An ensemble approach to species distribution modelling reconciles systematic differences in estimates of habitat utilization and range area

Author:

Harris J.1ORCID,Pirtle J. L.2ORCID,Laman E. A.3ORCID,Siple M. C.3ORCID,Thorson James T.4ORCID

Affiliation:

1. Washington Department of Fish and Wildlife Olympia Washington USA

2. Habitat Conservation Division, Alaska Regional Office, National Marine Fisheries Service National Oceanic and Atmospheric Administration Juneau Alaska USA

3. Resource Assessment and Conservation Engineering Division, Alaska Fisheries Science Center National Oceanic and Atmospheric Administration Seattle Washington USA

4. Resource Ecology and Fisheries Management, Alaska Fisheries Science Center National Oceanic and Atmospheric Administration Seattle Washington USA

Abstract

Abstract Species distribution models (SDMs) are an important tool for conservation and resource management. However, managers are often interested in derived quantities such as range or area occupied, and how these are calculated can have a large impact. Ecosystem‐based management typically requires spatial information about species distributions, which is increasingly generated from SDMs that are then processed to identify occupied habitat. Many types of SDMs exist, but there is little research regarding how this model‐choice affects outcomes when defining occupied habitat, in part because these models generate different types of output. We fit a suite of five SDMs to data for 208 species/life stage combinations in three marine ecosystems while ensuring that they all estimate a ‘common currency’ of numerical abundance. We then calculate out‐of‐sample predictive performance to weight these constituents in an ensemble SDM. Results show that this approach can reduce bias arising from a priori specification of individual SDMs resulting in a better fit to survey data (constituent SDMs had a median of 7% higher RMSE). The SDMs had a range of responses relative to the ensemble, with MaxEnt typically predicting a median 1.3% higher area occupied, and negative‐binomial GAMs predicting 21.4% lower area occupied. Two potential methods of identifying the area of occupied habitat from SDM outputs are compared—probability‐based and cumulative density‐based methods. We find that cumulative densities result in smaller estimates of area occupied, and we recommend careful consideration of how model‐choice affects occupied‐habitat estimates in spatial management. Policy implications: Finally, we discuss how the patterns identified during the 5‐year Review of Essential Fish Habitat for Alaska should be carefully considered by managers using SDMs to identify habitat that may be impacted by anthropogenic activities.

Publisher

Wiley

Subject

Ecology

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3