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A high‐resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring

Marc J. MetzgerSchool of GeoSciences University of Edinburgh Drummond Street Edinburgh EH8 9XP Scotland UKR.G.H. BunceEstonian University of Life Sciences 51041 Tartu EstoniaR.H.G. JongmanAlterra, Wageningen University and Research Centre PO Box 47 6700 AA Wageningen The NetherlandsRoger SayreClimate and Land Use Change Program United States Geological Survey 12201 Sunrise Valley Drive MS 519 Reston VA 20192 USAAntonio TrabuccoDivision Forest, Nature and Landscape KU Leuven Celestijnenlaan 200E 3001 Leuven BelgiumRobert J. ZomerCentre for Mountain Ecosystems Studies Kunming Insitute of Botany China
2012en
ABI

Аннотация

Abstract Aim To develop a novel global spatial framework for the integration and analysis of ecological and environmental data. Location The global land surface excluding A ntarctica. Methods A broad set of climate‐related variables were considered for inclusion in a quantitative model, which partitions geographic space into bioclimate regions. Statistical screening produced a subset of relevant bioclimate variables, which were further compacted into fewer independent dimensions using principal components analysis ( PCA ). An ISODATA clustering routine was then used to classify the principal components into relatively homogeneous environmental strata. The strata were aggregated into global environmental zones based on the attribute distances between strata to provide structure and support a consistent nomenclature. Results The global environmental stratification ( GEnS ) consists of 125 strata, which have been aggregated into 18 global environmental zones. The stratification has a 30 arcsec resolution (equivalent to 0.86 km 2 at the equator). Aggregations of the strata were compared with nine existing global, continental and national bioclimate and ecosystem classifications using the K appa statistic. Values range between 0.54 and 0.72, indicating good agreement in bioclimate and ecosystem patterns between existing maps and the GEnS . Main conclusions The GEnS provides a robust spatial analytical framework for the aggregation of local observations, identification of gaps in current monitoring efforts and systematic design of complementary and new monitoring and research. The dataset is available for non‐commercial use through the GEO portal ( http://www.geoportal.org ).

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