作者: João Gonçalves , Paulo Alves , Isabel Pôças , Bruno Marcos , Rita Sousa-Silva
DOI: 10.1007/S10531-016-1206-7
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摘要: Ongoing declines in biodiversity caused by global environmental changes call for adaptive conservation management, including the assessment of habitat suitability spatiotemporal dynamics potentially affecting species persistence. Remote sensing (RS) provides a wide-range satellite-based variables that can be fed into distribution models (SDMs) to investigate species-environment relations and forecast responses change. We address species’ at landscape level combining multi-temporal RS data with SDMs analysing inter-annual dynamics. implemented this framework vulnerable plant (Veronica micrantha), time-series RS-based metrics vegetation functioning related primary productivity, seasonality, phenology actual evapotranspiration. Besides variables, predictors structure, soils wildfires were ranked combined through multi-model inference (MMI). To assess recent dynamics, was generated model hindcasting. MMI highlighted strong predictive ability productivity water availability explaining test-species distribution, along soil, wildfire regime composition. The revealed effects short-term land cover variability climatic conditions. Multi-temporal further improved predictions, benefiting from time-series. Overall, results emphasize integration attributes function, composition spatial configuration improving explanation ecological patterns. Moreover, coupling functional may provide early-warnings future impacting suitability. Applications discussed include improvement monitoring strategies.