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by: Sallie Lind PhD


Sallie Lind PhD
GPA 3.84


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Class Notes
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This 76 page Class Notes was uploaded by Sallie Lind PhD on Wednesday September 9, 2015. The Class Notes belongs to ESRM 304 at University of Washington taught by Staff in Fall. Since its upload, it has received 30 views. For similar materials see /class/192036/esrm-304-university-of-washington in Environmental Science and Resource Management at University of Washington.

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Date Created: 09/09/15
EXSBM 304 November 1 71 200839 Resources amp Social Science Conceptual Frameworks Research Questions Kathleen L Wolf PhD kwolfuwashingtonedu wwwcfrwashingtoneduresearchenvmind What Are Human Dimensiuns l wnars New 0 Human d menim smmu c lm ways mm mm Namz s m a mmv dua s ems andsuue ymlcradwxm a mn mos Gramsan fmmmg n mna nmd hymn new nwmnmmanu Imam Bmduam Sludmlsand Pmlnssms 3 eaweamem mungn m m whnns myquot seen la no v Welcome Wexeome o HD guv a new cuuabma ve ageneies aea Management Questions w mm by eenua nguvernmema urgamzahnns nd pnva e e unrhnz Wm WHERE Haw WHV7 Who are me Qnmam stakehowoersv enmem auen and mews rela ed e me Whu are mg kg danishquot huma y 10 em m U s ee my managemem ms 5 a dynamms e ma 7 oheekmg fur new oomem Far more Inlurmalmn p ease see aoeunms 5th If you have any questions comments or renuests posx mem on me quotFnrumquot or oonxa us 31 ian he w We wumd ove m near yum yum How Do Use This Slte There are several ways m nd informa un on HDgav V sil me mmduchwn for a qmck primer on human ermensums arm apnhcanons tapC yuu wome ivke in address Visil Case some you are lmerested in how mhers appy easescience mulhple resmlmes s4multanauus1y oy gmng 10 me Pub ahnns page Check ounne Panner pages you are lnukmg Dr agencyrspecf c nfan39nahun Cream mm oomenL cnek me 5mm E bmmn mam gasswnrd Case Study Research Methods ryman amp Cramer 391 19197 Quantitative Data Analyse A Guide for Social Scientists 0 Galvan J L 2004 Writing Literature Reviews A Guide for Students of the Social and Behavioral Sciences 2nol Edition Chapter 5 Analyzing Literature from the Viewpoint of a Researcher 0 Shoemaker et al 2000 Social Science Methodologies for Studying lndividuals Responses in Human Issues in Horticulture Research HortTechnology Reserve Books Research Methods Creswell 1994 Research esigm Qualitative 8 Quantitative Approaches Robson 1993 Real World Research A Resource for Social Scientists and PractitionerResearchers Zeisel 1981 Inquiry by Design Tools for EnvironmentBehavior Research llpreferring simplicity is not denial of complexity but clari cation of the significant an architect somewhere Process of on a focus develop research questions V report w t you ve found choose a rese ch strategy carry out arran e practicalities co ect the data Primary Research Questions Framework include hypotheses Framework is project skeleton develop subquestions operationalize questions eld methods data collection Examples Framework Basics Who Where Why users general populace stakeholders managers decision makers on site near off site community region state plan manage evaluate forecast fund theory 1 Urban Forestry Shopping Environments Business Districts Urban orestry Shoping Visual quality viisUaI preference Ratings of varied images of streetscape conditions Shepper perceptions Maintenance and upkeep Product quality Merchant interaction Shopper patronage Travel time amp distance Length of stay Willingnesstopay for products CuHege n reresr Remurres rearnrrng research all peepres ereepu n5 haviuri vayammg namre m mes Research uzremr Kathleen L Wulf FhD Un vrnny ol Wasmngluu Namre and Consumer Environments Research eeeer new me when wrest IN nces business dr5l c mums Trees ann Trenspnnauen Sums an we value ainavmg quamy landscapes in urban roadsides ClvlcrEcolngy srne res ernemen nenawnrs and benems wnen penple ere eewe In the envrmnmem l y a Planning nnegraunq umen greening screnee wun carnmnnuy cnenge Urban Forestry and Human Bene ts Mere resources Emma and links r wwwcfrwashingt0meduresearchenvmimd Urban Youth Urban Forest Restoration Personal Development Urbain Forestry S t oi fa ofn Personal eVeIOPment PSth olofgical development Selfconcept and identity Con dence and selfef cacy Social development Improved family dynamics Community leadership Career development Ecological literacy Natural resource career knowledge amp interest Private andowngers Nonpo int Source Pollution amp Land Management Pollution amp Land Management Learning effectiveness Judgments of inter net site visits print materials classes etc Motivations to adopt behavior Environmental ethic Economic gain External in uences Satisfactions after doing recommended BMPs Landscape stewardship Intrinsic pleasure or value Health of personal land and animals fer Canceptual Framework Theory Prior Studies Case Studies Pilot Study Personal Experiences Field Managers amp Experts Social EWarld Park recreation evaluati n There are much bigger social questions about parks rec and open space 5 minute essay parks and people issuedynamic data collection about people what would be a research question 1 2 sentences Environmental Science and Resource Management ESRM 304 Autumn 2008 University otWashington 39 quot S D West College of Forest Resourc Salamander Survey at St Edward State Park To familiarize you with a timeconstrained methodology an example of catch per unit effort CPUE sampling and augment the Park database we will conduct a timeconstrained survey to compare abundance levels between coniferous forest and nearby deciduous forest habitats We will divide into teams of three persons and conduct four 10min surveys per team Teams will survey each habitat twice Areas surveyed will be at least 50m apart Animals will be captured and placed in plastic bags until identi ed to species by the class alter which time they should be released at the point of capture Combining the data between eld days this will result in a total of about 60 surveys with 30 surveys in each habitat type We will pool our capture data available electronically after Wednesday s trip with that from 20042007 and each team will prepare a brief report of the results The report will consist of a short introduction giving the purpose of the exercise a methods section describing the eld and analytical techniques a results section and a discussion of the results Your team report is due at the start of lab next week and should address the following 1 Identify the questions posed by the group eg possible differences in amphibian relative abundance or species richness the number of species between forest types 2 Identify the hypotheses under test the null hypotheses These could be species x habitat tesm or community measures x habitat tests such as species richness 3 Describe the nature 0 the data and how the data were collected 4 Perform statistical tests of the hypotheses ttest at 0101 will be OK a 39stributed with a logarithmic transformation trans X logx1 or log x1 The transformed data trans X are used in the ttest Richness need not be transformed b You may have to manipulate the combined data set in Excel before running a particular ttest c Use the option ofunequal variances foryour ttest llC and um 39 39 a amphibian species or community measures richness in these two habitat types b any complications of data interpretation an c suggestions for improving future work Species encountered at St Edward State Park may include the following Salamanders Frogs and Toads Northwestern salamander Ambystoma graeile Western toad Bufo boreas Coastal giant salamander Dieamptodon tenebrosus Paci c Treefrog Hyla regilla Longtoed salamander Ambystoma maerodaetylum Redlegged frog Rana aurora Roughskinned newt T arieha granulosa Redback salamander Plethodon vehiculum Ensatina Ematina esehseholtzii The Nature of Wildlife Populations Characteristics and Growth ESRM 304 The Nature of Populations I Population a group of conspecific individuals occupying a particular place at a particular time I This is an operational definition I Compare with Deme a population unevenly distributed in space with real natural boundaries A deme can be a subset of a population or an isolated or semiisolated population Population Features and Terms Abundance number of individuals Density number of individualsunit area Natality production of new individuals Mortality loss of individuals due to death Emigration amp Immigration loss or gain to a population due to movement of individuals Factors of Change in Abundance Birth Immigration gt Abundance gt Emigration Death 7183 Geometric Population Growth Numb er Time Growth under ideal conditions Occurs in populations in early stages of growth AN At AN change in number At change in time r per capita growth rate birth death N size of population rN Geometric Population Growth Numb er Time rN Al If r02 and N50 at the next time interval ANAt025010 80 NH 50106O and NW 72 And so on and so on and so on Logistic Population Growth Number Time Reality check modification of the geometric model Sets upper limit on population size AN N K N N K Carrying capacity Maximum population size that can be sustained on an area Logistic Population Growth rNE K N At N If r02 N590 and K100 ANAt02901 009090 1810902 and Nt190292 Number Population grows by 2 vs Tlme 18 individuals If N exceeds K growth becomes negative Numbers Temoral Pattern of Abundance Annual Years High and low abundance in each year Predominate pattern in temperate regions and the most common among vertebrate species Simple alteration of breeding and non breeding seasons Pattern can be stable or show longterm trend Numbers Temporal Pattern of Abundance Cyclic I Peaks of abundance occur at regular intervals With large difference in abundance between years I 35 cycle for voles lemmings I 911 year cycle for snowshoe hares lynx ruffed grouse I Relatively uncommon but striking effects Numbers Temporal Pattern of Abundance Irruptiye 20 30 Years 40 50 Irregular very large changes in abundance Peak abundances usually unpredictable Locust outbreaks mouse plagues defoliating insects Uncommon but very strong effects on ecosystem functions The Nature of Wildlife Populations Measuring Populations ESRM 304 Measuring Population Parameters I Measuring the factors causing change in populations birth death immigration and emigration requires individually marked animals I Individuals are captured in nests or when they reach trappable age and given a permanent mark leg band ear tag tattoo pit tag photographic record I Survival of individuals and population rates are obtained by periodically censusing the population I Emigration is the most difficult of the four parameters to measure because it is hard to distinguish from death I These are intensive expensive longterm studies that can be conducted on relatively few sites but are essential for a thorough understanding of population dynamics I ESRM 350 basic and especially FISH 577 Advanced Abundance I Sometimes measuring absolute abundance and density is important for wildlife studies but fortunately for many management issues these are not required An index of abundance may suffice It is often enough to know the direction and magnitude of change caused by an action I A good index is a measure that bears a consistent relationship to true abundance As the actual number of animals changes the index should change proportionately Catch Per Unit Effort Sampling I Time constrained sampling is a catch per unit effort method CPUE The index is the number of an1ma1s caught or observed per unit time I CPUE indices can be constructed for trapping returns caught 100 traps shing effort net hours tracking data trackskm audio surveys callskm hand searching person hr etc I Other CPUE indices involve area constrained sampling unit area searched I We will use a timeconstrained approach to index amph1b1an abundance dur1ng the field trip Censusing Wildlife Populations I In subsequent lectures we will discuss methods for measuring both density and indices of abundance but will focus on indices I We will concentrate on terrestrial vertebrates but recall that by Washington State law insects their eggs and larvae are also protected Wildlife I Methods vary as functions of species natural history and because of this the techniques are grouped by taxonomy and life style I Pondbreeders I Most frogs amp toads some salamanders Live at ponds or migrate seasonally between them and upland habitats Have pondadapted larvae I Streambreeders Some salamanders and one frog Live in or near streams Have streamadapted larvae I Upland breeders I Several salamanders I Lay eggs on moist sites on land I Full development in egg Fully terrestrial n0 aquatic larval stage Amphibians Terrestrial Searches I Upland and pond breeding salamanders I Searches constrained by time or area I Season after spring or fall rains I Equipment potato or hand rakes plastic bags ruler spring scale St Edward State Park Survey I Consult the handout for details I Jointly prepared field reports will be done in 3person teams I I We will combine our results with those of previous years I Bring your field guides Esau13304 En Vi mnment39a39 3 quot039 Resource Assessment Social Science 8 Natural Resources Research Design Methods 8 Measures Dr Kathy Wolf kwolfuwashingtonedu wildland forest values amp bene ts ecosystem services forest values how do we know imlrel Frenuentlv Fxnrp tarl Fore t Values Values Expressed as Values Expressed as Sustain Growth of Forests Minimize levels ot exotic insect a disease pests Minimize catastrapnic tevels af native mammals native insect amp disease pests Minimize catastroonlc nre events Minimize losses from catastrophic winds or other Inaturalquot events Sustain The Global Environment Avoid atmospheric 502 tit other pollutant uil up Conserve native furests in other countries Ensure Flam 8 Animal Diverslty Conserve t2 restore native lorest types a species Provide habitats for native species within rvivai a recovery or threatened ge d cie Protect native species trom invasive exotic spec39es Maintain genetic diversity ti architecture Ensure Productivity 039 Future Forests Maintain site quality Suslal watersheds Maintain faresl land base Timber Products Timcer volume Timtierouai Selected species Reserve Areas Recreation Remote Accessible Rural Lilestyles Commodityauependent NunaCommndilydependent Earnings Employment 3 ValueAdded Water Volumes 8t Usefulness Game 8t NonGame Fish 8t Wlldlife Viacility or Various Forest Economic Segments Sman private nomlndustrlal landowners Private industrial landowners Highavolume timber products manufacturers a P 1 ts manufaclulers utilizith highcquallty timber Recreation industry Low Public Costs of Managing Forest Lands cenic Existence 3 Historical Values Spiritual a Cultural Values FNVV xad tiomsz wam dmg car pradmctiam amm mp d y w Social and Cultural Values Across the Landscape Spectrum V Exurbanlrural 715 so 14 W King County LARGE FOREST LANDOWNERS PublidyOwned Forest Sir r 39jgw Forest Produtlion Distria V 39 5 Boundary Mandy 2005 Social Science Disciplines 0 psychology 0 social psychology 0 sociology 0 economics 0 political science 0 anthropology 0 geography unmui nmnm mmull mum unum Improved surgery and illness recovery Higher job satisfaction and reduced absenteeism Lower crime rates in well landscape areas Stress reduction in urban lifestyles Reduced violence and more constructive con ict resolution in domestic con ict Reduced ADHD symptoms urban parks amp open space Nam ba Parks Osaka Japan view from nearby hotel H m interior retail space ground level small plazas retail ent Namba Parks retail success amp nature experience benefits Carrying an lnvestiuation 39 Robson amp G a lvian decide on a focus develop research iqUieSUans Research Cycle carry out arran e practicalities co ect the data sources of questions social science questions V prO f S S Or me to behaviors 39 ersoniai interests What are perceptions theory amp assu m ptio management preposal expand theory program effectiveness inform policy amp practice decide on a focus develop research questions report what ou ve found investigation paradigms Quantitative approaches descriptive qualitative relational correlat39ion experimental quantitative quasiexperimental usually use statistics decide on a focus develop research questions choose a rese quantitative methidsi39 tests and scales observations structured interviews govt dat asets qualitative methods indepth interviews archival materials ethnographic contacts journaling select carry out nalysis arran e practicalities co eat the data sampling sampling frame random sample strati ed random sample snowball sample carry QUt nalysis arran e practicalities 7 7 co ect the data quantitative analysis statistics descriptives qualitative analysns inference content analysis thematic coding identi patterns seek general explanations nd meaning in apparent chaos build theory Who research sponsors scienti c community professi onalsrnanaigers collaboratOrs public How scienti c journals technical reports books public communications Carrying an lnvestiuation 39 Robson amp G a lvian decide on a focus develop research iqUieSUans Research Cycle carry out arran e practicalities co ect the data Fixed Area Plot Summary and beyond Seven step process for standard inventory data distillation 1 VOW500M Estimate tree volume or biomass for every tree on the plot Compute the Tree Factor the number per acre each tree represents Estimate number of trees per acre for each plot Estimate volume or biomass per acre for each plot Summarize per acre statistics with con dence interval Create Stand and Stock Tables example appears in Table 1 Estimate Site Index measure of site quality 8 Estimate Sample Size for a survey with speci ed reliability not always Example We would like an estimate of volume per acre cubicfoot basis for a second growth Douglas r stand growing in the Paci c Northwest including con dence interval and stand and stock tables Plot size used is 120 2 005 acre Partial listing of the data 11 3 plots Plot 1 Plot 2 Plot 3 M Ht M Ht M Ht 151 150 777 189 948 145 137 793 153 838 128 127 152 127 704 126 824 152 126 758 111 138 123 114 135 113 722 104 96 88 640 91 19 trees 16 trees 18 trees ESRM 304 Environmental amp Resource Assessment p1of7 Step 1 Estimate tree volume for trees on the plot Begin with trees having both a measured DBH amp Ht using a standard volume equation Browne 1967 see Table 2 For coastal immature Douglas r coefficients from Table 2 Appendix 10 2658025 DBH1739925HT1133187 Where CVTS denotes Cubic Volume including Top and Stump The fourth tree on plot 1 DBH 127 in HT 2 704 ft 10 26580251271739925 7041133187 fts Compute an average VolumeBasal Area or BiomassBasalArea Ratio VBAR sum of tree volumes sum of basal areas For plot 1 above VBAR 227 244 191 088 086 070 2 2713 Estimate volumes for all trees with a measured DBH only using the average VBAR The rst tree on plot 1 DBH 151 in BA 2 124 CVTS VBAR X BA 2 2713 X 124 336 ft3 Step 2 Compute Tree Factors the number per acre each tree represents For xed area plots 1 Tree Factor 2 Where a plot Slze 1n dec1mal fract10n of an acre 0 1 W 20 Wh1ch 1s same for every tree For the example Step 3 Compute number of trees per acre for each plot On plot 1 in this example there are 9 trees total and each tree represents 20 per acre so 9 X 20 180 trees per acre TPA ESRM 304 E Turnblom Fixedarea plot summary p 2 of7 Step 4 Compute volume per acre for each plot Find the products CVTS X Tree Factor for each tree and add them up Plot 1 4071 ft3 Plot 2 3117 ft3 Plot 3 5413 ft3 Step 5 Summarize per acre statistics with con dence interval Avg CVTS per acre 2 42003 ft3 acre Variance s2 13304493 ft3 acre2 Std Dev 2 11534 ft3 acre Std Err 6659 Desiring an 80 CI let s say to2o2 1886 80CI 42003 i 1886 66593 The true mean CVTS per acre for the sampled forest stand lies somewhere in the interval 29444 54562 ft3 acre unless a 20 chance occurred Step 6 Create Stand and Stock Tables Select DBH classes to use say 2inch classes for this example Stand Table trees per acre by DBH amp species Trees per acre in the 14 Class 2 count of trees m 14 Class on all plots 11 4 Four trees on all three plots fall into the 14 class so 267 Stock Table volume per acre by DBH amp species Volume acre in 14 class 2 Trees per acre in 14 class XVBAR X BA ESRM 304 E Turnblom Fixedarea plot summary p 3 of7 Table 1 Textbook example of Average Acre Stock Table Data from 208 acres of pitch pine type in Central New Hampshire After Table 113 in Husch Miller Beers 1972 Cubic Feet Per Acre DBH Pitch Balsam Red White Red Red White Amer inches Pine Fir Spruce Pine Pine Maple Birch Elm Total 6 176 25 50 39 145 43 396 7 379 40 40 129 670 8 276 224 500 9 255 201 134 134 76 800 10 608 188 188 270 106 1360 11 402 133 133 140 808 12 480 164 141 785 13 613 176 789 14 174 184 358 15 218 218 16 823 181 1004 17 18 1588 1588 19 20 377 377 Total 3639 1018 545 442 184 514 259 322 9653 Partial Stand Table for the Douglas r Example Per Acre DBH inches 9 10 11 ESRM 304 E Turnblom Fixedarea plot summary p 4 of7 Step 7 Estimate Site Index See Figure 1 below she 260 m 250 m w i 39 s 24o m i ai 23 391 2w m m g r39 I 220 w aianas a maag 20 i 39 mm 200 g 7 A 39 3990 I 11 quot dii 39 quotV WI39HF i 80 i A mg Ianng 3970 E g 39 E BEEF 395 I60 E m r I 19 iVI 4 ll Iw g g w iw i I m g 39 g k g gi y g gi i 7 1 I Am gg g E I 39 53quot v 5 g E WM 39 F E w 4 w m wamp g m 0 39m E l H my H EBB1E E i E 0 IO 20 30 4O 50 60 70 80 90 loo 0 3920 Age at Breast Height Years Figure 1 Site Index Curves for Douglas r From King J E 1966 Site Index Curves for Douglas r in the Paci c Northwest Weyerhaeuser Forestry Paper No 8 ESRM 304 E Turnblom Fixedarea plot summary p 5 of7 Determining Sample Size for your Use of statistical formulas preferred 2 2 nk where E2 next inventory For SRS infinite populations or sampling with replacement n number of sample units required for desired precision E with confidence level implied by z k k correction term to avoid iterating between t values Confidence level zvalue k 80 1282 131 90 1645 187 95 1960 244 99 2576 379 z standard normal deviate CV coefficient of variation standard deviation divided by mean in percent for forest to be sampled E allowable error ordesired precision in percent for average volume or basal area etc For SRS finite populations or sampling without replacement 2 N22 CV 11 where NE222 CV N Total number of sampling units in population and all other symbols are as before Rules of thumb For 110 acre plots in highly variable ie CV gt 45 populations Area in acres number of samples Upto 10 11 40 41 80 81 200 200 10 1 per acre 20 05 area in acres 40 025area in acres Use sample size formulas ESRM 304 E Turnblom Fixedarea plot summary p6of7 APPENDIX Table 2 Coefficients for Cubic Volume contents of various species A CUBIC VOLUME INCLUDING TOP AND STUMP CVTS Four methods are readily available to calculate cubic volume including top and stump 1 British Columbia Equation The British Columbia cubic volume equation 1 are presented in the torm Log CVTS A B Log DBH C Log HT Thi has been changed for the computer to CVTS 10 A DBH B HT MC 173 10quot DBIIHHIITC Table 1 British Columbia Cubic Volume Equation Coefficient PECIES A B C r DOUGLAS FIR Coastal Immature Less Than 140 Years 2658025 1739925 1133187 Coastal Mature 80 Years 2712153 1659012 1195715 Interior 2734532 1739418 1166033 WESTERN HEMLOCK Coastal Immature Less Than 140 Years 2702922 1842680 1123661 Coastal Mature 80 Years 2663834 1790230 1124873 Interior 2571619 1969710 977003 WESTERN RED CEDAR Coastal Immature Less Than 140 Years 2 441 193 1720761 1049976 Coastal Mature 80 Years 2379642 1682300 1039712 Interior 2464614 1701993 1067038 BALSAMI Coastal 2575642 1806775 1094665 Interior 2 502332 1864963 1004903 SITKA SPRUCE Immature Less Than 140 Years 2550299 1835578 1042599 Mature 140 Years 2700574 1754171 1164531 Interior 2539944 1841226 1034051 PINE Ponderosa 2729937 1909478 1085681 Lodgepole 2615591 1847504 1085772 Western White 2480145 1867286 994351 WESTERN LARCH 2624325 1847123 1044007 YELLOW CEDAR 2454348 1741044 1058437 HARDWOODS Alder 2672775 1920617 1074024 Maple 2 770324 1885813 1119043 Aspen 2635360 1946034 1024793 Birch 2757813 1911681 1105403 Cottonwood 2945047 1803973 1238853 ESRM 304 E Turnblom Fixed area plot summary p 7 of7


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