DOI: 10.5061/dryad.931zcrjhg
title: Data from: On the sampling design of spatially explicit integrated population models

description: It is important to understand metapopulation dynamics and underlying
 demographic processes in heterogeneous landscapes. Traditionally
 demographic parameters are estimated using capture-recapture data that can
 be difficult to collect. Spatially explicit dynamic N-mixture models allow
 inference for demographic parameters, including dispersal, using count
 data of unmarked animals, but these models have only been shown effective
 under constant demographic parameters and dispersal between adjacent local
 populations. In this study I aimed to compensate the weakness of spatially
 explicit dynamic N-mixtures and multistate capture-recapture models by
 jointly analyzing count and capture-recapture data. This spatially
 explicit integrated population model allows for spatiotemporal variation
 of demographic parameters in relation to environmental and density
 covariates and dispersal between any local populations. I conducted
 simulations to evaluate this model (1) for species with distinct life
 histories under different detection and capture probabilities, (2) when
 spatial sampling intensity varied, (3) when the length of survey period
 varied, (4) when the robust sampling design was adopted or not, and (5)
 when auxiliary information is partially available. I also provided an
 empirical example of Gadwall (Mareca strepera) metapopulation dynamics in
 North American prairies. The results showed that the model provided
 unbiased parameter estimates under a variety of ecological and sampling
 conditions, even when the spatial sampling intensity of capture-recapture
 survey was low (20% of the patches) with the complement of count data (≥
 60% of the patches). Also, the model only required a relatively short
 survey period (6~8 years) to provide unbiased inferences. The robust
 sampling design was not necessary for the model to provide unbiased
 inferences when spatial counts were intense, but became critical when
 spatial counts were sparse. Parameter estimates remain unbiased when
 auxiliary information is partially available. The model showed that
 Gadwall had low emigration probability (11.8%) but could disperse more
 than 200 km. Based on the results, I provide recommendations about the
 tradeoff between spatial sampling intensity, length of survey period, and
 the use of the robust sampling design when applying this model in real
 world studies. The model could have wide applications in the interface of
 metapopulation ecology and landscape ecology.
description: In this study I developed spatially explicit integrated
 population models by combining spatially explicit dynamic N-mixture models
 and multistate capture-recapture models. In addition to simulation
 studies, I used Norther American waterfowl survey data to illustrate the
 use of this modeling approach. The following data set
 was used in the case study. This data set contains population survey,
 capture-recapture, and environmental data that are used to illustate
 spatially explicit integrated population models. Population suyvey data
 (duck) are in a segment by year matrix. Capture-recapture data (ch) are
 orgainzed in an individual encounter histroy format, and thus are in an
 individual by year matrix. Environmental data (pond) are in a grid by year
 matrix.
description: Additional information available in attached README.txt