A stochastic movement model reproduces patterns of site fidelity and long-distance dispersal in a population of Fowler’s toads (Anaxyrus fowleri)

Dispersal without drivers: Intrinsic and extrinsic variables have no impact on movement distances in a terrestrial amphibian

Dispersive movements are often thought to be multicausal and driven by individual body size, sex, conspecific density, environmental variation, personality, and/or other variables. Yet such variables often do not account for most of the variation among dispersive movements in nature, leaving open the possibility that dispersion may be indeterministic. We assessed the amount of variation in 24 h movement distances that could be accounted for by potential drivers of displacement with a large empirical dataset of movement distances performed by Fowler's Toads (Anaxyrus fowleri) on the northern shore of Lake Erie at Long Point, Ontario (2002-2021, incl.). These toads are easy to sample repeatedly, can be identified individually and move parallel to the shoreline as they forage at night, potentially dispersing to new refuge sites. Using a linear mixed-effect model that incorporated random effect terms to account for sampling variance and inter-annual variation, we found that all potential intrinsic and extrinsic drivers of movement accounted for virtually none of the variation observed among 24 h distances moved by these animals, whether over short or large spatial scales. We examined the idea of movement personality by testing variance per individual toad and found no evidence of individuality in movement distances. We conclude that deterministic variables, whether intrinsic or extrinsic, neither can be shown to nor are necessary to drive movements in this population over all spatial scales. Stochastic, short time-scale movements, such as daily foraging movements, can instead accumulate over time to produce large spatial-scale movements that are dispersive in nature.

Individual Network Topology of Patch Selection Under Influence of Drifting Site Fidelity

Network theory has led to important insight into statistical-mechanical aspects of systems showing scaling complexity. I apply this approach to simulate the behavior of animal space use under the influence of memory and site fidelity. Based on the parsimonious Multi-scaled random walk model (MRW) an emergent property of self-reinforcing returns to a subset of historic locations shows how a network of nodes grows into an increased hierarchical depth of site fidelity. While most locations along a movement path may have a low revisit probability, habitat selection is maturing with respect to utilization of the most visited patches, in particular for patches that emerge during the early phase of node development. Using simulations with default MRW properties, which have been shown to produce space use in close statistical compliance with utilization distributions of many species of mammals, I illustrate how a shifting spatio-temporal mosaic of habitat utilization may be described statistically and given behavioral-ecological interpretation. The proposed method is illustrated with a pilot study using black bear Ursus americanus telemetry fixes. One specific parameter, the Characteristic Scale of Space Use, is here shown to express strong resilience against shifting site fidelity. This robust result may seem counter-intuitive, but is logical under the premise of the MRW model and its relationship to site fidelity, whether stable or shifting spatially over time. Thus, spatial analysis of the dynamics of a gradually drifting site fidelity using simulated scenarios may indirectly cast light on the dynamics of movement behavior as preferred patches are shifting over time. Both aspects of complex space use, network topology and dynamically drifting dispersion of site fidelity, provide in tandem important descriptors of behavioral ecology with relevance to habitat selection.

Toads use the subsurface thermal gradient for temperature regulation underground

As ectotherms with moist, permeable skins, amphibians continually seek a physiological balance between maintaining hydration and optimizing body temperature. Laboratory studies have suggested that dehydrated and starved amphibians should select cooler temperatures to slow the rate of water loss and reduce metabolism. However, much less is known about amphibian thermoregulatory behaviour in the wild, where environmental conditions and constraints may be more variable. In seasonally cold environments, where animals must maximize growth, gamete production and/or fat storage for winter dormancy over a short active season, maintaining a high metabolic rate may be primary. We investigated the thermoregulatory behaviour of the Fowler's Toads, Anaxyrus fowleri, in the wild at their northern range limit at Long Point, Ontario. We outfitted adult toads with small temperature loggers and radio-tracked them for periods of 24 hours. Simultaneously, we also recorded air and subsurface temperatures to a depth of 18.6 cm. When active at night, toads rapidly equilibrated with ambient air temperatures. However, during the day, resting toads selected and maintained body temperatures around 30 °C during the heat of the day by adjusting the depth to which they were buried. This strongly suggests that they behaviourally thermoregulate during their resting hours to maintain a high metabolic rate without regard to the dryness of their immediate surroundings.

Calibrating an individual-based movement model to predict functional connectivity for little owls

Dispersal is crucial for population viability and thus a popular target for conservation measures. However, the ability of individuals to move between habitat patches is notoriously difficult to estimate. One solution is to quantify functional connectivity via realistic individual-based movement models. Such simulation models, however, are difficult to build and even more difficult to parameterize. Here, we use the example of natal little owl (Athene noctua) dispersal to develop a new analysis chain for the calibration of individual-based dispersal models using a hybrid of statistical parameter estimation and Approximate Bayesian Computation (ABC). Specifically, we use locations of 126 radio-tracked juveniles to first estimate habitat utilization by generalized additive models (GAMs) and the biased random bridges (BRB) method. We then include the estimated parameters in a spatially explicit individual-based model (IBM) of little owl dispersal and calibrate further movement parameters using ABC. To derive efficient summary statistics, we use a new dimension reduction method based on random forest (RF) regression. Finally, we use the calibrated IBM to predict the dispersal potential of little owls from local populations in southwestern Germany to suitable habitat patches in northern Switzerland. We show that pre-calibrating habitat preference parameters while inferring movement behavioral parameters via ABC is a computationally efficient solution to obtain a plausible IBM parameterization. We also find that dimension reduction via RF regression outperforms the widely used least squares regression, which we applied as a benchmark approach. Estimated movement parameters for the individuals reveal plausible inter-individual and inter-sexual differences in movement behavior during natal dispersal. In agreement with a sex-biased dispersal distance in little owls, females show longer individual flights and higher directional persistence. Simulations from the fitted model indicate that a (re)colonization of northern Switzerland is generally possible, albeit restricted. We conclude that the presented analysis chain is a sensible work-flow to assess dispersal connectivity across species and ecosystems. It embraces species- and individual-specific behavioral responses to the landscape and allows likelihood-based calibration, despite an irregular sampling design. Our study highlights existing, yet narrow dispersal corridors, which may require enhancements to facilitate a recolonization of little owl habitat patches in northern Switzerland.