Beyond Precipitation: Physiographic Gradients Dictate the Relative Importance of Environmental Drivers on Savanna Vegetation

被引:44
作者
Campo-Bescos, Miguel A. [1 ,4 ]
Munoz-Carpena, Rafael [1 ]
Kaplan, David A. [2 ]
Southworth, Jane [3 ]
Zhu, Likai [3 ]
Waylen, Peter R. [3 ]
机构
[1] Univ Florida, Dept Agr & Biol Engn, Gainesville, FL 32610 USA
[2] Univ Florida, Dept Environm Engn Sci, Gainesville, FL 32611 USA
[3] Univ Florida, Dept Geog, Gainesville, FL 32611 USA
[4] Univ Publ Navarra, Projects & Rural Engn Dept, Pamplona, Spain
来源
PLOS ONE | 2013年 / 8卷 / 08期
基金
美国国家科学基金会; 美国国家航空航天局;
关键词
COMMON TRENDS; WOODY COVER; TREE COVER; AFRICAN SAVANNA; OKAVANGO DELTA; CLIMATE-CHANGE; SOIL-MOISTURE; AVHRR GIMMS; NDVI; RAINFALL;
D O I
10.1371/journal.pone.0072348
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:14
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