Pronounced Fidelity and Selection for Average Conditions of Calving Area Suggestive of Spatial Memory in a Highly Migratory Ungulate

Matthew D. Cameron,Kyle Joly,Christa P. H. Mulder,Greg A. Breed,Knut Kielland

doi:10.3389/fevo.2020.564567

Matthew D. Cameron, Kyle Joly + Show 3 more

Open Access

https://doi.org/10.3389/fevo.2020.564567

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Abstract

A distinguishing characteristic of many migratory animals is their annual return to distinct calving (birthing) areas in the spring, yet the navigational mechanisms employed during migration that result in this pattern are poorly understood. Effective conservation of these species requires reliable delineation of such areas, quantifying the factors that influence their selection, and understanding the underlying mechanisms resulting in use of calving areas. We used barren-ground caribou (Rangifer tarandus granti) as a study species and identified calving sites of the Western Arctic Herd in Alaska using GPS collar data from 2010–2017. We assessed variability in calving areas by comparing spatial delineations across all combinations of years. To understand calving area selection at a landscape scale, we performed a resource selection analysis comparing calving sites to available locations across the herd’s range and incorporated time-varying, remotely sensed metrics of vegetation quality and quantity. We found that whereas calving areas varied from year to year, this annual variation was centered on an area of recurring attraction consistent with previous studies covering the last six decades. Calving sites were characterized by high-quality forage at the average time of calving, but not peak calving that year, and by a narrow range of distinct physiographic factors. Each year, calving sites were located on areas of above-average conditions based on our predictive model. Our findings indicate that the pattern of spring migration for pregnant females was to migrate to areas that consistently provide high-quality forage when averaged across years, and then upon arriving at this calving ground, refine selection using their perception of annually varying conditions that are driven by environmental stochasticity. We suggest that the well-documented and widespread pattern of fidelity to calving grounds by caribou is supportive of a navigational mechanism based on spatial memory at a broad scale to optimize foraging and energy acquisition at a critical life-history stage. The extent to which migrants depend on memory to reach their spring destinations has implications for the adaptability of populations to changing climate and human impacts.

Highlights

Migration is a behavioral adaptation to seasonal environmental conditions and resource availability (Alerstam et al, 2003; Avgar et al, 2014)
Our goals were to (1) document spatial trends in the calving areas of the Western Arctic Herd (WAH), (2) investigate the landscape-level factors influencing selection for calving sites to better understand the emergent spatial patterns of calving areas, and (3) interpret our findings to better understand what navigational mechanisms could explain the phenomenon of fidelity of caribou to their calving grounds
The WAH utilizes over 350,000 km2 of northwestern Alaska, typically migrating from wintering areas in the south, which vary by year and individual, to the calving ground and summer range in the north (Figure 2; Lent, 1966; Dau, 2015, Joly and Cameron, 2019)

Summary

Introduction

Migration is a behavioral adaptation to seasonal environmental conditions and resource availability (Alerstam et al, 2003; Avgar et al, 2014). Examples of perception-based movement include animals “surfing a green wave” of high-quality forage as it moves across a spatial gradient (van der Graaf et al, 2006; Merkle et al, 2016; Aikens et al, 2017), whereas memory-based movements are characterized by animals moving independently of proximal resource gradients and moving to distant areas of high-quality resources (Howery et al, 1999; Polansky et al, 2015; Bracis and Mueller, 2017) Because these navigational processes cannot be directly measured in wild animals, inferring their relative influence from movement data requires integrating empirical observations with theoretical and experimental findings (Fagan et al, 2013)

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