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Sensitivity of global terrestrial ecosystems to climate variability: data and R code

Subtitle:
2000-2013 monthly time-series of 5km resolution MODIS-derived enhanced vegetation index, air temperature, water availability, cloud cover, supplementary files and R code
Abstract:

Seddon et al. (2016) Nature (DOI 10.1038/nature16986) ABSTRACT: Identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global significance. Here, we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognising that systems closer to critical thresholds respond more sensi...

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Department:
University of Bergen
Role:
Researcher
Department:
University of Oxford
Role:
Researcher
Department:
University of Oxford
Role:
Researcher
Department:
University of Oxford
Role:
Researcher
Department:
University of Oxford
Role:
Researcher
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Grant:
4501995279 (KJW, AWRS, PRL, DB)
Funding agency for:
Project
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Grant:
LIFE12 ENV/UK/000473 (KJW, DB, PRL)
Funding agency for:
Project
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Grant:
Fellowship (PRL)
Funding agency for:
Project
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Grant:
Independent Research Fellowship NE/L011859/1 (MMF)
Funding agency for:
Project
Publisher:
University of Oxford
Publication date:
2016
Spatial coverage:
Global (-180 - 180), (-60 - 90)
DOI:
Temporal coverage:
2000 - 2013
Language:
English
Format:
Digital
Documentation:
Data and coding scripts for Seddon et al. (2016) Nature (DOI 10.1038/nature16986). We derived monthly time-series of four key terrestrial ecosystem variables at 0.05 degree (~5km) resolution from observations by the MODIS sensor on Terra (AM) for the period February 2010-December 2013 inclusive, and developed a method to identify vegetation sensitivity to climate variability over this period (see Methods in main paper). This ORA item contains all data and files required to run the analysis ... Expand documentation

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