Spatially Variable Associations Between Forest Cover Loss and Precipitation Trends in the Yucatán Peninsula

The consequences of tropical forest cover loss for regional hydrometeorology and global ecosystem function represent one of the most pressing environmental challenges of our time. The Yucatán Peninsula (YP) has experienced unprecedented deforestation pressure over recent decades, yet the effects of vegetation loss on precipitation dynamics remain poorly understood and uncharacterized. This study examines the 30-year relationship (1993–2022) between land-cover change and precipitation trends in the YP using satellite-derived coverage indices from LANDSAT and monthly precipitation data from the CHIRPS dataset. We applied multi-scale buffer analysis, combined with Spearman’s ρ statistic for precipitation trend detection and Pearson correlation for annual and seasonal time series. The results reveal a persistent positive correlation between two-epoch mean vegetation biomass and precipitation availability, consistent with regional water recycling mechanisms. Using directional (upwind-sector) buffers and a pre-comparison-period NDVI baseline, extended to 250 km, Adjcor_sp_ΔNDVI, the partial correlation between vegetation loss and precipitation trend, net of NDVI baseline and water surface proportion, is season- and scale-dependent rather than a single degradation signal: negative (wetter-with-loss, opposing the hypothesis) at small scales for Annual (≤55 km, not significant) and at small-to-medium scales for MAM (≤95 km), and positive (drier-with-loss, the hypothesized direction) at large scales for Annual and MAM and throughout for JJA and SON. Under Tjostheim’s coefficient, the association is significant across most of the tested range for every series (108 of 135 cells, 80.0%, unchanged after Benjamini–Hochberg FDR correction): consistently in the hypothesized direction for JJA (24/27 scales, 15–250 km) and SON (20/27, 35–250 km); predominantly in the opposite direction for MAM (20 of 26 significant scales, ≤95 km) with a hypothesis-consistent minority at its largest scales (6/26, 125–250 km); and sign-dependent on scale for Annual (15/27, all hypothesis-consistent, 60–250 km) and DJF (23/27, 12 opposite-direction at small scales and 11 hypothesized-direction at large scales); this threshold marks the magnitude at which forest cover loss, driven by agriculture, urbanization, and infrastructure development, disrupts the vegetation–precipitation association. Seasonal decomposition under this revised method shows the hypothesized (positive) direction throughout both summer and fall, with summer’s signal detectable from a shorter buffer radius (15 km) than fall’s (35 km), consistent with direct, locally triggered convection during the wet-season core giving way to a longer-range moisture-recycling pathway by fall. Mean ΔNDVI does not differ between federal protected areas and the rest of the study area, a balance between coastal-ANP forest loss and weak-signal interior recovery; independent land-cover classification shows a net gain within protected areas that this vegetation-index comparison alone does not detect. These findings provide a quantitative, multiscale basis for conservation policy, highlighting priority zones for conservation intervention.