Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.