GENERAL INFORMATION

1. Paper information 

Efford MG, Fletcher D 2024. Effect of spatial overdispersion on confidence 
    intervals for population density estimated by spatial capture-recapture.
    bioRxiv DOI: 10.1101/2024.03.12.584742

Spatially explicit capture-recapture models are used widely to estimate the 
density of animal populations. The population is represented by an inhomogeneous 
Poisson process, where each point is the activity center of an individual and 
density corresponds to the intensity surface. Estimates of average density are 
robust to unmodeled inhomogeneity, but the coverage of confidence intervals is 
poor when the intensity surface is stochastic. Poor coverage is due to 
overdispersion of the number of detected individuals n with respect to the 
fitted Poisson distribution. We investigated overdispersion from stochastic 
generating models (log-Gaussian Cox process and Thomas cluster process). 
Variation in a scalar measure of local density - the detection-weighted mean 
density - predicts overdispersion when the generating process is known. A 
previously proposed correction for overdispersion was successful only in limited 
cases: rigorous correction for spatial overdispersion requires prior knowledge of 
the generating process. The problem is lessened by assuming population size to 
be fixed, but this assumption cannot be justified for common study designs. 

Simulations were performed in R using code in the R package 'overdispsim' 
archived at https://doi.org/10.5281/zenodo.15460402. 'overdispsim' may also be 
installed in R using -

install.packages("overdispsim", repos = "https://MurrayEfford.r-universe.dev")

A related R package 'secrRFS' performs calculations for an appendix in 
Efford and Fletcher (2024). It is archived at https://doi.org/10.5281/zenodo.15199559
and also may be installed from r-universe.

2. Originator

Murray G. Efford 
email: murray.efford@otago.ac.nz

ACCESS INFORMATION

1. Licenses/restrictions placed on the data: 

Creative Commons Attribution 4.0 International 

2. Recommended citation for this dataset: 

Efford, M. G. 2025. Simulations of overdispersed activity centres in spatially 
explicit capture--recapture.  [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15460421

DATA & CODE FILE OVERVIEW

Files in this repository
-----------------------------------------------------------------------------
README                   This file
Figures.R                R code for the simulations and Figures specifically 
                         reported in the text of Efford and Fletcher (2025).
Table.R                  R code for the simulations of spatial replication
                         in text Table 1 of Efford and Fletcher (2025).       
*.RData                  R data files output from overdispsim as listed below. 
overdispsim-vignette.pdf Vignette for 'overdispsim' that provides a detailed 
                         account of the simulations and includes R code to 
                         download and summarise the *.RData files
-----------------------------------------------------------------------------

Specific .RData files

File           AC distribution             Model fitted 
------------------------------------------------------------------
sims1.RData    LGCP                        none 
sims2.RData    Thomas process              none
sims3.RData    random habitat              none
sims1f.RData   fixed-N(A) LGCP             none
sims2f.RData   fixed-N(A) Thomas process   none
sims3f.RData   fixed-N(A) random habitat   none
sims1M.RData   LGCP                        full likelihood
sims2M.RData   Thomas process              full likelihood
sims3M.RData   random habitat              full likelihood
sims1fM.RData  fixed-N(A) LGCP             full likelihood
sims2fM.RData  fixed-N(A) Thomas process   full likelihood
sims3fM.RData  fixed-N(A) random habitat   full likelihood
sims1MCL.RData LGCP                        conditional likelihood
sims2MCL.RData Thomas process              conditional likelihood
sims3MCL.Rdata random habitat              conditional likelihood

Supplementary 'cohesion' simulations

File            AC distribution        Model fitted 
-------------------------------------------------------------
sims2C.RData    Thomas process         none
sims2Cf.RData   fixed cluster process  none
sims2CCL.RData  Thomas process         conditional likelihood
sims2CfCL.RData fixed cluster process  conditional likelihood

SOFTWARE VERSIONS

Simulations were mostly performed in R 4.3.2 with secr 4.6.5 and secrdesign 
2.8.2 in late 2023. However, LGCP and some Thomas simulations were repeated in 
2025 with a later version of spatstat.random (3.3.3012), and pre-CRAN versions 
secr 5.2.2 and secrdesign 2.9.3 (all available on r-universe).
(Note that spatstat.random changed its algorithm for rLGCP in the interim, 
resulting in slight differences in the random number stream, and 3.3.3012 
provided a native conditional simulation of the Thomas and LGCP processes).


