Mapping behavioral landscapes for animal movement: a finite mixture modeling approach

Abstract

Abstract. Because of its role in many ecological processes, movement of animals in response to landscape features is an important subject in ecology and conservation biology. In this paper, we develop models of animal movement in relation to objects or fields in a landscape. We took a finite mixture modeling approach in which the component densities are conceptually related to different choices for movement in response to a landscape feature, and the mixing proportions are related to the probability of selecting each response as a function of one or more covariates. We combined particle swarm optimization and an expectationmaximization (EM) algorithm to obtain maximum-likelihood estimates of the model parameters. We used this approach to analyze data for movement of three bobcats in relation to urban areas in southern California, USA. A behavioral interpretation of the models revealed similarities and differences in bobcat movement response to urbanization. All three bobcats avoided urbanization by moving either parallel to urban boundaries or toward less urban areas as the proportion of urban land cover in the surrounding area increased. However, one bobcat, a male with a dispersal-like large-scale movement pattern, avoided urbanization at lower densities and responded strictly by moving parallel to the urban edge. The other two bobcats, which were both residents and occupied similar geographic areas, avoided urban areas using a combination of movements parallel to the urban edge and movement toward areas of less urbanization. However, the resident female appeared to exhibit greater repulsion at lower levels of urbanization than the resident male, consistent with empirical observations of bobcats in southern California. Using the parameterized finite mixture models, we mapped behavioral states to geographic space, creating a representation of a behavioral landscape. This approach can provide guidance for conservation planning based on analysis of animal movement data using statistical models, thereby linking connectivity evaluations to empirical data.

An agent‐based movement model to assess the impact of landscape fragmentation on disease transmission

“…Importantly, however, our models predict that if the matrix between habitat fragments is somewhat permeable to animal movement, which might be the case for all but the most fragmentation-sensitive species, then high rates of between-patch disease transmission can result, even in highly fragmented landscapes. Bobcats in southern California tend to avoid urban areas, but will occasionally navigate across the urban matrix to visit disjunct habitat patches (Crooks 2002, Riley et al 2003, Riley et al 2010, Tracey et al 2013). As such, the actual permeability of the urban matrix in coastal southern California for bobcats is most consistent with the very low to low classification of non-habitat v www.esajournals.org permeability in our models (Tracey et al 2013).…”

“…Bobcats in southern California tend to avoid urban areas, but will occasionally navigate across the urban matrix to visit disjunct habitat patches (Crooks 2002, Riley et al 2003, Riley et al 2010, Tracey et al 2013). As such, the actual permeability of the urban matrix in coastal southern California for bobcats is most consistent with the very low to low classification of non-habitat v www.esajournals.org permeability in our models (Tracey et al 2013). GPS-collared bobcats in southern California typically engage in movement behavior that is consistent with point attraction (e.g., the PA d¼1000 rule) if they are residents or directional movement (e.g., the CRW k¼5 rule) if they are dispersers (Tracey et al 2013;unpublished data).…”

“…To facilitate comparison between simulated and actual landscapes, we computed the proportion of habitat and the fractal dimension of habitat patches for our southern California study area in coastal Orange County south of Los Angeles where we have conducted GPS telemetry studies on bobcats since 2002 (Riley et al 2010, Tracey et al 2013. Land cover data for our study area were compiled from land cover and impervious surface data from the National Land Cover Database (NLCD; Homer et al 2004) and land use from the Southern California Association of Governments (SCAG, http://www.scag.ca.…”

“…The movement rules have two components: directionality and non-habitat permeability. Data gathered from studies of radio-and GPS-collared bobcats in the region (Riley et al 2003, Riley et al 2010, Tracey et al 2013J. A. Tracey, unpublished data) informed the three types of directionality used in the move behavior rules (Table 1): a simple random walk (SRW rule), a correlated random walk (CRW rule), and point attraction (PA rule).…”

“…Bobcats are wideranging, fragmentation-sensitive carnivores; thus, they are excellent focal species for investigations of the impacts of urbanization in southern California and elsewhere (Laurenson et al 1998, Crooks 2002, Tigas et al 2002, Riley et al 2003, Ruell et al 2009). Intensive radio-and GPS telemetry studies have been conducted on the spatio-temporal movement patterns and habitat use of bobcats in urban areas near Los Angeles (Riley et al 2003, Riley et al 2010, Tracey et al 2013; these animals have also been screened for seroprevalence of multiple pathogens, including feline immunodeficiency virus (FIV; Franklin et al 2007, Bevins et al 2012, Lee et al 2012.…”