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The effect of forage seeding on vegetation dynamics and the early growth and survival of lodgepole pine… Powell, George Wilfred 1992

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The Effect of Forage Seeding On Vegetation DynamicsAnd the Early Growth and Survival of Lodgepole Pine(Pinus contorta var. latifolia Engelm.) on aForest Clear-cut.byGeorge Wilfred PowellB.Sc. (Agr.), The University of British Columbia, 1989A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF SCIENCEinTHE FACULTY OF GRADUATE STUDIES(Department of Plant Science)We accept this thesis as conformingto the required standardTHE UNIVERSITY OF BRITISH COLUMBIAMarch 1992© George Wilfred Powell, 1992In presenting this thesis in partial fulfilment of the requirements for an advanceddegree at the University of British Columbia, I agree that the Library shall make itfreely available for reference and study. I further agree that permission for extensivecopying of this thesis for scholarly purposes may be granted by the head of mydepartment or by his or her representatives. It is understood that copying orpublication of this thesis for financial gain shall not be allowed without my writtenpermission.(Signature)Department of  Thwr SCA EiJC—EThe University of British ColumbiaVancouver, CanadaDate  (V\1MC4 X) iqyz DE-6 (2/88)AbstractField trials of orchardgrass (Dactylis glomerata L.),smooth bromegrass (Bromus inermis Leys.), alsike clover(Trifolium hybridum L.), and a mixture by weight of 40%orchardgrass, 40% alsike clover, and 20% white clover(Trifolium repens L.), with five seeding rates by weight(0.5, 1.5, 3.0, 6.0 and 12.0 kg/ha), were conducted on aforest clear-cut in the Very Dry, Cool Montane Sprucebiogeoclimatic subzone in the southern interior of BritishColumbia. The treatments were monitored for the first twogrowing seasons for their influence on the vegetationdynamics, and the resultant interactions of the vegetationon the growth and survival of planted 1+0 lodgepole pine(Pinus contorta var. latifolia Engelm.) seedlings.Forage seeding had no effect on lodgepole pinesurvival. There was no significant difference in theheight, basal diameter or stem volume growth of lodgepolepine in 1990 among different species of forage or betweendomestic forages and native vegetation. In the second yearof the study (1991), decreases in the increment in lodgepolepine basal diameter were weakly associated with increasingseeding rate; however, lodgepole pine height, and stemvolume remained unaffected by species or seeding rate offorages. There was no difference in the effect of differentforage species or native vegetation on lodgepole pine growthin 1991. Stem volumes were lower in 1990 and 1991 oni iconifers with surrounding vegetation compared to the controlgroups with competing vegetation removed. Unit needle massdecreased with the absence of vegetation in 1991. There wasa positive correlation between cover of orchardgrass andoverwinter rodent damage of the lodgepole pine seedlingsfollowing the first growing season; however, lodgepole pinesurvival was independent of rodent damage.Density, cover, and height of vegetation werepositively correlated with pure live seeds sown per ha,although this effect was delayed to the second growingseason for height, and cover.Two-dimensional partitioning of the cover indicatedthat the seeded fraction of the total vegetative responsewas influenced by seeding rate and species of forage sown inboth growing seasons. The variability introduced by nativevegetation masked the treatment effect in the first year,such that overall there was no treatment effect for totalvegetative cover.Initial germination of forages was not linearly relatedto the initial cover of soil, litter or wood on the plots;however, development of the vegetation, in particular theclovers, was often correlated with the initial cover ofthese non-floristic cover components.iiiTable of Contents^Abstract   iiTable of Contents ^  iv^List of Tables   viList of Figures  viiiAcknowledgements   ix1. Introduction  ^11.1. Objectives and Hypotheses  ^21.1.1. Research Hypotheses  ^21.1.2. Statistical Hypotheses  ^41.2. Treatments and Levels  ^41.3. Literature Review  ^61.3.1. Conifer - Vegetation Interactions 61.3.2. Vegetation Dynamics ^ 101.3.3. Other Influences of Forage Seeding .^.^. 122. Study Site ^ 133. Methods 153.1. Experimental Set-up ^ 153.1.1. Site Preparation 153.1.2. Forage Seeding 163.1.3. Lodgepole Pine Planting ^ 163.2. Germination Trials ^ 163.3. Vegetation Dynamics Measurements 173.3.1.^Cover ^ 183.3.2.^Density 193.3.3. Height 193.3.4. Production 193.4. Lodgepole Pine Measurements ^ 203.4.1. Survival and Damage 203.4.2. Height ^ 203.4.3. Basal Diameter ^ 203.4.4. Unit Needle Mass 213.5. Weather Record 213.6. Photographic Record 213.7. Statistical Analyses ^ 223.7.1. Vegetation Dynamics ^ 223.7.2. Two-Dimensional Partitioning ^ 253.7.3. Lodgepole Pine 274. Results ^ 304.1. Germination Trials ^ 304.2. Vegetation Dynamics 304.2.1.^Cover ^ 304.2.2.^Density 444.2.3.^Height 504.2.4. Production 524.3. Lodgepole Pine ^ 544.3.1. Growing Season ^ 54iv4.3.2. Survival and Damage ^  544.3.3. Height ^  554.3.4. Basal Diameter ^  584.3.5. Unit Needle Mass  604.3.6. Stem Volume  604.4. Weather Record ^  615. Discussion ^  625.1. Vegetation Dynamics  625.1.1. Early Influence of Seeding Rate . . . ^▪ 625.1.2. Differences in Plant Development . . . ^•645.1.3. Plant Growth and Non-floristicCover Components ^  665.2. Two-Dimensional Partitioning ^  685.3. Lodgepole Pine Growth and Survival ^ 725.3.1. Lodgepole Pine Damage and Survival . . ^ 725.3.2. Lodgepole Pine Growth  735.4. Management Recommendations ^  756. Literature Cited ^  767. Appendix 1: Cover categories for two-dimensionalpartitioning  808. Appendix 2: Weather Summary for Tunkwa Lake^Research Site in 1990 and 1991   81VList of Tables1. Seeding rates of orchardgrass (Dactylisglomerata L.), smooth bromegrass (Bromusinermis Leys.), alsike clover (Trifoliumhybridum L.), and a mixture by weight of40% orchardgrass, 40% alsike clover, and 20%white clover (Trifolium repens L.) at TunkwaLake in 1990 ^  52. Seeding mixtures and rates used by Klinger (1986) . 83. Analysis of variance for the influence of foragespecies and seeding rate by mass on vegetationproduction, vegetation density, vegetation height,and total vegetative cover ^  234. Individual degree of freedom contrasts used todetermine specific differences among specieslevels in the analysis of variance ^  245. Orthogonal contrasts coefficients used toestimate polynomial models for seedingrate levels in the analysis of variance^256. Analysis of variance for the influence of foragespecies and seeding rate by mass on lodgepole pineheight, basal diameter, unit needle mass, damageand survival ^  287. Germination and purity of forage species sownat Tunkwa Lake in 1990 ^  308. Vegetative cover (%) at Tunkwa Lake in1990 and 1991 ^  379. Two-dimensional partitioning of total sum ofsquares, expressed as a percentage of totalcover at Tunkwa Lake in 1990 ^  3910. Two-dimensional partitioning of total sum ofsquares, expressed as a percentage of totalvegetative cover at Tunkwa Lake in 1990  ^4011. Two-dimensional partitioning of total sum ofsquares, expressed as a percentage of totalcover at Tunkwa Lake in 1991 ^  4212. Two-dimensional partitioning of total sum ofsquares, expressed as a percentage of totalvegetative cover at Tunkwa Lake in 1991  ^43vi13 . Average density of vegetation in 1990 and 1991at Tunkwa Lake ^  4514. Average height of herbaceous vegetation (cm) in1990 and 1991 at Tunkwa Lake ^  5115. Average production of herbaceous vegetation(kg/ha) in 1990 and 1991 at Tunkwa Lake ^ 5316. Average lodgepole pine height growth (cm)in 1990 and 1991 at Tunkwa Lake ^  5717. Average lodgepole pine basal diameter growth(mm) in 1990 and 1991 at Tunkwa Lake ^ 59vi iList of Figures1. Location of Tunkwa Lake research site ^ 142. Sampling locations within 4x4-m plots atTunkwa Lake ^  183. Cover on plots sown to smooth bromegrassat Tunkwa Lake, May 1990 to July 1991 ^ 314. Cover on plots sown to orchardgrassat Tunkwa Lake, May 1990 to July 1991 ^ 325. Cover on plots sown to alsike cloverat Tunkwa Lake, May 1990 to July 1991 ^ 336. Cover on plots sown to the mixtureat Tunkwa Lake, May 1990 to July 1991 ^ 347. Cover on plots with native vegetationat Tunkwa Lake, May 1990 to July 1991 ^ 358. The influence of pure live seeding rate of(pure seed sown/m) forages, and the initialcover (%) of litter on the density of seedlings(plants/re) in 1990 on plots sown to orchardgrassat Tunkwa Lake ^  469.^The influence of pure live seeding rate(pure seed sown/re) and the initial cover (%) ofwood on the density of vegetation (plants/re)in 1990 on plots sown to alsike clover atTunkwa Lake  ^4810. The interaction of the mean response of foragespecies and seeding rate on the average densityof vegetation (plants/re) in 1991 at Tunkwa Lake . . 4911. The interaction of the mean response of foragespecies and seeding rate on lodgepole pine heightgrowth (cm) in 1990 at Tunkwa Lake ^  56viiiAcknowledgementsI would like to express my sincere gratitude to all theindividuals and agencies who made completion of this projectpossible. Firstly, I wish to thank my thesis advisor, Dr.Michael Pitt, for his support, and commitment to this thesisand my education. Thanks to my other committee members, Dr.Brian Holl and Dr. Gordon Weetman, for their input. Dr.George Eaton was instrumental in my understanding of thestatistical analyses, in particular two-dimensionalpartitioning. Special thanks to Kevin Cameron, Reg Newman,Lyndsey Saver and Dr. Brian Wikeem of the Forest ScienceResearch Branch, British Columbia Ministry of Forests, forlogistical support in the set-up and sampling of the fieldwork, and personal support and encouragement of the project.Thanks also to Dr. Dee Quinton, Agriculture Canada ResearchStation, Kamloops, and Phil Youwe, Range Branch, BritishColumbia Ministry of Forests, for their suggestions andreview of the research proposal. I would also like to thankAinsworth Lumber Ltd., Savona, B.C., for their support inproviding a study site within their timber supply area.Funding for this project, in part, was provided by theBritish Columbia Cattlemen's Association, the BritishColumbia Ministry of Forests, and the Science Council ofBritish Columbia.ix1. IntroductionCompetition has been identified as a major interactionbetween conifers and herbaceous plants (McLean and Clark1980, Nordstrom 1984). Little research, however, has beendone in British Columbia to quantify the competition betweenconifer seedlings and seeded forages or to identify anypositive interactions between them. Moreover, there remainsinadequate information quantifying the effects of foragespecies, seeding rates and forage mixes on the competitivebalance between conifer and forages.Species and rate of seeding of forages will also affectthe botanical mix of native vegetation and the forageproduction on a clear-cut site. Despite the importantinfluence of seeded vegetation on both range management andsilviculture, vegetation dynamics following forage seedinghave never been monitored quantitatively on a clear-cut inBritish Columbia (Nordstrom 1984).This research follows recommendations in the reportprepared by Pitt (1989) for the Ministry of Forestsoutlining a five-year plan for integrated forest/rangeresearch in British Columbia. The research was conducted incooperation with the Forest Resource Development Agreement(FRDA) Project 3.55 research, "The Effects of CattleGrazing, Forage Seeding, Basal Scarring and Leader Damage onForest Regeneration," and was aimed at complementing theinformation generated in that program (Newman et al. 1989).11.1. Objectives and HypothesesThe objectives of this research are as follows:(1) to determine the effects of three forage speciesand an operational range forage mix, and fiveseeding rates on the growth and survival oflodgepole pine (Pinus contorta var. latifoliaEngelm.) on a forest clear-cut in the Very Dry,Cool Montane Spruce (MSxk) biogeoclimatic subzone;and,(2) to determine the effects of five seeding rates onthe establishment, growth and dynamics of threedomestic forages and an operational range foragemix on a forest clear-cut in the MSxkbiogeoclimatic subzone.1.1.1. Research HypothesesThese objectives are embodied in the researchhypotheses of the experiment, namely:(1) Forage species affects lodgepole pine growth andsurvival. Competitive advantage among forageswill not be equally expressed; forages withgreater cover, height, and production potentialwill impact lodgepole pine seedlings more thanforages with limited growth potential;(2) Seeding rate of forage affects lodgepole pinegrowth and survival. Increased seeding rate bymass and pure live seeds sown results in2increasing cover and density of forages. Anegative response in the lodgepole pine(mortality, decreased rate of growth) willcorrespond to increasing cover and density of theforages;(3) Seeding rate affects establishment, growth anddynamics of vegetation on forest clear-cuts. Therelationship between seeding rate and subsequentproduction, height, density, and cover of foragesremain unquantified on forest clear-cuts inBritish Columbia. For example, a high seedingrate may result in a stand consisting of manysmall plants and a low seeding rate may result ina stand of a few large plants, yet both ratescould have the same dry matter production andcanopy cover; and,(4) Vegetation dynamics on forest clear-cuts affectsthe growth and survival of lodgepole pine.Competitive balance between lodgepole pine andherbaceous vegetation will be affected by thevarying herbaceous vegetation cover, density, drymatter production, and height resulting fromdifferent seeding rates, and species present.31.1.2. Statistical HypothesesThe following null hypotheses, derived from theresearch hypotheses, were tested in this research:(1) Species of domestic forage has no effect on the height,basal diameter, unit needle mass, damage and survivalof lodgepole pine seedlings;(2) Seeding rate of domestic forage has no effect on theheight, basal diameter, unit needle mass, damage andsurvival of lodgepole pine seedlings;(3) Seeding rate has no effect on the cover, height,density, and dry matter production of domestic forageson forest clear-cuts; and(4) Cover, height, density and dry matter production ofvegetation have no effect on the height, basaldiameter, unit needle mass, damage and survival oflodgepole pine seedlings.1.2. Treatments and LevelsTwo factors, species at four levels, and seeding rateat five levels (Table 1) were arranged in a completelyrandom design in all factorial combinations. Two controlswere included in the randomization: a single control forboth species and seeding rate, consisting of lodgepole pineswith no seeded vegetation, in addition to a control for treegrowth consisting of lodgepole pines with competingherbaceous vegetation removed.Forage species were selected from the forages that4have been suggested as suitable for the MSxk (Nordstrom1984), and each represents a different class of forage.Species included a legume (alsike clover, Trifolium hybridumL.), a bunch grass (orchardgrass, Dactylis glomerata L.), asod grass (smooth bromegrass, Bromus inermis Leys.), and anoperational forage mixture (Table 1). Seeding rates wereselected to provide a broad comparison, higher and lowerthan the current operational rate of approximately 3 kg/ha.Table 1. Seeding rates of orchardgrass (Dactylis glomerataL.), smooth bromegrass (Bromus inermis Leys.), alsikeclover (Trifolium hybridum L.), and a mixture by weightof 40% orchardgrass, 40% alsike clover, and 20% whiteclover (Trifolium repens L.) at Tunkwa Lake in 1990.Species^ Rate(kg/ha) (live seed/m2 )Orchardgrass^ 0.5^35^1.5 1043.0 2086.0^41612.0 833Smooth bromegrass^ 0.5^111.5 323.0 656.0^13012.0 260Alsike clover^ 0.5^261.5 793.0 1576.0^31412.0 628Mixture^ 0.5 381.5^1263.0 2306.0 46112.0^92151.3. Literature Review1.3.1. Conifer - Vegetation InteractionsClark and Mclean (1975), in a laboratory study,concluded that survival, height, and plant mass of six-monthold lodgepole pine seedlings decreased as density oforchardgrass increased. Lodgepole pine survival increasedby four times (P<0.05), height increased by over one-fifth(P<0.05), and the average dry weight of lodgepole pineshoots plus roots increased ten times (P<0.05) between thehighest grass density (9.0 kg/ha) and no grass competition.Moreover, greater competition to lodgepole pine occurredwith orchardgrass, a non-rhizomatous plant, than withpinegrass (Calamagrostis rubesens Buckl.), which is weaklyrhizomatous. The response of lodgepole pine to grasscompetition was independent of a 2-, 4-, or 10-day wateringinterval.Clark and McLean (1979) conducted seeding rate andforage species field trials in the southern interior ofBritish Columbia on a subalpine, lodgepole pine site burnedand cleared of native vegetation. The seeding rate trialconsisted of orchardgrass sown at four rates from 2.2 - 17.9kg/ha, and the forage species trial included orchardgrass,timothy (Phleum pratense L.), smooth bromegrass, red fescue(Festuca rubra L.), hard fescue (Festuca ovina var.duriscula (L) Koch), and crested wheatgrass (Agropyroncristatum (L) Gaertn.) with their seeding rates adjusted to6account for variable seed number per unit mass of thedifferent species. Tree survival, grown from seed in thefield, was not affected (P>0.05) by density of orchardgrasssowing after four years. Total biomass of pine seedlingswas reduced by 68 to 93% (P<0.05) by presence of forages,and average stem height was reduced by 59 to 71% (P<0.05) atforage seeding rates greater than 4.5 kg/ha. Individualforage species did not differ (P>0.05) in their influence onthe survival or growth of lodgepole pine.Trowbridge and Holl (1992) reported that seeding alsikeclover at rates of 10, 20, and 30 kg/ha had no effect(P<0.05) on the survival or height growth of plantedlodgepole pine seedlings in the first three years. In thefourth year lodgepole pine height was reduced marginally(P<0.05) in clover plots compared to control plots withnative vegetation. Lodgepole pine diameter growth decreased(P<0.05) with seeding rate during the first three growingseasons; however, differences in the diameter increment werenot significant (P>0.05) in the fourth year after planting.Baron (1962) concluded that the survival, after oneyear, of planted ponderosa pine (Pinus ponderosa Dougl.) innorthern California was impeded by orchardgrass seedingcompared to a control consisting of native vegetation withno seeded grass.Krueger (1983) found no difference (P>0.05) in thesurvival or height growth of ponderosa pine, Douglas-fir7(Pseudotsuga menziesii (Mirbel) Franco.), western larch(Larix occidentalis Nutt.), and western white pine (Pinusmonticola Dougl.) seedlings in areas seeded to a mixture oforchardgrass, timothy, tall oatgrass (Arrhenatherum elatius(L.) Pres1.), smooth bromegrass, and white clover (Trifoliumrepens L.) at 2.68 kg/ha, as compared to unseeded areas ineastern Oregon.Klinger (1986) reported that the growth and survival oftwo-year old Douglas-fir seedlings was decreased (P<0.05) bythe presence of four different seeding mixtures (Table 2) innorth eastern Oregon; however, only the mixture containingred fescue, a strong-sod forming grass, resulted in survivalbelow the minimum requirement for tree stocking.Table 2. Seeding mixtures and rates used by Klinger (1986).Mixtures^ Rate (kg/ha)Colonial bentgrass (Agrostis tenuis Sibth.) 2.2Orchardgrass (Dactylis glomerata L.) 5.6Big trefoil (Lotus pendunculatus Cay.) 3.4Total 11.2Intermediate wheatgrass(Agropyron intermedium (Host) Beauv.) 33.6Orchardgrass 5.6Big trefoil 3.4Total 42.6Red fescue (Festuca rubra L.) 11.2Orchardgrass 5.6Big trefoil 3.4Total 20.2Pubescent wheatgrass(Agropyron trichophorum (Link) Richt.) 33.6Orchardgrass 5.6Big trefoil 3.4Total 42.68Squire (1977) found that the presence of Poa australisdecreased (P<0.01) the increment in mean height by 32%, anddecreased (P<0.05) the increment in basal area 5 cm abovethe ground by 51% of Monterey pine (Pinus radiata D. Don) inthe first two years after planting in south-westernAustralia.Elliot and White (1987), in a field study in a loggedand burnt-over area in Arizona, concluded that orchardgrassdecreased (P<0.05) ponderosa pine seedling height by 24%compared to unvegetated treatments, but was not differentthan the influence of native vegetation. Orchardgrass alsodecreased (P<0.05) tree diameters by 21% compared to novegetation, and by 15% compared to native vegetation.Orchardgrass had no influence (P>0.05) on tree survival, butdid reduce (P<0.05) the pre-dawn xylem moisture potential inthe conifers.Eissenstat (1980), and Eissenstat and Mitchell (1983),conducted a study in which container-grown Douglas-fir wasgrown with a 5:3:2 mixture by weight of orchardgrass,timothy, and red clover (Trifolium pratense L.) at 28 kg/ha.The seeding rate was chosen to maximize potentialinteractions between the species. Pre-dawn and midday xylemmoisture potentials in Douglas-fir were decreased (P<0.05)by the presence of the forage in the first year, but not thefollowing year, and Douglas-fir survival was not affected(P>0.05) in either year.91.3.2. vegetation DynamicsVegetation dynamics following forage seeding ontoclear-cuts has never been monitored quantitatively in anyecotype in British Columbia (Nordstrom 1984). Literatureconcerning vegetation dynamics in the Montane Spruce andsimilar ecosystems is typically a collection of anecdotaland operational information listing forage species or mixesthat have been deemed appropriate for use through 'trial anderror' (Christ 1934, Pickford and Jackman 1944, Pringle andMcLean 1962, Eddleman and McLean 1969, McLean and Bawtree1971, Berglund 1976, Carr 1980). Other studies haveincluded vegetation dynamics as supplemental information toother research, and are often qualitative.Anderson and Elliot (1957) visually estimated theground cover of several forage species following seedingonto burnt over land in the Peace River region. One yearfollowing seeding, smooth bromegrass varied between 33 and78% ground cover, and alsike clover varied between 2 and48%. All sites and plots were noted to be highly variable.Brooke and Holl (1988) reported broadcast seeding onsnow-covered clear-cuts in the southern interior of BritishColumbia resulted in successful establishment oforchardgrass, timothy and smooth bromegrass; however, it wasup to 23 times less successful (P>0.05) in the establishmentof alsike and white clover. A survey of existing winterseeding establishment (percent of pure live seed sown10resulting in established plants) showed the followingresults: orchardgrass, 2.3%; timothy, 1.2%; smoothbromegrass, 1.3%; and clovers, 0.1%. Moreover, two yearsafter seeding, orchardgrass had 21.9% establishment fromwinter seeding and 12% from spring seeding, compared toalsike clover, which had 0.2% and 13.2% establishmentrespectively, for these two timings of seeding. Winterseeded orchardgrass retained 50% of its germinatedpopulation between the first and second year, whereas,spring-seeded orchardgrass retained 30% of its first yearpopulation.Clark and McLean (1979) reported a mixture of timothy,orchardgrass, smooth bromegrass, crested wheatgrass, andalsike clover increased (P<0.05) forage production over afour-year period following seeding by 40 to 200%, comparedto native vegetation. Differences in forage productionresulting from the seeding rates of 2.2 to 17.9 kg/hadiminished over time; the production from the high ratedeclined (P<0.05) by 33% between the second and the fourthyear, and production from the low rate increased (P<0.05) by29% during this period.Klock, Tiedemann and Lopushinsky (1975) definedsuccessful forage establishment on disturbed mountain slopesof north-central Washington State as "greater than 20%vegetative cover within two years of seeding." Given thiscriteria, they found orchardgrass and smooth bromegrass were11among the successful species if sown at rates of 6.7 to 10.1kg/ha.1.3.3. Other Influences of Forage SeedingBeyond the immediate influence of forage seeding onbotanical composition and conifers, forage seeding alsoinfluences other aspects of the ecosystem.Quinton (1984) found that the largest portion of cattlediets on a forest clear-cut in south-central BritishColumbia seeded to forage was composed of graminoidsincluding seeded grasses; however, the highest utilizationrelative to availability was of forbs which included alsikeclover seeded onto the site.Sullivan and Sullivan (1984) found that seedingdomestic forages strongly positively influences rodentpopulations of deer mice (Peromyscus maniculatus Wagner) andvoles (Microtus spp.) on clear-cuts of the Interior Douglas-Fir biogeoclimatic zone.The preceding literature review reveals the lack ofdefinitive information on the influence of forage seeding onthe synecology of early seral forest sites. The oftenconflicting results of previous experimentation and the lackof information relevant to British Columbia's ecotypesexemplifies the need for more quantitative experimentation,and this research was aimed at addressing this lack ofinformation.122. Study SiteThe study site for this research is located near TunkwaLake (120 ° 57' W., 50 ° 30' N.) in the southern interior ofBritish Columbia (Figure 1). It was classified within PhaseIIa, Engelmann spruce (lodgepole pine)/ grouseberry -pinegrass, on sandy morainal gentle slopes, in the Very Dry,Cool Montane Spruce (MSxk) biogeoclimatic subzone (Hope etal. 1991). The elevation of the site is 1450 m, with aslope of 3% and a north-west aspect. Soil at the site is amelanic brunisol. The site supported a climax stand oflodgepole pine and Engelmann spruce before logging (Newman,pers. comm., 1990).13,Kamloops'MerrittTunkwaFig. 1. Location of Tunkva Lake research site.143. Methods3.1. Experimental Set-up3.1.1. Site PreparationThe research site and surrounding area was clear-cutlogged in the winter of 1988/89, and logging debris andwaste were bunched and burned in the fall of 1989 as part ofoperational forest management in the area. All other sitepreparations were conducted in the spring of 1990 betweenthe time of snow-melt and bud-break on the lodgepole pineseedlings.The experimental site was enclosed with a 4-m highpaige wire fence to exclude livestock and wild ungulates.The site contained 88, 4X4-m plots which were located withpermanent markers placed in the ground. To ensure acontinuous 2.5-m spacing of the trees from plot to plot, 1-mbuffer strips were laid out between the plots. A minimum 4-mbuffer (planted to trees) was located around the perimeterof the plots to eliminate edge effects.To achieve a desired average mineral soil exposure of15-25%, and to mix mineral soil with any unburned forestlitter, plots were scarified by hand with garden rakes; eachplot was passed over once completely to ensure even soildisturbance.153.1.2. Forage SeedingAlsike clover and white clover were coated with a clay-Rhizobium leguminosarum var. trifolii mixture which providedan average 2000 live Rhizobium cells per seed. This coatingalso added to the weight of seeds, decreasing the number ofpure live clover seeds per unit mass.Forages were seeded onto the plots by hand immediatelyfollowing snow-melt. Seed required for each 0.0016-ha plotwas calculated and this allotment was divided into quarters;each quarter of the plot was seeded by evenly scattering theseeds in a smooth sweeping motion from the centre of theplot. This method allowed for equal distribution of seed inthe plots. Seeding after snow-melt ensured there wasadequate moisture for germination.3.1.3. Lodgepole Pine PlantingLodgepole pine seedlings (1+0 PSB 313) were plantedimmediately after forage seeding. Each plot contained fourlodgepole pine seedlings at a 2.5-m spacing, and each treewas tagged with a number for sampling records.3.2. Germination TrialsGermination trials of the forage seed were conducted inaccordance with the procedure outlined by the Association ofOfficial Seed Analysts (1978), and were used to calculatethe number of pure live seed sown/ha (Table 1).163.3. Vegetation Dynamics MeasurementsTwo sets of vegetation dynamics measurements wereconducted within each plot: one centred on a randomlyselected lodgepole pine seedling to assess interaction oflodgepole pine and forages, and the second in the middle ofthe plot, without the influence of the tree seedlings, toassess the dynamics of the herbaceous vegetation. Samplelocations within each 4x4-m plot were allocated as indicatedin Figure 2. Sampling for forage production occurred inlxl-m sub-plots; each sub-plot, and the quarter section ofthe sub-plot actually clipped, were selected randomly;however, the same sub-plot was not clipped twice during thestudy.This sampling strategy allowed adequate interspersionof clippings while avoiding the confounding effects of theedge of the 4X4-m plots. This sampling strategy alsoensured that clippings did not influence the results of thedynamics measurements in the centre of the plot, nor thecompetitive balance between lodgepole pine and othervegetation.173.3.1. CoverBefore lodgepole pine planting and forage seeding in1990 the cover of litter, wood and exposed mineral soil ineach plot was estimated with the canopy coverage method in20- X 50-cm frames (Daubenmire 1959). This method was alsoused to determine the cover of all vegetation, litter, woodand exposed mineral soil twice each year, coincident withthe conifer measurements.0^0B.E.^A.^C.D.ONorth-east cornerCD^Conifer SeedlingsA.^Stand Dynamics MeasurementsB-E. Forage Production MeasurementsFig. 2. Sampling locations within 4X4-m plots at TunkwaLake.183.3.2. DensityIn 1990, density was determined by counting the numberof genets (Silvertown 1987:3) within a 20- x 50-cm frame attwo intervals. The first was a density count of theseedlings established after lodgepole pine bud-break, butbefore the estimated time of significant drying in the upper2.5-cm of soil. This is approximately representative of themaximum amount of field germination when moisture wasadequate and before any substantial seedling death due todesiccation or competition occurred. The second densitycounts were conducted after lodgepole pine bud-set. In 1991density counts were conducted twice, coincident with thelodgepole pine measurements.3.3.3. HeightHeight of all species included in the density countswas measured, to the nearest 0.1 cm, from ground level tothe tip of the highest leaf extended upward on a plantocularly estimated to be of average height within the plot.3.3.4. ProductionAn estimate of the available forage production forherbivore consumption was determined from oven-dry samplesobtained by clipping a 0.25-m2 frame (50x50 cm) to a 5-cmstubble height. In both 1990 and 1991, forage production wasdetermined at lodgepole pine bud set; vegetation wasseparated into one of the following six groups: smoothbromegrass, pinegrass, orchardgrass, clovers, other grasses,19and forbs. Each component was calculated separately inaddition to the total for the plot. Shrubs were notincluded in forage production calculations as they were notconsidered a forage source.3.4. Lodgepole Pine MeasurementsLodgepole pine survival, height, basal diameter, unitneedle mass and damage were measured annually before thestart of the lodgepole pine growing season (between snow-melt and bud-break) and immediately after the trees had setbud.3.4.1. Survival and DamageDuring each sampling period lodgepole pine survival anddamage were assessed. Death was defined as 99% or greaternecrotic needles. Damage classified as human, rodent,erosion, snow-press, lodging, frost, and other was alsonoted at this time, as was the type (scar, break orremoval), size (% girdle and length) and location of thedamage on the lodgepole pine.3.4.2. HeightHeight was measured to the nearest 0.1 cm on every treefrom the soil surface to the tip of the terminal bud.3.4.3. Basal DiameterBasal diameter was measured to the nearest 0.1 mm withcalipers placed around the stem immediately above the soilsurface.203.4.4. Unit Needle MassUnit needle mass (mass/conifer needle) was determinedfrom an oven-dry sample of ten lodgepole pine needles,removed from the most recent growth along the main stem ofall lodgepole pine seedlings in 1991 only. Needlescollected in 1990 were too variable in their numbercollected per tree to produce meaningful results.3.5. Weather RecordA daily record of maximum and minimum temperature,precipitation, maximum and minimum soil temperature, andsoil moisture was collected, from an existing CR-21 MicroData Logger on an adjacent FRDA project 3.55 research block,during the growing season of both study years.3.6. Photographic RecordAll treatments were photographed annually with a 35-mmSLR, with a 35-mm lens, at the last sampling date, toprovide a visual reference during data analysis andpresentation. Plots were photographed from the sameposition each year, 5 m perpendicular to the north-eastcorner, with a reference rod placed in the middle of theplot to aid in comparison.213.7. Statistical Analysis3.7.1. Vegetation DynamicsThe influence of seeding rate on vegetation height,density, total vegetative cover, and production was analyzedwith an analysis of variance (ANOVA) for a completely randomdesign with a factorial arrangement. The analysis has beenadjusted (Table 3) for the unbalanced design that resultsfrom a single control being used for both main effectfactors (Bergerud 1989). The analysis was carried out inthree stages. The first stage was a two-way ANOVA conductedon a sub-set of the data without the control included; thisanalysis derived the sum of squares for both treatmentfactors and their interaction term. The second stage was asimple one-way ANOVA conducted on a new factor called"treatment"; this factor has 21 levels consisting of 20levels of species and rate in all their possible factorialcombinations, and another level for the control. The secondstage derived the sum of squares for error and "treatment."The sum of squares for control was calculated by subtractingthe sum of squares for species, rate and their interactionfrom the sum of squares for "treatment." The third stage ofthe analysis was to produce a composite ANOVA table and tocalculate the mean squares and F-ratios in the normalmanner.22Table 3. Analysis of variance for the influence of foragespecies and seeding rate by mass on vegetationproduction, vegetation density, vegetation height, andtotal vegetative cover.Stage 1Source of variation Degrees of freedom^Sum of squaresSpecies^3^ SSARate 4 SSBSpecies X Rate^12 SSABError 60 Not UsedStage 2Source^df^ SSTreatment^20 SSMError 63^ SSEStage 3Source^df^ SSSpecies^(A-1)^ 3^SSARate (B-1) 4 SSBSpecies X Rate (A-1)(B-1)^12 SSABControl 1^SSC'Error^[(A X B)+1](R-1)^63 SSETotal [{(A)(B)+11{11}]-1^83'SSC = SSM - SSA - SSB - SSAB23Specific differences among species treatment means weredetermined using a set of individual degree of freedomcontrasts (Table 4); a set of orthogonal contrasts was usedto determine first (linear), second (quadratic extension) orthird (cubic extension) order polynomial relationships dueto seeding rate by mass (Table 5). Significant second andthird order polynomials are not reported because they didnot produce biologically meaningful results.Table 4. Individual degree of freedom contrasts used todetermine specific differences among species levels inthe analysis of variance.ul = Mixtureu2 = Alsike Cloveru3 = Smooth Bromegrassu4 = OrchardgrassContrast 1 (C1) = ul vs. u2, u3, u4Contrast 2 (C2) = u2 vs. u3, u4Contrast 3 (C3) = u3 vs. u4Tests of Orthogonality^Cl^C2^C3ul^-3 0 0u2 1^-2^0u3^1 1 -1u4 1^1^1Sum^0^0^0^= LinearlyIndependentC1vsC2=0-2+1+1=0ClvsC3=0+0-1+1=0C2vsC3=0+0-1+1=0 = MutuallyOrthogonal24Table 5. Orthogonal contrast coefficients used to estimatepolynomial models for seeding rate levels in the analysisof variance.Seeding Rate^Linear Quadratic Cubic^Deviationkg/ha0.5 -41 191 276 2061.5 -31 47 -169 -4603.0 -16 -119 -351 3226.0 14 -270 293 -7312.0 74 151 -49 53.7.2. Two-Dimensional PartitioningThe influence of seeding rate on botanical composition,as reflected in the changes in cover, was analyzed with two-dimensional partitioning. Two-dimensional partitioning is astatistical procedure suitable for simultaneouslydetermining the relative contribution of various componentsto the response of an additive multivariate system. It alsodetermines the effect treatments have on these individualcomponents and the system as a whole (Eaton et al. 1986).As the name implies, the analysis consists of two stages,described as follows: in one dimension, total variation incover is partitioned into orthogonalized cover components bylinear regression analysis; in the second dimension,variation of each of the cover components, as expressed thecoefficient of determination between total cover and a givencover component, is partitioned among treatment effects anderror following the procedure outlined for the ANOVA of thevegetation dynamics data. These two dimensions become thecolumns and rows, respectively of the tables in which the25results are summarized. Sums of products are alsocalculated, which are the sum of the interactions betweentreatments and component pairs. The order in which thecover components are placed into the regression analysis inthe first dimension is determined by their presumeddevelopmental sequence; if components are deemed to havesimilar development, then they can be ordered by some otherlogical attribute.To simplify the mathematics in the analysis, covercomponents with very small, or infrequent cover values, weregrouped into one of following eight categories: litter andwood, bare mineral soil, orchardgrass, clovers, smoothbromegrass, native graminoids, native forbs, and nativeshrubs. A complete list of the species included in each ofthese cover categories is presented in Appendix 1. Theninth category, total cover, is the sum of the cover valuesfor the eight previously listed categories.These cover components were ordered into the analysisas they are listed above. Plant litter, wood and baremineral soil were known to precede the vegetative covercomponents in the development of the site and, as the firstin succession, were the first components entered into theregression analysis. The six vegetative cover components donot have a true developmental sequence, in that, none is anecessary precursor to the development of others.Differences in the speed of establishment of the various26plant categories were considered in the ordering, and thedomestic species sown were the first to germinate on thesite and, therefore, domestic species were entered into theanalysis before the native vegetation.The influence of forage seeding on total vegetativecover and its components, were also of interest, primarilybecause it was assumed that total non-floristic covercomponents have no influence on the competition amonglodgepole pine and the surrounding vegetation. For thisreason two-dimensional partitioning was also conducted on asub-set of the cover data, utilizing only the vegetativecover components. For this second analysis, totalvegetative cover was calculated as the sum of the sixvegetative cover categories.3.7.3. Lodgepole PineThe effect of forage species and seeding rate by masson lodgepole pine height, basal diameter, unit needle mass,damage and survival were analyzed using analysis of variancefor a completely random design. The analysis has beenmodified similar to that used for vegetation dynamics withthe two following exceptions (Table 6): a second error termwas calculated for the sub-sampling of four lodgepole pineswithin each of the plots, and the entire three stageanalysis was conducted twice. The second analysis wasidentical to the first except that the control for nativevegetation was substituted with a control consisting of27Table 6. Analysis of variance for the influence of foragespecies and seeding rate by mass on lodgepole pine height,basal diameter, unit needle mass, damage and survival.Stage 1Source of variation Degrees of freedom^Sum of squaresSpeciesRateSpecies X RateExperimental ErrorSampling Error341260240SSASSBSSABNot UsedNot UsedStage 2Source^ df^ SSTreatment^20 SSMExperimental Error^63^ SSESampling Error^252 SSESStage 3Source df SSSpecies (A-1) 3 SSARate (B-1) 4 SSBSpecies X Rate (A-i) (B-i) 12 SSABControls 2 SSC'Experimental Error [(A X B)+1) (S-1) 63 SSESampling Error r[f(A)(B)+11{S-1}] 252 SSESTotal [{(A)(B)+11011{S}]-1 3351SSC = SSM - SSA - SSB - SSAB28lodgepole pine with no competing vegetation. The analysismust be conducted twice because the sum of squares for eachindividual control cannot be calculated from the pooledvariance if both were analyzed simultaneously.Individual degree of freedom contrasts for the specieslevels, and orthogonal contrasts for the seeding rate levelswere identical to those used for the vegetation dynamicsANOVA (Tables 4 and 5).The relationship between lodgepole pine basal diameter,height, unit needle mass, damage and survival to the numberof pure live forage seeds sown, total vegetative cover,vegetation height, density, and production were analyzedwith forward stepwise multiple regression and correlation.A separate regression was conducted for each forage speciestreatment for lodgepole pine basal diameter, height, unitneedle mass, damage, and survival.A chi-square analysis of 2 x 2 contingency tables forrodent damage and survival were used to determine iflodgepole pine survival was independent of rodent damage,and to determine if rodent damage and survival werehomogenously distributed among species factors and controls.294. Results4.1. Germination TrialsTable 7 displays the results of the laboratorygermination trials on forage species sown. These resultswere used to calculate the number of pure live seed sown perunit area (Table 1).Table 7. Germination and purity of forage species sown atTunkwa Lake in 1990.Forage Species^Germination^Pure live seed% of total weightOrchardgrass^93^97Smooth bromegrass^93 98Alsike clover 89 100White clover^90 994.2. Vegetation Dynamics4.2.1. CoverBefore the planting of lodgepole pine and seeding offorages in 1990 the average cover on the site consisted of24.7% bare mineral soil, 62.5% litter, and 9.2% wood.Figures 3 to 7 show the changes in cover categories for eachforage species sown over the first two growing seasons.30100806040200May^Jul^May^Jul1990^1991Soil M Litt/Wood I   Brin ill Gras =I Forb I I ShrbError bars = +/- one standard error.BRIN^ Smooth bromegrass.FORB Native forbs (Appendix 1).GRAS^ Native graminoids (Appendix 1).LITT/WOOD Plant litter and wood.SHRB^ Native shrubs (Appendix 1).SOIL Bare mineral soil.Fig. 3. Cover on plots sown to smooth bromegrass at TunkwaLake, May 1990 to July 1991.3110080604020May^Jul^May^Jul1990^1991MI Soil M Litt/Wood ni Dagl^Gras ^ Forb^ShrbError bars = +/- one standard error.DAGL^ Orchardgrass.FORB Native forbs (Appendix 1).GRAS^ Native graminoids (Appendix 1).LITT/WOOD Plant litter and wood.SHRB^ Native shrubs (Appendix 1).SOIL Bare mineral soil.Fig. 4. Cover on plots sown to orchardgrass at Tunkwa Lake,May 1990 to July 1991.32 OP0000May^Jul^May^Jul1990^1991MI Soil MO Litt/Wood 1771 Imp NMI Gras EaForb I I Slut)Error bars = +/- one standard error.FORB^ Native forbs (Appendix 1).GRAS Native graminoids (Appendix 1).LITT/WOOD^Plant litter and wood.SHRB Native shrubs (Appendix 1).SOIL^ Bare mineral soil.TRSP Clovers.Fig. 5. Cover on plots sown to alsike clover at TunkwaLake, May 1990 to July 1991.806040203380604020May^Jul^May^Jul1990^1991^NI Soil^M Litt/Wood^I Trap^MI Gras^I Forb^I^ I Shrb^MN DaglError bars = +/ - one standard error.DAGL^ Orchardgrass.FORB Native forbs (Appendix 1).GRAS^ Native graminoids (Appendix 1).LITT/WOOD Plant litter and wood.SHRB^ Native shrubs (Appendix 1).SOIL Bare mineral soil.TRSP^ Clovers.Fig. 6. Cover on plots sown to the mixture at Tunkwa Lake,May 1990 to July 1991.34 0000100806040200May^Jul^May^Jul1990^1991IIII Soil W% Litt/Wood El Gras 11111 Forb     ShrbError bars = +/- one standard error.FORB^ Native forbs (Appendix 1).GRAS Native graminoids (Appendix 1).LITT/WOOD^Plant litter and wood.SHRB Native shrubs (Appendix 1).SOIL^ Bare mineral soil.Fig. 7. Cover on plots with native vegetation at TunkwaLake, May 1990 to July 1991.35Total vegetative cover in 1990 averaged 4.4%, and wasnot influenced (P>0.05) by species or seeding rate (Table8). Total vegetative cover in 1991 averaged 26.8%, andincreased linearly with seeding rate by mass in 1991(r2=0.16, P<0.05). On plots seeded to the mixture, 18.3% ofthe variability in total vegetative cover was accounted for(P<0.06) by a positive linear relationship between cover andpure live seeding rate. On plots seeded to alsike clover,total vegetative cover increased linearly with the initialcover of wood on those plots in both 1990 (r2=0.255,P<0.02), and 1991 (r2=0.182, P<0.06). Total vegetativecover on plots seeded to alsike clover averaged 30.9% in1991, and was greater (P<0.025) than the average of thoseseeded to orchardgrass or smooth bromegrass (20.2%).36Table 8.^Vegetative cover (%) at Tunkwa Lake inand 1991. 1990Species Year Ratekg/ha0.5 1.5 3.0 6.0 12.0Orchardgrass 1990 avg 2.3 1.5 7.5 6.8 4.5SE 0.8 1.0 3.0 3.3 1.71991 avg 24.3 5.3 41.5 32.0 40.0SE 21.1 1.7 17.7 14.9 18.4Smooth brome 1990 avg 0.8 2.3 6.0 3.4 2.3SE 0.9 1.7 3.5 0.9 0.91991 avg 18.8 6.8 7.5 14.3 11.3SE 17.1 4.6 5.4 5.9 5.5Alsike clover 1990 avg 3.0 11.8 2.3 3.4 12.5SE 1.4 10.2 0.8 0.9 9.81991 avg 9.0 55.8 43.0 37.0 49.5SE 4.0 22.6 13.8 15.6 29.2Mixture 1990 avg 2.3 6.0 1.5 7.5 4.5SE 1.6 4.7 1.7 4.4 1.01991 avg 3.0 34.0 17.8 43.0 49.5SE 3.5 19.0 11.3 26.2 20.1NativeVegetation 1990 avg 0.0SE 0.01991 avg 21.0SE 16.537In 1990, litter and wood (36%), and bare mineral soil(47%) contributed the greatest amount of variability in thetotal cover of the plots, although neither of these twocover variables were influenced (P>0.05) by treatment (Table9). The combined contribution to total variability of allthree seeded vegetation cover classes was 8%, this similarto the variability contributed by the three nativevegetative cover components (9%), which was almostexclusively due to the contribution of native forbs.When the non-floristic cover components wereeliminated from the two-dimensional analysis (Table 10), thegreatest amount of variability in the total vegetative coverwas derived from the clovers (39%) and the native forbs(41%). Total vegetative cover and the native vegetativecomponents did not respond linearly to seeding rate orspecies factors in 1990; however, the cover of cloversdisplayed a linear relationship (r2=0.16, P<0.025) toseeding rate by mass. In addition, all three seeded covercomponents showed highly significant response to the speciesfactor; however, a significant response in the seededfraction was confounded by the contrasts used. Theycompared species sown exclusively to certain treatments, toother seeded species, which were not sown in thesetreatments.38Table 9. Two-dimensional partitioning of total sum ofsquares, expressed as aat Tunkwa Lake in 1990 1 .percentage of total coverSource df LW SL DG TS BI GS FB SB SP TOTTotal 83 36 47 1 6 1 0 9 0 0 100Treatment 20 10 6 0 2 0 0 2 0 0 23Rate 4 3 1 0 0 0 0 0 0 1 7Linear 1 2 0 0 0 0 0 0 0 -1 1Quad 1 1 0 0 0 0 0 0 0 1 2Cubic 1 0 1 0 0 0 0 0 0 2 3Dev 1 0 0 0 0 0 0 0 0 -1 0Species 3 1 0 0***2 1" 0"* 0 0 0 0 3Cl 1 0 0 0 0 0 0 0 0 -1 0C2 1 0 0 0 1*** 0 * 0 0 0 -1 0C3 1 0 0 0"* 0 0*" 0 0 0 2 3S X R 12 6 5 0 0 0 0 2 0 1 14Control 1 0 0 0 1*** 0 0 0 0 -1 0Error 63 26 41 1 4 1 0 7 0 -2 771 Zero values can result from rounding values less than0.500 down to 0.2 *^**^*** , Significant at 0.05, 0.01, and 0.001 levels,respectively.Explanation of Abbreviations:LW^Litter and wood.SL Bare mineral soil.DG^Orchardgrass.TS Clovers.BI^Smooth bromegrass.GS Native graminoids (Appendix 1).FB^Native forbs (Appendix 1).SB Native shrubs (Appendix 1).SP^Sums of products.TOT Total cover.df^Degrees of freedom in each column.S X R Species by rate interaction term.Linear, quad, cubic and dev refer to the orthogonalcontrasts used to find polynomial relationships for seedingrate.Cl, C2, and C3 refer to the individual degree of freedomcontrasts for species factors.39Table 10. Two-dimensional partitioning of total sum ofsquares, expressed as a percentage of total vegetativecover at Tunkwa Lake in 1990 1 .Source df DG TS BI GS FB SB SP TOTTotal 83 12 39 6 1 41 1 0 100Treatment 20 5 14 3 0 10 0 -9 25Rate 4 0 3 0 0 2 0 2 4Linear 1 0 3 *2 0 0 0 0 -2 2Quad 1 0 0 0 0 0 0 2 1Cubic 1 0 0 0 0 0 0 3 0Dev 1 0 0 0 0 1 0 -1 1Species 3 3 *** 5 * 2"* 0 1 0 -8 4Cl 1 0 0 0 0 0 0 -1 0C2 1 1 * 5** 0" 0 1 0 -7 3C3 1 2 *** 0 1*** 0 0 0 -0 1S X R 12 2 6 1 0 7 0 -3 15Control 1 0 0 0 0 0 0 0 2Error 63 7 25 3 1 30 1 9 751 Zero values can result from rounding values less than0.500 down to 0.2 *^**^*, Significant at 0.05, 0.01, and 0.001 levels,respectively.Explanation of Abbreviations:DG^Orchardgrass.TS Clovers.BI^Smooth bromegrass.GS Native graminoids (Appendix 1).FB^Native herbs (Appendix 1).SB Native shrubs (Appendix 1).SP^Sums of products.TOT Total vegetative cover.df^Degrees of freedom for each column.S X R Species by rate interaction term.Linear, quad, cubic and dev refer to the orthogonalcontrasts used to find polynomial relationships for seedingrate.Cl, C2, and C3 refer to the individual degree of freedomcontrasts for species factors.40In 1991, alsike clover and native forbs contributed thegreatest amount of variability to total cover (Table 11).Litter and wood contributed 6% of the total variability incover and their value declined (r 2=0.12, P<0.0005) withincreasing seeding rate. The cover of litter and wood onplots sown to alsike clover in 1991 (59.1%), were less(P<0.025) than on those sown to orchardgrass (71.7%) orsmooth bromegrass (87.1%). Native graminoids had 1.6% coverin 1991 on plots sown to forages; this was greater (P<0.05)than the cover of graminoids on plots with native vegetationalone (0.9%).When the non-floristic cover components are removedfrom the two-dimensional analysis in 1991 (Table 12),orchardgrass and the clovers contributed 81% of thevariability in total vegetative cover. As detailed earlier,total vegetative cover was greater on plots sown to alsikeclover than the average response of the seeded graminoids.None of native cover components were influenced by seedingrate or species of forage sown (P>0.05). Orchardgrassresponded to treatment in the same manner as it did in 1990,and the clovers exhibited a positive linear association withseeding rate by mass again (r 2=0.16, P<0.01). The effect oftreatments on smooth bromegrass could not be determined in1991 because smooth bromegrass contributed a negligibleamount of variability to total vegetative cover.41Table 11. Two-dimensional partitioning of total sum ofsquares, expressed as a percentage of total cover atTunkwa Lake in 1991 1 .Source df LW SL DG TS BI GS FB SB SP TOTTotal 83 6 0 12 31 0 8 41 2 0 100Treatment 20 3 0 6 12 0 2 9 0-10^23Rate 4 1"2 0 0 2 0 0 3 0 -1^7Linear 1 1 *** 0 0 0 0 0 0 0 -1^1Quad 1 0 0 0 0 0 0 0 0 1^2Cubic 1 0 0 0 0 0 0 3* 0 0^3Dev 1 0 0 0 1 0 0 0 0 -2^0Species 3 1* 0 4*** 5 ** 0 0 0 0 -7^3Cl 1 0 0 0 1 0 0 0 0 -1^0C2 1 0 * 0 2*** 4 *** 0 0 0 0 -6^0C3 1 0 0 2*** 0 0 0 0 0 -0^3S X R 12 1 0 2 4 0 1 5 0 0^14Control 1 0 0 0 1* 0 0* 1 0 -2^0Error 63 3 0 6 18 0 6 32 2 10^771 Zero values can result from rounding values less than0.5000 down to 0.2* , ", ***, Significant at 0.05, 0.01, and 0.001 levelsrespectively.Explanation of Abbreviations:LW^Litter and wood.SL Bare mineral soil.DG^Orchardgrass.TS Clovers.BI^Smooth bromegrass.GS Native graminoids (Appendix 1).FB^Native herbs (Appendix 1).SB Native shrubs (Appendix 1).SP^Sum of the products.TOT Total cover.df^Degrees of freedom for each column.S X R Species by rate interaction term.Linear, quad, cubic and deviation refer to the orthogonalcontrasts to determine polynomial relationships for seedingrate.Cl, C2, and C3 refer to the individual degree of freedomcontrasts for species factors.42Table 12. Two-dimensional partitioning of total sum ofsquares, expressed as a percentage of total vegetativecover at Tunkwa Lake in 1991 1 .Source df DG TS BI GS FB SB SP TOTTotal 83 22 59 0 5 13 1 0 100Treatment 20 11 32 0 1 4 0 -15 32Rate 4 1 6* 0 0 1 0 4 7*Linear 1 1 4 **2 0 0 0 0 4 5*Quad 1 0 0 0 0 0 0 0 1Cubic 1 0 0 0 0 1 0 -0 1Dev 1 0 1 0 0 0 0 -0 0Species 3 6 *** 17 *** 0 0 0 0 5 11*Cl 1 0 1 0 0 0 0 0 0C2 1 1" 16*** 0 0 0 0 5 7*C3 1 4 *** 0 0 0 0 0 -0 4S X R 12 4 8 0 1 1 0 8 14Control 1 0 1 0 0 1 0 -1 0Error 63 11 27 0 4 9 1 43 681 Zero values can result from rounding values less than0.500 down to 0.2* , ", ***, Significant at 0.05, 0.01, and 0.001 levels,respectively.Explanation of Abbreviations:DG^Orchardgrass.TS Clovers.BI^Smooth bromegrass.GS Native graminoids (Appendix 1).FB^Native herbs (Appendix 1).SB Native shrubs (Appendix 1).SP^Sum of the products.TOT Total vegetative cover.df^Degrees of freedom for each column.S X R Species by rate interaction term.Linear, quad, cubic and deviation refer to the orthogonalcontrasts used to determine polynomial relationships forseeding rate.Cl, C2, and C3 refer to the individual degree of freedomcontrasts for species factors.434.2.2. DensityDensity of vegetation increased linearly (r 2=0.18,P<0.0005) with seeding rate by mass, and with pure liveseeding rate (r2=0.23, P<0.001) in 1990; however, there wasno linear relationship (P>0.05) between these variables in1991 (Table 13).Density of vegetation on plots sown to smoothbromegrass in June 1990 increased linearly (r 2=0.60,P<0.001) with increasing pure live seeding rate; thestrength of this relationship declined in late July 1990(r2=0.29, P<0.01), and remained at this level to July 1991(r2=0.32, P<0.01).Density of vegetation on plots sown to orchardgrassalso had a positive linear relationship (r2=0.80, P<0.001)with pure live seeding rate in June 1990, and also declinedin July 1990 (r 2=0.37, P<0.005); there was no linearrelationship (P>0.05) between these two variables in July1991. Variability in the density of vegetation on plots sownto orchardgrass in June 1990 was further explained (r 2=0.85,P<0.001) by correlating the average cover of litter inaddition to pure live seeding rate (Figure 8).Density of vegetation on plots sown to the mixture waslinearly related (r 2=0.30, P<0.01) to pure live seeding ratein June 1990; however, there was no linear relationshipbetween density and pure live seeding rate on these plots inany other sampling period.44Table 13. Average density of vegetation in 1990 and 1991 atTunkwa Lake.DensitySeeding rate^ plant/m2Date (year-month)kg/ha seed/m2^90-06^90-07^91-05^91-07Avg SE Avg SE Avg SE Avg SEDAGL 0.5 35 5 0 23 2 18 1 30 11.5 104 8 0 10 1 15 1 35 23.0 208 35 2 83 3 38 2 285 126.0 416 70 1 73 2 45 1 38 012.0 833 158 3 130 6 58 2 63 2BRIN 0.5 11 5 0 10 1 13 1 30 11.5 32 5 0 8 1 8 1 15 13.0 65 5 0 35 1 15 1 23 16.0 130 8 0 15 1 30 2 58 412.0 260 70 2 75 5 45 2 105 5TRHY 0.5 26 13 1 8 0 5 1 40 21.5 79 13 1 30 2 38 2 50 23.0 157 103 6 50 3 30 2 40 16.0 314 75 4 38 1 18 1 28 212.0 628 620 43 158 13 70 5 100 6MIX^0.5 38 8 1 118 1 8 1 10 11.5 115 60 5 33 3 38 2 65 33.0 230 10 1 5 1 18 1 78 66.0 461 150 7 130 7 50 2 40 212.0 921 298 12 50 2 28 1 28 1NATV 0 0 0 0 0 5 0 133 12DAGL Orchardgrass.BRIN Smooth bromegrass.TRHY Alsike clover.MIX Mixture by weight of 40% orchardgrass, 40% alsikeclover, and 20% white clover.NATV Native vegetation control.4526Ca0 105rig. 8. The influence of pure live seeding rate (seedsown/me) of forages, and the initial cover (%) of litteron the density of seedlings (plants/me) in 1990 on plotssown to orchardgrass at Tunkwa Lake.46Density of vegetation on plots sown to alsike cloverincreased linearly (r 2=0.45, P<0.001) with increasing purelive seeding rate in June 1990. The strength of the linearrelationship declined in July 1990 (r 2=0.21, P<0.04), andthere was no linear relationship (P>0.05) between density onplots sown to alsike clover and pure live seeding rate in1991. Additional variability in density of vegetation onplots sown to alsike clover in July 1990 was accounted forby the initial cover of wood on these plots (R 2=0.72,P<0.001) (Figure 9). Density of vegetation on plots sown toalsike clover was correlated (r 2=0.36, P<0.005) with theinitial cover of wood in July 1991.No pattern could be discerned from the incrementalrecruitment and mortality of plants, in either the seededfraction, or total density, given the parameters measured inthis study. Moreover, there was no relationship (P>0.05)between establishment of seeded species, as a percentage ofpure live seed sown, and seeding rate or species of foragesown in any sampling period.Density of vegetation was unaffected (P>0.05) byspecies of forage sown in 1990. In 1991, smooth bromegrasshad an average density of 26 plants/m 2 , and was 62% lower(P<0.025) than the average density of orchardgrass (90plants/m 2 ).47606040To 30C•^V.40".10Milb4.4014WW■%:1111'4.11,4V//^#^0111410.400.^10.111011. 1110.:000. 4I■ I 1011MINNNVII^•.0.114011■ 111.11j01. 110.411:' OM* ZWINelt .40,0 ;4,111.^111.--.0701011■711,-•■■■^ 111M.1110°' 10.^ 0. ■■.1.,;:,^•^1101001iVnIZOZ.....11%.41t,kr;Now% rao- 0;Qvte %Me2010-to 11. .000. 40111,/dP '2'9°P^SeecPtpPboz.^tikawrig. 9. The influence of pure live seeding rate (seedsown/a2) and the initial cover (%) of wood on the densityof vegetation (plants/a2) in 1990 on plots sown to alsikeclover at Tunkwa Lake.48The interaction (P<0.0005) among species and seedingrate did not produce any biologically meaningful results(Figure 10).300250200150100500Density (plants/m2)0^2^4^6^8^10^12^14Seeding Rate (kg/ha)DAGL T BRIN —4(— TRHY -43- MIXFig. 10. The interaction of the mean response of foragespecies and seeding rate on the average density ofvegetation (plants/m 2) in 1991 at Tunkwa Lake.494.2.3. HeightThe average height of herbaceous vegetation was 5.1 cmin 1990 and 20.4 cm in 1991. A small portion of theincrease in plant height (r 2=0.09, P<0.01) can be attributedto increasing seeding rate by mass in 1991 (Table 14). Theaverage height of vegetation on plots seeded to alsikeclover in 1991, 21.9 cm, was 3% lower (P<0.005) than theaverage height of vegetation on plots seeded to orchardgrassand smooth bromegrass.There was a positive linear relationship (r2=0.206,P<0.04) in 1991 between average height and pure live seedingrate on plots sown to the mixture. In 1990, height ofvegetation on plots sown to alsike clover was positivelycorrelated (r 2=0.325, P<0.04), with the initial cover ofmineral soil and wood, and in 1991, height of vegetation waspositively correlated (r 2=0.37, P<0.004) with initial coverof wood on these plots.50Table 14.^Average height of herbaceous1990 and 1991 at Tunkwa Lake. vegetation (cm)^inSpecies Rate (kg/ha)0.5 1.5 3.0 6.0 12.0Orchardgrass 1990 avg 2.3 2.0 10.3 13.3 7.3SE 2.2 1.4 2.3 4.0^2.21991 avg 20.5 14.5 30.3 36.534.0SE 12.4 5.2 7.3 18.416.5Smooth brome 1990 avg 3.8 1.5 5.8 9.0^4.0SE 4.3 1.1 1.7 1.8^1.71991 avg 16.0 11.0 11.5 37.311.5SE 13.3 7.1 4.5 15.3 4.4Alsike clover 1990 avg 1.5 2.0 2.5 1.8^2.5SE 1.0 1.0 1.4 0.9^1.41991 avg 5.3 22.5 24.3 22.834.8SE 2.5 9.9 5.8 10.219.8Mixture 1990 avg 0.8 8.5 6.3 5.3^3.3SE 0.9 5.3 7.2 2.2^1.41991 avg 2.5 24.3 9.0 32.532.8SE 2.9 10.1 7.4 18.8 5.8NativeVegetation 1990 avg 0.0SE 0.01991 avg 11.5SE 5.4514.2.4. ProductionProduction of herbaceous vegetation averaged 20.3 kg/hain 1990, and in 1991, averaged 834.8 kg/ha; production wasnot linearly related (P>0.05) to seeding rate by mass ineither year (Table 15). Average production of plots withseeded vegetation in 1991 was 10 times greater (P<0.05) thanproduction of plots with native vegetation alone (79.3kg/ha). Average forage production in 1990 on plots sown toorchardgrass (33.7 kg/ha) was greater (P<0.05) than on plotssown to smooth bromegrass (6.3 kg/ha). In 1991, averageforage production on plots sown to alsike clover (1471.5 kg)was greater (P<0.005) than the average of the domesticgrasses (521.0 kg/ha).Forage production in 1990 increased linearly (r 2=0.186,P<0.06) with increasing pure live seeding rate on plots sownto smooth bromegrass. Forage production in 1990 waspositively correlated (R 2=0.651, P<0.001) with the initialcover of litter and wood on plots sown to alsike clover. In1991, forage production was positively correlated (r 2=0.227,P<0.03), with the initial cover of mineral soil on plotssown to the mixture, and positively correlated (r2=0.204,P<0.05) with the initial cover of wood on plots sown toalsike clover.52Seeded vegetation comprised 86% of total production in1990, and 83% of total production in 1991. The relativecontribution of seeded vegetation to total yield did notdiffer (P>0.05) among species or seeding rate levels ineither year.Table 15. Average production of herbaceous vegetation(kg/ha)^in 1990 and 1991 at Tunkwa Lake.Species Rate (kg/ha)0.5 1.5 3.0 6.0 12.0Orchardgrass 1990 avg 15.2 8.3 30.7 47.3 66.9SE 11.8 6.7 31.9 42.7 68.21991 avg 161.9 910.4 495.4 1084.1 364.6SE 62.8 622.2 153.7 721.1 191.4Smooth brome 1990 avg 6.9 0.8 0.9 3.4 19.5SE 8.0 0.5 0.6 1.3 14.81991 avg 650.3 101.5 61.2 881.2 499.7SE 228.6 104.5 58.5 368.2 262.7Alsike clover 1990 avg 0.5 18.0 6.5 7.7 35.9SE 0.6 12.3 2.6 5.8 33.01991 avg 576.0 1429.7 1010.1 3069.8 1271.8SE 432.4 950.6 697.2 1223.7 988.5Mixture 1990 avg 16.4 19.6 94.1 24.3 3.8SE 10.8 22.0 39.9 17.1 2.51991 avg 108.4 1149.1 1121.6 925.4 1578.4SE 120.9 1284.8 499.7 788.9 1322.3NativeVegetation 1990 avg 0.0SE 0.01991 avg 79.3SE 69.9534.3. Lodgepole Pine4.3.1. Growing SeasonIndividual lodgepole pines commenced candling(initiation of terminal bud growth) in 1990 between June 6and June 19. Terminal buds on the lodgepole pine set (end ofterminal bud growth) between July 20 and July 25. Lodgepolepine commenced candling in 1991 between May 30 and June 14,and terminal buds set on the lodgepole pine in the 1991growing season between July 22 and July 29.4.3.2. Survival and DamageThere was 100% survival of lodgepole pine during the1990 growing season. There was 2.8% mortality during theoverwinter period between the 1990 and 1991 growing seasons,and an additional 3.1% during the 1991 lodgepole pinegrowing season; cumulative mortality during the two years ofthe study was 5.9% of the lodgepole pine planted in May1990.A single lodgepole pine seedling was damaged (humaninduced) during the first growing season. Rodents damaged23.9% of the lodgepole pine during the overwinter periodbetween the 1990 and 1991 growing season; rodents were theonly source of damage during this period. Rodent damage wasalmost exclusively scars of 2 cm or less in length resultingfrom chewing the bark and cambium. The remainder of rodent-induced damage was removal of the main lodgepole pine stemor laterals. There was no damage recorded during the 199154lodgepole pine growing season. Lodgepole pine survival wasindependent (P>0.05) of rodent damage, and rodent damage wasequally distributed among the forage species factors andcontrols. Rodent damage was correlated (r 2=0.534, P<0.001)to increases in total vegetative cover on plots sown toorchardgrass.4.3.3. HeightThe average lodgepole pine height at the end of thegrowing season in 1990 was 19.1 cm, and 21.3 cm in 1991.Height growth in 1990 averaged 6.5 cm, and there was nodifference (P>0.05) among species or seeding rate factors,nor between seeded vegetation and native vegetation(P>0.05). The height growth in 1990 of lodgepole pine grownwith vegetation (6.4 cm) was 14% less (P<0.05) than thecontrol group grown without competing vegetation (7.3 cm).An interaction (P<0.05) between seeding rate and speciesfactors did not produce any biologically meaningful results(Figure 11). The average height growth in 1991 was 3.9 cm,and was not affected by forage species sown or seeding rate(Table 16).Lodgepole pine height growth in 1990 was negativelycorrelated with forage production (r 2=0.291, P<0.01) onplots sown to orchardgrass. In 1991, lodgepole pine heightgrowth was correlated (R 2=0.341, P<0.03) with totalvegetative cover and density of vegetation on plots sown toalsike clover.550Height Growth (cm)0^2^4^6^8^10^12^14Seeding Rate (kg/ha)— DAGL ---+— BRIN —II— TRHY --61- MIX1086Fig. 11. The interaction of the mean response of foragespecies and seeding rate on lodgepole pine height growth(cm) in 1990 at Tunkwa Lake.56Table 16. Average lodgepole pine height growth (cm) in1990 and 1991 at Tunkwa Lake.Species Year Rate (kg/ha)0.5 1.5 3.0 6.0 12.0Orchardgrass 1990 avg 6.8 6.1 6.8 7.2 5.9SE 0.4 0.6 0.3 0.5 0.31991 avg 3.2 4.8 4.0 4.4 3.6SE 0.7 0.8 0.8 1.0 0.9Smooth brome 1990 avg 6.1 6.3 6.1 6.1 6.7SE 0.4 0.4 0.3 0.5 0.51991 avg 2.9 5.1 4.1 4.9 2.6SE 0.8 0.8 0.8 1.0 0.5Alsike clover 1990 avg 5.7 6.6 6.3 6.5 7.0SE 0.4 0.4 0.3 0.3 0.41991 avg 2.7 5.1 4.3 2.8 3.4SE 0.8 1.1 0.8 0.5 0.8Mixture 1990 avg 6.0 6.1 7.9 6.4 5.8SE 0.4 0.4 0.5 0.3 0.41991 avg 2.9 3.4 4.4 2.5 4.2SE 0.6 0.7 0.9 1.1 0.9NativeVegetation 1990 avg 6.4SE 0.41991 avg 4.7SE 0.5No CompetingVegetation 1990 avg 7.3SE 0.41991 avg 4.8SE 1.0574.3.4. Basal DiameterThe average lodgepole pine basal diameter at the end ofthe growing season in 1990 was 3.1 mm, and 5.5 mm in 1991.Basal diameter growth averaged 0.6 mm in 1990, and was notinfluenced by species or seeding rate. In 1991, basaldiameter growth averaged 1.3 mm and was unaffected byspecies of forage sown (Table 17). Increment in basaldiameter declined marginally (r2=0.03, P<0.05) withincreasing seeding rate by mass and also (r 2=0.07, P<0.07)with pure live seeding rate in 1991.Increment in basal diameter in 1990 was negativelycorrelated (r 2=0.177, P<0.07) with forage production onplots sown to orchardgrass. In 1991, basal diameter growthwas correlated (r 2=0.341, P<0.03) with total vegetativecover and density of vegetation on plots sown to alsikeclover.58Table 17. Average lodgepole pine basal diameter growth (mm)in 1990 and 1991 at Tunkwa Lake.Species^Year^Rate (kg/ha)0.5 1.5 3.0 6.0 12.0Orchardgrass 1990 avg 0.7 0.6 0.5 0.8 0.6SE 0.1 0.1 0.1 0.1 0.11991 avg 1.3 1.4 1.1 1.3 1.2SE 0.2 0.5 0.3 0.3 0.2Smooth brome 1990 avg 0.5 0.7 0.6 0.7 0.5SE 0.1 0.1 0.1 0.1 0.11991 avg 1.0 2.1 1.4 2.1 0.8SE 0.2 0.3 0.3 0.3 0.1Alsike clover 1990 avg 0.7 0.7 0.7 0.6 0.6SE 0.1 0.1 0.1 0.1 0.11991 avg 1.0 1.4 1.5 0.9 0.6SE 0.3 0.3 0.3 0.2 0.2Mixture 1990 avg 0.5 0.5 0.7 0.5 0.8SE 0.1 0.1 0.1 0.1 0.11991 avg 1.4 0.9 1.1 1.5 0.8SE 0.2 0.1 0.3 0.4 0.2NativeVegetation 1990 avg 0.4SE 0.11991 avg 1.6SE 0.2No CompetingVegetation 1990 avg 0.8SE 0.11991 avg 1.5SE 0.2594.3.5. Unit Needle MassThe average mass of ten lodgepole pine needles takenfrom the current year's growth was 0.073 g at the end of thegrowing season in 1991. The ratio of unit needle mass atthe end of the lodgepole pine growing season to the unitneedle mass at the beginning of the growing season in 1991averaged 1.076. There was no difference (P>0.05) in thisgrowth ratio among species or seeding rate factors. The1991 growth ratio of unit needle mass for the control withno competing vegetation averaged 0.667, and was lower(P<0.025) than the average ratio for lodgepole pine withsurrounding vegetation.4.3.6. Stem VolumeStem volume on the conifer seedlings was estimated bythe following formula: (Basal Diameter) 2 (Height).Average growth in stem volume in 1990 was 1.1 ± 0.0cm 3 , and in 1991 averaged 4.4 + 0.3 cm 3 . Growth in stemvolume did not differ among forage species or seeding rate,nor between seeded vegetation and the native vegetationcontrol, in either year of the study. Average growth instem volume in 1990 for conifers with surrounding vegetation(1.1 + 0.0 cm 3 ) was 27% lower (P<0.05) than the control withcompeting vegetation removed (1.5 + 0.1 cm 3). Averagegrowth in stem volume in 1991 for conifers with surroundingvegetation (4.3 + 0.3 cm 3 ) was 42% lower (P<0.05) than thecontrol with competing vegetation removed (7.4 + 1.5 cm3 ).604.4. Weather RecordThe daily record for maximum and minimum temperature,precipitation, maximum and minimum soil temperature, andsoil moisture during both growing seasons is detailed inAppendix 2.During the 1990 lodgepole pine growing season there was158.0 mm of precipitation and 336.7 growing degree days. Inthe 1991 lodgepole pine growing season there was 129.0 mm ofprecipitation, and 329.2 growing degree days.The permanent wilting point in the upper 2.5 cm ofsoil, first occurred on July 21 in the 1990 lodgepole pinegrowing season, and on July 24 in the 1991 growing season.These dates marked the point at which pronounced seedlingmortality due to desiccation could occur. The last springfrost occurred on June 5, 1990, just before the firstlodgepole pine seedlings candled, and the first frost in thefall of 1990 occurred on September 30. Lodgepole pine bud-set during the first growing season, July 20-25, 1990,coincided with moisture levels below the permanent wiltingpoint, 10-cm below the soil surface. The last spring frostof the second growing season occurred on June 19, and thefirst fall frost occurred on August 25. Permanent wiltingpoint at the 10-cm soil level first occurred on August 14,1991; lodgepole pine bud-set in the second growing seasoncoincided with significant drying at the 10-cm soil level inthe two previous weeks.615. Discussion5.1. Vegetation Dynamics5.1.1. Early Influence of Seeding RateThe number of pure live forage seeds sown had thegreatest influence on vegetation dynamics of the parametersmeasured on this site. This is apparent in the relationshipof plant density to seeding rate very early in thedevelopment of the vegetation. There were strong linearrelationships between seeding rate and seedling densitycounts for most forage species in June 1990. As otherfactors influenced the dynamics beyond germination(microclimatic variability, interspecific and intraspecificcompetition) there was a decline in the strength of therelationship between seeding rate and density for allspecies sown.Total vegetative cover in 1990 was not linearly relatedto seeding rate, because the seeded vegetation did notdevelop sufficiently in the first year for the differencesin the plant numbers to express themselves as differences intotal vegetative cover. The cover of domestic foragespecies was weakly influenced by seeding rate in 1990, butwas masked by the variability introduced by the nativespecies occurring on the plots. This is readily apparent inthe two-dimensional partitioning of the cover data. Duringthe second growing season, when the plants had establishedto a greater degree, a small portion (16.4%) of the62variability in vegetative cover was explained by the seedingrate. Once again a stronger treatment response was isolatedin the seeded fraction, because uncontrolled variability wasintroduced with the native species on the plots.Plant height also showed a patterned response to theseeding rate of forages in the second growing season. Theweak relationship between seeding rate and plant height inthe 1991 growing season could be a result of differences inthe proportions of mature and immature herbaceous plants.Observation showed that herbaceous vegetation on plotsseeded at higher rates tended to develop more rapidly thanthose at lower rates. It was more likely to have a higherproportion of immature, and, therefore, shorter vegetation,at the lower seeding rates than vegetation at the higherseeding rates. It is anticipated that as the standsdevelop, plant height will show no response to seeding rate,as most of the plants reach maturity, or plant height willbe negatively related to seeding rate due to greaterinterspecific and intraspecific competition associated withhigher seeding rates.Plant production had no linear relationship withseeding rate in either growing season. The relationship ofplant production to seeding rate was probably delayedsimilar to the response of total vegetative cover; the standhad not developed sufficiently to reflect differences inseeding rate. Alternately, other factors, such as63microclimatic variability, and distribution of availablesoil nutrients could mask the influence of seeding rate.5.1.2. Differences in Plant DevelopmentIn most circumstances, seeded treatments producedvegetation with greater height, density, production, andtotal vegetative cover than the control plots with nativevegetation alone. Although native and domestic forbs(clovers) both had a strong initial influence on vegetativecover, the seeded vegetation grew more rapidly than thenative vegetation. This is evident in the contribution tovariability in total vegetative cover by native forbs whichdeclined by a third between the first and second growingseasons. Observation over the two growing seasons, however,showed that, except for lodgepole pine and the nativeshrubs, all of the species observed on the plots (Appendix1) flowered by the fall of 1991. The exact influence oftreatments on reproductive potentials of the variousspecies, however, was not monitored.Native herbaceous plants, although not as advanced indevelopment as the seeded component of the vegetation,contributed 41% of the variability in total vegetative coverin 1990, and 13% of the variability in total vegetativecover in the second growing season. This is indicative oftheir importance in vegetation development, and also is areflection of the uncontrolled distribution of native plantson the research site. The strong presence of the native64forbs in the botanical composition in the first yearindicates that they are rapid in establishing followingdisturbance, although, once established they developsignificantly slower than the domestic species. Plantswhich are included in the native forbs category (Appendix 1)are a mixture of weed or invader species, such as dandelion(Taraxacum officinale L.), and site-specific species, suchas heart leaf arnica (Arnica cordifolia L.).In general, there was very little difference in theearly vegetation dynamics in 1990 among species of foragesown. In the second growing season differences indevelopment were expressed. The clovers developed morerapidly than seeded grasses; clovers produced 50% greatervegetative cover, and 282% greater forage production thanthe seeded grasses in 1991. Thirty-nine percent of thevariability in total vegetative cover in 1990 was due to theclovers, compared to the combined variability of 18%contributed by the orchardgrass and smooth bromegrass.Thirty-one percent of the variability in total cover, and59% of the variability in vegetative cover was accounted forby the clovers during the 1991 growing season. During thissame period the combined contribution of the seeded grasseswas 12% of total cover and 22% of vegetative cover.Of the seeded grasses, orchardgrass was the most rapidin its development. Orchardgrass had 535% greaterproduction than smooth bromegrass in 1990, and smooth brome65had 62% lower density than orchardgrass in 1991. During the1991 growing season smooth bromegrass contributed almost novariability in either total cover or vegetative cover.These data are consistent with generally heldassumptions that alsike clover is rapid in its development,and smooth bromegrass establishes more slowly.5.1.3. Plant Growth and Non-floristic Cover ComponentsThe early development of some the seeded herbaceousplant species, in particular the clovers, was firmlycorrelated to the cover of the non-floristic covercomponents: wood, undecomposed plant litter and bare mineralsoil. The growth and survival of lodgepole pine, however,was not correlated (P>0.05) with any of the non-floristiccover components.Alsike clover had the closest relationship between itsdynamics and the initial cover of the non-floristic covercomponents, in particular the initial cover of wood. All ofthe dynamics parameters (vegetative cover, density, height,and production) on plots sown to alsike clover werepositively correlated with the initial cover of wood onthose plots at some time during the first two growingseasons.Total vegetative cover on plots sown to alsike cloverincreased with increasing cover of wood in both 1990(r2=0.26, P<0.02), and 1991 (r 2=0.18, P<0.06). Density ofvegetation on plots sown to alsike clover was partially66explained by the pure live seeding rate in 1990 (r 2=0.21,P<0.04); however, the inclusion of the initial cover of woodin the correlation model explained 51% more of thevariability in density during this period (R 2=0.72,P<0.001). During the second growing season density ofvegetation on alsike clover plots was not linearly relatedto seeding rate, although, cover of wood explained 36%(P<0.005) of the variability in density. Height ofvegetation on alsike clover plots was also correlated to thecover of bare mineral soil and wood in 1990 (R 2=0.33,P<0.04), and with wood alone (r 2=0.37, P<0.004) in 1991.Production also displayed a positive relationship with thecover of wood; in 1990 it was correlated with litter andwood (R2=0.65, P<0.001) and with wood alone (r2=0.20,P<0.05) in 1991.The association between the vegetation dynamics ofplots sown to alsike clover and the cover of wood on theseplots might be explained by the wood's ability to trapmoisture the surface horizon of the soil immediately beneathit. Alsike clover is known to grow best where soil moistureis abundant (Heath et al. 1973: 157, Walton 1983: 86). Theincremental moisture associated from additional wood couldexplain the increases in vegetative cover, density, heightand production of the alsike clover dominated plots.675.2. Two-Dimensional PartitioningDetermining the influence of treatments on multivariatesystems, where more than one dependent response variable isof interest, has always presented a challenge to find theappropriate statistical analysis. Traditionally, andinappropriately, multivariate data have been divided into aseries of univariate data sets, in which each dependentvariable was analyzed alone with the independent variable(s)by a method such as the univariate analysis of variance(ANOVA). This approach seriously inflates the probabilityof a type I error.Changes in botanical composition, as reflected indifferences in the cover of different species or speciesgroups, is an example of a multivariate system that presentsdifficulties in analyzing the data. Moreover, analysis ofthese data are further complicated because the responsevariables are highly correlated. Stroup and Stubbendieck(1983) cited similar difficulties in analyzing changes inbotanical composition, and suggested the application of themultivariate analysis of variance (MANOVA).Two-dimensional partitioning of variation (TDP)provides another feasible alternative for additivemultivariate data sets. TDP is not just an alternativemethod of computing well-known statistics, it is an extendedframework from which to study multivariate systems and theirrelationships to their components, while simultaneously68determining the effect of treatments on all components. Itprovides the analysis to detect "which treatment effects onyield components are treatment effects on yield" (Eaton etal. 1986).TDP was originally applied to horticulturalapplications in which treatment effects on total plantyield, and the constituent plant parts contributing to yield(yield components) were monitored (Eaton et al. 1986). Itevolved as an extension to sequential yield componentanalysis (Eaton and Kyte 1978) and sequential plant growthanalysis (Jolliffe et al. 1982). It provided the analyticalframework from which to assess how carbohydrate production(total yield) was partitioned among the componentscontributing to yield (e.g. stems, leaves, flowers, fruit),and how treatments influenced the components, and,therefore, ultimately total yield. TDP has also been appliedto data which are transformed into an additive system(Hesketh et al. 1990).TDP is advantageous, in that it utilizes two commonstatistical techniques, linear regression and ANOVA, withresults that are readily interpretable by the researcher.TDP assumes multicollinearity among the dependentvariables being assessed. That is total cover, or totalvegetative cover, is assumed to be the sum of individualcover components. Moreover, the value of the covercomponents is assumed to be influenced directly by the value69of the other components. The first step of TDP is to removethis collinearity through linear multiple regression. Aseach component is added into the multiple regression modelthe variability explained by the regression line is removed,hence, removing any of the codependence contained in thevariables being regressed. The residuals are retained andthe newly orthogonalized variables are then collectivelyregressed against the next unorthogonalized variable enteredin the model. The residual values of the components whichare used in the final multiple regression vary in the sameproportions as the unorthogonalized data. Afterorthogonalization is achieved the data are used to calculatethe amount of variability contributed by each of thedependent response variables by regressing total cover (ortotal vegetative cover) on each of its constituent covercomponent's residuals. The value of the constituent covercomponent's contribution to total variability is equal tothe simple regression coefficient for that variable in themultiple regression model. Alternatively, the covercomponent's contribution can be calculated by the incrementin the partial regression coefficient resulting from addingthe cover component into the multiple regression model.One weakness in the application of the TDP approach toplant dynamics is that the value of the simple regressioncoefficients will vary depending on the order in which thecover components are entered into the multiple regression70model during the orthogonalization procedure. Therefore,the placement of the constituent components in the modelshould have an developmental basis or other biologicalsignificance to guide their ordering. Often the order willnot be readily apparent, and the investigator will have toarrange the variables in groups, or enter them in batches.Care should be taken, therefore, not to place too muchemphasis on the absolute values for a given component'scontribution to total variability if the variables areentered in groups.The second dimension of TDP is a simple analysis ofvariance on each of the cover components. The value fortotal sum of squares is substituted with the percentvariability that the cover component contributes to totalvariability. The proportions between the sum of squares fortreatment and error, and total sum of squares are used tocalculate the ANOVA based on contribution to variability intotal cover (Tables 9 to 12).The power of TDP is in its ability to detect treatmenteffects on components of the multivariate system andsimultaneously compare these responses to the treatmenteffect on the system as a whole. In effect, the variabilityin total cover (or total vegetative cover) is partitionedsuch that the components which are influenced by treatmentcan be identified, and how they in turn contribute to theresponse of total cover to treatment.71In this experiment total cover, or spatial area, waspartitioned into various cover components contributing tothat spatial arrangement. These cover components are abioassay for the general dynamics of the plant population onthe site.TDP is suitable for other applications where treatmenteffects on the components of an additive system, and thesystem as a whole are of interest. For example, total drymatter production of a mixed stand can be attributed to eachof the individual species of plants contributing toproduction.5.3. Lodgepole Pine Growth and Survival5.3.1. Lodgepole Pine Damage and SurvivalThe early conifer survival on this site was notinfluenced by forage seeding. Winter damage on thelodgepole pine induced by rodents was positively related tothe seeding of orchardgrass, although the lodgepole pinesurvival was independent of rodent damage. It is uncertainwhy there was a strong linear relationship betweenorchardgrass vegetative cover and rodent damage on lodgepolepine, and not a similar response with the other foragespecies seeded on the site. It is possible that the rodentsprefered orchardgrass as a source of visual cover and food.725.3.2. Lodgepole Pine GrowthLodgepole pine height and basal diameter growth wereunaffected by the orchardgrass, smooth bromegrass, alsikeclover, and the forage mixture seeding treatments.Lodgepole pine seedlings were overtopped by all seededvegetation in the second growing season; however, theyremained taller than the native vegetation controls duringboth growing seasons. The height of the herbaceousvegetation possibly influenced the competition for light onthe site. One possible expression of the competition forlight was in the ratio of lodgepole pine unit needle mass atthe end of the second growing season to the unit needle massat the beginning of the second growing season. Unit needlemass growth ratio for lodgepole pine with competingvegetation increased slightly, while lodgepole pine with nocompetition had, on average, only two-thirds the unit needlemass at the end of the growing season that they had at thebeginning of the growing season. These data contradict theassumption that competing vegetation should decrease needlemass.Height of lodgepole pine with surrounding vegetationwas on average 14% shorter than conifers with no competitionat the end of the second growing season. There were nodifferences in the height growth of lodgepole pine, however,due to species of forage sown, nor were there differenceexpressed between seeded and native vegetation. Even though73there were significant differences in the density, height,production, and cover of vegetation surrounding thelodgepole pine, these differences in surrounding vegetationwere not manifested in differences in tree growth.Moreover, these differences in vegetation surrounding thelodgepole pine did not effect the ratio of needle massesover the second growing season. This contradicts thefindings of Trowbridge and Holl (1992) who reported theneedle mass of lodgepole pine two years after planting andseeded with alsike clover was less (P<0.05) than plots withnative vegetation alone.Conifer basal diameter growth was also unaffected bythe seeding rate of forages. In the second growing season(1991) there were very weak linear relationships betweendecreases in the growth of basal diameter and increasingseeding rate.Both conifer height growth and basal diameter growthwere negatively correlated to vegetation production in 1990on plots sown to orchardgrass, and positively associatedwith increases in density and vegetative cover on plots sownto alsike clover in 1991. No explanation as to why thesevariable combinations were of importance was determined.745.4. Management RecommendationsThese data indicate that forage species selection andseeding rate will not greatly influence the very earlygrowth and survival of planted lodgepole pine in the VeryDry, Cool Montane Spruce biogeoclimatic subzone, and shouldnot impede the Ministry of Forests objective of achieving aminimum lodgepole pine stocking rate of 1100 stems/ha, 12 -15 years after planting. These results, however, give noindication of the medium and long-term influence of forageseeding on lodgepole pine growth and survival, and must beconsidered within the context of the whole process fromplanting of conifers and the seeding of forages to the free-to-grow stage in the lodgepole pine.If rodent damage is of concern, eliminatingorchardgrass from operational seeding should be considered;rodent damage was positively associated with the vegetativecover of orchardgrass. Reduction of the seeding rate oforchardgrass or a decreased percent composition in theseeding mix should also reduce the potential for rodentinduced damage on the conifers.Concurrent planting of conifers and seeding of forageshas produced favourable results. It is conjectured thatplanting conifers into an established forage stand wouldhave resulted in lower survival and lower growth rates inthe lodgepole pine.756. Literature CitedAnderson, C.H., and C.R. Elliot. 1957. Studies on theestablishment of cultivated grasses and legumes onburned-over land in northern Canada. Can. J. Plant Sci.37:97-101.Association of Official Seed Analysts. 1978. Rules fortesting seeds. J. Seed Technol. 3:29-35, 39-40, 49-50.Baron, F.J. 1962. Effects of different grasses on ponderosapine seedling establishment. U.S.D.A. Forest Serv.,Res. Note PSW-199.Bergerud, W. 1989. ANOVA: Factorial designs with a separatecontrol. Biometrics Information Pamphlet No. 14,B.C. Minist. of Forests Lands, Victoria, B.C.Berglund, E.R. 1976. Seeding to control erosion along forestroads. Ext. Circ. No. 885. Oreg. St. Univ., Corvallis,Oreg.Brooke, B.M. and F.B. Holl. 1988. Establishment of winterversus spring aerial seedings of domestic grasses andlegumes on logged winter sites. J. Range Manage.41:53-57.Carr, W.W. 1980. A handbook for forest roadside erosioncontrol in British Columbia. Land Manage. Report No. 4,B.C. Minist. of Forests, Victoria, B.C.Christ, J.H. 1934. Reseeding burned-over lands in northernIdaho. Agr. Exp. Sta. Bull. No. 201. Univ. Idaho,Moscow, Idaho.Clark, M.B., and A. McLean. 1975. Growth of lodgepole pineseedlings in competition with different densities ofgrass. B.C. Forest. Serv., Res. Note 70, Victoria, B.C.Clark, M.B., and A. McLean. 1979. Growth of lodgepole pinein competition with grass. B.C. Forest Serv., Res. Note86, Victoria, B.C.Daubenmire, R. 1959. A canopy coverage method ofvegetational analysis. Northwest Sci. 33:43-64.Eaton, G.W., P.A. Bowen, and P.A. Jolliffe. 1986. Two-dimensional partitioning of yield variation. HortSci.21:1052-1053.76Eaton, G.W., and T.R. Kyte. 1978. Yield component analysisin the cranberry. J. Amer. Soc. Sci. 103:578-583.Eddleman, L. and A. McLean. 1969. Herbage - its productionand use within the coniferous forest. Pages 179-196 inConiferous forests of the northern rocky mountains:Proc. of the 1968 symp. Centre for Natur. Resour.,Univ. Mont., Missoula, Mont.Eissenstat, D.M. 1980. Water competition and animal damagein a grass seeded Douglas-fir plantation. M.Sc. Thesis.Univ. of Idaho, Moscow, Idaho.Eissenstat, D.M., and J.E. Mitchell. 1983. Effects ofseeding grass and clover on growth and water potentialof Douglas-fir seedlings. Forest Sci. 29:166-179.Elliot, K.J., and A.S. White. 1987. Competitive effects ofvarious grasses and forbs on ponderosa pine seedlings.Forest Sci. 33(2):156-166.Heath, M.E., D.S. Metcalfe, and R.E. Barnes. 1973. Forages:The science of grassland agriculture. Iowa St. Univ.Press, Ames, Iowa.Hesketh, J.L., G.W. Eaton, and T.E. Baumann. 1990.Strawberry plant spacing on raised beds. Fruit Var. J.44:12-17.Hope, G.D., W.R. Mitchell, D.A. Lloyd, W.L. Harper, and B.M.Wikeem. 1991. Montane spruce zone. Pages 183-194 in D.Meidinger, and J. Pojar, eds. Ecosystems of BritishColumbia. Research Branch, B.C. Ministr. Forest,Victoria, B.C.Jolliffe, P.A., G.W. Eaton, and J. Lovett Doust. 1982.Sequential analysis of plant growth. New Phytologist92:287-296.Klinger, G.E. 1986. Effects of grass legume competition onshrub and hardwood invasion in newly harvested clear-cuts. M.Sc. Thesis (Forest Resour.), Univ. Wash.,Pullman, Wash.Klock, G.O., A.R. Tiedemann, and W. Lopushinsky. 1975.Seeding recommendations for disturbed mountain slopesin north-central Washington. Res. Note PNW-244.U.S.D.A. Forest Serv.77Krueger, W.C. 1983. Cattle grazing in managed forests. Pages24-41, in B.F. Roche Jr., and D.M. Baumgartner, eds.Forestland grazing. Wash. St. Univ., Pullman, Wash.McLean, A., and A.H. Bawtree. 1971. Seeding forest rangelandin British Columbia. Can. Dept. of Agr. Pub. No. 1463,Ottawa, Ont.McLean, A., and M.B. Clark. 1980. Grass, trees and cattle onclear-cut logged areas. J. Range Manage. 33:213-217.Newman, R., M.D. Pitt, D. Quinton, B. Wikeem, and P. Youwe.1989. The effects of cattle grazing, forage seeding,basal scarring and leader damage on forestregeneration. Working plan. B.C. Minist. Forest,Intern. Rep., Kamloops, B.C.Nordstrom, L.O. 1984. The ecology and management of forestrange in British Columbia: A review and analysis. B.C.Forest Serv., Land Manage. Rep. 19. Victoria, B.C.Pickford, G.D., and E.R. Jackman. 1944. Reseeding easternOregon summer ranges. Circ. No. 159, Agr. Expt. Stat.,Oreg. St. College, Corvallis, Oreg.Pitt, M.D. 1989. Integrated Forest/Range Research Five YearPlan. Forest. Can. and B.C. Minist. Forest, Joint pub.Governments of Can. and B.C., Victoria, B.C.Pringle, W.L., and A. McLean. 1962. Seeding forest ranges inthe dry belt of British Columbia. Can. Dept. Agr. Pub.No. 1147, Ottawa, Ont.Quinton, D.A. 1984. Cattle diets on seeded clear-cut areasin central interior British Columbia. J. Range Manage.37:349-352.Silvertown, J. 1987. Introduction to plant populationecology. John Wiley and Sons, Inc., New York.Squire, R.D. 1977. Interacting effects of grass competition,fertilizing and cultivation on the early growth ofPinus radiata, D. Don. Aust. Forest Res. 7:247-252.Stroup, W.W., and J. Stubbendieck. 1983. Multivariatestatistical methods to determine changes in botanicalcomposition. J. Range Manage. 36:208-212.Sullivan, T.P., and D.S. Sullivan. 1984. Influence of rangeseeding on rodent populations in the interior ofBritish Columbia. J. Range Manage. 37:163-165.78Trowbridge, R., and F.B. Boll. 1992. Early growth oflodgepole pine after establishment of alsike clover-Rhizobium nitrogen-fixing symbiosis. Can J. Forest Res.(in press).Walton P.D. 1983. Production and management of cultivatedforages. Reston Publishing Co., Reston, Virginia.79Appendix 1. Cover Categories for Two-DimesionalPartitioning.Cover category^Code Cover componentsLitter/woodSoilSmooth bromegrassOrchardgrassCloversNative graminoidsNative forbsNative shrubsLTWD Undecomposed leaf litter, humus.Wood.SOIL Bare mineral soil.BRIN Bromus inermus Leys.DAGL Dactylis glomerata L.TRSP Trifolium hybridum L.Trifolium repens L.GRAS Calamagrostis rubescens Buckl.Carix richardsonii L.Luzula hitchcockii Hamet-AhtiFORB Arnica cordifolia Hook.Cornus canadensis L.Epilobium angustifolium L.Epilobium paniculatum Nutt.Equisetum scirpoides Michx.Petasites palmatus (Ait.) Cronq.Taraxacum officinale WeberSHRB Arctostaphylos uva-ursi L.Linnaea borealis L.Lonicera involucrataVaccinium scoparium LeibergRibes lacustre (Pers.) Poir.80Appendix 2.^Weather Summary for Tunkwa Lake Research^Site^in^1990 and^1991.Weather Data^1990SOIL TEMPERATURE^(C) SOIL MOISTURE^(EARS)2.5cm^10.0cm AIR^TEMP^(C)^2.5cm^10.0cmDATE^MAX^MIN^MAX^MIN^MAX^MIN^MAX^MIN^MAX^!INPREO:F.(mm)24-Apr 10.4 0.8 10.4 2.5 10.2 -2.4 15.00 )15.30 •:15.11 ;15.00 :1.025-Apr 0.8 1.0 2.7 1.1 2.4 -3.5 1.55 '15.00 1,26 .., 15.00 6.026-Apr 4.1 0.2 1.8 0.2 4.3 -3.6 1.85 2.00 1.55 1.67 2.327-Apr 1.4 -0,1 1.4 0.7 2.3 -6.2 1.88 2.08 1.56 1,67 1^r!i28-Apr 0.8 0.1 0.8 0.6 0.7 -5.1 1.92 2.01 1.57 1,51 1.029-Apr 5.8 -0.1 1.6 0.4 3.9 -4.5 1.85 2.06 1.54 1.55 1.030-Apr 10.8 0.0 3.1 0.6 12.1 0.2 1.72 2.04 1.49 1.64 0.101-May 7.4 1.6 3.7 1.9 7.6 2.6 1.74 1.88 1.49 1.57 2.002-May 12.1 2.1 5.3 2.6 11.9 1.6 1.66 1.84 1.46 1.54 LO03-May 9.6 2.3 5.3 3.2 12.6 1.5 1.72 1.85 1.49 1.55 1.004-May 16.8 2.3 7.8 3.5 19,8 3.1 1.62 1.87 1,45 1.57 0.005-May 14.9 4.1 7.9 5,1 19.9 0.9 1,67 1.88 1.50 1.59 0.006-May 9.3 1.2 6,6 3.6 4.7 -3.8 1.84 2.02 1.59 1.69 0.007-May 8.3 1.4 4.5 3.1 4.1 -3.9 1.83 2.03 1.64 1,73 1.008-May 13.8 1.2 5.8 2.7 9.9 -1.6 1.72 1.99 1.56 1.70 2.009-May 10.4 2.6 5.6 3.7 10.8 1.8 1.78 1.93 1.57 1.64 0.010-May 10.5 3.7 5.9 4.3 10,1 1.0 1.75 1,91 1.55 1.63 2.011-May 10.7 2.7 5.8 4.0 8.5 1.1 1.72 1.87 1.54 1.60 1.012-May 9.3 2.1 5.5 3.9 7.3 0.1 1.77 1.90 1.55 1.61 0.013-May 6.9 2.2 5.0 3.8 4.6 -0.4 1.74 1.90 1.52 1.62 5.014-May 10.1 1.7 5.3 3.1 8.4 0.0 1.68 1.85 1.45 1.54 3.015-May 11.3 1.6 5.9 3.2 11.4 1.6 1.71 1.88 1.45 1.53 1.316-May 10.8 1.9 5.8 3.7 3.5 0.4 1.71 1.88 1.45 1.53 2.017-May 9.7 3.0 5.5 4.3 8.5 1.0 1.67 1.79 1.40 1.47 6.018-May 11.3 3.0 6.2 4.1 8.4 0.5 1.65 1.79 1.37 1.42 3.019-May 11.5 2.0 6.3 3.9 12.0 -0.7 1.66 1.84 1.37 1.43 1.020-May 6.6 2.2 5.8 4.2 5.3 -0.6 1.68 1.83 1.33 1.44 8.021-May 11.5 1.2 6.3 3.2 11.6 -1.6 1.64 1.87 1,37 1.44 0322-May 7.9 3.4 5.8 4.7 6.5 1.0 1.69 1.79 1.40 1.44 2.023-May 10.7 1.5 5.8 3.8 8.7 -1.9 1.68 1.88 1.37 1.48 7.024-May 6.7 3.4 5.0 4.3 4.2 0.9 1.67 1.75 1.30 1.39 11.025-May 8.0 3.0 5.1 4.2 4.6 1.3 1.68 1.79 1.36 1.40 8.026-May 11.2 2.8 6.4 4.4 11.6 0.6 1.66 1.82 1.36 1.43 1.027-May 10.8 4.7 6.9 5.3 12.4 5.6 1.68 1.80 1.43 1.48 3.028-May 10.6 6.6 7.3 6.2 9.9 4.8 1.64 1.73 1.33 1.46 1.029-May 11.7 5.8 7.6 6.2 10.3 3,7 1.61 1.74 1.31 1.38 2.030-May 15.2 3.3 8.2 5.7 14.0 0.6 1.63 1.82 1.38 1.4831-May 9.7 4.0 7.5 6.1 9,9 1.5 1.68 1.85 1,43 1.51 7.001-Jun 10,9 2.9 7.2 5.3 10.9 0.3 1^71 1.85 1.47 1.52 ni.002-Jun 13.3 5.1 8.0 6.1 13.5 3.6 1.68 1.83 1,47 1.52 2,253-Jun 9.9 4.9 7.3 6,: 9.9 3.2 1.73 1.85 1.48 1.53 4.1'04-Ln 10.4 3.4 6.9 5.4 8.1 0.6 1.76 1.90 1,50 1.54 „.005-Jun 11.4 1.9 4.7 12.8 -2.2 1.75 1.97 1.51 1.5936-Jun 11.0 2.6 7,3 5.1 12.2 1,6 1.65 1.95 1.48 1.59 7.fl37-Jun 17.0 3.7 8,6 5.6 11.3 1.5 1.67 1.88 1.45 1.53 1.281Weather Data 1990SOIL TEMPERATURE^;ID)2.5cm^10.0cm TEN?^2'SOIL MOISTURE^BARS)2.5cm^10.3cmDATE MAX MIN MAX MIN MAX M:N MAX MIN MAX MIN emm;08-Jun 10.0 3.1 7.4 5.6 9.9 - 1 . 73 1.92 1.51 :.so ^39-Jun 10.6 4.6 7.6 5.9 10.9 ,^; 1.62 1.90 2 37 1.56 !I10- 1 un 8.5 4.0 7,4 6.3 6.3 3.8 1.54 1.74 1.33 1.2911-Jun 5.3 2.7 6.3 4.9 7.2 1,71 1.80 1.37 1.50 6.311-Jun 7.8 2.9 5.6 4.8 3.6 1.3 1.59 1.84 1.24 1.43 7.012-Jun 15,4 4.6 6.0 5.3 13.2 1.5 1.61 1.79 1 .01 1.4114-jun 5.9 5.5 9.9 5.5 16.9 4.1 1.56 1.81 1.40 1.4615-Jun 18.7 7.1 10.6 7.7 19.0 9.2 1.61 1.80 1.42 1.19 0.016-Jun 15.2 8.5 9.9 8.5 13.0 6.4 1.53 1.78 1.30 1.45 19.217-Jun 19.2 6.2 10.5 7.6 17.5 4.5 1.49 1.67 1.27 1.38 0.010-Jun 13.8 8.2 9.9 8,5 13.6 5.4 1.55 1.69 1.36 1.44 7.319-jun 14.2 7.2 9.8 8.1 13.8 6.1 1.58 1.69 1.39 1.44 0.020-Jun 15.6 7.8 10.3 8.4 15,6 6,0 1.58 1.72 1.41 1.46 0.021-Jun 21.4 7.1 12.2 8.5 20.9 6.0 1.53 1.75 1,39 1,48 0.022-Jun 20.1 9.3 12.7 10.1 25.2 10.7 1.58 1.72 1.40 1.47 1.023-dun 19.0 10.1 12.9 10.6 21.5 9.4 1.60 1.74 1.44 1.49 0.024-Jun 17.5 9.1 12.4 10.5 19.7 7.9 1.66 1.80 1.49 1.54 0.025-Jun 17.2 8.5 12.2 10.3 17.9 7.4 1.71 1.88 1.54 1.61 0.026-Jun 17,0 7.9 12.0 9.9 17.0 5.2 1.73 1.93 1.61 1.67 0.027-Jun 16.3 7.3 11.7 9.7 17.0 4.3 1.84 2.01 1.67 1.71 0.028-jun 16.0 8.4 11.4 3.8 15.9 5.0 1.90 2.08 1.71 1.76 0.029-Jun 16.1 7.6 11.7 9.5 18.8 4.3 1.95 2.11 1.75 1.80 0.030-Jun 17,4 9.5 12.1 10.3 16.7 6.0 2.00 2.22 1.78 1.84 0.001-jui 17.2 7.8 12.0 9.7 15.2 4,6 2.08 2.29 1.84 1.89 0.082-Jul 11.8 8.2 11.4 10,0 8.2 3.1 1.82 2.27 1.84 1.90 8.323-Jul 12,3 6.2 10.1 8,6 13.6 2.5 1.82 1.97 1.82 1.89 0.034-Jul 16.6 6.7 11.5 8,6 19.4 4.3 1.81 1.99 1.78 1.87 3.005-Jul 15.5 8.5 11.5 9.9 18.7 6.3 1.84 2.01 1,77 1,84 4.036-Jul 11.2 9.1 11.0 9.8 7.8 5.0 1.58 1.85 1.43 1.78 37.027-Jul 14.8 8.8 11.0 9.3 15,8 4.6 1.64 1.76 1.39 1.44 0.005-Jul 16.0 8.3 11.9 9.7 20.4 5.8 1.59 1.72 1.39 1.44 0,039-Jul 10.5 8.9 12.4 10.2 21.3 6.7 1.60 1.72 1.42 1.46 0.10-Jul 20.1 9.6 13.6 10.7 26.2 8,7 1.59 1.73 1.44 1.48 0.011-Jul 21.2 11.1 14.3 11.8 27.7 12,7 1,63 1.74 1.47 1.52 0.012-Jul 21.1 12.9 14.6 12.6 25.8 12,5 1.64 1.80 1.52 1.5813-Jul 19.3 10.3 14.0 12.1 21.9 8.6 1.79 1.92 1.58 1.66 7814-Jul 19.9 10.0 14.0 11.9 22.3 10.7 1.88 2.06 1.66 1.76 0.515-Jul 20.7 9.6 14.1 11.7 24.2 9.4 2.01 2.29 1.76 1.85 0.016-Jul 18.6 10.8 13.6 12.1 19.7 8.7 2.29 2.85 1.84 1.9517-Jul 15.4 8.9 12.9 11.3 16.6 7.2 2.85 3.44 1.95 2.31 0.018-Jul 14.9 8.4 12.0 10.7 16.2 5.2 3.44 4.26 2,01 2.0819-Jul 17.6 8.9 12.6 10.6 18.5 7.7 4.27 5.91 2.38 2.21 "13-Jul 19.6 8.1 13.1 10.4 20.6 6.9 5.93 9.16 2.21 2 .73 0.021-Jul 18.1 8.6 13.0 10.7 23.9 8.5 9.16 14.22 2.73 4.87 2.212-Jul 21.3 9.8 14.0 11.2 25.8 10.5 14.19 24.61 4.88 12.9423-Jul 16.2 11.7 13.3 12.2 20.3 10,3 2.25 27.38 12.94 20.93 8.024-Jul 13.4 13. 7 12.3 11.4 13.6 7.3 1.98 2.26 11.78 20.13 '25-Jul 17.4 10.9 14.3 11.1 20.8 8.7 1.55 2.01 2.14 11.78 2582Weather Data 1990DATE5013 TEMPERATURE2.5cm^10.0cmMAX^MIN^MAX^!INAIR^TEMP^r.,1)MAX^MIN2.5cmMAX^KM(3A53MAX^mIN26-Jul 18.4 11.7 13.9 12.0 22.6 21 . 1 •^7_. 7: :. 1.90 ..36 314 , .,,..,27-Jul 17.6 11.1 13.5 12.1 19,9 10.2 1.97 2.08 1.97 2,10 3128-jui 18.7 9.8 12.6 11.5 22.4 in^I.,.. 2.04 2.22 2.03 ,^,,..,'' 7a29-31 19,4 1.9 12.9 11,6 24.9 :2 . 2 2.13 2.39 312 11120-3131..jc-..15.81Q^;.,.,12,11 ,1^7,,,-12.911^,...::2.2.,., .-=.:25 . 721 . 3:1.6 7.42.39,,^.,, ,,..2! 2.56 2.23,...,.•,01-Ag 15.2 :.5 14.1 12.4 21.4 11.6 2.45 2.31 2.27 2.72 8.812-Lg13-Aug15.515.99.8G.413.3 11.6.,^I...-:20.221.73,79.7 3.923126.382,81 2.784,594,5315^101.8,.004-Aug 20,1 9.3 131 11.4 25.4 9.6 6.38 12.36 '15.11:318 3.305-Aug 19.9 11. 7 14.3 :2.3 97^^:,:.:. 14.1 12.36 )15.00 )15.08 .'15.10 1.016-Aug 21.5 12.3 14.5 12.5 22.1 11.3 )15.00 )15.00 )15.10 15.18 2. 307-Aug 20.2 9.7 14.2 11.9 23.7 6.5 )15.00 )15.00 )15.00 )15.00 0.1OF-Aug 21.9 9.9 14,6 11.9 25.7 9.4 )15.00 )15.00 )15.00 '.15.00 0.009-Aug 23.1 10.5 15.0 12.1  25 . 8Q 13.1 )15,00 )15,00 )15.00 )15,01 0.010-Aug 23.2 11.7 15.5 12.6 26.4 15.9 115,00 )15.00 )15.10 )15.00 0.011-Aug 22.8 12.8 15.6 13,1 26.0 13.6 )15.00 )15.01 )15.00 )15,00 0.012-Aug 23,9 12 16.0 17 27.1 13.1 )15.00 15,00 )15.00 ', 15,00 0.013-Aug 23.4 13,1 16.1 13.6 25,7 13.4 )15.00 )15.00 )15.00 )15.00 0.0I4-Aug 23.5 10.5 15.6 12.9 24.1 7.5 )15.00 )15,00 ,15.00 15.00 0.025-Aug 23.5 11.3 15.6 12.7 22.6 10.7 )15.00 )15,00 )15.00 )15.00 0.016-Aug 16.2 11.2 14,4 12.7 16,7 8.5 )15.00 )15.00 )15.00 )15.00 0.017-Aug 17.5 8.8 13.2 11.7 18.6 6.9 )15.00 )15.00 ,15,00 ',15.00 5.018-Aug 15.7 3.9 12.5 11.3 15.6 5.5 )15.10 115,00 )15.00 )15.00 5.019-Aug 20.2 8.7 13.7 10.8 20.6 7.3 5.38 )15.00 :15.00 )15.00 0.020-Aug 21.6 11.9 14.6 12.1 24.2 15.2 4.33 5.61 15.0,1 )15.00 0.021-Aug 16.8 12.6 14.0 12.8 19,3 8.5 4.63 5.28 )15.00 )15.00 4.022-Aug 17.8 9,1 13.5 12.0 16.3 3,0 2.61 4.63 )15.00 115.01 3.323-Aug 11.6 6.1 12.1 10.1 10.0 1.3 2.47 2.70 )15.00 )15.21 1.024-Aug 12.0 5.9 10.4 9.0 10.8 2.1 2.24 2.63 )15.00 '15.00 1,025-Aug 9.7 6.4 9.8 8.7 6.4 1.5 1.93 2.41 )15.10 :'15,00 5.026-Aug 10.8 5.8 9.5 8.2 11.5 1.3 2.05 2.23 )15,00 )15,00 1.127-Aug 16.2 4.8 10.9 7.8 16.9 1.3 2.12 2.42 )15.00 )15,10 0.128-Aug 17,0 6.4 11.5 8.7 19.7 5.6 2.29 2.54 13.43 ., 15.00 0.029-Aug 13.3 8.5 10.7 9.7 15.8 5.6 2.47 2.61 11.93 13.43 4.030-Aug 14.2 7.4 10.7 9.2 13.6 4.3 2,34 2.52 10.88 11.99 1.131-Aug 14.6 6.6 10.6 8.9 13.0 9^PL.,. 2.41 2.64 10.33 11.92 1^'i.J01-Sep 13.4 6.0 10.1 5.5 13.8 3.1 2.51 2.73 10.65 11.17 8.102-Sep 13.5 5.0 10.2 8.0 15.1 7 . Q.v 2.58 2.86 11.17 1318 0.803-Sep 15.8 5.1 10.4 8,1 14.3 4.2 2.64 3.01 11.78 14.14 8,104-Sep 17.1 3.7 10.5 7 . 1:, 28.4 1.4 2.78 3.22 14.14 -15.00 0.005-Sep 18.5 5.6 11.3 8.3 i2.H 6.2 3.22 4.47 '21510 -15.01 0.116-Sep 19.5 7.3 11.9 9,1 22.4 7.1 4.51 11.30 )15,18 )15.11 8.187-Sep 20.1 7,9 12.3 1.5 23.9 9,3 11.38 15.03 1502 15.00 3.018-Sep 317 9.7 12.3 18,4 22.9 12.8 )15.10 )15.00 . , 15.00 )15.11 0.019-Sep 19.5 7.8 12,5 .L, , .I.,' 8^' 22^2iii...... 6 . 8 '15 . 33 )15.00 )15.01 )15,10 8^11-Sep 21.1 31 12.6 9.9 23.3 31 15.00 15.00 :, 15.00 15.3C:1-3 ,.q, 19.9 7,5 12.5 9,8 22 222.2 3.4 )15,00 )15.00 )15.01 -'15.12 r,^n.vWeather Data 1990SOIL TEMPERATURE^(C)2.5cm^10.0cm AIR TEE?^(C;SOIL^!1.IST7RE^;EARS)2.5cm 10.0cmPRECIP.DATE MAX MIN MAX !IN !AX !IN !AX !IN !AX !IN (mm)12-Sep 14.7 6.9 11.5 .0.1 1.1 15,33 11,31 .;-15.01 )15,11 0.013-Sep 18.2 5.1 11.3 3.5 19.6 .,1 .;15.00 0.311-Sep 18.9 5,7 11.5 8.6 21.1 4.9 :'15.00 ,15.55 )15.01 5.115-Sep 15,7 7,1 13.9 c 18.6 7.3 :..15,03 15.00 3.016-Sep 11,4 7.4 10,2 9.3 10.5 4.9 15.11 :1571 ., , 1505 )15,001-Sep 13,4 5.1 9.8 3.1 :6.8 2 .5 )15.03 15.30 :15.00 ::.15,00 0,018-Sep 15.1 8.5 11.4 8,2 16,6 6,4 . ,15.10 )15.10 .15,15 1.5.10 3,319-Sep 15.9 5.6 10,2 8.3 12.9 „.. :, 15.00 )15.30 .„.15.50 15.73 ii20-Sep 16.5 4.1 11.3 7.5 17.0 6,0 )15,0021-Sep 18.3 7.9 11.3 8.9 18,6 7 . ' •15.00 ..,15.05 )15.33 7L022-Sep 18.3 7.5 11.4 8,9 22.4 7^,,. :,15.00 1.5.00 15.1.1 0.023-Sep 19,6 8.4 12.1 8.5 22.5 10.9 . ,15.00 ?15.00 .15.50 )15.07 3.324-Sep 18.6 7.6 11.9 9.5 23.5 7.5 )15.00 15.130 >15.00 )15.00 0.025-Sep 17.3 6.7 11.5 9.4 16.5 6.7 . ,15.00 :15.00 )15.00 )15,00 0,026-Sep 16.1 3.4 10.3 7.8 17.1 1.6 )15.00 )15.00 )15.00 )15.01 0.027-Sep 15.2 2.7 9.7 7.1 16.8 3.9 15.00 )15.00 15.00 15.00 0.028-Sep 11.2 5.9 9.2 7.8 16.1 8.8 15.00 )15.00 )15.00 0.029-Sep 12.6 5.3 9.3 8.2 11.2 1.3 )15.00 )15.00 )15.00 )15.00 0.030-Sep 12.9 2.9 8.9 6.8 13.3 -5.1 -215.10 '15.00 )15.10 )15.00 0.034Weather Data 1991SOIL TEFERATUE IC)^ SOIL M0I37788 (BA33)DATE2.5cmMAX^MIN^10.3cm^Al9^TEMPMAX^MIN^MAX 471i2.5cmMAX^MIN10.GcmMAX^!IN15-May 12.3 2.2 7.3 3.6 12,2 15.32 15.30 ., 15.0016-May 10,8 1.9 6.8 2.4 11.6 0.7 15.00 )15.00 15.00 . , 15.0017-May 9.1 2.6 5.5 3,3 4,,^,,.„,., 1.6 15.05 15.00 15,00 15.0218-May 7.8 4.4 6.0 4.5 10.5 4.3 .15.20 !15.00 ,-15,90 15.2013-May :2.4 4.9 8.4 ;^.,,,..:... 17.F 6.6 )15.93 15.00 15.10 , 15.0120-May 14.4 6.7 9.9 5.4 19.5 8,5 )15.00 :, 15.00 715.90 15.0021-May 16.5 4.2 11.2 4.3 19.4 5,9 15.00 15.30 15.33 'H15.032-May 12.4 5,1 2.5 6,4 3, 7 15.00 .15.00 15 . 30 15.2023-May 8.4 3.' " ;^.r,.i,, 72. -0,8 )15.00 )5.00 1,.5.00 f,15.0324-May :0.5 3.3 7.1 4.3 9.9 -1.6 :, 15.00 15.00 )15.00 ':15.3025-May 9.9 3.7 7.3 4.6 8.0 -0.6 0.45 )15.00 0.35 . 15.0026-May 6.9 2.6 5.3 2.7 8.2 -1.1 0.45 0.48 3 . 35 0.3727-May 9.3 2.3 6.5 3.5 9.4 -0.1 0.46 0.50 0.35 0.3728-May 11.7 2.5 7.6 3.9 12.3 1.5 0.45 0.49 3.35 3.3629-May 13.1 3.3 8.9 4.6 15.2 1.7 0.45 0.48 3.35 3.3520-May 12.0 3.3 8.1 4.9 13.3 1.2 0.44 0.48 2.34 0.3521-May 13.3 5.3 8.9 6.0 12.5 2.9 0.44 0.47 0.34 3.3531-Jun 15.1 3.7 10.0 5.3 14.5 2,0 0.43 0.47 0.34 0.3502-Jun 15.9 4.3 10.6 5.9 15.3 1.3 0.44 0.47 0.34 0.3523-Jun 12.8 4.5 2.3 6.7 11.7 -0.2 0.45 0.48 0.35 0.3504-Jun :1.1 3.3 7.5 5.1 7^!);A: -1.1 0.46 0.50 0.35 0.3635-Jun 8.2 2.9 6.6 4.6 7.9 -1.7 0.47 0.49 0,35 0.3606-Jun 14.6 3.1 9.6 4.6 15.4 2.2 0.45 0.49 ,)^1;v.,.., 0.3607-Jun 12.8 5.6 2.3 6.5 16.2 6.9 0.45 0.48 0.35 0.3635-Jun 11.2 6.2 9.1 7.0 13.1 5.6 0.45 0.48 0.35 0.3602-Jun 13.8 6.3 9.4 6.9 13.9 4.9 0.45 0.46 0.35 0.3510-Jun 17.7 5.5 11.8 6.7 19.6 3.9 0.45 0.48 0.35 0.3611-Jun 14.2 3.3 10.9 8.8 15.6 6.3 0.46 0.48 0.35 0.3612-Jun 14.4 6.0 10.0 7.7 10.5 0.8 0.45 0.50 0.35 0.3513-Jun 11.3 4.8 8.5 6.5 8.3 0.5 0.47 0.51 0.36 0.3714-Jun 13.7 4.5 8.8 6.1 10.5 0.6 0.46 0.50 0.36 0.3715-Jun 9.8 4.7 7.9 6.0 8.5 1.2 0.48 0.50 0.36 0.3716-Jun 12.0 4.3 8.5 5.7 11.3 0.4 0.48 0.51 0.36 0.3717-Jun 9.8 4.4 7.6 5.6 5.3 0.4 0.45 0.51 3,05 0.3718-Jun 11.4 4.6 8.4 5.7 12.5 1.9 0.45 0.48 0.35 0.3719-Jun 14.6 4.9 9.5 6.1 12.6 1.7 0.45 0.48 0.35 0.3720-Jun 17.3 5.3 11.6 6.6 17.7 5.3 0.44 0.48 0,35 3,3521-Jun 11.9 7.6 9.7 8.3 12.1 5.3 0.44 0.47 0.35 1.3422-Jun 12.2 7.6 9.9 8.2 12.2 5.3 0.44 0.46 0,35 0.3623-Jun 13.4 8.1 10.5 8.4 11.0 4.9 0.43 0.45 0.34 3,2524-Jun 13.3 8.0 10.5 8.5 11.7 4.9 0.43 0.45 3.34 0.2525-Jun 13.6 7.4 :0.7 8.3 13.7 5.6 0.43 0,45 3.34 0.3526-Jun 14.4 7.3 10.5 5.0 14.1 5.7 0.43 3.45 0,34 0.3527-Jun 13.7 7.5 10.9 8.2 13.3 4,3 0.43 0.45 0.34 0.3528-Jun 15,7 7.1 11.7 8.2 17.0 4.3 0.43 0.46 0.34 P^1;v.v.,9-Jun 18.5 7.7 13.4 8.7 20.8 6,0 0.43 0.45 3.3430-1un 15.4 10.3 13.6 10.2 23.1 8,7 0.43 0.45 0.34 3.353.00n .nn,J,;4,033.000.000.003.335.007.004.0013.007.000.001.003.001.000.000.000.000.000.000.000.000.003.301.000.000.001.303.000.000.008.000.002,900,333.0011.004.0C20.003.0024.005.003.000.205.301.35„.",85Weather Data^1991SOIL TEMPERATHE (C)2.5cm^10.0cm AIR TEMP cSOIL MOISTLIRE^(BARS)2.5cmPRECIPDATE MAX MIN MAX !IN MAX MIN MAX MIN MAX M:N mic)01-Jul 15.0 9.4 12.1 15.1 15.9 6.6 0.43 1.45 0.34 0.35 1.0002-Jul 19.4 7.8 14.1 9.2 2•,7 K 0.43 3,45 5.34 0.35 3.0003-4ul 20,1 9.3 14.7 13.7 23. 8.4 3.43 0.45 1.34 0.35 0.5034-Jul 20,3 10.5 15.2 11.3 22.9 2. 7 3.44 0,46 0.35 0.3535-Jul 19.8 10.7 15.1 11.6 20.3 10.6 0.44 0.48 1.35 0.35 0.0006-jl 15.8 9,7 13.1 11.2 14.3 3.5 0.46 0.48 0.35 0.36 0.0057-jul 121 5. 11.3 9.8 9.9 1.1 0,47 0,49 1.35 5.36 1. 30jti35-Jul 17.3 7,4 13.1 1.9 19.4 3.1 0.46 0.49 0.35 0.37 0,0309-jui 16.2 9.0 14.1 10.1 22.3 8.5 0.47 0.54 0.35 0.36 0.0531-Jul 17.9 9.9 13.8 10.9 21.0 9.4 0.52 0.68 0.35 0.36 0.00.--Jul 18.3 11.2 14.1 11.5 21.9 10.1 0.62 0.97 0.34 0.36 2.3012-Jul 17.5 13.4 14.1 11.2 19.1 8.8 0.65 1.75 3.33 0.36 0.0013-Jul 17.1 11.5 14:11.8 18.5 11.9 1.63 6.38 0.30 5.34 5.0014-Jul 16.2 10.1 13.2 11.5 15.1 6.0 5.18 6.79 3.28 0.31 2.0015-Jul 17.0 8.5 13.5 10.1 17.5 3.7 3.27 3.68 0.31 0.32 5.0018-Jul 13.9 8.9 11.7 9.8 14.4 5.3 0.45 8.68 0.31 0.39 10.0017-Jul 15.6 8.5 12,5 9.7 16.1 5.9 0.45 0.47 0.35 0.36 0.0018-Jul 15.5 6.9 12.6 10.0 16.2 5.1 0.46 0.49 0.35 0.36 0.0019-Jul 13.3 8.8 11.6 9.9 14.8 3.7 0.48 0.52 0.35 0.36 0.0020-Jul 15.4 8.9 12.5 9.7 17.5 4.6 0.50 0.53 0.35 0.37 0.0021-Jul 13.6 9.0 11,7 10.0 13.8 5.4 0.62 0.73 0.36 0.37 2.0022-Jul 16.1 8.5 12.7 9.5 18.0 5.1 0,58 0.74 0.36 0.37 0.0023-Jul 17.5 9.1 13.8 10.1 21.6 5.7 0.73 3.12 0.37 0.38 0.0024-Jul 18.7 10,3 14.6 11.0 25.3 8.9 3.12 )15.00 0.36 1.12 0,0225-Jul 19.6 11.9 15.1 12.1 27.4 11.2 )15.00 )15.00 1.13 4.65 2.0026-Jul 17.6 10,2 14,1 11.3 18.6 7.8 3,64 )15.00 1.49 6,13 1900.27-Jul 15.4 10.1 12.9 10.7 17.0 7.8 0.50 0.64 0.44 1.48 0.0028-Jul 15,5 10.1 13.1 10.9 17.2 6.7 0.51 0.55 0.41 0.44 0.0029-Jul 15.9 9.8 13.1 10.7 18.2 6.8 0.54 0.65 0.43 0.46 0.0030-Jul 16.2 10.4 13.2 10.9 18.3 6.2 0.64 0.90 0.46 0.58 0.0031-Jul 15.8 8.8 12.9 10,3 19.8 4.4 0.90 1.99 0.58 1.18 0.0001-Aug 17.1 9.7 13.6 10.5 21.2 7.1 1.99 12.53 1.18 4.16 0.0002-Aug 16.2 10.2 13.4 11.1 20.9 10.2 12.59 )15.00 4.16 7.84 0.0003-Aug 17.6 10.3 14.0 11.1 21.9 7.6 )15.00 )15,00 7,81 12,15 0.0004-Aug 18.8 11.2 14.7 11.7 24.2 11.3 )15.00 )15.00 11.22 ',15.00 0.0005-Aug 19.4 11.3 15.0 12.0 24.5 11.1 15.00 )15.90 )15.00 )15.00 0.0006-Aug 17.4 11.6 14.4 12.2 21.8 9.8 )15.00 )15.00 15.00 )15.00 0.0207-Aug 15.7 11.0 13.5 11.9 21.0 7.8 )15.00 , 15.00 15.00 )15.50 3.0508-Aug 17.8 11.3 14.1 11.8 21.4 9.8 11.25 ?15.00 .15.00 )15.00 0.5009-Aug 18.7 12.4 14.6 12.3 21.4 13.1 13.00 '15.33 15.00 ',15.00 3.1310-Aug 14.2 11.5 13.2 12.1 15.7 7.7 )15.00 )15.05 15.05 )15,00 0.5011-Aug 13.1 10.5 12.1 10.9 12.2 6.7 0.71 )15.0(3 )15.00 .. , 15.00 16.3012-Aug 13.7 10.5 12.0 10.8 13.9 6.7 0.53 0.75 0.63 )15.00 1.0013-Aug 13.5 13.2 11.8 10.5 13.8 7.1 0.45 0.53 0.35 0.62 5.5014-Aug 13.1 9.? 11.5 10.3 15.1 6.9 0.45 0.48 0.35 0.36 4.0015-Aug 15.9 10.6 13.1 10.8 18.3 8.6 0.45 0.47 0.35 0.36 0.0006-Aug 17.5 11.1 14.1 11.3 23.1 10.7 0.45 0.47 5.35 0.36 0.0086Weather Data 1991SOIL TEMPERATURE (C)^ SOIL MOISTURE 8ARS)2.5cm^10.0cm^AIR TEMP (C)^2.5cm^10.0cmDATE^MAX MIN MAX MIN MAX MIN MAX MIN MAX MINPEECIP(mm;17-Aug^18.5 12.4 15.0 :2.: 13.0 2.46 0.51 0.36 0.37 0.0018-Aug^17.4 12,7 14,7 12.7 25.3 12.6 0.50 0.56 0.37 0.35 00012-Aug^19.1 12,7 15.2 12,7 25.2 " 2 0,55 3.82 0.33 0.41 2102-Aag^18.3 13.2 15.1 13.1 24.2 12.9 0.62 0.86 0.41 0.55 0.0021-Aug^18.7 12.8 15.2 13.2 23.1 10.9 0.86 1.37 0.65 3.24 1.2022-Aug^15.4 12.2 15.0 12.6 22.9 10.6 1.87 11.40 3.24 3.41 0.00:3-Aug^18,7 12.0 14.9 12.5 22.8 9.3 11.45 >15.00 3.41 12.24 0.0024-Aug^17.8 11.7 14.3 12.3 19.2 6.7 15.00 >15.00 13.00 15.20 0.0025-Aug^13.6 9.7 02.0 10.9 13.0 4.9 2.8: )15.00 )15.00 )15.20 6.0026-Aug^13.7 8.2 11.6 9.7 14.6 2.9 1.40 2.81 13.74 )15.00 0.3227-Aug^12.6 8.6 10.7 9.5 11.6 4.3 0.63 1.53 8.27 13.74 6.0028-Aug^11.8 8.9 10.6 9.3 11.6 5.5 0.63 0.65 1.95 8.27 0.0029-Aug^11.5 8.2 10.1 8.9 10.2 4.5 0.59 0.64 1.12 1.95 0.0030-Aug^11.0 8.1 9.9 8.6 14.2 4.9 0.58 0,62 0.86 1,12 1.0031-Aug^12.2 9.6 10.7 9.7 14.6 7.9 0.58 0.60 0.80 0.86 0.0001-Sep^11.3 8.8 10.1 9,3 10.8 4.9 0.54 0.61 0.74 0.84 4.0002-Sep^12.4 7.1 10.2 8.2 13.0 2.0 0.52 0.56 0.61 0.74 0.0003-Sep^11.1 6.3 9.3 7.7 12.5 0.6 0.54 0.58 0.59 0.65 0.0004-Sep^13.4 6.7 10.5 7.6 17,5 2.6 0.54 0.60 0.57 0.64 0.0005-Sep^14.4 7.7 11.2 8.4 20.3 5.5 0.59 0.65 0.64 0.81 0.0096-Sep^15.3 9.0 11.8 9.2 22.2 8.5 0.64 0.75 0.81 1.78 0.0027-Sep^15.2 9.9 11.9 9,8 19.9 7.9 0.75 0.88 1.78 5,19 0.0008-Sep^12.4 8.8 10.8 9.5 14.2 4.9 0.87 1.00 5.19 8.51 7,0009-Sep^10.6 7,0 9.5 8.2 10.2 2.7 0.75 0.87 8.51 9.61 0.0210-Sep^12,8 6.9 10.3 7.9 16.3 2.0 0.72 0.79 7.75 9.98 0.0011-Sep^13.1 7,7 10.5 8.5 17.0 6.3 0.73 0.81 7.59 9.41 0.0012-Sep^14.1 8.0 11.1 8.5 21.0 6.0 0.78 0.90 8.69 10.88 0.0013-Sep^12.9 9,1 10.6 9.5 16.5 6.3 0.89 1.23 10.83 14.61 0.0014-Sep^10.1 6.7 9.5 8.0 8.9 0.2 0.99 1.33 13,68 15.56 9.0015-Sep^11.3 6.3 9.3 7.3 14,7 3.6 0.85 1.00 13.06 15.94 0.1016-Sep^12.7 7.3 10.1 7.8 18.3 4.2 0.81 0.91 11.22 14.54 0.0017-Sep^12.5 7.8 10.2 8.8 14.8 6.3 0.83 0.99 10.65 13.43 0.0018-Sep^12.2 6.8 9.9 7.7 16.9 5.1 0.94 1.08 11.88 14.00 0.0019-Sep^13.6 8.2 10.7 8.5 21.9 5.7 1.08 1.55 13.00 >15.00 0.0020-Sep^13.5 8.9 10.8 8.9 19.3 7.4 1.55 4.08 15.87 )15.00 0.0021 - Sep^10.4 6.3 9.6 7.8 9.1 1.9 4.08 )15.00 )15.00 )15.00 0.0022 -Sep^9.3 5.5 8.1 6.8 8.8 -0.7 15.95 )15.00 >15.00 )15.00 0.0023 - Sep^7,5 5.5 7.0 6.4 8.5 2.5 15.22 )15.00 )15.00 '15.00 9.0024 - Sep^11.4 5.9 8.9 6.4 14.4 3.3 2.99 15.22 >15.00 )15.00 0.0025 - Sep^12.5 7.0 9.6 7.3 19.2 5.6 1.91 2.99 )15.90 )15.00 0.0026 - Sep^12.7 7.4 9.9 7.7 21.1 6.2 1.66 2.08 13.94 )15.00 0.0027-Sep^13.4 7.6 10.3 7.9 22,9 6.9 1.69 2.10 12.48 ›15.00 0.0028-Sep^:3.6 8.9 10.7 8.6 22.7 9.7 2.08 2.92 12. 7 7 14.97 0.0029-Sep^12.1 8.2 10.1 8.8 16.1 5.4 2,92 4.81 14.34 15.00 0.0030-Sep^10.7 6.8 9.0 7.6 13.6 4.7 4.81 8.72 )15.00 )15.10 9,0087

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