Combining Satellite Remote Sensing and Climate Data in Species Distribution Models to Improve the Conservation of Iberian White Oaks (Quercus L.)

被引:20
作者
Vila-Vicosa, Carlos [1 ,2 ,3 ]
Arenas-Castro, Salvador [1 ,4 ,5 ]
Marcos, Bruno [1 ,3 ]
Honrado, Joao [1 ,3 ]
Garcia, Cristina [1 ,6 ]
Vazquez, Francisco M. [7 ]
Almeida, Rubim [1 ,2 ,3 ]
Goncalves, Joao [1 ]
机构
[1] Univ Porto, CIBIO Res Ctr Biodivers & Genet Resources, InBIO Res Network Biodivers & Evolutionary Biol, Campus Agr Vairao,Rua Padre Armando Quintas, P-4485661 Vairao, Portugal
[2] Univ Porto, MHNC UP Nat Hist & Sci Museum, Praca Gomes Teixeira, P-4099002 Porto, Portugal
[3] Univ Porto, Fac Sci, Biol Dept, Rua Campo Alegre S-N, P-4169007 Porto, Portugal
[4] Inst Politecn Viana do Castelo, Escola Super Tecnol & Gestao, P-4900347 Viana Do Castelo, Portugal
[5] Univ Porto, Fac Ciencias, CICGE Ctr Invest Ciencias Geoespaciais, Observ Astron Prof Manuel de Barros, Alameda Monte Virgem, P-4430146 Vila Nova De Gaia, Portugal
[6] Univ Liverpool, Inst Integrat Biol IIB, Dept Evolut Ecol & Behav, Biosci Bldg, Liverpool L69 7ZB, Merseyside, England
[7] CICYTEX Ctr Invest Cient & Tecnol Extremadura, Agr Res Ctr, Ctra A-V,Km372, Badajoz 06187, Spain
关键词
climate change; satellite remote sensing; species distribution models; Quercus; oak forests; biodiversity conservation; Iberian Peninsula; MULTIMODEL INFERENCE; HABITAT SUITABILITY; FUTURE; MANAGEMENT; DIVERSITY; TAXONOMY; DIFFERENTIATION; PHYLOGEOGRAPHY; DYNAMICS; PATTERNS;
D O I
10.3390/ijgi9120735
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Iberian Peninsula hosts a high diversity of oak species, being a hot-spot for the conservation of European White Oaks (Quercus) due to their environmental heterogeneity and its critical role as a phylogeographic refugium. Identifying and ranking the drivers that shape the distribution of White Oaks in Iberia requires that environmental variables operating at distinct scales are considered. These include climate, but also ecosystem functioning attributes (EFAs) related to energy-matter exchanges that characterize land cover types under various environmental settings, at finer scales. Here, we used satellite-based EFAs and climate variables in species distribution models (SDMs) to assess how variables related to ecosystem functioning improve our understanding of current distributions and the identification of suitable areas for White Oak species in Iberia. We developed consensus ensemble SDMs targeting a set of thirteen oaks, including both narrow endemic and widespread taxa. Models combining EFAs and climate variables obtained a higher performance and predictive ability (true-skill statistic (TSS): 0.88, sensitivity: 99.6, specificity: 96.3), in comparison to the climate-only models (TSS: 0.86, sens.: 96.1, spec.: 90.3) and EFA-only models (TSS: 0.73, sens.: 91.2, spec.: 82.1). Overall, narrow endemic species obtained higher predictive performance using combined models (TSS: 0.96, sens.: 99.6, spec.: 96.3) in comparison to widespread oaks (TSS: 0.80, sens.: 92.6, spec.: 87.7). The Iberian White Oaks show a high dependence on precipitation and the inter-quartile range of Normalized Difference Water Index (NDWI) (i.e., seasonal water availability) which appears to be the most important EFA variable. Spatial projections of climate-EFA combined models contribute to identify the major diversity hotspots for White Oaks in Iberia, holding higher values of cumulative habitat suitability and species richness. We discuss the implications of these findings for guiding the long-term conservation of Iberian White Oaks and provide spatially explicit geospatial information about each oak species (or set of species) relevant for developing biogeographic conservation frameworks.
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页数:25
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