DOI: 10.5061/dryad.30mb4
title: Data from: A multistate dynamic site occupancy model for spatially aggregated sessile communities

description: Estimation of transition probabilities of sessile communities seems easy
 in principle but may still be difficult in practice because resampling
 error (i.e. a failure to resample exactly the same location at fixed
 points) may cause significant estimation bias. Previous studies have
 developed novel analytical methods to correct for this estimation bias.
 However, they did not consider the local structure of community
 composition induced by the aggregated distribution of organisms that is
 typically observed in sessile assemblages and is very likely to affect
 observations. We developed a multistate dynamic site occupancy model to
 estimate transition probabilities that accounts for resampling errors
 associated with local community structure. The model applies a
 nonparametric multivariate kernel smoothing methodology to the latent
 occupancy component to estimate the local state composition near each
 observation point, which is assumed to determine the probability
 distribution of data conditional on the occurrence of resampling error. By
 using computer simulations, we confirmed that an observation process that
 depends on local community structure may bias inferences about transition
 probabilities. By applying the proposed model to a real data set of
 intertidal sessile communities, we also showed that estimates of
 transition probabilities and of the properties of community dynamics may
 differ considerably when spatial dependence is taken into account. Results
 suggest the importance of accounting for resampling error and local
 community structure for developing management plans that are based on
 Markovian models. Our approach provides a solution to this problem that is
 applicable to broad sessile communities. It can even accommodate an
 anisotropic spatial correlation of species composition, and may also serve
 as a basis for inferring complex nonlinear ecological dynamics.
description: Site occupancy data from
 rocky intertidal communitiesData file written in the
 Rdump format. This is a sort of text file and can be loaded into R by
 source("dumpdata.R"), defining the following objects: * Y : a
 3-dimensional array of observation of site occupancy state. Each dimension
 represents: [Quadrat, Site, Time]. * x : a matrix in which each row
 representing spatial coordinate of a site. * I : an integer representing
 the number of sites per quadrat. * J : an integer representing the number
 of quadrats. * S : a vector indicating the number of states modeled in
 each quadrat. * T : an integer representing the number of time points. *
 state_list : a list of vectors representing ecological states modeled in
 each quadrat.dumpdata.RR script for data analysesAn R script to estimate transition probabilities by using the naive estimator, nonspatial and spatial model. It also includes codes for estimating and plotting some properties of community dynamics as well as those for drawing estimated local community structure.Rscript.RModel file for the nonspatial modelJAGS model file for the nonspatial model.model_nonspatial.jagsModel file for the spatial modelJAGS model file for the spatial model.model_spatial.jagsParameter estimatesThis compressed file contains R binary files including estimates of transition probabilities and others, obtained for each quadrat by using the naive estimator, nonspatial and spatial model. They are obtained as outputs from the codes in the "Rscript.R" file.results.zipPosterior samplesThis compressed file contains R binary files including JAGS output (i.e., posterior samples) for each quadrat. They are obtained as outputs from the codes in the "Rscript.R" file, and are also used to produce files contained in the "results.zip" file.posterior_samples.zip