Identifying degraded lands and degradation trends is essential to determine measures that contribute to avoiding, reducing, and reversing the rate of deterioration of natural resources. In this study, we assessed the state and trend of degradation in Ixtacamaxtitlan, Puebla, Mexico, by determining the spatial and temporal changes of three indicators, Land Cover (LC), Land Productivity Dynamics (LPD), and Soil Organic Carbon (SOC), during the period 2000–2015, using global data proposed by the Convention to Combat Desertification for the implementation of Land Degradation Neutrality (LDN). The results showed increases in croplands (6.89%) and a reduction in grasslands (9.09%), with this being the transition that presents the most significant extension in the territory. The LPD is the indicator where the most deterioration was observed, and due to negative changes in LC, SOC losses were estimated at more than 7000 tons in the study period. The proportion of degraded land was 19% of approximately 567.68 km2 of Ixtacamaxtitlan’s surface. Although the municipality presents incipient degradation and only a tiny part showed improvement, identifying areas with degradation processes in this work will favor degradation monitoring and the adequate planning and application of restoration measures in the local context to promote the path towards LDN.
La determinación de cambios en la cubierta terrestre (CT) es importante para entender la dinámica de los ecosistemas. En este estudio se analizaron los cambios espaciales y temporales en el municipio de Ixtacamaxtitlán, Puebla durante el periodo 2000-2015, utilizando los mapas globales de la Agencia Espacial Europea ESA-CCI-LC. Para ello, se determinó la matriz de cambios, la tasa anual de cambio y la probabilidad de permanencia, así como la precisión del mapa de CT 2015. Los resultados indican que las pérdidas se concentraron en las coberturas arboladas y pastizales (0.27% y 8.83%, respectivamente), mientras que las ganancias se dieron en tierras de cultivo y zonas urbanas (6.9% y 8.11%, respectivamente). La mayoría de los cambios se observaron en las zonas de fácil acceso ubicadas en la porción centro-norte del municipio. De las 1962 ha que presentaron cambios entre categorías, en 87.4% el cambio fue negativo y en 12.6% fue positivo, destacando la transición de pastizales y superficies arboladas hacia tierras de cultivo, causadas por diversos procesos socioeconómicos presentes en la zona como marginación, migración, acceso a programas gubernamentales, expansión de áreas agrícolas y diversificación de cultivo. El mapa de CT 2015 mostró una alta precisión a escala subnacional (85.64%) lo que revela que este conjunto de datos es confiable para el estudio de las transformaciones en el territorio.
Forests play an essential role in climate change as they are the terrestrial ecosystems that store the highest C content in their soils and biomass. Despite this, the lack of information at the subnational level hinders their proper management and conservation. This study aimed to identify the extension and distribution of forests and to develop an empirical model for the spatial prediction of soil organic matter (SOM) in Ixtacamaxtitlan, Puebla, Mexico, based on environmental variables generated through Geographical Information Systems. A supervised classification in Landsat 8 images was used to define the forest cover, and environmental variables related to topography, climate and vegetation were generated. Finally, a Multiple Linear Regression model validated with the leave-one-out cross-validation method was used to examine the relationships between the covariates and the SOM and estimate its content in forest. The results show that the forest cover extension is 41%, with an overall accuracy of 97.7%. The model shows a good fit (R2cv = 0.69, RMSEcv = 1.53). The mean of SOM was 5.2%, and upper values were consistent with higher altitude, precipitation and cooler temperature. Estimating SOM content in forest areas is essential in developing planning strategies at the subnational level to mitigate the harmful effects of climate change.
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