Contributors: Shirley Pledger, Alexey Botvinnik, Günter Kratz, Oliver Kellenberger, Jürgen Meinecke

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1 Wildlife Simulation Package Walter Zucchini 1, David Borchers 2, Stefan Kirchfeld 1, Martin Erdelmeier 1 & Jon Bishop 2 Institut für Statistik und Ökonometrie Research Unit for Wildlife Population Assessment 1 University of Göttingen 2 University of St. Andrews Contributors: Shirley Pledger, Alexey Botvinnik, Günter Kratz, Oliver Kellenberger, Jürgen Meinecke Downloaded fromhttp:// Page 1 of 20

2 Concepts in animal abundance estimation State model Describes the spatial distribution and characteristics of animals in a region Who lives here and where are they? Population: group size, composition (gender, type), position, exposure Survey design Describes the covered region, survey units, effort (observers/traps) Where, how, and how hard we look. Survey design: plot sampling, removal methods, mark-recapture, distance sampling, etc. Observation model Describes the probability that animals with given characteristics are detected. What we assume we are likely to see. Detection probability: certain, constant, distance dependent, covariate-dependent Downloaded fromhttp:// Page 2 of 20

3 Abundance estimation process in WiSP generate.region generate.density region density 1.) Define survey region & population density functions objects Downloaded fromhttp:// Page 3 of 20

4 Generating a survey region Survey region = An area of given height and width survey region 10 0 Downloaded fromhttp:// Page 4 of 20

5 Generating a population density (1) The population density defines the spatial distribution of animals in the survey region. Simple density with linear trend: high density Density y x low density Downloaded fromhttp:// Page 5 of 20

6 Generating a population density (2) Increase complexity by adding hotspots and coldspots: hotspot Density y coldspot x Downloaded fromhttp:// Page 6 of 20

7 Generating a population density (3) Add more complexity: Strips of constant density no animals here Density y x Downloaded fromhttp:// Page 7 of 20

8 Abundance estimation process generate.region generate.density region density 1.) Define survey region & population density setpars.population generate.population 2.) Generate population population functions objects Downloaded fromhttp:// Page 8 of 20

9 Generating a population The population specifies the positions and characteristics of groups and individuals Population parameters region density probability distributions of group and individual characteristics (group sizes and exposures) number of groups Downloaded fromhttp:// Page 9 of 20

10 Generating a population Region, density and N Generate population Population population parameters group-size distribution exposure distribution Downloaded fromhttp:// Page 10 of 20

11 A population with 500 groups large group low exposure small group high exposure 10 0 Downloaded fromhttp:// Page 11 of 20

12 Abundance estimation process in WiSP generate.region generate.density region density 1.) Define survey region & population density 3.) Generate survey design setpars.design generate.design setpars.population generate.population 2.) Generate population design population functions objects Downloaded fromhttp:// Page 12 of 20

13 Survey designs for closed populations plot sampling Count all animals in a selected sub-region distance sampling line transect point transect Count along a transect record the distances Count within a circle record the distances removal methods Repeatedly remove some mark-recapture various nearest object single nearest object Repeatedly capture, mark, return Measure distance to nearest object detected Downloaded fromhttp:// Page 13 of 20

14 Survey designs with Incomplete Coverage plot sampling (random) line transect 50 point transect Downloaded fromhttp:// Page 14 of 20

15 Abundance estimation process in WiSP generate.region generate.density region density 1.) Define survey region & population density 3.) Generate survey design setpars.design generate.design setpars.population generate.population 2.) Generate population design population setpars.survey generate.sample 4.) Survey population sample functions objects Downloaded fromhttp:// Page 15 of 20

16 A line-transect survey Specify design pars Generate design (random) Specify survey pars Do survey to generate a sample Downloaded fromhttp:// Page 16 of 20

17 Abundance estimation process in WiSP State Model generate.region region generate.density density 1.) Define survey region & population density 3.) Generate survey design setpars.design generate.design setpars.population generate.population 2.) Generate population Design design population Observation Model setpars.survey generate.sample sample 4.) Survey population point.sim.est point.est int.est 5.) Compute estimates simulation est point est interval est functions objects Downloaded fromhttp:// Page 17 of 20

18 Assumed model vs reality generate.region generate.density region density 1.) Define survey region & population density 3.) Generate survey design setpars.design generate.design setpars.population generate.population 2.) Generate population design population setpars.survey generate.sample sample 4.) Define generating observation model and survey population point.est point est int.est interval est 5.) Compute estimates using assumed observation model functions objects Downloaded fromhttp:// Page 18 of 20

19 Assessing sensitivity to assumptions Generating observation model defines the true detection/capture probabilities for all animals Assumed observation model is what we use to carry out the estimation Mark-recapture method Homogeneity equal capture probabilites Heterogeneity trap-shyness, unequal exposure Estimate Assumed observation model Assumption violated Generate Generating observation model Enables sensitivity analysis Downloaded fromhttp:// Page 19 of 20

20 Function and object names Prefix * (action) setpars.survey generate.design plot.design generate.sample summary.sample point.est interval.est point.sim etc. * incomplete list Example: + Suffix (method extension).cr 1.dp.lt.no.pl.pt.rm 2 capture-recapture double-platform line-transect nearest object plot sampling point-transect removal 1 Estimation functions for.cr extension are.crm0,.crmt, crmb, crmh 2 Estimation functions for.rm extension are.rm,.ce and.cir setpars.survey.pt Set survey parameters for a point transect Also summary() and plot() functions for most objects Downloaded fromhttp:// Page 20 of 20