Seasonal Precipitation Variability and Its Impact on Vegetation Dynamics under Climate Change and Aridity Spectra of the Southwest United States Ecosystems



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This study combines hydro-climatological and biological components for addressing variability in precipitation and vegetation patterns under climate change. We explore the marginal and interactive effects of vegetation and atmospheric variables in order to better understand the plausible changes in terrestrial hydrological processes. We target the southwest United States, known for its diversified ecosystem and depleting water resources. Specifically, we employ an entropy-based disorder index to address precipitation variability and evaluate the marginal effect of watershed topography. Results show that the variability gradually increases westward. We concluded a significant watershed topography effect, which suggests that hilly reliefs have a stabilizing effect on seasonal precipitation variability in time and space. We conclude the necessity to include watershed topography information in climate model parameterizations. However, the implication of a spatial precipitation gradient raises questions regarding vegetation dynamics. In order to understand these dynamics, we analyze the inclusion of precipitation variability in conjunction with the Normalized Difference Vegetation Index (NDVI) during the growing season. We identify three climatic regions based on the United Nations Aridity Index (AI): a relatively humid region with AI?0.65, an intermediate region with 0.50?AI<0.65, and a relatively dry region with AI<0.50. We target four types of vegetation covers: deciduous forest, shrubland, pasture, and grassland. We conclude significant positive trends in the NDVI series for both relatively humid and intermediate climatic regions. In the arid region, we find distinct responses to precipitation for perennial vegetation versus annual vegetation types. The magnitude of these responses tends to increase with environmental aridity. Later we apply the entropy theory to investigate the joint inclusion of precipitation, soil moisture, and temperature in vegetation dynamics analysis. Results reveal trends toward maximum entropy; however, the variable precipitation remained particularly determinant from a marginal point of view. We use a probabilistic approach to analyze the climate change impact on future precipitation patterns. We conclude significant drifts in seasonal precipitation regimes and a meaningful spatial weight. Finally, we emphasize the plausible implications of our findings for future water management. Nevertheless, we suggest further studies on the topic particularly at a global scale.