Abstract

MENDEZ-ZUNIGA, Jesús Emmanuel; ZUNIGA-VASQUEZ, José Manuel  and  COLIN, José Guadalupe. Relationship of climate and remote sensing data with tree diversity in a temperate forest. Rev. mex. de cienc. forestales [online]. 2024, vol.15, n.85, pp.97-122.  Epub Nov 19, 2024. ISSN 2007-1132.  https://doi.org/10.29298/rmcf.v15i85.1477.

Quantifying biodiversity is key to natural resource conservation; however, data collection can be time-consuming and costly. Given that climate and remote sensing data help in the prediction of species diversity, the objective of this study was to analyze the relationship of climate data and the Normalized Difference Vegetation Index (NDVI) with tree diversity in a temperate forest in Northern Mexico. Species richness (S), Simpson's (1-D) and Shannon's (H) diversity indices were calculated at 663 sampling sites. Subsequently, an exploratory regression analysis was performed to obtain regression models that would account for the relationship of tree diversity indices with the NDVI, climatic data, and the number of trees. The best model for each diversity index and its predictor variables was integrated into a Geographically Weighted Regression (GWR) model. The results showed that the relationship of diversity indices and predictor variables varies across the space. The variables showed greater predictive potential in the Northern and Northwestern part of the study area. The NDVI was the variable with the greatest relative influence in the explanation of the diversity indices; therefore, it can function as a proxy for factors associated with tree diversity.

Keywords : Spatial distribution; vegetation index; diversity indices; forest management; spatial regression; species richness.

        · abstract in Spanish     · text in English | Spanish     · English ( pdf ) | Spanish ( pdf )