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

Abstract

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.

Unsustainable anthropogenic mortality disrupts natal dispersal and promotes inbreeding in leopards

“…While the PMC leopard population is currently recovering from high levels of anthropogenically‐linked mortality (Rogan et al, ), demographic‐based metrics alone do not reveal the loss of genetic diversity and the consequences this may have for the future health and viability of the population (Kendall et al, ). Our results thus further highlight the importance of population connectivity to ensure gene flow and genetic diversity through immigration (Fattebert, Robinson, et al, ; Frankham, ; Hauenstein et al, ).…”

“…Few protected areas sufficiently encompass the wide range of these species and large, solitary carnivores effectively confined to small reserves often suffer edge effects and even localized extinction (Woodroffe & Ginsberg, ). Our study demonstrates novel genetic consequences underlying this process and emphasizes the importance of managing and mitigating the effects of increasingly threatened protected areas and fragmented corridors of structurally suitable habitat that maintain effective connectivity (Fattebert, Balme, et al, ; Hauenstein et al, ; Kaiser, ).…”

A Practical Guide for Conducting Calibration and Decision-Making Optimisation with Complex Ecological Models

“…In decision tasks, an operational model is optimised to assess limit conditions (e.g., "what is the largest/smallest response of the system such that ..."), minimise a risk or evidence trade-offs. Note that methodologies have been proposed to assist model users in the construction of the objective functions, for example to choose the most relevant statistics for an ABC optimisation algorithm [8,26,85,125]. When data are qualitative (e.g.…”

Forecasting Seasonal Habitat Connectivity in a Developing Landscape

“…Dynamic connectivity can be modeled using different connectivity algorithms such as least-cost paths [20,21], resistant kernels [22], circuit theory [23,24], and, increasingly, individual-based movement models (IBMMs; e.g., [25,26]). In cost-path, kernel, and circuit theory approaches, resistance surfaces are typically derived for different temporal periods and connectivity is analyzed separately for each (e.g., [13,27]).…”

“…This allows simulated individuals to respond to a dynamic environment within a single model, resulting in a single summary output. Simulating sequential movements of individuals may be important for understanding movement response to future environmental conditions [30]-especially spatiotemporal dynamics of distributional shifts (e.g., range expansion, reintroductions) where the leading edges of species' distributions are conditional upon individual locations at a given point in time [26,31]. IBMMs can also be parameterized with empirical data allowing for realistic simulations of movement and behavior for a population of interest [32].…”