Deforestation and Its Effect on Surface Albedo and Weather Patterns

Abstract

Deforestation is an important environmental problem and a key promoter of regional climate change through modifying the surface albedo. The objective of this research was to characterize the impact of deforestation and land use changes on surface albedo (α) and climate patterns in a tropical highland region of Mexico, between the years 2014 and 2021. The main land cover types are coniferous forests (CF), oak and gallery woodlands (OGW), and annual agriculture (AA), which represent more than 88% of the regional territory. We used 2014 and 2021 Landsat 8 OLI images with topographic and atmospheric correction in order to develop an inventory of albedo values for each land cover type in both time scenarios. Albedo images were generated by using the equation proposed by Liang in 2001, which is based on the reflectance of the bands 2, 3, 4, 5, and 7. Differences in albedo values were calculated between the years 2014 and 2021, and those differences were correlated with variations in climate parameters, for which we used climate data derived from the WRF model. In addition, the different land use changes found were classified in terms of triggers for increasing or decreasing surface albedo. We used the Mann–Whitney U Test to compare the 2021 − 2014 climatic deviations in two samples: Sample A, which included sites without albedo change in 2021; and Sample B, including sites with albedo change in 2021. Results showed that between 2014 and 2021, at least 38 events of land use change or deforestation occurred, with albedo increments between 1 and 11%, which triggered an average increment of 2.16% (p < 0.01; Mann–Whitney U Test) of the regional surface albedo in comparison to the 2014 scenario. In this period, the albedo for CF, OGW, and AA also increased significantly (p < 0.001; Mann–Whitney U Test) by +79, +12, and +9%, respectively. In addition, the regional albedo increment was found to be significant and negatively correlated (p < 0.01 Spearman’s coefficient) with relative humidity (RH), maximum temperature (Tmax), and minimum temperature (Tmin), and correlated (p < 0.01) positively with diurnal temperature range (DTR). The Mann–Whitney U Test revealed that 2021 climatic variations in Sample B sites are statistically different (p < 0.05) to 2021 climatic variations in Sample A sites, which demonstrates that albedo changes are linked to a decrease in minimum temperature and relative humidity and an increase in DTR. Conversion of CF and OGW into AA, perennial agriculture (PA), or grassland (GR) always yielded an albedo increment, whilst the conversion of AA to irrigation agriculture (IA) or PA triggered a decrease in albedo, and finally, the pass from GR or AA to protected agriculture (PA) caused albedo to increase or decrease, depending on the greenhouse covers materials. Reducing deforestation of CF and OGW, conversion of AA or GR into PA, and selecting adequate greenhouse covers could help to mitigate regional climate change.