Fast land use changes have strongly affected arid and semi-arid regions at a global scale, affecting food security of the inhabitants of these regions. This study evaluated the fragmentation degree in the Chihuahua´s desert region of Mexico by using data from the Landsat TM sensor. Nine scenes, taken with Landsat TM5 sensor from the years 1990, 2000, and 2012, were used for the analysis. The coverage of seven land uses (grasslands, shrubland, croplands, sandy desert vegetation, forest, water bodies, and urban areas) was obtained under supervised classification techniques and the accuracy level was evaluated through the Kappa multi-varied discrete index. The classification showed a good reliance level having global accuracies of 93, 93.2 and 90.3% for the years 1990, 2000 and 2012, respectively. The fragmentation analysis showed an increase in the number of patches, an indicator of the ecosystem degradation process. The patches number increased from 8,354.23 in 1990 to 9,658.36 in 2000 and to 11,469 in 2012. Simpson and Shannon diversity indexes proved a clear fragmentation process. During the period of 1990−2012, grasslands were the most affected vegetation type with a reduction of 30.7% in its area. Such reduction was mainly attributed to invasions of shrubland communities and to an increase in cropland areas.
In order to understand the environmental variables that may impact more on the distribution of species of trees and shrubs, a correlation analysis applying the Covariation (C) of Gregorius was conducted among 14 variables of climate and physiography, and the number of individuals of 72 species, which were found in 1804 sampling plots (covering about 123,317 km²) of the National Forests and Soils Inventory (INFyS) developed by the National Forest Commission in Mexico (CONAFOR). Among the studied species there are several of the genera Quercus, Pinus and Junniperus, which are mainly distributed in the Sierra Madre Occidental, where they stand out for their abundance. The results show that the density of 88% of the studied species have a significant correlation (P <0.025) with at least five of the 14 variables analyzed. Seven of the variables showed significant correlation (P <0.025) with at least 74% of the studied species: ‘Julian date of last spring frost’ with an average value of covariation (C) equal to 0.71, ‘average duration of the frost-free period’ with average value of C = 0.71’, degree days above 5℃’ with covariation of 0.69, ‘altitude above sea level’ with C = 0.66; ‘mean temperature in the coldest month’, ‘mean temperature in the warmest month’ and ‘mean annual temperature’, with average values of C = 0.65 for each of these last three variables. The ‘geographic orientation of the ground’ was the least correlated with the density of the species, since only 10% of them showed significant correlation with this variable.
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