Modeling Behavior by Coastal River Otter (Lontra Canadensis) in Response to Prey Availability in Prince William Sound, Alaska: A Spatially-Explicit Individual-Based Approach

Abstract

Effects of climate change on animal behavior and cascading ecosystem responses are rarely evaluated. In coastal Alaska, social river otters (Lontra Canadensis), largely males, cooperatively forage on schooling fish and use latrine sites to communicate group associations and dominance. Conversely, solitary otters, mainly females, feed on intertidal-demersal fish and display mutual avoidance via scent marking. This behavioral variability creates “hotspots” of nutrient deposition and affects plant productivity and diversity on the terrestrial landscape. Because the abundance of schooling pelagic fish is predicted to decline with climate change, we developed a spatially-explicit individual-based model (IBM) of otter behavior and tested six scenarios based on potential shifts to distribution patterns of schooling fish. Emergent patterns from the IBM closely mimicked observed otter behavior and landscape use in the absence of explicit rules of intraspecific attraction or repulsion. Model results were most sensitive to rules regarding spatial memory and activity state following an encounter with a fish school. With declining availability of schooling fish, the number of social groups and the time simulated otters spent in the company of conspecifics declined. Concurrently, model results suggested an elevation of defecation rate, a 25% increase in nitrogen transport to the terrestrial landscape, and significant changes to the spatial distribution of “hotspots” with declines in schooling fish availability. However, reductions in availability of schooling fish could lead to declines in otter density over time.

Dynamics, Persistence, and Genetic Management of the Endangered Florida Panther Population

“…We investigated Florida panther population dynamics and persistence using 2 complementary modeling frameworks: matrix population models (Caswell ) and IBMs (Grimm and Railsback , McLane et al , Railsback and Grimm , Albeke et al ). Matrix population models offer a flexible and powerful framework for investigating the dynamics and persistence of age‐ or stage‐structured populations (e.g., Caswell , Robinson et al , Kohira et al , Hunter et al , Hostetler et al ).…”

“…Despite many advantages offered by matrix population models, it is difficult to incorporate attributes of individuals such as genetics or behavior within that framework. Agent‐based or IBMs (Grimm , Grimm and Railsback , McLane et al , Railsback and Grimm , Albeke et al ) offer an alternative modeling framework with tremendous flexibility. Individual‐based models are computer simulation models that rely on a bottom‐up approach that begins by explicitly considering the components of a system (i.e., individuals); population‐level properties emerge from the behavior of, and interactions among, discrete individuals.…”

“…Individual‐based models are computer simulation models that rely on a bottom‐up approach that begins by explicitly considering the components of a system (i.e., individuals); population‐level properties emerge from the behavior of, and interactions among, discrete individuals. Using IBMs, it is possible to explicitly represent attributes of individuals such as movement, mating, or genetics (McLane et al , Railsback and Grimm , Albeke et al ). We used individual‐based population models as the primary population modeling approach because they offered a framework for an explicit consideration of genetics both at individual and population levels.…”

Spatial Demographic Models to Inform Conservation Planning of Golden Eagles in Renewable Energy Landscapes

“…Additionally, the process of developing a mechanistic population model demands that authors make explicit assumptions about system dynamics, which ultimately enhances transparency within a management context (Grimm 1999, Munns 2006. This process allows researchers to synthesize and extend knowledge gained from empirical field studies while allowing managers to understand and utilize scientific information in the pursuit of effective conservation policy (Katzner et al 2007, Schmolke et al 2010, Albeke et al 2015.…”

Indirect effects of bioinvasions in Yellowstone Lake: The response of river otters to declines in native cutthroat trout

“…Second, we considered a time-varying structure with φ as a linear function (on the logit scale) of precipitation in the study area during the months June, July, and August (the covariate precip; National Climatic Data Center, Wyoming Climate Division 1; http://lwf.ncdc.noaa.gov). Previous studies have found that climatic factors can affect the abundance of otters and their prey (e.g., Ruiz-Olmo et al, 2011;Albeke et al, 2015), so the precip covariate was included to test the hypothesis that apparent survival of otters was related to drought conditions present during the study (Koel et al, 2005;Teisberg et al, 2014). Finally, we modeled φ as a linear function of the annual number of spawning trout in Clear Creek (the covariate spawners; Koel et al, 2012), which we assumed was representative of cutthroat trout abundance throughout our study area.…”