气候变化领域集成服务门户(CCPortal): Incorporating canopy structure from simulated GEDI lidar into bird species distribution models

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DOI	10.1088/1748-9326/ab80ee
	Incorporating canopy structure from simulated GEDI lidar into bird species distribution models
	Burns P.; Clark M.; Salas L.; Hancock S.; Leland D.; Jantz P.; Dubayah R.; Goetz S.J.
发表日期	2020
ISSN	17489318
卷号	15 期号:9
英文摘要	The Global Ecosystem Dynamics Investigation (GEDI) lidar began data acquisition from the International Space Station in March 2019 and is expected to make over 10 billion measurements of canopy structure and topography over two years. Previously, airborne lidar data with limited spatial coverage have been used to examine relationships between forest canopy structure and faunal diversity, most commonly bird species. GEDI's latitudinal coverage will permit these types of analyses at larger spatial extents, over the majority of the Earth's forests, and most importantly in areas where canopy structure is complex and/or poorly understood. In this regional study, we examined the impact that GEDI-derived Canopy Structure variables have on the performance of bird species distribution models (SDMs) in Sonoma County, California. We simulated GEDI waveforms for a two-year period and then interpolated derived Canopy Structure variables to three grid sizes of analysis. In addition to these variables, we also included Phenology, Climate, and other Auxiliary variables to predict the probability of occurrence of 25 common bird species. We used a weighted average ensemble of seven individual machine learning models to make predictions for each species and calculated variable importance. We found that Canopy Structure variables were, on average at our finest resolution of 250 m, the second most important group (32.5%) of predictor variables after Climate variables (35.3%). Canopy Structure variables were most important for predicting probability of occurrence of birds associated with Conifer forest habitat. Regarding spatial analysis scale, we found that finer-scale models more frequently performed better than coarser-scale models, and the importance of Canopy Structure variables was greater at finer spatial resolutions. Overall, GEDI Canopy Structure variables improved SDM performance for at least one spatial resolution for 19 of 25 species and thus show promise for improving models of bird species occurrence and mapping potential habitat. © 2020 The Author(s). Published by IOP Publishing Ltd.
英文关键词	bird species distribution models; canopy structure; GEDI; lidar; machine learning
语种	英语
scopus关键词	Data acquisition; Ecosystems; Forecasting; Forestry; Optical radar; Population distribution; Space stations; Spatial variables measurement; Topography; Airborne lidar data; Auxiliary variables; Forest canopy structure; International Space stations; Machine learning models; Predictor variables; Probability of occurrence; Variable importances; Birds; bird; coniferous forest; ecological modeling; forest canopy; habitat type; latitudinal gradient; lidar; phenology; satellite data; spatial resolution; species diversity; species occurrence; California; Sonoma County; United States; Aves; Coniferophyta
来源期刊	Environmental Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/153789
作者单位	School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, AZ, United States; Geography, Environment and Planning, Sonoma State University, Rohnert Park, CA, United States; Point Blue Conservation Science, Petaluma, CA, United States; School of Geosciences, University of Edinburgh, Edinburgh, United Kingdom; Madrone Audubon Society, Santa Rosa, CA, United States; Department of Geographical Sciences, University of Maryland, College Park, MD, United States
推荐引用方式 GB/T 7714	Burns P.,Clark M.,Salas L.,et al. Incorporating canopy structure from simulated GEDI lidar into bird species distribution models[J],2020,15(9).
APA	Burns P..,Clark M..,Salas L..,Hancock S..,Leland D..,...&Goetz S.J..(2020).Incorporating canopy structure from simulated GEDI lidar into bird species distribution models.Environmental Research Letters,15(9).
MLA	Burns P.,et al."Incorporating canopy structure from simulated GEDI lidar into bird species distribution models".Environmental Research Letters 15.9(2020).