Comparing citizen science and professional data to evaluate extrapolated mountain goat distribution models

Elizabeth P Flesch,Jami J Belt

doi:10.1002/ecs2.1638

Abstract

AbstractCitizen science provides a prime opportunity for wildlife managers to obtain low‐cost data recorded by volunteers to evaluate species distribution models and address research objectives. Using mountain goat (Oreamnos americanus) location data collected through aerial surveys by professionals, ground surveys by professionals, and ground surveys by volunteers, we evaluated two mountain goat distribution models extrapolated across Waterton‐Glacier International Peace Park. In addition, we compared mountain goat location data by observer and survey type to determine whether there were differences that affected extrapolated model evaluation. We found that all dataset types compared similarly to both mountain goat models. A mountain goat occupancy model developed in the Greater Yellowstone Area (GYA) was the most informative in describing mountain goat locations. We compared Spearman‐rank correlations (rs) for occupancy probability bin ranks in the GYA model extrapolation and area‐adjusted frequencies of mountain goat locations, and we found that all datasets had a positive correlation, indicating the model had useful predictive ability. Aerial observations had a slightly greater Spearman‐rank correlation (rs = 0.964), followed by the professional ground surveys (rs = 0.946), and volunteer ground datasets (rs = 0.898). These results suggest that with effective protocol development and volunteer training, biologists can use mountain goat location data collected by volunteers to evaluate extrapolated models. We recommend that future efforts should apply this approach to other wildlife species and explore development of wildlife distribution models using citizen science.

Highlights

Building models to predict how environmental factors influence habitat selection of wildlife is a critical step in development of monitoring strategies and assessment of the effects of habitat changes on species distribution, such as those caused by climate change or human impact (Stillman and Brown 1994, Guisan and Zimmermann2000)
Over 95% of the observed mountain goat locations from volunteer ground, professional ground, and professional aerial survey platforms fell within the area predicted as suitable mountain goat habitat by both extrapolated models
When the Yellowstone model was validated in the Greater Yellowstone Area (GYA) using aerial survey locations, 72.1% of points were within suitable habitat, 85.8% of points were within 100 m of predicted suitable areas, and 92.5% of points were within 200 m of predicted suitable areas (DeVoe et al 2015)

Summary

Introduction

Building models to predict how environmental factors influence habitat selection of wildlife is a critical step in development of monitoring strategies and assessment of the effects of habitat changes on species distribution, such as those caused by climate change or human impact (Stillman and Brown 1994, Guisan and Zimmermann2000). FLESCH AND BELT ecological models can ideally be extended to inform ecological studies in different areas and enable conservation questions to be addressed across a broader landscape scale. The extrapolated model must be evaluated, as landscape features in the new study area may affect species in different ways and at dissimilar spatial scales (Wiens 1989, Hobbs 2003, McAlpine et al 2008, Mayor et al 2009, Zanini et al 2009). Evaluation of existing models can determine how well model predictions match actual species locations and can provide information for managers to decide whether an extrapolated model is useful or accurate (Gutzwiller and Barrow 2001)

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Results

Conclusion