DOI: 10.5061/dryad.gb5mkkwkj
title: Terrestrial land-cover type richness is positively linked to landscape-level functioning

description: 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 that landscape richness promotes landscape functioning at
 spatial scales relevant for management.
description: 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 Federal Office of Topography
 (swisstopo, product name: DHM25). Climatic variables were derived from
 interpolated gridded monthly datasets provided by the Swiss Office of
 Meteorology and Climatology (MeteoSwiss, product names: TabsM, RhiresM,
 msg.SIS.M). Data processing was done using the R 3.5 software
 (http://r-project.org). References: Didan, K. (2015). MOD13Q(A)1 MODIS/Terra Vegetation Indices 16-Day L3 Global 250(500)m SIN GridV006. doi:10.5067/MODIS/MOD13Q(A)1.006. Accessed on January,16,2016 (November,20,2017) at https://e4ftl01.cr.usgs.gov/MOLT. NASA EOSDIS Land Processes DAAC. Schaaf, C. & Wan, Z. (2015). MCD43A3 MODIS/Terra+Aqua BRDF/Albedo Daily L3 Global - 500m V006. NASA EOSDIS Land Processes DAAC. Accessed on January, 12, 2017 at https://doi.org/10.5067/modis/mcd43a3.006.
description: 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).