Beyond precipitation: physiographic gradients dictate the relative importance of environmental drivers on savanna vegetation
Fecha
2013Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión publicada / Argitaratu den bertsioa
Impacto
|
10.1371/journal.pone.0072348
Resumen
Background: Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to
predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to
improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving
vegetation change in southern African savanna, a ...
[++]
Background: Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to
predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to
improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving
vegetation change in southern African savanna, and how they vary across physiographic gradients.
Methodology/Principal Findings: We applied Dynamic Factor Analysis (DFA), a multivariate times series dimension
reduction technique to ten years of monthly remote sensing data (MODIS-derived normalized difference vegetation index,
NDVI) and a suite of environmental covariates: precipitation, mean and maximum temperature, soil moisture, relative
humidity, fire and potential evapotranspiration. Monthly NDVI was described by cyclic seasonal variation with distinct
spatiotemporal patterns in different physiographic regions. Results support existing work emphasizing the importance of
precipitation, soil moisture and fire on NDVI, but also reveal overlooked effects of temperature and evapotranspiration,
particularly in regions with higher mean annual precipitation. Critically, spatial distributions of the weights of environmental
covariates point to a transition in the importance of precipitation and soil moisture (strongest in grass-dominated regions
with precipitation,750 mm) to fire, potential evapotranspiration, and temperature (strongest in tree-dominated regions
with precipitation.950 mm).
Conclusions/Significance: We quantified the combined spatiotemporal effects of an available suite of environmental
drivers on NDVI across a large and diverse savanna region. The analysis supports known drivers of savanna vegetation but
also uncovers important roles of temperature and evapotranspiration. Results highlight the utility of applying the DFA
approach to remote sensing products for regional analyses of landscape change in the context of global environmental
change. With the dramatic increase in global change research, this methodology augurs well for further development and
application of spatially explicit time series modeling to studies at the intersection of ecology and remote sensing. [--]
Materias
Environmental drivers,
Savanna vegetation,
Dinamic factor analysis (DFA),
NDVI
Editor
Public Library of Science
Publicado en
Plos One, 8(8): e72348
Departamento
Universidad Pública de Navarra. Departamento de Proyectos e Ingeniería Rural /
Nafarroako Unibertsitate Publikoa. Landa Ingeniaritza eta Proiektuak Saila
Versión del editor
Entidades Financiadoras
This study was funded by National Aeronautics and Space Administration Land-Cover/Land-Use Change Program (NASA LCLUC) Project # NNX09AI25G, titled ‘‘The Role of Socioeconomic Institutions in Mitigating Impacts of Climate Variability and Climate Change in Southern Africa’’, and National Science Foundation Integrative Graduate Education and Research Traineeship (NSF-IGERT) 0504422 Adaptive Management of Water, Wetlands and Watershed.
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La licencia del ítem se describe como © 2013 Campo-Bescos et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.