Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1371/journal.pone.0172107 |
Remote-sensing based approach to forecast habitat quality under climate change scenarios | |
Requena-Mullor, Juan M.1; Lopez, Enrique1,2; Castro, Antonio J.1,3; Alcaraz-Segura, Domingo1,4; Castro, Hermelindo1,5; Reyes, Andres1; Cabello, Javier1,5 | |
通讯作者 | Requena-Mullor, Juan M. |
来源期刊 | PLOS ONE
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ISSN | 1932-6203 |
出版年 | 2017 |
卷号 | 12期号:3 |
英文摘要 | As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios. |
类型 | Article |
语种 | 英语 |
国家 | Spain ; USA |
收录类别 | SCI-E |
WOS记录号 | WOS:000396021100012 |
WOS关键词 | SPECIES DISTRIBUTION MODELS ; BADGERS MELES-MELES ; LANDSCAPE-SCALE ; EUROPEAN BADGER ; DISTRIBUTIONS ; SELECTION ; HETEROGENEITY ; DIVERSITY ; GRADIENT ; IMPACTS |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/201605 |
作者单位 | 1.Univ Almeria, Andalusian Ctr Assessment & Monitoring Global Cha, Almeria, Spain; 2.Univ Almeria, Dept Educ, Didact Expt Sci Area, Almeria, Spain; 3.Idaho State Univ, Dept Biol Sci, Gale Life Sci Bldg Rm 207,8th Ave,Mail Stop, Pocatello, ID 83209 USA; 4.Univ Granada, Dept Bot, Granada, Spain; 5.Univ Almeria, Dept Biol & Geol, Almeria, Spain |
推荐引用方式 GB/T 7714 | Requena-Mullor, Juan M.,Lopez, Enrique,Castro, Antonio J.,et al. Remote-sensing based approach to forecast habitat quality under climate change scenarios[J],2017,12(3). |
APA | Requena-Mullor, Juan M..,Lopez, Enrique.,Castro, Antonio J..,Alcaraz-Segura, Domingo.,Castro, Hermelindo.,...&Cabello, Javier.(2017).Remote-sensing based approach to forecast habitat quality under climate change scenarios.PLOS ONE,12(3). |
MLA | Requena-Mullor, Juan M.,et al."Remote-sensing based approach to forecast habitat quality under climate change scenarios".PLOS ONE 12.3(2017). |
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