Global Spatial–Temporal Variability in Terrestrial Productivity and Phenology Regimes between 2000 and 2012

Bibliographic Data

ID7634979
AuthorsShanley D Thompson (University of Victoria), Trisalyn A Nelson, Trisalyn Nelson (0000-0003-2537-6971, Arizona State University), Nicholas C Coops (0000-0002-0151-9037, University of British Columbia), Michael A Wulder (0000-0002-6942-1896, Canadian Forest Service), T C Lantz (0000-0001-5643-1537, University of Victoria)
Year2017
Volume107
Issue6
Pages1519-1537
Publication date2017-11-02
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueAnnals of the American Association of Geographers (JOURNAL)
Journal identifiersISSN: 2469-4452 • E-ISSN: 2469-4460
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/24694452.2017.1309964
OpenAlexW2612061294
LanguageEN
Citations received2
References cited109

The productivity and phenology of vegetation are spatially and temporally variable ecosystem functions. Monitoring spatial–temporal patterns in these functions can improve our understanding of global change and natural ecosystem variability and inform management actions. Researchers typically focus on temporal changes within or among static regions and omit dynamics of spatial configuration. Our goal was to assess global spatial–temporal variability in productivity and phenology regimes between 2000 and 2012 using a temporally dynamic functional type classification. Fourteen functional types were defined for each year by clustering the annual sum and annual variability (seasonality) of the fraction of photosynthetically active radiation (fPAR)—a biophysical proxy for vegetation greenness or productivity—from the Moderate Resolution Imaging Spectrometer (MODIS). The fourteen functional types ranged from tundra (low cumulative fPAR and highly seasonal) to tropical forests (high cumulative fPAR and low seasonality). Variability in the mean of the fPAR metrics and in two spatial pattern metrics was assessed for each functional type. Many pixels changed from one cluster to another then back again, suggesting considerable short-term variability. Temporal variability in the mean of the fPAR metrics was relatively low, with changes instead primarily manifested in spatial pattern. Spatial pattern was most variable within tundra, grasslands, shrublands, and savannas. A dynamic classification demonstrated the variability in spatial patterns of primary productivity and can be used for future monitoring

Climatology · Common spatial pattern · Ecosystem · Geography · Phenology · Photosynthetically active radiation · Physical geography · Primary production · Productivity · Seasonality · Shrubland · Spatial ecology · Spatial variability · Statistics · Tundra · Environmental Science · Land Use and Ecosystem Services · Remote Sensing in Agriculture · Species Distribution and Climate Change · Ecology

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