DOI: 10.5061/dryad.j0zpc86tr
title: Scripts from: Performance of generalized distance sampling models with temporary emigration: a simulation study

description: Generalized distance sampling (GDS) models are the distance sampling
 equivalent of temporary emigration N-mixture models. In addition to
 density and the perceptibility component of detection, both contain an
 additional parameter for availability for detection which becomes
 estimable when data from repeated 'visits' are available. GDS
 models thus account for open populations. This makes them more robust,
 since natural populations are hardly ever perfectly closed, arguably even
 over the course of a single breeding season. However, the performance of
 these models has not been tested thoroughly, and prior (unpublished)
 analyses suggested that biased estimates, especially for density (high)
 and availability (low), may typically occur under certain conditions. We
 conducted three simulation studies and found that bias arises in
 low-information scenarios, particularly with low sample sizes and low
 parameter values. Our simulations enable us to determine "estimation
 frontiers", which separate satisfactory from unsatisfactory
 estimation performance. Typically, 4-5 replicates, 100-200 sites, and
 specific combinations of parameter values - particularly those linked to
 availability and detection probability - are required for reliable
 estimates. We found that inclusion of covariates in the models could
 improve estimates in some situations by reducing the incidence of extreme
 estimates. One novel result from our simulations is that while density and
 availability may be non-identifiable under some combinations of sample
 size and for certain parameter values, their product (i.e., the density of
 the available population) may be more reliably inferred. Our findings
 provide important insights for study design and for obtaining and
 interpreting abundance estimates in models with temporary emigration, all
 with important implications for ecology and wildlife management.
description: # Title of Dataset: Performance of generalized distance sampling models
 with temporary emigration: a simulation study --- ## Description of the
 data The study was not based on real data. All data used in the study were
 generated using simulation code. ## Code/Software The dataset contains
 four R files with simulation codes: 1. Code_1_simGDS_function.R- R code
 with data simulation function; 2. Code_2_gds_Sim1.R - R code to perform
 Simulation 1 with varying number of sites (20–500) and of surveys (2–10);
 3. Code_3_gds_Sim2.R - R code to perform Simulation 2 with varying number
 of sites (20–500), surveys (2–10), density λ (0.01-2 individuals per
 hectare), availability ϕ (0.01-1), and the parameter that governs the
 decline of the detection function over distance σ (20-200 meters); 4.
 Code_4_gds_Sim3.R - R code to perform Simulation 3 with effects of three
 continuous covariates on all the three parameters (λ,ϕ,σ). First, run
 Code_1. The other codes are independent, but the first simulation (Code_2)
 is simpler and the third (Code_4) is the most complex. Each simulation
 code (codes 2, 3, and 4) generates 10,000 simulation data.