36% 47% 24% 40% 36% 45% 34% 35%Coho salmon 51% 50% 40% 49% 53% 60% 45% 48% 53% 60% 53% 53%Chinook salmon 45% 47% 11% 43% 47% 72% 17% 42% 49% 70% 46% 48%Small squid 14% 13% 2% 18% 18% 28% 3% 17% 18% 28% 17% 17%Large squid 8% 7% -1% 10% 10% 17% 0% 10% 10% 16% 10% 10%Ratfish 5% 5% 0% 6% 5% 9% 1% 6% 5% 8% 5% 5%Dogfish 3% 3% 2% 5% 4% 6% 2% 5% 4% 5% 4% 4%Pollock 23% 24% 6% 31% 27% 44% 7% 29% 29% 43% 23% 25%Forage fish -1% 0% -1% -2% 0% -1% -1% -2% 0% 0% -1% -1%Hake 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0% 0%Eulachon -6% -6% -3% -10% -4% -9% -4% -9% -4% -8% -7% -6%Juvenile herring -37% -38% -6% -36% -38% -35% -16% -37% -38% -35% -35% -36%Adult herring -53% -54% -24% -51% -54% -52% -32% -52% -55% -52% -51% -52%POP 28% 27% 14% 30% 26% 35% 18% 30% 24% 34% 30% 29%Inshore rockfish 0% 0% 0% -1% 0% 1% 0% -1% -1% 1% 0% 0%Piscivorous rockfish 1% 1% 1% 2% 2% 2% 1% 2% 2% 1% 1% 1%Planktivorous rockfish 4% 4% 2% 7% 4% 9% 3% 5% 4% 9% 4% 4%Arrowtooth flounder 8% 8% 3% 8% 8% 12% 3% 8% 8% 11% 8% 8%Flatfish -4% -4% -2% -6% -3% -3% -3% -6% -3% -3% -4% -4%Juvenile halibut 4% 4% 4% 5% 4% 5% 4% 4% 4% 5% 5% 5%Adult halibut 10% 10% 5% 10% 8% 12% 5% 10% 9% 12% 10% 10%Pacific cod 30% 29% 9% 37% 25% 52% 11% 35% 26% 48% 32% 32%Sablefish 20% 21% 6% 26% 23% 29% 6% 23% 24% 29% 20% 22%Lingcod -18% -19% -1% -23% -15% -20% -3% -23% -16% -20% -16% -18%Shallowwater benthic fish 3% 3% -4% 1% 1% 11% -4% 1% 2% 9% 4% 4%Small demersal elasmobranchs 2% 2% 3% 1% 3% 2% 2% 1% 3% 2% 2% 2%Large demersal sharks 4% 4% 2% 4% 3% 4% 2% 4% 3% 4% 4% 4%Salmon sharks 42% 41% 29% 52% 43% 45% 30% 49% 44% 45% 43% 43%Blue sharks 24% 23% 8% 27% 23% 34% 9% 27% 24% 33% 25% 25%Large crabs -12% -12% -2% -15% -11% -15% -4% -15% -11% -14% -12% -12%Small crabs -3% -3% 0% -2% -3% -5% 0% -3% -3% -5% -3% -3%Commercial shrimp 20% 19% 39% 26% 25% 15% 30% 23% 25% 16% 19% 20%Epifaunal invertebrates -1% -1% 0% -2% -1% -1% 0% -2% -2% -2% -1% -1%Infaunal carnivorous invertebrates -2% -2% 0% -3% -2% -3% -1% -3% -3% -3% -2% -2%Infaunal detritivorous invertebrates -2% -1% 0% -3% -2% -2% 0% -3% -2% -2% -2% -2%Carnivorous jellyfish -1% -1% 0% -2% -1% -2% 0% -2% -1% -2% -1% -1%Euphausiids 8% 7% 1% 11% 9% 12% 2% 10% 9% 12% 9% 9%Copepods -1% -1% 0% -4% -2% -3% -1% -3% -2% -3% -2% -2%Corals and sponges 0% 0% 0% 0% 0% 0% 0% 0% 0% -1% 0% 0%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton -1% -1% 0% -2% -2% -2% 0% -2% -2% -2% -2% -2%Detritus -1% -1% 0% -2% -2% -2% 0% -2% -2% -2% -1% -1%Total -1% -1% 0% -2% -1% -1% 0% -2% -2% -1% -1% -1%RESULTS	TABLES		72	Scenario	7:	No	fishing	anywhere		Group name Group Name Group name Group name Group name Group name no fishing anywhereGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverSea Otters -5% -5% -2% -2% -6% -10% -1% -2% -9% -10% -5% -6%Gray whales 1% 1% 0% 1% 1% 2% 0% 1% 1% 2% 1% 1%Humpback whales -11% -10% -4% -15% -11% -14% -4% -14% -11% -14% -12% -12%Minke whales -13% -12% -6% -16% -13% -17% -6% -15% -14% -17% -14% -14%Blue whales 1% 1% -2% 6% 1% 5% -1% 5% 1% 5% 1% 2%Fin whales 0% 0% -2% 2% -1% 1% -1% 1% -1% 1% 0% 0%Sei whales 5% 4% 1% 11% 5% 10% 1% 10% 5% 10% 6% 6%Sperm whales 1% 1% 3% 2% 2% -1% 3% 2% 1% -1% 2% 2%Resident orcas 216% 205% 39% 240% 261% 446% 45% 245% 271% 432% 248% 256%Transient orcas 9% 9% 3% 8% 13% 11% 3% 8% 13% 12% 9% 10%Small odontocetes -17% -17% 12% -21% -15% -21% 8% -21% -15% -20% -18% -18%Seals -22% -21% 15% -24% -20% -25% 11% -25% -21% -25% -22% -22%Sea lions 64% 62% 114% 60% 68% 54% 113% 58% 66% 54% 64% 63%Seabirds -5% -5% 5% -8% -6% -10% 4% -7% -6% -9% -6% -6%Transient salmon 132% 111% 280% 78% 66% 57% 271% 92% 58% 53% 152% 133%Coho salmon 130% 120% 186% 99% 164% 190% 199% 98% 151% 178% 148% 142%Chinook salmon 48% 46% 36% 27% 65% 90% 48% 29% 63% 86% 54% 55%Small squid 12% 10% 6% 19% 16% 19% 9% 19% 13% 19% 15% 15%Large squid -21% -17% -26% -22% -27% -33% -22% -22% -25% -31% -27% -26%Ratfish -5% -5% -5% -10% -2% -5% -5% -9% -3% -5% -6% -5%Dogfish 106% 103% 78% 121% 125% 149% 79% 119% 127% 148% 112% 115%Pollock -3% -3% -2% -3% -4% -5% -2% -3% -5% -5% -3% -4%Forage fish -6% -5% -4% -12% -9% -9% -4% -11% -8% -9% -8% -8%Hake 189% 186% 176% 201% 185% 206% 177% 204% 188% 206% 193% 195%Eulachon 9% 9% 7% 7% 8% 13% 6% 9% 9% 12% 9% 9%Juvenile herring -43% -41% -79% -49% -44% -39% -76% -48% -41% -38% -45% -43%Adult herring -32% -30% -75% -41% -33% -26% -72% -39% -31% -25% -34% -32%POP 214% 218% 142% 179% 291% 229% 151% 186% 260% 235% 211% 217%Inshore rockfish 79% 65% 49% 87% 131% 164% 50% 90% 126% 158% 100% 105%Piscivorous rockfish 57% 57% 44% 57% 58% 111% 44% 53% 60% 109% 60% 62%Planktivorous rockfish 86% 89% 67% 88% 94% 145% 69% 83% 97% 144% 87% 91%Arrowtooth flounder 21% 22% 22% 20% 23% 16% 20% 21% 23% 17% 20% 20%Flatfish -28% -27% -46% -37% -25% -25% -47% -34% -24% -25% -30% -28%Juvenile halibut -15% -14% -11% -20% -10% -22% -11% -20% -10% -21% -17% -16%Adult halibut -4% -3% -2% -9% 1% -8% -2% -9% 0% -7% -5% -5%Pacific cod -19% -23% 47% -29% -25% -35% 43% -27% -28% -34% -15% -21%Sablefish 44% 45% 31% 13% 53% 63% 30% 17% 56% 65% 45% 48%Lingcod 377% 370% 496% 330% 380% 405% 446% 351% 359% 405% 390% 380%Shallowwater benthic fish -75% -74% -90% -83% -68% -80% -91% -81% -68% -79% -78% -76%Small demersal elasmobranchs 78% 79% 85% 78% 83% 66% 82% 79% 82% 67% 75% 76%Large demersal sharks 16% 15% 23% 19% 15% 14% 22% 18% 14% 14% 16% 16%Salmon sharks 1086% 1075% 615% 1113% 1342% 1460% 657% 1083% 1353% 1457% 1121% 1150%Blue sharks 53% 50% 54% 63% 48% 59% 54% 62% 47% 57% 57% 55%Large crabs -41% -41% -33% -46% -39% -48% -36% -44% -38% -46% -43% -42%Small crabs 13% 12% 3% 17% 16% 12% 2% 17% 16% 12% 13% 13%Commercial shrimp -33% -32% -88% -38% -35% -35% -79% -38% -32% -34% -35% -34%Epifaunal invertebrates 0% 0% 1% -1% 0% 0% 1% -1% 0% 0% 0% 0%Infaunal carnivorous invertebrates 0% 0% 1% -1% 0% 0% 0% -1% -1% 0% 0% 0%Infaunal detritivorous invertebrates 0% 0% 0% -1% 0% 0% 0% -1% 0% 0% 0% 0%Carnivorous jellyfish 0% 0% 2% 0% 0% 0% 2% 0% 0% 0% 0% 0%Euphausiids 3% 2% -3% 7% 4% 5% -1% 6% 4% 5% 3% 4%Copepods 2% 1% 2% 1% 2% 4% 1% 2% 2% 4% 2% 2%Corals and sponges 1% 1% 1% 1% 1% 2% 1% 1% 1% 2% 1% 1%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%Phytoplankton -1% -1% 0% -2% -1% -1% 0% -2% -1% -1% -1% -1%Detritus -1% 0% 0% -2% -1% -1% 0% -1% -1% -1% -1% -1%Total 4% 3% 8% 3% 4% 5% 6% 3% 3% 4% 5% 4%	 	 APPENDIX	D					73	Catch	Scenario	1:	No	fishing	in	MPA	  no fishing in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup Name Group name Group name Group name Group name Group nameSeals -4% 47% -100% -100% -100% -100% 80% 67% 56% 72% -100% 67%Sea lions -3% 45% -100% -100% -100% -100% 94% 70% 53% 72% -100% 67%Transient salmon -1% 49% -100% -100% -100% -100% 112% 88% 50% 83% -100% 81%Coho salmon 4% 44% -100% -100% -100% -100% 129% 80% 102% 130% -100% 106%Chinook salmon -4% 38% -100% -100% -100% -100% 93% 67% 73% 100% -100% 82%Large squid 11% 58% -100% -100% -100% -100% 75% 68% 62% 64% -100% 65%Ratfish 0% 52% -100% -100% -100% -100% 80% 67% 58% 62% -100% 63%Dogfish -4% 52% -100% -100% -100% -100% 79% 82% 51% 69% -100% 70%Pollock -2% 57% -100% -100% -100% -100% 79% 72% 61% 65% -100% 68%Forage fish 0% 55% -100% -100% -100% -100% 81% 70% 58% 65% -100% 67%Hake 0% 58% -100% -100% -100% -100% 88% 72% 59% 65% -100% 68%Eulachon 9% 54% -100% -100% -100% -100% 55% 51% 53% 55% -100% 53%Adult herring 4% 46% -100% -100% -100% -100% 26% 51% 53% 50% -100% 51%POP -11% 23% -100% -100% -100% -100% 102% 81% 34% 56% -100% 60%Inshore rockfish 2% 71% -100% -100% -100% -100% 102% 153% 79% 169% -100% 130%Piscivorous rockfish -11% 63% -100% -100% -100% -100% 91% 115% 62% 90% -100% 86%Planktivorous rockfish -9% 61% -100% -100% -100% -100% 98% 123% 59% 81% -100% 86%Arrowtooth flounder -5% 41% -100% -100% -100% -100% 75% 68% 48% 59% -100% 60%Flatfish 3% 47% -100% -100% -100% -100% 67% 59% 61% 61% -100% 61%Juvenile halibut -2% 45% -100% -100% -100% -100% 81% 58% 57% 67% -100% 61%Adult halibut -1% 45% -100% -100% -100% -100% 81% 60% 59% 72% -100% 65%Pacific cod 0% 41% -100% -100% -100% -100% 102% 65% 58% 58% -100% 63%Sablefish -5% 35% -100% -100% -100% -100% 99% 38% 67% 67% -100% 67%Lingcod 0% 43% -100% -100% -100% -100% 161% 105% 51% 82% -100% 85%Shallowwater benthic fish 10% 64% -100% -100% -100% -100% 21% 56% 61% 45% -100% 52%Small demersal elasmobranchs -4% 45% -100% -100% -100% -100% 86% 62% 54% 60% -100% 60%Large demersal sharks 6% 53% -100% -100% -100% -100% 86% 70% 60% 66% -100% 65%Large crabs 9% 60% -100% -100% -100% -100% 40% 63% 61% 33% -100% 56%Small crabs 3% 53% -100% -100% -100% -100% 80% 69% 58% 65% -100% 65%Commercial shrimp -5% 53% -100% -100% -100% -100% 31% 47% 54% 47% -100% 48%Epifaunal invertebrates -4% 48% -100% -100% -100% -100% 49% 49% 48% 49% -100% 49%Infaunal detritivorous invertebrates 6% 54% -100% -100% -100% -100% 83% 71% 60% 66% -100% 67%Carnivorous jellyfish 3% 49% -100% -100% -100% -100% 80% 67% 56% 70% -100% 66%Corals and sponges 10% 57% -100% -100% -100% -100% 79% 59% 62% 59% -100% 66%Macrophytes 3% 102% -100% -100% -100% -100% 102% 102% 102% 102% -100% 102%RESULTS	TABLES		74	Scenario	2:	Only	Haida	fisheries	in	MPAs		  Group name Group Name only haida fisheries in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group name Group nameSeals -4% 47% -100% -100% -100% -100% 80% 67% 56% 72% -100% 67%Sea lions -3% 45% -100% -100% -100% -100% 94% 70% 53% 72% -100% 67%Transient salmon -1% 49% -100% -100% -100% -100% 112% 88% 50% 83% -100% 81%Coho salmon 5% 43% -99% -99% -99% -100% 128% 79% 101% 130% -99% 106%Chinook salmon -4% 38% -100% -100% -100% -100% 93% 67% 73% 100% -100% 82%Large squid 11% 58% -100% -100% -100% -100% 75% 68% 62% 64% -100% 65%Ratfish 0% 52% -100% -100% -100% -100% 80% 67% 58% 62% -100% 63%Dogfish -4% 52% -100% -100% -100% -100% 79% 82% 51% 69% -100% 70%Pollock -2% 57% -100% -100% -100% -100% 79% 72% 61% 65% -100% 68%Forage fish 0% 55% -100% -100% -100% -100% 81% 70% 58% 65% -100% 67%Hake 0% 58% -100% -100% -100% -100% 88% 72% 59% 65% -100% 68%Eulachon 9% 54% -100% -100% -100% -100% 55% 51% 53% 55% -100% 53%Adult herring 4% 45% -100% -100% -100% -100% 26% 51% 53% 49% -100% 51%POP -11% 23% -100% -100% -100% -100% 102% 81% 34% 56% -100% 60%Inshore rockfish 2% 71% -100% -100% -100% -100% 102% 153% 79% 169% -100% 130%Piscivorous rockfish -11% 63% -100% -100% -100% -100% 91% 115% 62% 90% -100% 86%Planktivorous rockfish -9% 61% -100% -100% -100% -100% 98% 123% 59% 81% -100% 86%Arrowtooth flounder -5% 41% -100% -100% -100% -100% 75% 68% 48% 59% -100% 60%Flatfish 3% 47% -100% -100% -100% -100% 67% 59% 61% 61% -100% 61%Juvenile halibut -2% 45% -100% -100% -100% -100% 81% 58% 57% 67% -100% 61%Adult halibut -1% 45% -100% -100% -100% -100% 81% 60% 59% 72% -100% 65%Pacific cod 0% 41% -100% -100% -100% -100% 102% 65% 58% 58% -100% 63%Sablefish -5% 35% -100% -100% -100% -100% 99% 38% 67% 67% -100% 67%Lingcod 0% 43% -100% -100% -100% -100% 161% 105% 51% 82% -100% 85%Shallowwater benthic fish 10% 64% -100% -100% -100% -100% 21% 56% 61% 45% -100% 52%Small demersal elasmobranchs -4% 45% -100% -100% -100% -100% 86% 62% 54% 60% -100% 60%Large demersal sharks 6% 53% -100% -100% -100% -100% 86% 70% 60% 66% -100% 65%Large crabs 9% 60% -100% -100% -100% -100% 40% 63% 61% 33% -100% 56%Small crabs 3% 53% -100% -100% -100% -100% 80% 69% 58% 65% -100% 65%Commercial shrimp -5% 53% -100% -100% -100% -100% 31% 47% 54% 47% -100% 48%Epifaunal invertebrates -3% 46% -97% -96% -96% -98% 48% 47% 46% 48% -97% 47%Infaunal detritivorous invertebrates 6% 54% -100% -100% -100% -100% 83% 71% 60% 66% -100% 67%Carnivorous jellyfish 3% 49% -100% -100% -100% -100% 80% 67% 56% 70% -100% 66%Corals and sponges 10% 57% -100% -100% -100% -100% 79% 59% 62% 59% -100% 66%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%	 	 APPENDIX	D					75	Scenario	3:	No	ground	fish	trawl	in	MPAs		  Group name no groundfish trawl in mpaGroup Name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group name Group name Group nameSeals 2% 2% 2% 2% 2% 1% 1% 2% 2% 1% 1% 1%Sea lions 0% 0% 2% 1% 0% 0% 1% 0% 0% 0% 0% 0%Transient salmon 0% 0% -1% -1% 0% 0% -1% -1% 0% 0% -1% 0%Coho salmon 0% 0% -6% -1% 1% 0% -4% -1% 1% 0% -1% 0%Chinook salmon 0% 0% -1% -1% 0% 0% -2% -1% 0% 0% 0% 0%Large squid 10% 56% -100% -100% -100% -100% 77% 69% 61% 65% -100% 65%Ratfish 1% 47% -99% -94% -93% -78% 84% 68% 52% 51% -89% 59%Dogfish 0% 8% -13% -16% -21% -16% 12% 14% 11% 12% -16% 12%Pollock -2% 55% -100% -99% -99% -94% 83% 73% 59% 62% -98% 67%Forage fish 1% 55% -100% -100% -100% -100% 84% 72% 59% 66% -100% 68%Hake 0% 0% -1% -1% 0% 0% -1% -1% 0% 0% 0% 0%Eulachon 1% 1% -2% -1% -1% 0% 5% 0% 1% 1% -1% 1%Adult herring 1% 3% -8% -3% 1% -3% -5% 0% 3% -1% -2% 0%POP -10% 24% -100% -100% -100% -100% 109% 86% 34% 59% -100% 64%Inshore rockfish 0% 4% -10% -6% -1% -1% 0% 2% 6% 4% -4% 4%Piscivorous rockfish -8% 53% -82% -84% -87% -77% 78% 101% 54% 67% -81% 71%Planktivorous rockfish -8% 61% -98% -98% -99% -98% 99% 126% 58% 80% -98% 86%Arrowtooth flounder -4% 41% -99% -98% -98% -96% 85% 74% 47% 60% -98% 63%Flatfish 3% 45% -100% -98% -97% -92% 89% 63% 59% 59% -96% 61%Juvenile halibut 1% 4% -22% -7% -5% -5% 11% 5% 5% 4% -6% 5%Adult halibut 0% 2% -13% -4% -3% -3% 8% 4% 3% 3% -3% 3%Pacific cod 1% 39% -98% -95% -93% -92% 131% 68% 54% 59% -94% 64%Sablefish 0% 3% -7% -16% -7% -6% 7% 8% 5% 4% -7% 5%Lingcod -3% 32% -86% -86% -86% -79% 134% 82% 37% 52% -84% 62%Shallowwater benthic fish 4% 9% -48% -2% -1% -3% 5% 7% 6% 1% -3% 4%Small demersal elasmobranchs -3% 44% -100% -99% -99% -97% 93% 64% 53% 60% -98% 60%Large demersal sharks 5% 53% -100% -100% -100% -100% 87% 71% 59% 66% -100% 65%Large crabs 2% 3% -13% 1% 1% -4% -1% 4% 2% -1% -1% 2%Small crabs 3% 53% -100% -100% -100% -100% 80% 70% 58% 65% -100% 65%Commercial shrimp 0% 1% -15% -1% 0% -1% -2% 0% 1% -1% -1% 0%Epifaunal invertebrates 0% 1% -4% -2% -1% -2% 2% 2% 1% 2% -2% 2%Infaunal detritivorous invertebrates 6% 54% -100% -100% -100% -100% 84% 73% 59% 66% -100% 67%Carnivorous jellyfish 2% 13% -23% -25% -26% -18% 17% 19% 15% 14% -22% 16%Corals and sponges -2% 23% -80% -58% -63% -41% 67% 28% 45% 30% -69% 44%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%RESULTS	TABLES		76	Scenario	4:	Heavy	fishing	2-times	everywhere		 Group name Group Name Group name heavy fishing 2timesGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group name Group nameSeals 138% 127% 210% 182% 124% 152% 223% 161% 120% 140% 152% 139%Sea lions 54% 48% 78% 69% 47% 66% 82% 60% 44% 58% 62% 55%Transient salmon -100% -100% -99% -100% -100% -100% -99% -100% -100% -100% -100% -100%Coho salmon -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100% -100%Chinook salmon -98% -98% -97% -97% -98% -99% -98% -97% -98% -99% -98% -98%Large squid 150% 146% 167% 164% 157% 137% 166% 166% 148% 138% 153% 150%Ratfish 91% 89% 110% 114% 89% 70% 111% 111% 84% 72% 92% 89%Dogfish -12% -12% 13% -17% -20% -31% 10% -16% -22% -30% -13% -15%Pollock 101% 100% 109% 107% 105% 80% 108% 107% 101% 83% 100% 99%Forage fish 102% 102% 107% 115% 108% 77% 109% 114% 103% 81% 101% 99%Hake -94% -95% -90% -95% -95% -96% -91% -95% -95% -96% -94% -95%Eulachon 110% 107% 110% 120% 109% 122% 130% 112% 106% 119% 115% 112%Adult herring 125% 109% 899% 243% 121% 71% 810% 205% 119% 71% 136% 125%POP -64% -66% -41% -54% -73% -69% -44% -57% -71% -70% -62% -65%Inshore rockfish -37% -37% 27% -37% -51% -73% 20% -43% -53% -71% -40% -48%Piscivorous rockfish 18% 17% 32% 23% 21% -19% 31% 25% 17% -16% 15% 13%Planktivorous rockfish -5% -7% 12% -5% -5% -37% 10% -2% -10% -35% -5% -8%Arrowtooth flounder 43% 39% 68% 62% 34% 29% 74% 57% 30% 29% 46% 41%Flatfish 141% 136% 206% 175% 141% 115% 222% 165% 135% 118% 144% 139%Juvenile halibut 34% 31% 72% 67% 23% 32% 74% 56% 22% 30% 36% 33%Adult halibut 28% 26% 59% 56% 20% 27% 62% 47% 20% 25% 30% 28%Pacific cod 91% 93% 12% 114% 98% 80% 24% 109% 97% 81% 86% 90%Sablefish -13% -17% 44% 63% -21% -34% 45% 48% -26% -35% -10% -18%Lingcod -97% -97% -94% -97% -97% -99% -94% -97% -97% -99% -97% -97%Shallowwater benthic fish 258% 246% 771% 343% 228% 281% 937% 291% 227% 275% 275% 264%Small demersal elasmobranchs -24% -25% -5% -14% -26% -33% -6% -17% -27% -32% -25% -25%Large demersal sharks 108% 110% 81% 116% 111% 97% 84% 120% 109% 100% 105% 107%Large crabs 311% 296% 174% 436% 274% 501% 225% 379% 252% 460% 350% 311%Small crabs 95% 95% 92% 91% 106% 79% 92% 93% 102% 82% 92% 93%Commercial shrimp 138% 135% 7409% 160% 141% 137% 2052% 147% 141% 138% 139% 139%Epifaunal invertebrates 101% 101% 111% 102% 99% 101% 112% 99% 99% 101% 101% 100%Infaunal detritivorous invertebrates 103% 103% 102% 115% 108% 85% 103% 115% 103% 89% 101% 101%Carnivorous jellyfish 99% 95% 153% 111% 93% 96% 156% 101% 87% 90% 104% 96%Corals and sponges 100% 98% 96% 116% 108% 104% 94% 105% 103% 100% 103% 100%Macrophytes 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%	 	 APPENDIX	D					77	Scenario	5:	Heavy	fishing	2-times,	but	not	in	MPA		  Group name Group Name Group name Group name heavy fishing but not in mpaGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup name Group nameSeals 110% 215% -100% -100% -100% -100% 488% 429% 238% 253% -100% 281%Sea lions 39% 104% -100% -100% -100% -100% 251% 224% 119% 132% -100% 150%Transient salmon -96% -94% -100% -100% -100% -100% -84% -87% -97% -96% -100% -92%Coho salmon -96% -95% -100% -100% -100% -100% -71% -86% -87% -97% -100% -89%Chinook salmon -80% -75% -100% -100% -100% -100% 69% -48% -56% -90% -100% -56%Large squid 167% 273% -100% -100% -100% -100% 398% 358% 301% 294% -100% 318%Ratfish 84% 172% -100% -100% -100% -100% 307% 259% 186% 179% -100% 213%Dogfish -10% 39% -100% -100% -100% -100% 120% 90% 22% 28% -100% 64%Pollock 96% 206% -100% -100% -100% -100% 303% 275% 224% 206% -100% 245%Forage fish 104% 210% -100% -100% -100% -100% 319% 284% 223% 205% -100% 247%Hake -91% -86% -100% -100% -100% -100% -68% -83% -86% -89% -100% -84%Eulachon 129% 224% -100% -100% -100% -100% 239% 224% 220% 246% -100% 229%Adult herring 116% 187% -100% -100% -100% -100% 1055% 436% 243% 190% -100% 274%POP -62% -51% -100% -100% -100% -100% 66% 32% -58% -39% -100% -15%Inshore rockfish -17% 34% -100% -100% -100% -100% 212% 229% 11% 49% -100% 90%Piscivorous rockfish 13% 99% -100% -100% -100% -100% 197% 265% 91% 83% -100% 144%Planktivorous rockfish -4% 60% -100% -100% -100% -100% 173% 215% 45% 34% -100% 106%Arrowtooth flounder 23% 76% -100% -100% -100% -100% 208% 176% 83% 106% -100% 130%Flatfish 126% 214% -100% -100% -100% -100% 449% 317% 276% 242% -100% 278%Juvenile halibut 43% 103% -100% -100% -100% -100% 371% 204% 115% 172% -100% 160%Adult halibut 38% 94% -100% -100% -100% -100% 311% 189% 114% 169% -100% 154%Pacific cod 81% 146% -100% -100% -100% -100% 246% 285% 219% 197% -100% 230%Sablefish -12% 18% -100% -100% -100% -100% 272% 119% 47% 32% -100% 66%Lingcod -88% -84% -100% -100% -100% -100% 5% -49% -93% -93% -100% -72%Shallowwater benthic fish 274% 454% -100% -100% -100% -100% 1144% 486% 419% 448% -100% 446%Small demersal elasmobranchs -32% 0% -100% -100% -100% -100% 92% 37% 9% 8% -100% 19%Large demersal sharks 113% 206% -100% -100% -100% -100% 266% 277% 232% 232% -100% 244%Large crabs 292% 468% -100% -100% -100% -100% 323% 594% 450% 638% -100% 507%Small crabs 97% 191% -100% -100% -100% -100% 265% 241% 219% 203% -100% 223%Commercial shrimp 124% 257% -100% -100% -100% -100% 2459% 264% 271% 253% -100% 257%Epifaunal invertebrates 93% 196% -100% -100% -100% -100% 213% 198% 195% 199% -100% 198%Infaunal detritivorous invertebrates 111% 205% -100% -100% -100% -100% 308% 284% 226% 218% -100% 244%Carnivorous jellyfish 95% 180% -100% -100% -100% -100% 377% 297% 194% 186% -100% 223%Corals and sponges 121% 211% -100% -100% -100% -100% 283% 235% 236% 220% -100% 248%Macrophytes 107% 303% -100% -100% -100% -100% 303% 303% 303% 303% -100% 303%RESULTS	TABLES		78	Scenario	6:	Herring	fisheries	5-times	everywhere		 Group name Group Name Group name Group name Group name herring fisheries 5timesGroup name HG_TotalRegion UnprotectedHG_West MPAHG_East MPAHG_North MPAMainland MPAHG_West SpilloverHG_East SpilloverHG_North SpilloverMainland SpilloverAll MPAAll SpilloverGroup nameSeals -38% -38% -20% -40% -37% -39% -23% -40% -37% -39% -38% -38%Sea lions -22% -23% -7% -22% -21% -25% -7% -23% -22% -24% -22% -23%Transient salmon 38% 40% 12% 48% 39% 60% 14% 47% 39% 57% 38% 40%Coho salmon 62% 61% 30% 60% 59% 76% 35% 59% 59% 74% 64% 63%Chinook salmon 56% 57% 2% 52% 51% 86% 9% 52% 53% 83% 59% 60%Large squid 14% 15% -7% 13% 11% 23% -6% 13% 12% 22% 13% 14%Ratfish 7% 8% -6% 9% 5% 12% -5% 8% 6% 12% 6% 7%Dogfish 4% 4% -2% 7% 4% 9% -1% 6% 5% 9% 5% 5%Pollock 29% 33% 0% 35% 27% 50% 1% 33% 30% 48% 27% 31%Forage fish 0% 1% -7% 0% 0% 4% -7% 0% 1% 4% -1% 0%Hake 0% 0% -2% 0% 0% 1% -1% 0% 0% 1% 0% 0%Eulachon -4% -5% -15% -6% 0% -8% -16% -7% 2% -6% -4% -2%Adult herring 157% 147% 466% 177% 150% 182% 424% 165% 136% 177% 173% 162%POP 31% 31% 10% 33% 28% 42% 15% 33% 27% 40% 33% 32%Inshore rockfish 0% 0% -2% 0% -1% 3% -2% -1% -2% 3% 0% 0%Piscivorous rockfish -1% 0% -4% 3% -1% 5% -4% 1% -1% 5% 0% 0%Planktivorous rockfish 2% 3% -4% 8% 1% 14% -3% 4% 3% 13% 3% 4%Arrowtooth flounder 10% 11% -2% 10% 9% 17% -1% 10% 9% 16% 10% 11%Flatfish -2% -2% -8% -4% -2% 1% -8% -4% -2% 0% -2% -2%Juvenile halibut 4% 3% 2% 5% 3% 7% 2% 3% 3% 6% 5% 4%Adult halibut 10% 9% 1% 10% 8% 14% 2% 9% 8% 13% 11% 10%Pacific cod 33% 33% 4% 40% 25% 56% 6% 37% 26% 52% 35% 35%Sablefish 29% 33% -6% 32% 29% 38% -5% 24% 32% 38% 26% 31%Lingcod -18% -19% -7% -22% -16% -17% -9% -22% -17% -17% -17% -18%Shallowwater benthic fish 8% 7% -15% 6% 9% 10% -13% 6% 10% 9% 9% 9%Small demersal elasmobranchs 5% 5% -3% 4% 4% 7% -2% 4% 4% 6% 5% 5%Large demersal sharks 6% 6% -3% 7% 4% 9% -2% 7% 4% 8% 6% 6%Large crabs -12% -11% 8% -18% -11% -17% 5% -17% -10% -15% -13% -12%Small crabs -2% -1% -5% 0% -3% -1% -5% -1% -2% -1% -2% -2%Commercial shrimp 19% 18% 41% 35% 38% 12% 28% 27% 38% 14% 17% 19%Epifaunal invertebrates -2% -2% 1% -2% -2% -2% 1% -2% -3% -2% -2% -2%Infaunal detritivorous invertebrates -1% 0% -6% -1% -2% 2% -6% -1% -1% 2% -1% 0%Carnivorous jellyfish 2% 2% -8% 2% 1% 6% -8% 3% 1% 6% 3% 3%Corals and sponges -5% -5% -8% -2% -4% 1% -8% -7% -3% 0% -5% -5%Macrophytes 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%	 	 APPENDIX	D					79	Scenario	7:	No	fishing	anywhere	[				No	catch]               

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