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Impact of partial harvesting on the net ecosystem production of a mixed conifer forest following mountain… Mathys, Amanda 2012

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Impact of partial harvesting on the net ecosystem production of a mixed conifer forest following mountain pine beetle attack  by Amanda Mathys  B.Sc. (Honours), Queen’s University, 2008  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Soil Science)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  August 2012  © Amanda Mathys, 2012  Abstract  The recent mountain pine beetle (MPB) outbreak has had a major impact on the carbon (C) cycling of lodgepole pine forests in British Columbia. Mitigation efforts to control the insect outbreak have led to increased harvesting rates in the province. This study determines whether partial harvesting as an alternative forest management response to clearcutting can increase the net ecosystem production (NEP) of a mixed conifer forest (MPB-09) in Interior BC. Using the eddy-covariance (EC) technique, the C dynamics of the 70-year old stand were studied over the two years after partial harvest following MPB attack and also compared to an adjacent clearcut (MPB-09C) over the growing season. The annual NEP at MPB-09 increased from -107 g C m-2 in 2010 to -57g C m-2 in 2011. The increase of NEP was because the associated increase in annual gross ecosystem photosynthesis (GEP) from 812 g C m-2 in 2010 to 954 g C m-2 in 2011 exceeded the increase in annual respiration (Re) from 920 g C m-2 to 1011 g C m-2 in the two years of study. During the growing season of 2010, NEP at MPB-09C was -132 g C m-2 indicating high C losses in the clearcut. MPB-09 was a C sink during the growing season of both years, increasing from 9 g C m-2 in 2010 to 47 g C m-2 in 2011. The increase of NEP in the partially harvested forest suggests stand recovery following harvest, which corresponds to a 25% increase in the maximum assimilation rate in the second year. This study shows that retaining the healthy residual forest can greatly enhance the C sequestration of MPB-attacked stands and has important implications for forest management.  ii  Table of Contents  Abstract .................................................................................................................................... ii Table of Contents ................................................................................................................... iii List of Tables ........................................................................................................................... v List of Figures ........................................................................................................................ vii List of Symbols and Acronyms .............................................................................................. x Acknowledgements .............................................................................................................. xiii 1.  Introduction ................................................................................................................... 1  2.  Methods......................................................................................................................... 7  3.  4.  5.  2.1  Site description...................................................................................................... 7  2.2  Flux and climate measurements .......................................................................... 11  2.3  Data analysis and quality control ........................................................................ 13  Results ......................................................................................................................... 19 3.1  Climate data ........................................................................................................ 19  3.2  Seasonal and diurnal variation in NEP ............................................................... 22  3.3  Annual NEP, GEP and Re ................................................................................... 24  3.4  Environmental controls on GEP and Re .............................................................. 27  3.5  Comparison of partial and clearcut harvesting ................................................... 29  Discussion ................................................................................................................... 32 4.1  NEP of the partial harvested stand ...................................................................... 32  4.2  Growing-season NEP of the clearcut and partial harvested stand ...................... 35  Conclusions ................................................................................................................. 39  iii  References .............................................................................................................................. 41 Appendices ............................................................................................................................. 54 Appendix A.  Site pictures of harvesting operations and the partial harvested stand ... 54  Appendix B.  Diagram and photographs of the MPB-09 flux tower ............................ 58  Appendix C.  Soil profile description ............................................................................ 60  Appendix D.  Soil water retention characteristics ......................................................... 63  Appendix E.  Flux footprint at MPB-09 ....................................................................... 65  Appendix F.  Friction velocity (u*) threshold determination ........................................ 67  Appendix G.  Matlab program for calculating fluxes from covariances ....................... 68  Appendix H.  Evapotranspiration at MPB-09 ............................................................... 70  iv  List of Tables  Table 2.1. Site description at MPB-09 after partial harvesting. Brackets indicate standard deviations from the mean (± S.D.). ......................................................................................... 10 Table 2.2. Parameters for energy balance closure at MPB-09 in 2010 and 2011. Regression equation slope and intercept for H + λE vs. Ra are shown for the full year and the growing season (1 May-30 September). ............................................................................................... 17 Table 3.1. Mean annual climate conditions at MPB-09 (growing season value in brackets). 21 Table 3.2. Annual totals of net ecosystem production (NEP), gross ecosystem photosynthesis (GEP) and respiration (Re) in g C m-2 y-1 at MPB-09. Brackets show the lower and upper 95% confidence interval for the annual totals derived from the Monte Carlo simulation (see section 2.3.2 for details). ......................................................................................................... 26 Table 3.3. Parameters for the relationships of nighttime respiration (Re) to soil temperature at the 3-cm depth (Ts) using the logistic equation, and the relationships of gross ecosystem photosynthesis (GEP) to downwelling PAR (Q) using the Michaelis-Menten function. ....... 29 Table 3.4. Growing season (June – September) totals of net ecosystem production (NEP), gross ecosystem photosynthesis (GEP) and respiration (Re) for the clearcut (MPB-09C) and partial harvested stand (MPB-09) in 2010 and 2011. ............................................................. 31 Table C.1. Soil profile description at plot 1 (54°13’30.7” N, 122°36’52.2” W) at an elevation of 679 m, an aspect of 200° and a slope of 10%. Source: P. Sanborn (UNBC) ..................... 60 Table C.2. Soil profile description at plot 2 (54°13’27.6” N, 122°36’52.8” W) at an elevation of 685 m, an aspect of 40° and a slope of 5%. Source: Dr. P. Sanborn (UNBC) ................... 61  v  Table E.1. Mean climate values used to calculate the mean monthly flux source area in July and September 2010 at MPB-09, including air temperature at 26 m (Ta), horizontal wind speed (u), latent (λE) and sensible heat (H). ........................................................................... 66  vi  List of Figures  Figure 1.1. Timber volume harvested in relation to annual allowable cut (AAC) in the Interior of BC. Source: Bogdanski et al. (2011) ....................................................................... 3 Figure 2.1. Site location of the MPB-09 flux tower near Prince George in the Interior of British Columbia. ...................................................................................................................... 7 Figure 2.2. Partial harvested cutblock with location of the MPB-09 flux tower. The clearcut MPB-09C is located 1 km north of MPB-09. Source: Nishio (2010) ....................................... 8 Figure 2.3. Annual energy balance closure at MPB-09 with half-hourly values of latent (λE) plus sensible (H) heat flux plotted against available energy flux (Ra). Bin averages of 10 data points are displayed as squares for 2010 and circles for 2011. The solid and dashed lines are the linear regression lines for 2010 and 2011, respectively. The grey dashed line is the 1:1 line representing complete closure.......................................................................................... 18 Figure 3.1. Climate data at MPB-09 for 2010 (black lines) and 2011 (grey lines), with 5-day averaged air temperature (Ta), cumulative rainfall for the growing season and downwelling PAR (Q). ................................................................................................................................. 20 Figure 3.2. 5-day averaged soil temperature (Ts) and volumetric soil water content (θ) at 3cm depth at MPB-09 for 2010 (black lines) and 2011 (grey lines). ....................................... 21 Figure 3.3. Ensemble averaged diurnal net ecosystem production (NEP) during the growing season of 2010 (black lines) and 2011 (grey lines) showing (a) April (b) May (c) June (d) July (e) August and (f) September. Monthly NEP values for the two years shown in the panels are g C m-2 month-1. ..................................................................................................... 23  vii  Figure 3.4. 5-day averaged (a) net ecosystem production (NEP), (b) gross ecosystem photosynthesis (GEP) and (c) ecosystem respiration (Re) in 2010 and 2011. ........................ 25 Figure 3.5. Cumulative annual (a) net ecosystem production (NEP), (b) gross ecosystem photosynthesis (GEP) and (c) ecosystem respiration (Re) in 2010 (black lines) and 2011 (grey lines)........................................................................................................................................ 26 Figure 3.6. Relationship between nighttime ecosystem respiration (Re) with friction velocity threshold (u*th) applied (u*th = 0.2 m s-1) and 3-cm soil temperature (Ts) in 2010 (circles, solid line) and 2011 (squares, dashed line). Each data point is an average of 10 half-hour values. The equation parameters are shown in Table 3.3. .................................................................. 27 Figure 3.7. Light-response curve showing gross ecosystem photosynthesis (GEP) plotted against downwelling PAR (Q) for 2010 (solid line) and 2011 (dashed line). Each data point is an average of 50 half-hour values and are shown as circles for 2010 and squares for 2011. The equation parameters are given in Table 3.3. .................................................................... 28 Figure 3.8. Monthly total net ecosystem production (NEP) during the growing season (10 June to 22 September) of 2010 for MPB-09 (black bars) and MPB-09C (grey bars). ........... 30 Figure A.1. Partial harvest procedure at MPB-09 showing a) a Madill 3200B feller-buncher removing lodge-pole pine along extraction trails and b) a Caterpillar 535B grapple skidder moving logs to road side landing. Source: G. Nishio ............................................................. 54 Figure A.2. Logs are loaded onto truck by a John Deere 2054 loader at road side landing where they are transported away. Source: G. Nishio .............................................................. 55 Figure A.3. Site photographs of understory at MPB-09. ........................................................ 56 Figure A.4. Above canopy photographs at MPB-09 with partial harvested trails .................. 57 Figure A.5. 360° view of MPB-09 above the canopy taken with AMSPEC II webcam. ....... 57  viii  Figure B.1. Flux tower design and location of equipment at MPB-09. The tower was 32 m tall and made from scaffold sections 2.1 m long x 1.5 m wide. ............................................. 58 Figure B.2. Flux tower and eddy covariance system consisting of a sonic anemometer (model CSAT3, CSI) and open path infrared gas analyzer (IRGA, model LI-7500, LI-COR Inc.) at MPB-09. The distance between the centre of the anemometer and IRGA arrays was 20 cm. 59 Figure C.1. Soil profile at MPB-09. Source: Dr. P.Sanborn (UNBC) .................................... 62 Figure D.1. Partial water retention curve for MPB-09 showing volumetric water content (θ) at a given matric potential (Ψ) for 3-10 cm depth (squares and dashed line) and 10-40 cm depth (circles and solid line). .................................................................................................. 64 Figure E.1. Daytime (10:00 – 14:00 PST) flux footprint at MPB-09 in July 2010 showing the 80% (blue line) and 90% (red line) cumulative daytime flux contours under mean climate conditions. ............................................................................................................................... 65 Figure E.2. Daytime (10:00 – 14:00 PST) flux footprint at MPB-09 in September 2010 showing the 80% (blue line) and 90% (red line) cumulative daytime flux contours under mean climate conditions. ........................................................................................................ 66 Figure F.1. Half-hour nighttime NEE at MPB-09 plotted against friction velocity (u*) for 2011. Bin averages of 100 half-hour data points are shown with their standard deviations. The vertical dashed line shows the threshold friction velocity (u*th) of 0.2 m s-1. ................. 67 Figure H.1 Monthly total E at MPB-09 for 2010 (black) and 2011 (grey). ............................ 70  ix  List of Symbols and Acronyms  Symbol / Acronym  Units  Definition  Amax  μmol m-2 s-1  photosynthetic capacity  BC  British Columbia  CO2  carbon dioxide  C  carbon  CSI  Campbell Scientific Inc.  E  mm time-1  EC  evapotranspiration eddy covariance  Fc  μmol m-2 s-1  CO2 flux  G  W m-2  soil heat flux  H  W m-2  sensible heat flux  GEP  g C m-2 time -1or μmol m-2 s-1  gross ecosystem photosynthesis  IRGA LAI  infrared gas analyzer m2 m-2  leaf area index  LFH  litter-fibric-humus  MPB  mountain pine beetle  MΨ  g  mass of wet soil a given matric potential  Md  g  mass of oven-dried soil  NEE  μmol m-2 s-1  net ecosystem exchange  NEP  g C m-2 time -1 or μmol m-2 s-1  net ecosystem production  PAR  μmol m-2 s-1  photosynthetically active radiation  Q  μmol m-2 s-1  downwelling photosynthetically active radiation  x  Symbol  Units  Definition  Rn  W m-2  net radiation flux  Ra  W m-2  available energy flux  Ra  g C m-2 time -1 or μmol m-2 s-1  autotrophic respiration  Re  g C m-2 time -1 or μmol m-2 s-1  ecosystem respiration  Rh  g C m-2 time -1 or μmol m-2 s-1  heterotrophic respiration  Rs  g C m-2 time -1 or μmol m-2 s-1  soil respiration  r1,2,3  μmol m-2 s-1 or °C  empirical parameters  r2  coefficient of determination  sc  mol CO2 mol-1 dry air  CO2 mixing ratio  St  W m-2  energy storage in the air column and biomass below the EC sensors  S.D.  standard deviation  Ta  C  air temperature at 26-m  Ts  C  soil temperature at 3-cm depth  t  hours  time of day (PST)  u  m s-1  horizontal wind speed  u*  m s-1  friction velocity  u*th  m s-1  threshold friction velocity  Vs  m3 m−3  volume of soil  v  m s-1  lateral wind speed  w  m s-1  vertical wind speed    mol C mol-1 photons  quantum yield  λE  W m-2  latent heat flux  ρa  mol dry air m−3  dry air density  xi  Symbol  Units  Definition  ρc  mol CO2 m−3  atmospheric CO2 density  ρw  kg m−3  liquid water density  θ  m3 m−3  volumetric soil water content  θΨ  m3 m−3  volumetric soil water content at a given matric potential  Ψ  kPa  soil matric potential  xii  Acknowledgements  I am very thankful to my supervisor Andy Black who spent countless hours guiding my through my M.Sc. and whose passion and enthusiasm in sciences have been very inspiring. Many thanks to Zoran Nesic, Nick Grant and Mathew Brown for helping with the data collection procedure and the technical aspects in flux tower operations. This project was made possible through the continuous support of the UBC Biometeorology group, including Dominic Lessard, Rick Ketler, Andrew Hum, Iain Hawthorne and Trevor Baker, who amongst much other help were involved in tower installation and maintenance. It has been great working with Carmen Emmel and Eugénie Paul-Limoges, from doing a tour of the towers to attending international conference and sharing grad school life experiences. Dave Spittlehouse from BC Ministry of Forests, Lands and Natural Resource Operations is acknowledged for providing data on snowfall and helping to establish communication with the Ministry. I am thankful to my committee members Andreas Christen, Paul Jassal and Mark Johnson for their continuous support during my M.Sc. Special thanks to my parents, family members and friends in Vancouver. I appreciate the financial support provided by a Natural Sciences and Engineering Research Council of Canada (NSERC) strategic grant to Andy Black, as well as grants from the Canadian Foundation for Climate and Atmospheric Science (CFCAS), the BC Ministry of Forests, Lands and Natural Resource Operations and TerreWEB.  xiii  1.  Introduction  Forest management practices such as mitigation efforts in response to insect outbreaks and harvesting have an impact on the forest carbon (C) balance. In British Columbia (BC) the mountain pine beetle (MPB) outbreak began in the 1990s and has affected a total area of 18.1 million ha with a recent expansion into Alberta (B.C. Ministry of Forests, Lands and Natural Resource Operations, 2012). The unprecedented scale of the outbreak has killed 710 million m3 of mature lodgepole pine trees from 1999 to 2011 (Walton, 2012). This amounts to 53% of the merchantable pine volume in BC. Reasons for the spread are the changing climate which has been attributed to elevated carbon dioxide (CO2) and other greenhouse gas emissions on a global scale (IPCC, 2007). In western Canada, temperatures have increased by 1.7 °C from 1895 to 1995 (Déry and Jackson, 2005) allowing the beetle to survive through the winter to the following year (Carroll et al., 2006; Safranyik and Wilson, 2006). Furthermore, fire suppression in BC has led to a large abundance of mature lodgepole pine trees that provide a favorable habitat for the MPB (Taylor and Carroll, 2004). In response to the outbreak, the forest sector increased the annual allowable cut by 15 million m3 to about 67 million m3 per year in Interior BC (Bogdanski et al. 2011; Snetsinger, 2011). The total volume of timber harvested peaked in the province in 2005 at almost 60 million m3 y-1 and declined thereafter with the proportion of pine removed increasing from approximately 40% to more than 60% as shown in Fig. 1.1 (Peter and Bogdanski, 2010). The most common forest management strategy in BC is to clearcut the entire stand. As an alternative practice, partial harvesting can be undertaken to reduce the disturbance of the forest. This can help maintain the forest’s role of providing environmental services such as sustaining energy and  1  water cycles, providing habitat for wildlife, and reducing runoff to rivers and streams. Furthermore, protecting the non-pine secondary structure provides opportunities for mid-term timber harvest that can help reduce the predicted shortage in 15-50 years (Nishio, 2010). Coates et al. (2006) define secondary structure as all the non-pine canopy and sub-canopy trees as well as seedlings and saplings that survive the beetle outbreak. Accordingly, the stands that contain healthy residual vegetation provide potential for a next generation of forest cover (Burton, 2006; Coates et al., 2006). About 20-30% of pine-leading stands in north-central B.C. have been found to have abundant secondary structure that can contribute to the mid-term timber supply (Coates et al., 2006). Local efforts in the Prince George region of BC have attempted to minimize the disturbance on forest soils and vegetation cover through partial harvest operations and increasing the sustainability of the management practice. For example, Dave Jorgenson, a local logger, has successfully protected the secondary structure when salvage logging a number of MPB-attacked lodgepole pine and spruce stands (Jorgenson, 2009, pers. comm.). Nishio (2010) has been conducting research comparing partial harvesting and clearcutting methods and determining their impact on forest damage, windthrow and the costs of operations.  2  Figure 1.1. Timber volume harvested in relation to annual allowable cut (AAC) in the Interior of BC. Source: Bogdanski et al. (2011)  The forest C budget of Canada is strongly influenced by disturbances such as insect infestation, fire and harvesting which can shift forests from C sinks to C sources (Amiro et al. 2010, Kurz et al., 2008). Currently, there is limited information available on how post beetleoutbreak disturbance affects the C dynamics of the stand. Monitoring the forest net ecosystem production (NEP) over the long term has been recommended to help provide a better understanding of how management decisions on insect control affect forest productivity (Amiro et al., 2010; Kurz and Apps, 1999). NEP is the balance of C uptake  3  through gross ecosystem photosynthesis (GEP) and C loss resulting from ecosystem respiration (Re), i.e. NEP = GEP – Re. NEP is an indicator of whether the stand is sequestering or losing C to the atmosphere and can be measured using the eddy-covariance (EC) technique. The EC method is a widely accepted procedure to determine the net ecosystem exchange (NEE) between land surfaces and the atmosphere. NEP is well approximated by NEE and is calculated as NEP = -NEE (Landsberg and Gower, 1997). A global network of EC sites known as FLUXNET has been established to make long-term measurements of NEE, evapotranspiration (E) and related ecosystem measurements around the world (Baldocchi, 2003; Baldocchi, 2008). Studies have recently been examining the effects of the MPB on the C dynamics of forests that are left to recover naturally (Brown et al., 2012; Edburg et al. 2011; Kurz et al., 2008). EC measurements were made in two beetle-attacked lodgepole pine stands located approximately 20 and 120 km north of the current study (Brown et al., 2010, Brown et al., 2012). The recovery of the two stands occurred more quickly than previously assumed, with C neutrality reached within 3 to 5 years following the beetle attack (Brown et al., 2012). This was attributed to the compensatory C uptake of the surviving trees and understory vegetation and reduced competition for soil nutrients and water due to tree mortality. Furthermore, growing season C flux measurements of lodgepole pine stands that were clearcut harvested were found to remain annual C sources for at least 10 years (Brown et al. 2010). A similar general outcome was reported by Edburg et al. (2011) who used the Community Land Model (CLM) to determine how long-term C fluxes are affected after MPB outbreak. Their particular outcomes varied depending on the severity of the outbreak and the snagfall transfer rate (the fall and transfer to coarse woody debris). They predicted a secondary decrease in  4  NEP once the dead standing trees fall, increasing heterotrophic respiration (Rh) with a greater amount of coarse woody debris available to decompose (Edburg et al., 2011). They also simulated NEP responses to clearcut harvesting the beetle-killed trees and found the harvested stands to be a C source for 25 years before returning to a C sink. Overall they found management decisions to have a major impact on the C balance in post outbreak stands (Edburg et al., 2011). Kurz et al. (2008) used the C budget model of the Canadian Forest Sector (CBM-CFS3) to determine the cumulative MPB impact in BC’s forest. They predicted a loss of 270 Mt C over a 374,000 km2 forest area from 2000 to 2020 with the removal of beetle-killed and healthy trees contributing an additional loss of 50 Mt C during salvage harvest operations. Such emissions over 20 years are comparable with the Canadian transportation sector emissions (200 Mt CO2) over 5 years (Kurz et al., 2008). These studies along with others looking at the impact of clearcut harvesting have shown the disturbances to have a major impact on the NEP of the stands turning them into net sources of C (Humphreys et al., 2005; Zha et al., 2009). The removal of aboveground biomass reduces the stand’s ability to carry out photosynthesis while the harvest debris decompose and can increase Re. Various studies have researched the effects of forest thinning and have generally found that retaining the residual trees can increase forest productivity (Taylor et al, 2008; Saunders et al; 2012, Lee et al., 2002, Misson et al., 2005; Vesala et al; 2005) While some research exists on the effects of the MPB attack on C exchange processes (Brown et al., 2012; Kurz et al., 2008; Edburg et al., 2011), there have been limited studies that have made direct C exchange measurements of managed forests following MPB outbreak. This study uses the EC technique to determine the impact of partial harvesting on the NEP of the forest. It also compares the growing season C balance of the partial cut forest  5  with a clearcut located nearby to determine the effect of these different forest management practices on the NEP of the stands. It is hypothesized that partial harvesting can help reduce CO2 emissions of the forest compared to clearcut harvesting. Retaining biomass can maintain the photosynthetic capacity thus enhancing the C sequestration of the residual stand. Furthermore, a reduced amount of dead roots, coarse woody debris and litter are left behind to decompose and contribute to soil respiration (Rs) compared to a clearcut. Partial harvesting helps provide a continuous supply of litter fall, which can shade the soil surface reducing soil temperature and Rh (Taylor et al., 2008). This choice of harvesting practice can affect the forest’s capability for C uptake, while at the same time preserving habitat for ecosystem biodiversity and maintaining the future economic viability of the forest to meet society’s needs by providing a midterm timber supply within 20 years compared to approximately 80 years required for a clearcut. The specific objectives of this study are 1) to determine the annual NEP of a partial harvested mixed-conifer stand following an MPB attack, 2) to partition NEP of the stand into GEP and Re to gain a better understanding of the controls on NEP and how they are affected by environmental factors, 3) to compare NEP of the partial harvested stand to a clearcut nearby to see how the different management practices affect the C uptake of the forest following an MPB attack.  6  2.  2.1  Methods  Site description  The study site (MPB-09) is located in the Interior of BC near Summit Lake, which is 46 km north of Prince George (Fig. 2.1; Table 2.1). Following MPB attack in 2005 and 2006, the 70-year-old stand was partially harvested in a 39.7-ha cutblock (Nishio, 2010).  Figure 2.1. Site location of the MPB-09 flux tower near Prince George in the Interior of British Columbia.  7  Harvesting operations occurred from February to March 2009. The beetle-killed lodgepole pine trees were selectively removed along manually selected trail spacings and approximately 41% of the trees were retained in the stand (Fig. 2.2). In the process, the trees were felled by a feller-buncher and then skidded to roadside landings (Appendix A). This technique reduces the impact of soil compaction by constraining the movement of the logging equipment to the designated trails. Furthermore, Nishio (2009) found that the deep snow conditions in the winter protected 13-30% more understory than when harvesting occurred after snow melt.  MPB-09  Figure 2.2. Partial harvested cutblock with location of the MPB-09 flux tower. The clearcut MPB-09C is located 1 km north of MPB-09. Source: Nishio (2010)  8  The harvested volume of the cut block was 152 m3/ha with a total volume of 6022 m3 (Nishio, 2010). The overstory basal area was reduced from 14.9 m2/ha prior to harvesting to 7.6 m2/ha after harvesting. The residual canopy is composed of a combination of black spruce (Picea mariana), hybrid white spruce (Picea engelmannii x glauca) and subalpine fir (Abies lasiocarpa) trees. The understory consists of tree and shrub species including pink spiraea (Spiraea douglasii subsp. menziesii), bearberry honeysuckle (Lonicera involucrate) and willow (Salix sp.). In May 2010, the stand was replanted with tree seedlings consisting of 57% lodgepole pine and 43% hybrid white spruce at a planting density of 1370 stems per hectare within both the harvested trails and retention areas. The ground cover consists of mosses, grasses and ferns. Coarse woody debris, plant litter and exposed soil are also found on the forest floor as a result of the harvesting activities. The large plateau northwest of Prince George contains bedrock derived from volcanic rock and soils formed from finetextured glaciolacustrine deposits. The site lies on generally level ground and the soil is classified as an Orthic Gray Luvisol with a silty clay loam texture (Dr. P. Sanborn, Appendix B). The surface organic layer (LFH) has an average thickness of 6.9 cm. Adjacent to MPB-09 was a 4.2-ha clearcut (MPB-09C), which had the same understory composition and soil type as in the partially harvested stand (Nishio, 2010). It lies approximately 1 km north of the partial cut block shown in Fig. 1. and was harvested at the same time. The harvested volume at the clearcut was 474 m3 and it was replanted with the same seedlings as at MPB-09 in the spring of 2010. The stand is in the Sub-Boreal Spruce Biogeoclimatic Zone (SBSmk1) (Meidinger and Pojar, 1991). Soil and vegetation characteristics were obtained from ground plots that were established in 2010 by the Canadian Forest Service as part of the National Forest Inventory and are summarized in  9  Table 2.1 (NFI, 2008). Soil water retention curves were determined in the laboratory from soil samples collected in the field at three depths (Appendix C).  Table 2.1. Site description at MPB-09 after partial harvesting. Brackets indicate standard deviations from the mean (± S.D.). MPB-09 Stand age (yr)  ~70 (± 10)  Site location  54°13’25.4’’N 122°36’53.5’’W  Elevation (m)  680  Canopy height (m)  ~16 (± 4)  Stand density (stems ha-1)  435 (41%)a  Overstory basal area (m2/ha)  7.6b  Dominant tree species  Picea mariana, Picea engelmannii x glauca, Abies lasiocarpa  Understory vegetation  Spiraea douglasii, Lonicera involucrata, Salix spp.  Overstory LAI (m2 m-2)  1.3  Soil classification  Orthic Gray Luvisolc  Litter-fibric-humus (LFH) C (kg ha-1)  30.6-42.6  Average LFH thickness (cm)  6.9  Mineral soil C (0-55 cm) (kg ha-1)  75.6-158.9  Soil bulk density (kg m-3)  1247-1495d  Soil texture  Silty clay loamb  a  % of original full population. Nishio (2010). c Data from Dr. P. Sanborn (UNBC). d Volumetric coarse fraction < 1%. b  10  2.2  Flux and climate measurements  Long-term eddy-covariance and climate measurements have been continuously made since October 2009. Instruments were mounted on a scaffold tower that was 2.1 m long, 1.5 m wide and 32 m high. An ultrasonic anemometer was installed at a height of 26 m (model CSAT3, Campbell Scientific Inc. (CSI), Logan, Utah, U.S.A.) along with an open-path infrared gas analyzer (IRGA, model LI-7500, LI-COR Inc., Lincoln, Nebraska, U.S.A) to measure CO2 and H2O densities at a frequency of 10 Hz (Appendix C). The tower was positioned in the prevailing wind direction facing the west so that the footprint lay within the partial cut block (Appendix D). Calibrations were performed in the laboratory prior to installation at the site. The IRGA was replaced in 2011 to ensure calibrations were maintained. Climate measurements included air temperature and humidity (model HMP45C, Vaisala Oyj, Helsinki, Finland). Comparison of calculated specific humidity from the IRGA water vapor density with the HMP showed that the measurements were in good agreement. Downwelling and upwelling shortwave radiation and longwave radiation were measured with a net radiometer (model CNR1, Kipp and Zonen B.V., Delft, The Netherlands) above the canopy at the 30-m height and below the canopy upwelling shortwave radiation was measured with a Black & White Pyranometer (model 8-48, Eppley Laboratory Inc., Newport, Rhode Island, U.S.A.) at the 3-m height. Quantum sensors (model LI-190AS, LI-COR Inc.) were used to measure downwelling and upwelling photosynthetically active radiation (PAR) above the canopy as well as below-canopy downwelling PAR. Rainfall was measured with a tipping-bucket rain gauge (model 52203 R.M. Young Co., Traverse City, MI) at the 5-m height in an open area where interception by the canopy was negligible. Wind speed was recorded with a propeller-vane anemometer (model 05103 R.M. Young Co.). Two soil  11  profiles were established to measure soil temperature at depths of 3, 10, 20, 50 and 100 cm using soil thermistors (model ST100, Apogee Instruments Inc. Logan, Utah, U.S.A.). Volumetric soil water content was also measured in two soil profiles at 3-cm, 20-cm, 50-cm and 100-cm depths with water content reflectometers (model CS615 and CS616, CSI). Soil heat flux was measured at the 3-cm depth with 4 soil heat flux plates that were homemade (using Peltier coolers) and calibrated at UBC and was corrected for heat storage in the 3-cm soil surface layer. The surface temperature of the forest floor was measured with a downward-facing infrared radiometer (model Apogee SI-111, CSI) and snow depth with an acoustic distance sensor (model SR50A, CSI) mounted at 3.6 m height. The climate measurements were sampled at a rate of 0.5 Hz and the climate and flux data were recorded on two data loggers (model CR1000, CSI). The half-hour averages and covariances used to derive the turbulent fluxes were calculated and sent to UBC Biometeorology Laboratory via cell-phone connection on a daily basis. A compact flash card stored the high frequency data and was replaced every 2-4 weeks. The forest leaf area index (LAI) was measured in 2011 using a LI-COR Plant Canopy Analyzer (model LAI- 2000, LI-COR Inc.) and a Tracing Radiation and Architecture of Canopies (TRAC) system (Third Wave Engineering, Nepean, Ontario, Canada) following the procedure outlined by Chen et al. (2006). At MPB-09C, EC measurements were taken during the growing season of 2010, using a sonic anemometer (model CSAT3, CSI.) and an open-path IRGA (model LI-7500, LI-COR Inc.) mounted on a tripod at 2.2 m above the ground. Above-canopy upwelling and downwelling shortwave and longwave radiation (model CNR1, Kipp and Zonen B.V.) were measured at the 2.2-m height, as well as air temperature and relative humidity (model  12  HMP45C, Vaisala Oyj). Soil temperature (copper-constantan thermocouple) was measured at depths of 3, 10, 20, 50 and 80 cm, soil heat flux (4 heat-flux plates) at a depth of 3 cm and soil water content (model EC-5, Decagon Devices Inc., Pullman, Washington) at the 3-cm, 20-cm, 50-cm and 80-cm depths. The EC and climate data were recorded on a data logger (model CR5000, CSI) and the system was powered with a 100-W solar panel. The 90% cumulative contour of the daytime flux footprint generally extended no further than 200 m upwind of the tripod.  2.3  Data analysis and quality control  2.3.1  Flux calculations  The following flux calculations and quality control procedures were carried out once the high frequency data arrived at the UBC Biometeorology Lab. CO2 Fluxes ( ) were calculated by taking the covariance of the vertical wind speed (w) and the CO2 mixing ratio ( ) using the equation:  (1) where  =  / ,  is mean dry air density,  is CO2 density and primes are fluctuations  from the mean (Baldocchi, 2003). The covariances were block averaged in 30 min intervals with no detrending applied. Three coordinate rotations were performed on each half hour average to align the vertical velocity measurement normal to the mean wind streamlines, bringing the mean vertical and lateral ( ) wind vector as well as the covariance between the wind components (  ) to be zero (Tanner and Thurtell, 1969). Half-hour averaged data  points were removed when instruments malfunctioned during events such as snow, rain and  13  frost by setting limits of average, minimum, maximum and standard deviations on CO2 and H2O fluxes. The data were also visually inspected and the high frequency data were examined before removing data points that deviated from the general course of the time series. Net ecosystem exchange (NEE) was calculated using:  NEE =  + St  (2)  where St is the rate of change of CO2 storage in the air column below the EC system. The storage term was calculated using the procedure of Morgenstern et al. (2004) by taking the difference between the mean  for the following and previous half hour at EC sensor height.  To deal with the questionable nighttime flux measurements in calm conditions, data were rejected when the friction velocity (u*) fell below a threshold (u*th) of 0.2 m s−1. This value was determined by sorting increasing nighttime NEE according to u* into bin averages of 100 data points each and identifying at what u* value NEE no longer increased (Appendix E). Flux measurements were also removed when the wind direction came from NE to SE (45135°), as the footprint extended outside the partial cut block. This also removed data points corresponding to when the wind blew through the tower before reaching the EC system that was oriented in a westward direction. The known sensor heating problem of the open-path system during the winter time (Burba et al., 2008; Amiro et al., 2010) was dealt with by removing data when NEE < 0 in the winter (air temperature < 5C) and then gap filling with modeled Re as described in Brown et al. (2010). The remaining NEE data appeared to be relatively consistent when plotted against 3-cm soil temperature (Ts), giving confidence in the quality of the flux measurement. NEP was obtained from NEP = - NEE. A positive NEP  14  indicates CO2 uptake by the forest ecosystem and a negative NEP indicates CO2 being emitted to the atmosphere. Missing data were gap filled according to standard methods developed by the Fluxnet Canada Research Network (Barr et al., 2004). Respiration was modeled using a logistic equation relating nighttime Re to soil temperature at the 3-cm depth:  Re   r1 1  exp[ r2 (r3  Ts )]  (3)  where r1, r2 and r3 are model fitted empirical constants. Equation (3) was used to gap fill nighttime data and calculate daytime half-hourly Re (the latter using daytime Ts). Half-hourly GEP values were calculated by adding measured daytime NEP to modeled daytime Re. Gaps in GEP were filled using the rectangular hyperbolic Michaelis-Menten relationship with PAR (Q):  GEP   QAmax Q  Amax  (4)  where  is the quantum yield and Amax is the photosynthetic capacity. Annual relationships were first used to model Re and GEP values using (3) and (4), which then were adjusted by including an additional parameter. This time-varying parameter was used to make the modeled mean value equal to the mean measured value within a moving window interval that was 100 points wide and moved at an increment of 20 points at a time (Barr et al., 2004). The gap filling procedure was slightly altered according to Brown et al. (2010) by not applying the moving window during the wintertime when large data gaps occurred. When high frequency data from the flash card were lost due to technical issues, values were calculated 15  by applying the WPL equation (Webb et al., 1980) to the half hour averaged covariances sent from the data logger on a daily basis (Appendix F).  2.3.2  Uncertainty analysis  Uncertainties exist on the annual totals of NEP, GEP and Re which are caused by random and systematic errors. The effect of random error in half-hourly flux measurements on the uncertainty of annual NEP was determined based on a 20% random error (Wesely and Hart, 1985; Morgenstern et al., 2004). Monte Carlo simulation was used to obtain the uncertainty in gap filling where random gaps were generated in the original non-gap filled dataset. The missing data were then filled using the temperature and light response functions as described above (Equation 3 and 4) and the new annual sums of NEP, GEP and Re were calculated. The procedure was repeated 500 times in order to determine the 95% confidence interval (Krishnan et al., 2006). All data analysis and statistical calculations were carried out with Matlab (Version 7.5.0, The MathWorks, Natick, MA, USA).  2.3.3  Energy balance closure  To assess the quality of the EC measurements, an energy balance closure analysis was conducted. The energy balance of the forest ecosystem can be expressed as Ra = λE + H (Monteith and Unsworth, 1990), where Ra is the available energy flux entering the ecosystem, and λE and H are the turbulent fluxes of latent and sensible heat leaving the ecosystem. Ra is equal to Rn - G - St, where Rn is the net radiation above the stand and G is the soil heat flux. St is the rate of change in latent and sensible heat storage in the air column, the energy storage in the biomass (tree boles, branches and foliage) and the energy required  16  for photosynthesis (Blanken et al., 1997; Lee and Black, 1993). Energy balance closure (EBC) is defined as (Wilson et al., 2002; Barr et al., 2006):  EBC   H  E Rn  G  S t  (5)  EBC at MPB-09 was determined as the slope of the regression of half-hourly measurements of H + λE vs. Ra. The slope was very similar in the two years at 0.80 with an intercept of 5.28 W m-2 in 2010 and -0.3 W m-2 in 2011 (Fig. 2.3, Table 2.2). During the growing season, the slope was 0.82 in 2010 and 2011 indicating the quality of the EC measurements was constant during the two years. Values of EBC in this study are consistent with other Fluxnet sites around the world. Wilson et al. (2002) found a mean EBC of 80% at 22 Fluxnet sites with 50 years of data. Leuning et al. (2012) suggest reasons for the imbalance that can be caused by errors in the measurements of turbulent fluxes, net radiation and change in energy storage terms. They point out that selection of a homogeneous, level site can also contribute to improving the quality of measurement. In this study, an energy balance correction was not applied to the flux data.  Table 2.2. Parameters for energy balance closure at MPB-09 in 2010 and 2011. Regression equation slope and intercept for H + λE vs. Ra are shown for the full year and the growing season (1 May-30 September). Annual  Growing season  Slope  Intercept (W m-2)  r2  Slope  Intercept (W m-2)  r2  2010  0.80  5.28  0.81  0.82  10.87  0.83  2011  0.79  -0.30  0.77  0.82  3.79  0.81  17  Figure 2.3. Annual energy balance closure at MPB-09 with half-hourly values of latent (λE) plus sensible (H) heat flux plotted against available energy flux (Ra). Bin averages of 10 data points are displayed as squares for 2010 and circles for 2011. The solid and dashed lines are the linear regression lines for 2010 and 2011, respectively. The grey dashed line is the 1:1 line representing complete closure.  18  3.  3.1  Results  Climate data  The climate at the site is characterized by cold winters and short warm summers with moderate annual precipitation typical for the Sub-Boreal Spruce zone. Historical mean annual Ta reported at the Prince George International Airport is 4 °C from 1971-2000 (Environment Canada, 2012). 2010 was a warmer and drier year with a mean annual Ta of 4.9 °C compared to 3.0 °C in 2011 (Fig. 3.1; Table 3.1). During the growing season of 2010, 120 mm less rainfall occurred at MPB-09 compared to the following year. During the dry summer of 2010, θ at the soil surface layer of 3 cm depth dropped to its lowest value of 0.26 m3 m-3 on August 21, with only 16 mm of rainfall during the previous 55 days. The matric potential during this time was -200 kPa, indicating that θ at its lowest value was still available to plants. In contrast, 156 mm of rain fell during the same period in the following year during which θ remained at an average value of 0.55 m3 m-3. An extended dry period was also observed at two lodgepole pine stands nearby in 2010 (Brown et al. 2012). The coldest wintertime temperatures observed at the site during the two years of study were -30 °C on Nov 23, 2010 and -33 °C on Feb 19, 2011. Snowfall began in mid November of both years, and a 1-metre deep snow layer persisted for 4-5 months during the winter. During this time, a minimum Ts of -0.5 °C was observed near the soil surface. In the first winter after harvesting snowfall was approximately 253 mm liquid water equivalent with a total annual precipitation of 614 mm from Nov 1, 2009 to Oct 31, 2010. In the following winter of 2010/2011, snowfall was 367 mm and annual precipitation was approximately 845 mm. Snowmelt occurred on April 10, 2010 and April 27, 2011 and coincided with an  19  increase in Ts in the upper 20 cm of the soil profile. The growing season length (daily mean Ta > 0 °C and daily mean Ts > 1 °C) lasted almost two weeks longer in 2010 than in 2011.  Figure 3.1. Climate data at MPB-09 for 2010 (black lines) and 2011 (grey lines), with 5-day averaged air temperature (Ta), cumulative rainfall for the growing season and downwelling PAR (Q).  20  Figure 3.2. 5-day averaged soil temperature (Ts) and volumetric soil water content (θ) at 3cm depth at MPB-09 for 2010 (black lines) and 2011 (grey lines).  Table 3.1. Mean annual climate conditions at MPB-09 (growing season value in brackets).  2010  2011  Ta (26 m) (°C)  4.9 (12.7)  3.0 (11.6)  Ts (3 cm) (°C)  6.1 (12.0)  5.3 (10.9)  225  343  θ (m3 m-3) (0-10-cm depth)  0.49 (0.44)  0.55 (0.55)  Q (μmol m-2 s-1)2  245 (406)  224 (345)  158  146  Rainfall total1 (mm)  Growing season length3 (days) 1  Total for growing season. 24-h average. 3 Growing season length defined as days when daily mean Ta > 0 °C and Ts > 1 °C. 2  21  3.2  Seasonal and diurnal variation in NEP  Monthly C exchange varied between the two years and their seasons (Fig 3.2). Higher NEP was observed during the spring of 2010 than in 2011. In 2010, the monthly total NEP was 8.6 g C m-2 in April and 3.7 g C m-2 in May, whereas in 2011 it was 4.8 g C m-2 and 4.0 g C m-2 in the two months respectively. The earlier onset of spring in 2010 with warmer Ta and Ts compared to 2011, led to a greater C uptake during the daytime, which more than compensated for the high C losses during the nighttime in April and May. In both years, the highest NEP was in June, with monthly total values of 25.1 g C m-2 in 2010 and 42.9 g C m-2 in 2011. That monthly total NEP in June 2011 was almost double the value of the previous year, due to much higher daytime values in 2011, while nighttime values remained the same. The greater uptake during the daytime in 2011 was likely due to a higher GEP of increasing vegetation growth perhaps in response to more light penetration through the canopy and reduced competition for nutrients and water following the lodgepole pine removal. Nighttime Re reached its highest values in July of both years with ensemble averaged nightime values of 5.7 μmol m-2 s-1 in 2010 and 8.2 μmol m-2 s-1 in 2011 (Fig 3.2d). During the second half of the growing season monthly NEP declined in both years and became negative in August of 2010 but remained positive in August of 2011 (Fig 3.2e). This shows that while Re dominated in August of 2010, GEP dominated in the same month of the following year. By September, C losses during the nighttime exceeded photosynthetic uptake during the daytime leading to a negative monthly NEP in both years.  22  Figure 3.3. Ensemble averaged diurnal net ecosystem production (NEP) during the growing season of 2010 (black lines) and 2011 (grey lines) showing (a) April (b) May (c) June (d) July (e) August and (f) September. Monthly NEP values for the two years shown in the panels are g C m-2 month-1.  23  3.3  Annual NEP, GEP and Re  The annual courses of the 5-day averages of NEP, GEP and Re are shown in Fig. 3.3. In both 2010 and 2011, NEP was generally positive during the growing season with a greater CO2 uptake in 2011. NEP reached its lowest 5-day average in October 2010 and September 2011, falling to -1.9 g C m-2 in both years. In July, GEP reached its maximum 5-day average value of 6.7 g C m-2 day-1 in 2010 and 9.4 g C m-2 day-1 in 2011. The highest 5-day average Re was observed during the same month, increasing from 6.0 g C m-2 day-1 in 2010 to 8.4 g C m-2 day-1 in 2011. During the wintertime when Re dominated the forest C balance, the average values of NEP in 2010 and 2011 were -0.57 g C m-2 day-1 and -0.76 g C m-2 day-1, respectively. Annual NEP increased from -121 g C m-2 y-1 in 2010 to -48 g C m-2 y-1 in 2011 (Fig. 3.4; Table 3.2). The stand remained an annual C source in both years, but the losses were lower in the second year. GEP increased from 802 g C m-2 y-1 in 2010 to 951 g C m-2 y-1 in 2011. This increase was greater than that of Re from 923 g C m-2 y-1 in 2010 to 999 g C m-2 y1  in 2011. The much higher GEP in the second year after harvesting, explains the significant  increase of NEP despite the shorter growing season length in 2011. The 95% confidence intervals on the annual totals of NEP, GEP and Re are shown in Table 3.2. These indicate that the annual values changed significantly in the two years and that the stand was clearly a C source in 2010 and 2011. Furthermore, the 20% random error associated with each half-hour measurement of NEP resulted in an uncertainty less than 3 g C m-2 y-1 in both years.  24  Figure 3.4. 5-day averaged (a) net ecosystem production (NEP), (b) gross ecosystem photosynthesis (GEP) and (c) ecosystem respiration (Re) in 2010 and 2011.  25  Figure 3.5. Cumulative annual (a) net ecosystem production (NEP), (b) gross ecosystem photosynthesis (GEP) and (c) ecosystem respiration (Re) in 2010 (black lines) and 2011 (grey lines).  Table 3.2. Annual totals of net ecosystem production (NEP), gross ecosystem photosynthesis (GEP) and respiration (Re) in g C m-2 y-1 at MPB-09. Brackets show the lower and upper 95% confidence interval for the annual totals derived from the Monte Carlo simulation (see section 2.3.2 for details).  NEP  GEP  Re  2010  -107 (-120, -98)  812 (798, 823)  920 (908, 929)  2011  -57 (-72, -45)  954 (932, 971)  1011 (987, 1040)  26  3.4  Environmental controls on GEP and Re  The relationship between nighttime Re and Ts at the 3-cm depth was described using the logistic model (Equation 3; Fig. 3.5). At lower Ts, Re showed a similar response in both years. For Ts > 10 °C, the increase of Re was greater in 2011 compared to 2010. Ts explained 58% of the variance in Re in 2010 and 48% in 2011. The relationship between temperaturenormalized Re and θ was found to be very weak (r2 = 0.0036) indicating that the difference in response at higher temperatures could not be explained with differences in soil moisture between the two years.  Figure 3.6. Relationship between nighttime ecosystem respiration (Re) with friction velocity threshold (u*th) applied (u*th = 0.2 m s-1) and 3-cm soil temperature (Ts) in 2010 (circles, solid line) and 2011 (squares, dashed line). Each data point is an average of 10 half-hour values. The equation parameters are shown in Table 3.3.  27  The relationship between GEP and Q was modeled using the rectangular hyperbolic light response function, i.e. the Michaelis-Menten relationship (Equation 4; Fig. 3.6; Table 3.3). The photosynthetic capacity (Amax) increased by 25% from 12.13 μmol m-2 s-1 in 2010 to 15.18 μmol m-2 s-1 in 2011. Quantum yield (α) increased as well from and 0.044 mol C mol-1 photons in 2010 to and 0.066 mol C mol-1 photons in 2011, respectively. In both years GEP increased almost linearly with Q up to approximately 400 μmol m-2 s-1 above which GEP asymptotically approached Amax (Fig. 3.6).  Figure 3.7. Light-response curve showing gross ecosystem photosynthesis (GEP) plotted against downwelling PAR (Q) for 2010 (solid line) and 2011 (dashed line). Each data point is an average of 50 half-hour values and are shown as circles for 2010 and squares for 2011. The equation parameters are given in Table 3.3.  28  Table 3.3. Parameters for the relationships of nighttime respiration (Re) to soil temperature at the 3-cm depth (Ts) using the logistic equation, and the relationships of gross ecosystem photosynthesis (GEP) to downwelling PAR (Q) using the Michaelis-Menten function.  Year  Nighttime Re and Ts  GEP and Q  r1 (μmol m-2 s-1)  r2 (°C-1)  r3 (°C)  2010  5.55  0.30  6.92  2011  12.73  0.21  13.50  3.5  α (mol mol-1 photons)  Amax (μmol m-2 s-1)  0.58  0.044  12.13  0.26  0.48  0.066  15.18  0.26  r2  r2  Comparison of partial and clearcut harvesting  NEP was measured in the clearcut (MPB-09C) from June 10 to September 22, 2010. During all of the growing season months the clearcut was a C source, with monthly total NEP values ranging from -20 g C m-2 month-1 in June to -65 g C m-2 month-1 in September (Fig. 3.7). In comparison, the partial harvested stand (MPB-09) was a C sink in June and July and a weak source in August and September of 2010. During the entire growing season, the clearcut was a large C source of 132 g C m-2. MPB-09 was a weak C sink of 9 g C m-2 in 2010 and a moderate C sink of 47 g C m-2 in 2011 during the same period. For 2010, growing season totals of GEP and Re were 298 g C m-2 and 430 g C m-2 for MPB-09C and 530 g C m-2 and 521 g C m-2 for MPB-09, respectively (Table 3.4). Average daily (24-h) NEP at MPB-09C was -1.2 g C m-2 during the growing season. In comparison, measurements taken in two nearby clearcuts in July and August of 2007 showed the average daily NEP to be -0.87 and 0.37 g C m-2 2 years and 10 years after harvesting respectively (Brown et al. 2010).  29  Figure 3.8. Monthly total net ecosystem production (NEP) during the growing season (10 June to 22 September) of 2010 for MPB-09 (black bars) and MPB-09C (grey bars).  30  Table 3.4. Growing season (June – September) totals of net ecosystem production (NEP), gross ecosystem photosynthesis (GEP) and respiration (Re) for the clearcut (MPB-09C) and partial harvested stand (MPB-09) in 2010 and 2011.  NEP  GEP  Re  -132  298  430  MPB-09 2010  9  530  521  MPB-09 2011  47  712  665  MPB-09C 2010  31  4.  4.1  Discussion  NEP of the partial harvested stand  In the first two years after partial harvesting the MPB-attacked stand, MPB-09 was a C sink during the growing season, but the high Re losses during winter led it to be an annual C source. The annual NEP of the residual forest increased from -107 g C m-2 in 2010 to -57 g C m-2 in 2011. Both GEP and Re increased in the second year after harvesting but the increase of GEP was greater, indicating a higher photosynthetic uptake of stand compared to the previous year. The cooler and wetter conditions in 2011 may have provided favorable conditions for plant growth enhancing stand recovery and photosynthesis of the residual forest. Although the growing season lasted two weeks longer in 2010, the greater C uptake during the mid summer of 2011 played a more dominant role in increasing the annual NEP at MPB-09. Bergeron et al. (2008) reported a similar finding in a boreal black spruce forest in Quebec, Canada. When comparing the C dynamics between a clearcut and a mature forest, he found the annual NEP of the disturbed site to be mostly affected by summer conditions, unlike the mature forest that was more influenced by environmental factors in the spring. High C losses were observed at MPB-09 in August and September, which similar to the boreal forest, coincides with warm soil conditions and high respiration rates as a result of an increase in Rh from the decomposing coarse woody debris (Mkhabela et al., 2009; Barr et al., 2007). The same as for an unharvested beetle-killed stand located approximately 30 km away, the greatest C uptake was in June when leaf emergence of the understory broadleaf vegetation occurred (Brown et al., 2010). There the majority (65-68%) of net ecosystem photosynthesis was found to come from the understory non-tree species, indicating the  32  importance of broadleaf residual vegetation in contributing to C uptake of these disturbed sub-boreal forests (Bowler et al., 2012). The compensatory effects of the surviving vegetation following thinning is known to lead to vegetation shifts through less competition for resources such as light, nutrients and water (Campbell et al., 2009, Saunders et al., 2012; Vesala et al., 2005). By removing trees from the stand, the forest canopy opens up allowing more light to penetrate through the canopy and increase the photosynthetic capacity of the underlying vegetation (Saunders et al., 2012). Campbell et al. (2009) found the increase in light use efficiency of a thinned ponderosa pine stand on clay loam soils in the northern Sierra Nevada to be attributable a greater amount of fine root and shrub growth with a smaller relative increase of overstory production. The significant contribution of understory CO2 uptake was also found in a ponderosa pine forest showing a shift in species following thinning (Misson et al., 2005). The high abundance of understory broadleaf vegetation at MPB-09 highlights its importance in increasing NEP of the partial harvested forest, with the increase of shrub LAI compensating for the loss of tree LAI following the disturbance. While no data are available prior to harvesting at this site, studies have consistently shown a reduction of GEP after clearcutting and forest thinning due to the removal of aboveground biomass (Misson et al., 2005; Dore et al., 2010, Campbell et al., 2009, Giasson et al., 2006). Misson et al. (2005) found that forest thinning in a young ponderosa pine forest in the Sierra Nevada of California had a greater impact on GEP than Re. Consequently the forest became a weak C source of 13 g C m-2 after thinning but shifted back to a sink after one year. Greater reductions in GEP than Re have also been reported at a coastal Douglas-fir forest in British Columbia after clearcut harvesting (Humphreys et al., 2006) as photosynthesis of the stand is greatly reduced as a result of biomass removal.  33  At MPB-09, both GEP and Re increased in 2011 even though air temperature was above the historical average in 2010 and incident PAR was greater. As shown in the light response curve, the photosynthetic capacity of the stand increased in the second year after harvesting. The increase of both GEP and Amax has been shown in other studies to coincide with an increase of LAI after harvesting (Zha et al., 2009; Humphreys et al., 2005; Bergeron et al., 2008). The development stage following harvesting has also been found to have a greater impact on annual NEP than climate variability between years (Humphreys et al., 2006; Bergeron et al., 2008). The observed increase of NEP could thus be attributed to stand regeneration at MPB-09 as an increase in the understory vegetation was observed from 2010 to 2011. The relationship of Re to soil moisture θ showed little response with the fine textured soil having a high water holding capacity leading to more plant available water. The dry period during the summer of 2010 didn’t seem to greatly affect Re and NEP, as the stand may have been able to access water from deeper soil horizons. The matric potential during this time was well above the permanent wilting point indicating that the trees weren’t water stressed during low θ conditions in 2010. Kljun et al. (2006) found little response to drought at a poorly drained black spruce forest in Saskatchewan, Canada compared to a nearby aspen forest with a coarser, relatively well-drained soil. Dilustro et al. (2005) found that Rs and θ correlated significantly at sandy sites but not at clayey sites in managed mixed pine forests in southeastern Georgia as the fine textured soils buffer soil moisture effects on Rs due to a slow release of moisture. Harvesting has been shown to increase (Ohashi et al., 1999), decrease (Saunders et al., 2012; Dore et al., 2010, Sullivan et al. 2008) or have no effect (Misson et al., 2005, Campbell et al., 2009) on Re and Rs. A decline of Re has been explained through the reduction  34  of both autotrophic respiration (Ra) and Rh resulting from a decrease in live branch, stem and root biomass after thinning. Harvesting can reduce soil CO2 release by raising the water table at wet sites and creating anaerobic conditions as well as by compacting the soil through logging activities that alter the soil structure and reduce aeration (Bergeron et al., 2008; Tang et al., 2005). The increase in Re observed at this site in the second year after the disturbance may have been due to an increase of Ra, which has been shown to correlate with an increase in above ground biomass as the forest recovers (Jassal et al., 2007). Microbial decomposition can also play a role from the greater inputs of dead roots, coarse woody debris and above ground litter after harvest, although retaining forest cover can help reduce soil temperature and Re through shading of the forest floor (Taylor et al., 2008; Kurz and Apps, 1999).  4.2  Growing-season NEP of the clearcut and partial harvested stand  During the growing season of 2010, the clearcut MPB-09C was a large C source, whereas MPB-09 was a weak sink. Given that the two stands had the same site characteristics such as vegetation, soil type, time of harvest and climate conditions, this shows that harvesting intensity has a major impact on the net CO2 emissions of the forest. By retaining the healthy secondary structure, GEP of the partial cut forest was enhanced leading to C uptake during the growing season of 2010. Total losses during the measurement period in the clearcut were 132 g C m-2 with an average daily loss of 1.2 g C m-2. Since there was no C uptake during the remainder of the year, MPB-09C was likely a large annual C source. In comparison, a clearcut on Vancouver Island, BC lost 620 g C m-2 one year after harvesting with a growing season average loss of 1.6 g C m-2 day-1 (Humphreys et al., 2005). Zha et al. (2009) reported a harvested jackpine stand in the boreal forest to be an annual C source of 152 g C m-2 two  35  years after clearcutting. Sub-boreal clearcuts in the area that were replanted with lodgepole pine seedlings were shown to still be growing-season C sources of 0.37 g C m-2 day-1 10 years following harvesting (Brown et al., 2010). Pypker and Fredeen (2002) measured growing-season NEP at a clearcut on clay rich soils that was planted with hybrid white spruce. They found it to have a daily NEP average of 0.3 g C m-2 day-1over a shorter period of the growing season (27 June to 3 September) 5 years after harvest and to be a C source of 0.9 g C m-2 day-1 6 years after harvesting when measured over the entire growing season (24 May to 20 September). Such interannual variability in clearcuts has been previously observed and attributed to responses to environmental conditions and their dynamic structure from plant regrowth (Bergeron et al., 2008; Humphreys et al., 2005). Both GEP and Re were greater at MPB-09 than at MPB-09C during the growing season. The greater Re in the partial harvested stand could have been due to greater Ra from the remaining standing forest. A modeling study by Grant et al. (2007) has shown that in the first 4 years after clearcut harvesting, Re is dominated by Rh from the fine and coarse litter debris left on the site on Vancouver Island. As the stand recovers and matures, Rh decreased and Ra dominated Re. Consequently, with increasing stand age there seemed to be a greater contribution of Ra versus Rh to overall Re (Grant et al. 2007). A similar trend could be expected at MPB-09C with Rh controlling Re in the first few years after the disturbance, unlike the partial harvested stand where both Rh and Ra would be contributing to Re. There is limited research into the effects of management responses to insect outbreaks on the forest C balance. Some studies have focused on the effects of forest thinning and reduced-impact logging as a silvicultural practice and to reduce the risk of fire. Amiro et al. (2010) reported that stand-replacing practices such as clearcut harvesting have a greater  36  impact on NEP than insect outbreaks and forest thinning, which showed a more rapid recovery after the disturbance. This study shows that partial harvesting following insect outbreak reduces C losses as compared to clearcutting. Previous findings from a study at two beetle-killed lodgepole pine stands nearby that were left to recover naturally, found the forests to recover more quickly than previously hypothesized and becoming C neutral annually within 3 to 5 years after attack (Brown et al., 2010, Brown et al., 2012). In 2010, MPB-09 was a greater C source than the unharvested beetle-killed stands, which at that point had reached the grey-attack stage where the trees were dead and many of the needles of the trees had fallen. Furthermore, one year after partial harvesting, MPB-09 was losing more CO2 than one year after the insect attack in the unharvested stand, indicating that the harvesting disturbance had a greater impact on NEP than the MPB attack itself. The results in this study agree with previous research, which predicted that the impact of salvage harvesting of beetle-killed forests over an area of 374,000 km2 would add an additional 50 Mt C to the atmosphere from 2000 to 2020 (Kurz et al., 2008). Lee et al. (2002) used the biometric approach to compare control plots with partial and clearcut boreal mixed wood forests in Ontario. Similar to this study, they found a significantly higher C assimilation in the partial cut site than in the clearcut 5 years after harvest, with the greatest C sequestration at the control site. Consequently, the choice of management strategy in response to MPB outbreak can have a major impact on NEP. The clearcut MPB-09C was a much larger C source during the growing season indicating that partial harvesting is more favorable in reducing CO2 emissions of the stand. Since the healthy trees are retained, more aboveground biomass increases the photosynthetic capacity of the forest thus increasing the annual NEP. The risk  37  of windthrow can affect the residual stand after the disturbance due to greater wind exposure. One year after harvesting, the windthrow at this site was 9%, indicating the trees were developing windfirm characteristics perhaps because of previous exposure at its location close to the block edge (Nishio, 2011). If the recovery of the residual forest continues at the same rate, the stand would likely return to a C sink more quickly than clearcuts in the area which as indicated above, were still a source after 10 years. The understory LAI would continue to increase until the canopy closes and less solar radiation reaches the forest floor, which would shift the CO2 uptake contribution of the stand to the tree canopy.  38  5.  Conclusions  This study examined the effects of partial harvesting on the C balance of a sub-boreal forest that was previously attacked by the MPB. NEP of the residual forest was measured with the EC technique in the first two years after removal of the lodgepole pine trees. Results were compared with a clearcut during the growing season to see how the different management practices after a beetle attack affect the productivity of the forest. The study contributes to the existing knowledge of the effects of disturbances on forest C balances by providing direct C flux measurements in a managed beetle-killed forest. The main research findings are:  1. Annual NEP of the partial harvested stand, MPB-09, increased in the second year after harvesting although the forest remained a C source in both years. Seasonal variations of NEP were evident with the greatest C uptake in mid summer of 2010 and 2011. The residual forest was a C sink in the growing season of the two years, with growing season NEP increasing significantly in 2011.  2. Ecosystem respiration increased from the first to the second year in the partial harvested forest. This could be from a combination of an increase in Rh from the decomposing coarse woody debris, dead roots and harvest remains as well as an increase in Ra which is often coupled with an increase in GEP from the above-ground biomass.  39  3. The increase of GEP observed in the second year was greater than the increase in Re indicating that the photosynthetic capacity of the forest played a major role in increasing annual NEP. By retaining the healthy residual spruce and subalpine fir trees, the C uptake of the stand was enhanced. Both GEP and Amax increased significantly in the second year which was likely because of stand regeneration through greater light penetration to the forest floor and the reduced competition for nutrients and water. Favorable climate conditions could have also contributed to enhancing forest growth.  4. The clearcut, MPB-09C, was a large C source during the growing season of 2010 with high Re losses during all months of the measurement period. This shows that the choice between partial harvesting and clearcutting forests after MPB attack has a major impact on NEP over the long term. The partial harvested stand was a weak C sink during the same time period, indicating that the remaining trees and understory vegetation in the partial harvested stand can greatly contribute to reducing net CO2 emissions and enable the forest to return to being a C sink unlike clearcuts which have been found to still be a C source after 10 years. Consequently, when considering forest management practices in response to the MPB outbreak, partial harvesting can contribute to enhancing C sequestration of the forest by retaining the healthy residual vegetation.  40  References  Amiro, B.D., Barr, A.G., Black, T.A., Iwashita, H., Kljun, N., McCaughey, J.H., Morgenstern, K., Murayama, S., Nesic, Z., Orchansky, A.L. and Saigusa, N.: Carbon, energy and water fluxes at mature and disturbed forest sites, Saskatchewan, Canada. Agr. Forest Meteorol., 136, 237–251, 2006.  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Wesely, M.L. and Hart, R.L.: Variability of short term eddy-correlation estimates of mass exchange, in: Hutchinson, B.A., Hicks, B.B., eds: The Forest-Atmosphere Interaction, D. Reidel, Dortrecht, pp. 591-612, 1985.  Wilson, K.B., Goldstein, A.H., Falge, E., Aubinet, M., Baldocchi, D., Berbigier, P., Bernhofer, C., Ceulemans, R., Dolman, H., Field, C., Grelle, A., Ibrom, A., Law, B.E., Kowalski, A., Meyers, T., Moncrieff, J., Monson, R., Oechel, W., Tenhunen, J., Valentini, R. and Verma, S.: Energy balance closure at FLUXNET sites, Agr. Forest Meteorol., 113, 223–243, 2002.  Zha, T., Barr, A.G., Black, T.A., McCaughey, J.H., Bhatti, J., Hawthorne, I., Krishnan, P., Kidston, J., Saigusa, N., Shashkov, A., Nesic, Z. Carbon Sequestration in boreal jack pine stands following harvesting. Global Change Biol., 15, 1475-1487, 2009.  53  Appendices Appendix A. Site pictures of harvesting operations and the partial harvested stand  a)  b)  Figure A.1. Partial harvest procedure at MPB-09 showing a) a Madill 3200B feller-buncher removing lodge-pole pine along extraction trails and b) a Caterpillar 535B grapple skidder moving logs to road side landing. Source: G. Nishio 54  Figure A.2. Logs are loaded onto truck by a John Deere 2054 loader at road side landing where they are transported away. Source: G. Nishio  55  2009  2010  2011  Figure A.3. Site photographs of understory at MPB-09.  56  Figure A.4. Above canopy photographs at MPB-09 with partial harvested trails  Figure A.5. 360° view of MPB-09 above the canopy taken with AMSPEC II webcam. Source: T. Hilker  57  Appendix B. Diagram and photographs of the MPB-09 flux tower  Figure B.1. Flux tower design and location of equipment at MPB-09. The tower was 32 m tall and made from scaffold sections 2.1 m long x 1.5 m wide.  58  Figure B.2. Flux tower and eddy covariance system consisting of a sonic anemometer (model CSAT3, CSI) and open path infrared gas analyzer (IRGA, model LI-7500, LI-COR Inc.) at MPB-09. The distance between the centre of the anemometer and IRGA arrays was 20 cm.  59  Appendix C. Soil profile description Soil descriptions were carried out by Dr. Paul Sanborn (Ecosystem Science and Management Program, UNBC) in two soil pits at the NFI plots. The soils were classified as Orthic Gray Luvisols containing a parent material derived from fine-textured glaciolacustrine sediments (Table C.1 and C.2). A photograph of the soil pit is shown in Fig. C.1. Table C.1. Soil profile description at plot 1 (54°13’30.7” N, 122°36’52.2” W) at an elevation of 679 m, an aspect of 200° and a slope of 10%. Source: P. Sanborn (UNBC)  Horizon L/S Fm  Depth (cm) 5-4 4-2  Description Living feathermoss with intermingled litter. Very dark brown (10YR 2/2 m); semi-decomposed organic matter; noncompact matted; abundant, very fine, fine, and medium, horizontal roots; abrupt, wavy boundary; 2-4 cm thick.  Hi  2-0  Black (10YR 2/1 m); granular; abundant, very fine, fine, and medium, horizontal roots; abundant charcoal fragments; abrupt, wavy boundary; 13 cm thick.  Ae  0-10  Dark brown (10YR 3/3 m); silt loam; strong, fine granular; friable; plentiful, very fine, fine, and medium, horizontal and oblique roots; clear, wavy boundary; 5-15 cm thick.  Bt  10-70  Brown (10YR 4/3 m), with < 1 cm wide discontinuous gray (2.5Y 5/1 m) vertical channels; heavy clay; strong, fine and medium subangular blocky; sticky, very plastic; few, very fine and fine, oblique and vertical, and few, medium and coarse, oblique roots; clear, wavy boundary; 50-65 cm thick.  C  70-90+  Dark grayish brown (2.5Y 4/2 m) and yellowish brown (10YR 5/4 m); silty clay; massive, with pseudoplaty units from varved bedding; sticky, very plastic.  60  Table C.2. Soil profile description at plot 2 (54°13’27.6” N, 122°36’52.8” W) at an elevation of 685 m, an aspect of 40° and a slope of 5%. Source: Dr. P. Sanborn (UNBC)  Horizon L/S  Depth (cm) 6-5  Fm  5-1  Description Living feathermoss with intermingled litter. Very dark brown (10YR 2/2 m); semi-decomposed organic matter; noncompact matted; abundant, very fine, fine, and medium, horizontal roots; abrupt, wavy boundary; 2-4 cm thick.  Hi  1-0  Black (10YR 2/1 m); granular; abundant, very fine, fine, and medium, horizontal roots; abrupt, broken boundary; 0-2 cm thick.  Ahe  0-7  Brown (10YR 4/3 m); silt loam; strong, fine and medium granular; friable; plentiful, very fine, fine, medium and coarse, horizontal and oblique roots; clear, wavy boundary; 5-9 cm thick.  Bt1  7-20  Brown (10YR 5/3 m); heavy clay / silty clay; strong, fine subangular blocky; sticky, very plastic; plentiful, very fine, fine, medium, and coarse, oblique and horizontal roots; gradual, wavy boundary; 10-20 cm thick.  Bt2  20-70  Yellowish brown (10YR 5/4 m) and grayish brown (10YR 5/2 m); heavy clay / silty clay; strong, medium, subangular blocky; very sticky, very plastic; few, very fine, fine, and medium, oblique roots; gradual, wavy boundary; 40-60 cm thick.  BC  70-100+  Grayish brown (10YR 5/2 m, 2.5Y 5/2 m); silty clay; massive, with minor weak, coarse subangular blocky; sticky, very plastic; few, coarse, vertical roots.  61  Figure C.1. Soil profile at MPB-09. Source: Dr. P.Sanborn (UNBC)  62  Appendix D. Soil water retention characteristics  Soil water retention characteristics were determined from soil samples taken at 3-10 cm, 1020 cm and 30-40 cm depth. Three replicates were used for each depth. The samples were repacked into cores to the field bulk density following the procedure of Klute (1986). Water retention curves were then determined using a pressure plate apparatus by applying pressures ranging from -10 to -300 kPa (Klute, 1986; Topp et al., 1993). The volumetric water content (θΨ) for a given matric potential Ψ was calculated as:  where Vs is the volume of the soil sample (m3), ρw is the density of water (1000 kg m-3) and MΨ and Md are the masses (kg) of the wet soil at Ψ and the oven-dried soil, respectively. The water retention curves are shown in Fig. D.1. for both the LFH (3-10 cm) and mineral (10-40 cm) soil horizon.  63  Figure D.1. Partial water retention curve for MPB-09 showing volumetric water content (θ) at a given matric potential (Ψ) for 3-10 cm depth (squares and dashed line) and 10-40 cm depth (circles and solid line).  64  Appendix E. Flux footprint at MPB-09  The flux footprint analysis was carried out using the method of Kormann and Meixner (2001). The mean flux source area was calculated for daytime July and September 2010 using mean climate conditions (Fig. E.1 and E.2; Table E.1).  Figure E.1. Daytime (10:00 – 14:00 PST) flux footprint at MPB-09 in July 2010 showing the 80% (blue line) and 90% (red line) cumulative daytime flux contours under mean climate conditions.  65  Figure E.2. Daytime (10:00 – 14:00 PST) flux footprint at MPB-09 in September 2010 showing the 80% (blue line) and 90% (red line) cumulative daytime flux contours under mean climate conditions.  Table E.1. Mean climate values used to calculate the mean monthly flux source area in July and September 2010 at MPB-09, including air temperature at 26 m (Ta), horizontal wind speed (u), latent (λE) and sensible heat (H).  Relative humidity (%) Ta (°C) u (m s-1) Wind direction (°) H (W m-2) λE (W m-2)  July 43 20 2.2 248 196 147  September 59 12 2.0 197 121 95  66  Appendix F. Friction velocity (u*) threshold determination  Figure F.1. Half-hour nighttime NEE at MPB-09 plotted against friction velocity (u*) for 2011. Bin averages of 100 half-hour data points are shown with their standard deviations. The vertical dashed line shows the threshold friction velocity (u*th) of 0.2 m s-1.  67  Appendix G. Matlab program for calculating fluxes from covariances  The following Matlab program was used to perform calculations on the half-hour averages, covariances and variances of CO2 and H2O densities, the 3 wind components u, v, w and Ts that were sent daily to the UBC Biometeorology Lab from the site data logger. These averages and covariances were used on occasions when the high-frequency data was lost from the compact flash card of the data logger. The calculations include applying 3 coordinate rotations and the WPL correction to the flux data: 1. Coordinate rotation and WPL correction: [wT_rot, wH_rot, wc_rot, uw_rot, vw_rot] = rotate_cov_matrices(meansIn, C1, C2, T_w); % WPL for rotated and unrotated covariances [Fc_wpl, E_wpl] = apply_WPL_correction(c_w, H_w, T_w, co2_avg, h2o_avg, Tair, pbar); %unrotated [Fc_rot, E_rot] = apply_WPL_correction(wc_rot, wH_rot, wT_rot, co2_avg, h2o_avg, Tair, pbar); %rotated Code for function: apply_WPL_correction.m % convert units (temperature to K and pressure to Pa) T = T + 273.15; P = P .* 1000; % calculate c (total molar density of moist air, mmol m-3) using the ideal gas law P = RcT and convert from mol to mmol c = P ./ (T.*8.314) .* 1000; % calculate dry air density cd (mmol m-3) cd = c - cv - cc; % calculate Fc with WPL correction and convert to micromol m-2 s-1 Fc_wpl = (w_cc + (cc./cd) .* (w_cv + (c.*w_T ./ T))) .* 1000; % calculate E with WPL correction (mmol m-2 s-1) E_wpl = (1 + (cv./cd)) .* (w_cv + (cv.*w_T ./ T));  68  2. Calculate fluxes: % Fc is already in the correct units (mol m-2 s-1) after the WPL correction, λE and H are calculated as follows (see fr_calc_eddy) R = 8.31451; ZeroK = 273.15; % convert molar densities to mixing ratios (avg, std, max, min) [Cmix_avg, Hmix_avg,Cmolfr_avg, Hmolfr_avg] = fr_convert_open_path_irga(co2_avg,h2o_avg,Tair,pbar); mol_density_dry_air = (pbar./(1+Hmix_avg/1000)).*(1000./(R*(Tair+ZeroK))); % Latent heat flux (W m-2) is calculated as (see fr_calc_eddy): LE_rot = E_rot.*mol_density_dry_air; % Sensible heat flux (W m-2) calculation: rho_moist_air = rho_air_wet(Tair,[],pbar,Hmolfr_avg); Cp_moist = spe_heat(Hmix_avg); Hsens_rot = wT_rot .* rho_moist_air .* Cp_moist; % (d) Ustar (m s-1) ustar_rot=NaN.*ones(length(T_w),1); for i=1:length(uw_rot),ustar_rot(i)=(uw_rot(i)^2 + vw_rot(i)^2)^0.25; end  69  Appendix H. Evapotranspiration at MPB-09  E at MPB-09 was obtained from fluxes of λE measured with the EC technique at a height of 26 m. Gap filling was undertaken following the procedure of Amiro et al. (2006). Annual total E increased from 316 mm in 2010 to 332 mm in 2011 (Fig. H.1).  Figure H.1 Monthly total E at MPB-09 for 2010 (black) and 2011 (grey).  70  

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