Understanding spatially explicit capture–recapture parameters for informing invasive animal management

Abstract

Spatially explicit capture-recapture modeling is used to estimate population density to enhance our ecological understanding and management of wildlife populations. The two primary parameters estimated in the capture process of these models are σ and g 0 . The σ parameter is the standard deviation of a bivariate normal home range kernel (indicating home range size), while g 0 is the probability of capture by a device placed at the home range center. These parameters are being increasingly generalized and used in simulation models to predict the detection or capture rates of invasive animals to inform management strategies. Given the sensitivity of simulation model predictions to parameter values, we performed an analysis of preexisting GPS telemetry and trapping data of invasive brushtail possums (Trichosurus vulpecula) across New Zealand to address the following three questions. First, how does σ vary with population density, habitat, and age-sex class? Second, how is g 0 influenced by home range size (i.e., σ) and trap type? Third, how does the predicted probability of capture or detection of individuals vary with σ, different trap types and trap densities? We used data from 180 possums across 18 sites to develop a Bayesian hierarchical model. Results showed that σ decreased with increasing population density and increasing area of productive grassland. There was a strong negative relationship between σ and g 0 , and g 0 was highest for cage traps and lowest for raised leg-hold traps. Despite the potential compensatory inverse effect of g 0 with σ, the probability of capturing a randomly located possum by a large array of traps increased with increasing σ. Results show that selection of σ for predictive simulation modeling should begin with an estimated population density. The associated g 0 should then be identified as a function of σ, and stochasticity should be incorporated to account for inter-individual variability. The approach employed here provides a methodology for estimating density, σ, and g 0 using trapping and telemetry data, and our results will help guide careful consideration of density, σ, and g 0 to improve the accuracy of simulation studies across species.

Eradicating an invasive mammal requires local elimination and reduced reinvasion from an urban source population

“…However, we acknowledge that there are gaps in our understanding of urban landscapes and the organisms that occupy them that will affect model outputs. We used mean values of home range size and trapping parameters ( and ), despite knowing that these vary by individual, across habitats, and by device type (Anderson, Rouco, et al, 2022; Latham et al, 2022; Mackenzie et al, 2022). Indeed, new behavioral syndromes can be selected for in urban areas (Lowry et al, 2013), potentially leading to individuals that are more or less likely to be trapped (bold or wary) (Garvey et al, 2020).…”

“…The effect of a heterogeneous landscape structure on target species' behavior and population dynamics might be complex (O'Reilly- Nugent et al, 2016;With, 2002), reducing the capacity for managers to anticipate the probability of elimination or reinvasion. For example, trap layouts based on an average home range size would fail to eliminate all individuals if home range size and shape varied across individuals and habitats (Anderson, Rouco, et al, 2022). Similarly, reinvasion pressure might be underestimated if combinations of habitats facilitate dispersal (O'Reilly- Nugent et al, 2016).…”

Invasive species eradication: How do we declare success?

“…Values for the spatially explicit detection parameters (𝑔 0 and 𝜎) of animals in monitoring devices can be obtained from published reports, experimental or field studies (Efford 2004;Ball et al 2005;Ramsey et al 2015;Anderson et al 2022b) or expert opinion (Anderson et al 2022a). Similarly, detection experiments have typically been used to estimate the probability of weed detection given a certain amount of search effort (Garrard et al 2008;Hauser et al 2022).…”

Spatially explicit capture-recapture estimate of hedgehog population density in exotic grassland, New Zealand

“…Capture-recapture methods provide a more robust estimate of population density by estimating the unsampled fraction of the population, while spatially explicit capturerecapture (SECR) models also account for variable detectability of animals associated with their movements relative to trap locations (Efford 2004;Efford & Fewster 2013). Spatially explicit capture-recapture estimates density and parameters that are needed to predict the detection or capture rates of potential surveillance and trapping regimes (Anderson et al 2022). These spatial detection parameters are known as σ (the spatial decay parameter for a half-normal home-range kernel to model the decline in encounter probability with distance between the home-range centre and trap), and ɡ 0 (the nightly probability of a hedgehog being captured in a trap at the centre of its home range).…”