Jeff A. Tracey

Permeability of Roads to Movement of Scrubland Lizards and Small Mammals

A primary objective of road ecology is to understand and predict how roads affect connectivity of wildlife populations. Road avoidance behavior can fragment populations, whereas lack of road avoidance can result in high mortality due to wildlife-vehicle collisions. Many small animal species focus their activities to particular microhabitats within their larger habitat. We sought to assess how different types of roads affect the movement of small vertebrates and to explore whether responses to roads may be predictable on the basis of animal life history or microhabitat preferences preferences. We tracked the movements of fluorescently marked animals at 24 sites distributed among 3 road types: low-use dirt, low-use secondary paved, and rural 2-lane highway. Most data we collected were on the San Diego pocket mouse (Chaetodipus fallax), cactus mouse (Peromyscus eremicus), western fence lizard (Sceloporus occidentalis), orange-throated whiptail (Aspidoscelis hyperythra), Dulzura kangaroo rat (Dipodomys simulans) (dirt, secondary paved), and deer mouse (Peromyscus maniculatus) (highway only). San Diego pocket mice and cactus mice moved onto dirt roads but not onto a low-use paved road of similar width or onto the highway, indicating they avoid paved road substrate. Both lizard species moved onto the dirt and secondary paved roads but avoided the rural 2-lane rural highway, indicating they may avoid noise, vibration, or visual disturbance from a steady flow of traffic. Kangaroo rats did not avoid the dirt or secondary paved roads. Overall, dirt and secondary roads were more permeable to species that prefer to forage or bask in open areas of their habitat, rather than under the cover of rocks or shrubs. However, all study species avoided the rural 2-lane highway. Our results suggest that microhabitat use preferences and road substrate help predict species responses to low-use roads, but roads with heavy traffic may deter movement of a much wider range of small animal species.

A Set of Nonlinear Regression Models for Animal Movement in Response to a Single Landscape Feature

The study of individual animal movement in relation to objects in a landscape is important in many areas of ecology and conservation biology. Yet, many of the models used by ecologists do not account for landscape features and thus may not be conducive to analysis of animal movement data. This article develops a set of nonlinear regression models for both move angles and move distances in relation to a single object in the landscape. Our models incorporate the concept of perceptual range from theories of animal movement behavior. We describe numerical methods for obtaining the maximum likelihood estimates of the model parameters. For illustration, we show results from both computer simulated data and real movement data collected for a red diamond rattlesnake (Crotalus ruber) via radio telemetry field techniques.

Movement-based estimation and visualization of space use in 3D for wildlife ecology and conservation

Advances in digital biotelemetry technologies are enabling the collection of bigger and more accurate data on the movements of free-ranging wildlife in space and time. Although many biotelemetry devices record 3D location data with x, y, and z coordinates from tracked animals, the third z coordinate is typically not integrated into studies of animal spatial use. Disregarding the vertical component may seriously limit understanding of animal habitat use and niche separation. We present novel movement-based kernel density estimators and computer visualization tools for generating and exploring 3D home ranges based on location data. We use case studies of three wildlife species – giant panda, dugong, and California condor – to demonstrate the ecological insights and conservation management benefits provided by 3D home range estimation and visualization for terrestrial, aquatic, and avian wildlife research.

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

Landscape changes can result in habitat fragmentation and reduced landscape connectivity, limiting the ability of animals to move across space and altering infectious disease dynamics in wildlife. In this study, we develop and implement an agent-based model to assess the impacts of animal movement behavior and landscape structure on disease dynamics. We model a susceptible/infective disease state system applicable to the transmission of feline immunodeficiency virus in bobcats in the urbanized landscape of coastal southern California. Our agent-based model incorporates animal movement behavior, pathogen prevalence, transmission probability, and habitat fragmentation to evaluate how these variables influence disease spread in urbanizing landscapes. We performed a sensitivity analysis by simulating the system under 4200 different combinations of model parameters and evaluating disease transmission outcomes. Our model reveals that host movement behavior and response to landscape features play a pivotal role in determining how habitat fragmentation influences disease dynamics. Importantly, interactions among habitat fragmentation and movement had non-linear and counter-intuitive effects on disease transmission. For example, the model predicts that an intermediate level of non-habitat permeability and directionality will result in the highest rates of between-patch disease transmission. Agent-based models serve as computational laboratories that provide a powerful approach for quantitatively and visually exploring the role of animal behavior and anthropogenic landscape change on contacts among agents and the spread of disease. Such questions are challenging to study empirically given that it is difficult or impossible to experimentally manipulate actual landscapes and the animals and pathogens that move through them. Modeling the relationship between habitat fragmentation, animal movement behavior, and disease spread will improve understanding of the spread of potentially destructive pathogens through wildlife populations, as well as domestic animals and humans.

Urban Habitat Fragmentation and Genetic Population Structure of Bobcats in Coastal Southern California

Abstract Although habitat fragmentation is recognized as a primary threat to biodiversity, the effects of urban development on genetic population structure vary among species and landscapes and are not yet well understood. Here we use non-invasive genetic sampling to compare the effects of fragmentation by major roads and urban development on levels of dispersal, genetic diversity, and relatedness between paired bobcat populations in replicate landscapes in coastal southern California. We hypothesized that bobcat populations in sites surrounded by urbanization would experience reduced functional connectivity relative to less isolated nearby populations. Our results show that bobcat genetic population structure is affected by roads and development but not always as predicted by the degree that these landscape features surround fragments. Instead, we suggest that urban development may affect functional connectivity between bobcat populations more by limiting the number and genetic diversity of source populations of migrants than by creating impermeable barriers to dispersal.

Inter-Individual Variability of Stone Marten Behavioral Responses to a Highway

Efforts to reduce the negative impacts of roads on wildlife may be hindered if individuals within the population vary widely in their responses to roads and mitigation strategies ignore this variability. This knowledge is particularly important for medium-sized carnivores as they are vulnerable to road mortality, while also known to use available road passages (e.g., drainage culverts) for safely crossing highways. Our goal in this study was to assess whether this apparently contradictory pattern of high road-kill numbers associated with a regular use of road passages is attributable to the variation in behavioral responses toward the highway between individuals. We investigated the responses of seven radio-tracked stone martens (Martes foina) to a highway by measuring their utilization distribution, response turning angles and highway crossing patterns. We compared the observed responses to simulated movement parameterized by the observed space use and movement characteristics of each individual, but naïve to the presence of the highway. Our results suggested that martens demonstrate a diversity of responses to the highway, including attraction, indifference, or avoidance. Martens also varied in their highway crossing patterns, with some crossing repeatedly at the same location (often coincident with highway passages). We suspect that the response variability derives from the individuals familiarity of the landscape, including their awareness of highway passage locations. Because of these variable yet potentially attributable responses, we support the use of exclusionary fencing to guide transient (e.g., dispersers) individuals to existing passages to reduce the road-kill risk.

Modeling and inference of animal movement using artificial neural networks

Movement of animals in relation to objects in their environment is important in many areas of ecology and wildlife conservation. Tools for analysis of movement data, however, still remain rather limited. In previous work, we developed nonlinear regression models for movement in relation to a single landscape feature. Here we greatly expand these previous models by using artificial neural networks. The new models add substantial flexibility and capabilities, including the ability to incorporate multiple factors and covariates. We devise a likelihood-based model fitting procedure that utilizes genetic algorithms and demonstrate the approach with movement data for red diamond rattlesnakes. The proposed methodology can be useful for global positioning system tracking data that are becoming more common in studies of animal movement behavior.

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

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 expectation-maximization (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.

Wild Felids as Hosts for Human Plague, Western United States

Plague seroprevalence was estimated in populations of pumas and bobcats in the western United States. High levels of exposure in plague-endemic regions indicate the need to consider the ecology and pathobiology of plague in nondomestic felid hosts to better understand the role of these species in disease persistence and transmission.

Setting priorities for private land conservation in fire-prone landscapes: Are fire risk reduction and biodiversity conservation competing or compatible objectives?

Although wildfire plays an important role in maintaining biodiversity in many ecosystems, fire management to protect human assets is often carried out by different agencies than those tasked for conserving biodiversity. In fact, fire risk reduction and biodiversity conservation are often viewed as competing objectives. Here we explored the role of management through private land conservation and asked whether we could identify private land acquisition strategies that fulfill the mutual objectives of biodiversity conservation and fire risk reduction, or whether the maximization of one objective comes at a detriment to the other. Using a fixed budget and number of homes slated for development, we simulated 20 years of housing growth under alternative conservation selection strategies, and then projected the mean risk of fires destroying structures and the area and configuration of important habitat types in San Diego County, California, USA. We found clear differences in both fire risk projections and biodiversity impacts based on the way conservation lands are prioritized for selection, but these differences were split between two distinct groupings. If no conservation lands were purchased, or if purchases were prioritized based on cost or likelihood of development, both the projected fire risk and biodiversity impacts were much higher than if conservation lands were purchased in areas with high fire hazard or high species richness. Thus, conserving land focused on either of the two objectives resulted in nearly equivalent mutual benefits for both. These benefits not only resulted from preventing development in sensitive areas, but they were also due to the different housing patterns and arrangements that occurred as development was displaced from those areas. Although biodiversity conflicts may still arise using other fire management strategies, this study shows that mutual objectives can be attained through land-use planning in this region. These results likely generalize to any place where high species richness overlaps with hazardous wildland vegetation.