Towards biologically realistic estimates of home range and spatial exposure for colonial animals - Holly I. Niven; Jana W. E. Jeglinski; Geert Aarts; Ewan D. Wakefield; Jason Matthiopoulos (Methods in Ecology and Evolution)
Abstract Mobile colonial animals are particularly vulnerable to localised stressors around their colonies. Accurate home range (HR) estimation is therefore fundamental for spatial risk assessment. HRs are shaped by complex interactions between landscape permeability to movement and spatial resource competition between and within colonies, which are challenging to implement with density estimation methods (e.g. kernel smoothing) or species distribution models. We propose a new HR estimation method for colonial animals that accounts for such spatially complex interactions without computationally expensive individual‐based modelling (IBM). We present a model for colony space use following mechanistic rules of (1) heterogeneous landscape permeability, (2) between‐ and within‐colony density‐dependent competition, (3) flexible definitions of overlap between colonies, and (4) secondary space use due to commuting. Using the example of Northern gannets (Morus bassanus) foraging around the British Isles, we show how model parameters can be fitted to a small subset of tracking data from a colony network and how resulting estimated HRs can be used to derive colony‐specific exposure to a spatial stressor (offshore wind farms). Validation with simulated data showed a high level of overlap between true and estimated HRs and no significant difference between true and estimated colony‐specific exposure to an example stressor. Estimated gannet HRs showed striking similarities to tracking data from 10 gannet colonies. Our model assigned 73% of tracking locations to their correct colonies, compared to 41% and 31% from HRs derived from two approaches commonly used for risk assessments. These methods also underestimated exposure compared to our model‐derived HR. In contrast to industry‐standard approaches, our method relies neither on exhaustive tracking from all colonies nor on computer‐intensive IBMs. Rather, it can predict HRs from colony size estimates and locations and can be flexibly tuned to different species' characteristics to investigate fundamental and applied questions on colonial space‐use patterns.