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DOI10.3389/fmars.2019.00003
Predicting Optimal Sites for Ecosystem Restoration Using Stacked-Species Distribution Modeling
Zellmer, Amanda J.1; Claisse, Jeremy T.1,2; Williams, Chelsea M.1,2; Schwab, Stuart3; Pondella, Daniel J., II1
发表日期2019
EISSN2296-7745
卷号6
英文摘要

Habitat restoration is an important tool for managing degraded ecosystems, yet the success of restoration projects depends in part on adequately identifying preferred sites for restoration. Species distribution modeling using a machine learning approach provides novel tools for mapping areas of interest for restoration projects. Here we use stacked-species distribution models (s-SDMs) to identify candidate locations for installment of manmade reefs, a useful management tool for restoring structural habitat complexity and the associated biota in marine ecosystems. We created species distribution models for 21 species of commercial, recreational, ecological, or conservation importance within the Southern California Bight based on observations from long-term reef surveys combined with high resolution (200 m x 200 m) geospatial environmental data layers. We then combined the individual species models to create a stacked-species habitat suitability map, identifying over 800 km(2) of potential area for reef restoration within the Bight. When considering only the 21 focal species, s-SDM scores were positively associated with observed bootstrap species richness not only on natural reefs (linear model: slope = 0.27, 95% CI = 0.17-0.36, w = 1), but also this result was supported by two independent test datasets. The predicted richness from this linear model was associated with observed species richness when considering only the focal species on manmade reefs (linear model: slope = 0.52, 95% CI = 0.130-92, w = 1) and also when considering 204 other non-focal species on both natural and manmade reefs in southern California (slope = 3.65, 95% CI = 2.93-4.37, w = 1). Finally, our results demonstrate that the existing manmade reefs included in our study on average are located in regions with habitat suitability that is not only less suitable than natural reefs (t-value = -5.4; p < 0.05), but also only slightly significantly better than random (p < 0.05), demonstrating a need for more biologically informed placement of manmade reefs. The stacked-species distribution model provides insight for marine restoration projects in southern California specifically, but more generally this method can also be widely applied to other types of habitat restoration including both marine and terrestrial.


WOS研究方向Environmental Sciences & Ecology ; Marine & Freshwater Biology
来源期刊FRONTIERS IN MARINE SCIENCE
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/93397
作者单位1.Occident Coll, Vantuna Res Grp, Dept Biol, Los Angeles, CA 90041 USA;
2.Calif State Polytech Univ Pomona, Dept Biol Sci, Pomona, CA 91768 USA;
3.Univ Calif Riverside, Dept Evolut Ecol & Organismal Biol, Riverside, CA 92521 USA
推荐引用方式
GB/T 7714
Zellmer, Amanda J.,Claisse, Jeremy T.,Williams, Chelsea M.,et al. Predicting Optimal Sites for Ecosystem Restoration Using Stacked-Species Distribution Modeling[J],2019,6.
APA Zellmer, Amanda J.,Claisse, Jeremy T.,Williams, Chelsea M.,Schwab, Stuart,&Pondella, Daniel J., II.(2019).Predicting Optimal Sites for Ecosystem Restoration Using Stacked-Species Distribution Modeling.FRONTIERS IN MARINE SCIENCE,6.
MLA Zellmer, Amanda J.,et al."Predicting Optimal Sites for Ecosystem Restoration Using Stacked-Species Distribution Modeling".FRONTIERS IN MARINE SCIENCE 6(2019).
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