Development of an individual-based model to evaluate elk (Cervus elaphus nelsoni) movement and distribution patterns following the Cerro Grande Fire in north central New Mexico, USA

Abstract

Though studies have modeled the effects of fires on elk, no studies have related the effects of post-fire landscape succession on ungulate movements and distribution using dynamic modeling techniques. The purpose of this study was to develop and test a spatially-explicit, stochastic, individual-based model (IBM) to evaluate potential movement and distribution patterns of elk (Cervus elaphus nelsoni) in relation to spatial and temporal aspects of the Cerro Grande Fire that burned north central New Mexico in May of 2000. Following extensive literature review, the SAVANNA Ecosystem Model was selected to simulate the underlying post-fire successional processes driving elk movement and distribution. Standard logisitic regression was used to analyze habitat-use patterns of ten elk from data collected using global positioning system radio collars while an additional five animals were used as an independent test set during model validation. Static variables in the form of roads, buildings, fences, and habitual use/memory were used to modify a map of impedance values based on the logistic regression of slope, aspect, and elevation. Integration with SAVANNA came through the application of a habitat suitability index (HSI), which combined movement rules written for the IBM and variables modified and produced by the dynamic ecological processes run in SAVANNA. Overall pattern analysis indicated that realistic migrational processes and habitat-use patterns emerged from movement rules incorporated into the IBM in response to advancing and receding snow when compared to the independent test set. Primary and secondary movement pathways emerged from the collective responses of simulated individuals. Using regression analyses, no significant differences between simulated animals and animals used in either model development or an independent test set revealed any differences in response to snow patterns. These considerations suggest the model was adequately corroborated based on existing data and outlined objectives.

Introduction

Long-term studies on the movement and distribution patterns of species at local and regional scales are needed because those are the scales at which conservation strategies are planned and implemented (Saunders and Hobbs, 1991). In early May 2000, the Cerro Grande Fire (CGF) in north central New Mexico burned approximately 19,020 ha as well as 400 residences in the town of Los Alamos. That fire, coupled with the region's unique fire history and interagency collaborations, presented a unique opportunity to study the long-term ecological consequences of large-scale fires on the regional elk (Cervus elaphus nelsoni) herd. Consequently, a “Participating Agreement” was signed by the Santa Fe National Forest (USFS), U.S. Department of Energy's Los Alamos National Laboratory (LANL), and the National Park Service (BNM) to collaborate in data collection efforts to evaluate and mitigate potential changes in movement and distribution patterns of elk following the Cerro Grande Fire.

Though many methods are available for modeling animal movements and distribution (e.g., path analysis, fractal analysis, random walks, structural equation modeling), there has been a growing interest in the use of individual-based models (IBMs) in ecological applications. Individual-based approaches to modeling animal movements address principles that are largely ignored in other modeling environments. First, IBMs acknowledge that individuals are behaviorally and physiologically distinct because of genetic and environmental influences and second, they acknowledge that interactions among individuals are inherently localized (Slothower et al., 1996, Schank, 2001). An advantage to IBMs is that they do not require many of the simplifying assumptions and mathematical derivations typically needed in more aggregated models (Railsback et al., 1999) thus resulting in a more realistic representation of real-world phenomena.

Integrated models of disturbance and succession offer a means of comparing long-term effects of fire events on forest vegetation and other ecosystem processes, including animal movement and distribution that may otherwise be difficult to observe empirically (Keane et al., 1989, He and Mladenoff, 1999, Turner et al., 2001). In addition, successional models enable evaluation of the cumulative effects of management practices and ecosystem response in a spatial context over long time periods (Keane and Hann, 1998). Several approaches have been used to model post-fire succession (Keane and Long, 1998, Barrett, 2001, Turner et al., 2001) but current efforts are focused on stochastic approaches that examine the relationship between fire regimes and landscape heterogeneity as well as fire-affected landscape changes through time (He and Mladenoff, 1999). The majority of post-fire successional models are designed specifically for evaluating forest (i.e., tree) dynamics and not the understory component to the degree deemed critical for modeling elk movement and distribution. As a result, the temporal resolution of such models is often in the range of years to decades—much longer than the daily or seasonal time step desired to evaluate elk movement across the Jemez.

Though studies have evaluated the effects of fire scale and pattern on elk (C. elaphus) (Turner et al., 1994), no studies have related the effects of post-fire landscape succession on ungulate movements and distribution using dynamic modeling techniques. Consequently, models linking the responses of herbivores to environmental heterogeneity and successional dynamics following large-scale fires are needed (Turner et al., 1994). Therefore, the purpose of this study was twofold: (1) to identify, calibrate, and validate a model that could simulate the underlying post-fire successional processes driving elk movement and distribution following the CGF; (2) to develop and integrate into the post-fire successional model a spatially-explicit, stochastic, individual-based model to evaluate potential movement and distribution patterns of elk in relation to spatial and temporal aspects of the CGF. Conceptualization, development, integration, and validation of the individual-based model are discussed here. Identification, development, and validation of the post-fire successional model are described in Rupp (2005).