气候变化领域集成服务门户(CCPortal): Spatio-temporal remotely sensed indices identify hotspots of biodiversity conservation concern

CCPortal

DOI	10.1016/j.rse.2021.112368
	Spatio-temporal remotely sensed indices identify hotspots of biodiversity conservation concern
	Silveira E.M.O.; Radeloff V.C.; Martinuzzi S.; Martínez Pastur G.J.; Rivera L.O.; Politi N.; Lizarraga L.; Farwell L.S.; Elsen P.R.; Pidgeon A.M.
发表日期	2021
ISSN	00344257
卷号	258
英文摘要	Over the course of a year, vegetation and temperature have strong phenological and seasonal patterns, respectively, and many species have adapted to these patterns. High inter-annual variability in the phenology of vegetation and in the seasonality of temperature pose a threat for biodiversity. However, areas with high spatial variability likely have higher ecological resilience where inter-annual variability is high, because spatial variability indicates presence of a range of resources, microclimatic refugia, and habitat conditions. The integration of inter-annual and spatial variability is thus important for biodiversity conservation. Areas where spatial variability is low and inter-annual variability is high are likely to limit resilience to disturbance. In contrast, areas of high spatial variability may be high priority candidates for protection. Our goal was to develop spatio-temporal remotely sensed indices to identify hotspots of biodiversity conservation concern. We generated indices that capture the inter-annual and spatial variability of vegetation greenness and land surface temperature and integrated them to identify areas of high, medium, and low biodiversity conservation concern. We applied our method in Argentina (2.8 million km2), a country with a wide range of climates and biomes. To generate the inter-annual variability indices, we analyzed MODIS Enhanced Vegetation Index (EVI) and Land Surface Temperature (LST) time series from 2001 to 2018, fitted curves to obtain annual phenological and seasonal metrics, and calculated their inter-annual variability. To generate the spatial variability indices, we calculated standard deviation image texture of Landsat 8 EVI and LST. When we integrated our inter-annual and spatial variability indices, areas in the northeast and parts of southern Argentina were the hotspots of highest conservation concern. High inter-annual variability poses a threat in these areas, because spatial variability is low. These are areas where management efforts could be valuable. In contrast, areas in the northwest and central-west are where protection should be strongly considered because the high spatial variability may confer resilience to disturbance, due to the variety of conditions and resources within close proximity. We developed remotely sensed indices to identify hotspots of high and low conservation concern at scales relevant to biodiversity conservation, which can be used to target management actions in order to minimize biodiversity loss. © 2021 Elsevier Inc.
英文关键词	EVI; Image texture; Landsat; LST; MODIS; Phenology; Temperature; Time series; Vegetation greenness
语种	英语
scopus关键词	Atmospheric temperature; Biodiversity; Conservation; Environmental protection; Forestry; Image texture; Remote sensing; Surface measurement; Surface properties; Textures; Vegetation; Biodiversity conservation; Enhanced vegetation index; Habitat conditions; Interannual variability; Remotely sensed indices; Spatial variability; Standard deviation; Vegetation greenness; Land surface temperature; annual variation; biodiversity; land surface; Landsat; management practice; MODIS; phenology; remote sensing; spatial variation; spatiotemporal analysis; surface temperature; Argentina
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178898
作者单位	SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706, United States; Centro Austral de Investigaciones Científicas (CADIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Houssay 200, Ushuaia, Tierra del Fuego 9410, Argentina; Facultad de Ciencias Agrarias, Universidad Nacional de Jujuy, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Juan Bautista Alberdi 47, Jujuy, Y4600DTA, Argentina; Wildlife Conservation Society, Bronx, NY 10460, United States
推荐引用方式 GB/T 7714	Silveira E.M.O.,Radeloff V.C.,Martinuzzi S.,et al. Spatio-temporal remotely sensed indices identify hotspots of biodiversity conservation concern[J],2021,258.
APA	Silveira E.M.O..,Radeloff V.C..,Martinuzzi S..,Martínez Pastur G.J..,Rivera L.O..,...&Pidgeon A.M..(2021).Spatio-temporal remotely sensed indices identify hotspots of biodiversity conservation concern.Remote Sensing of Environment,258.
MLA	Silveira E.M.O.,et al."Spatio-temporal remotely sensed indices identify hotspots of biodiversity conservation concern".Remote Sensing of Environment 258(2021).