Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 503986
Title Estimating and analyzing savannah phenology with a lagged time series model
Author(s) Boke-Olén, Niklas; Lehsten, Veiko; Ardö, Jonas; Beringer, Jason; Eklundh, Lars; Holst, Thomas; Veenendaal, Elmar; Tagesson, Torbern
Source PLoS One 11 (2016)4. - ISSN 1932-6203
DOI http://dx.doi.org/10.1371/journal.pone.0154615
Department(s) Nature Conservation and Plant Ecology
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2016
Abstract

Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r2 of 0.6 and root mean squared error of 0.1. We therefore expect similar average results when applying the model to other savannah areas and further expect that it could be used to estimate the productivity of savannah regions.

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