Linking behavioral states to landscape features for improved conservation management.

Maitreyi Sur,Todd C Esque,Kathleen Longshore,Brian Woodbridge,Peter H Bloom,Jim R Belthoff,Jeff A Tracey,Kenneth E Nussear,Robert N Fisher,Todd E Katzner,Melissa A Braham

doi:10.1002/ece3.7621

Abstract

A central theme for conservation is understanding how animals differentially use, and are affected by change in, the landscapes they inhabit. However, it has been challenging to develop conservation schemes for habitat‐specific behaviors.Here we use behavioral change point analysis to identify behavioral states of golden eagles (Aquila chrysaetos) in the Sonoran and Mojave Deserts of the southwestern United States, and we identify, for each behavioral state, conservation‐relevant habitat associations.We modeled behavior using 186,859 GPS points from 48 eagles and identified 2,851 distinct segments comprising four behavioral states. Altitude above ground level (AGL) best differentiated behavioral states, with two clusters of short‐distance movement behaviors characterized by low AGL (state 1 AGL = 14 m (median); state 2 AGL = 11 m) and two associated with longer‐distance movement behaviors and characterized by higher AGL (state 3 AGL = 108 m; state 4 AGL = 450 m).Behaviors such as perching and low‐altitude hunting were associated with short‐distance movements in updraft‐poor environments, at higher elevations, and over steeper and more north‐facing terrain. In contrast, medium‐distance movements such as hunting and transiting were over gentle and south‐facing slopes. Long‐distance transiting occurred over the desert habitats that generate the best updraft.This information can guide management of this species, and our approach provides a template for behavior‐specific habitat associations for other species of management concern.

Highlights

A central theme underpinning conservation is the need to understand how animals use, and are affected by change in, the landscapes they inhabit (Baldwin et al, 2018; Betts et al, 2019)
Management actions sometimes account for variation in habitat associations with time of year and individual age, developing conservation schemes for habitat use specific to different behavioral states presents a unique set of challenges
Altitude above ground level was the best differentiator among behavioral states (Table 1, Figure 2a), with two clusters characterized by low AGL (state 1 AGL = 14 m; state 2 AGL = 11 m; for means, see Table 1) and two by higher AGL (Wilcoxon–Mann–Whitney test for AGL of states 1 & 2 vs. states 3 & 4: z = 60.14, p

Summary

| INTRODUCTION

A central theme underpinning conservation is the need to understand how animals use, and are affected by change in, the landscapes they inhabit (Baldwin et al, 2018; Betts et al, 2019). We use BCPA to identify behavioral states of golden eagles in the Sonoran and Mojave Deserts of the southwestern United States, and we use this knowledge to understand, for each behavioral state, habitat associations relevant to species conservation In these deserts, Golden Eagles encounter threats from climate change and renewable energy development (Braham et al, 2015; Vandergast et al, 2013) and there is management interest in understanding how eagle behavior may influence their vulnerability to renewable energy development. Golden Eagles encounter threats from climate change and renewable energy development (Braham et al, 2015; Vandergast et al, 2013) and there is management interest in understanding how eagle behavior may influence their vulnerability to renewable energy development To address this information need, we used a BCPA and clustering to identify eagle behaviors, and subsequently, we asked if different behaviors occurred with equal frequencies in different habitat types. This analytical approach provides unique information that can augment recently implemented conservation strategies in the study area (CBI, 2013)

| METHODS

Findings

| DISCUSSION

| CONCLUSIONS