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Terrestrial land-cover type richness is positively linked to landscape-level functioning

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DataONE2025-02-07 更新2025-04-26 收录
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Biodiversity–ecosystem functioning (BEF) experiments have shown that local species richness promotes ecosystem functioning and stability. Whether this also applies under real-world conditions is still debated. Here, we focus on larger scales of space, time and ecological organization. We develop a quasi-experimental design in which we relate land-cover type richness as measure of landscape richness to 17-year time series of satellite-sensed functioning in 4,974 landscape plots 6.25 or 25 ha in size. We choose plots so that landscape richness is orthogonal to land cover-type composition and environmental conditions across climatic gradients. Landscape-scale productivity and temporal stability increase with landscape richness, irrespective of landscape plot size. Peak season near-infrared surface albedo, which is relevant for surface energy budgets, is higher in mixed than in single land-cover type landscapes. Effect sizes are as large as those reported from BEF-experiments, suggesting th..., In these datasets (data_250m.csv, data_500m.csv) we combine a variety of geographic information data to elucidate the relationship between land-cover type richness and landscape-level functioning (satellite-sensed proxies of productivity, phenology and albedo) in the years 2000-2016 across large environmental gradients in Central Europe (Switzerland). Data were extracted for landscapes with an area of either 250m x 250m (in data_250m.csv) or 500m x 500m (in data_500m.csv) across Switzerland, averaged for the 17 year time period and then aggregated according to land-cover type compositions and blocks of biogeographic region - altitude range combinations. Satellite-sensed proxies of productivity, phenology and albedo were derived from MODIS MOD13Q1, MOD13A1 and MCD43A3 products (Didan 2015, Schaaf & Wan 2015). Information on land-cover was derived from data provided by the Swiss Federal Statistical Office (GEOSTAT, product name: NOAS04). Topographic data was obtained from the Swiss F..., We provide a description of the dataset column names in the data_description.txt file. For further details on data characteristics and processing, please have a look at the Methods section and the reporting summary file of the related main manuscript (DOI: 10.1038/s41467-019-14002-7).
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2025-02-12
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