Spatial distribution of population and forest cover in extractive reserves in the Amazon biome, Brazil
DOI:
https://doi.org/10.20947/S0102-3098a0294%20Palabras clave:
Distribución Espacial, Áreas Protegidas, LUCC, Fragmentación Forestal, Regresión Lineal, Valor de ShapleyResumen
Este estudio relaciona las medidas espaciales de la cobertura forestal con las medidas de la distribución espacial de la población en las 31 Reservas Extractivas (REs) dentro del bioma amazónico, Brasil, en 2010. Integramos capas de información sobre las REs, la cobertura forestal y la distribución espacial de la población en un Sistema de Información Geográfica. Producimos 24 variables en tres grupos: 1) Población, 2) Condiciones Externas (ambas como variables predictoras), y 3) Cobertura Terrestre (variables predichas). Evaluamos si las variables predictoras están correlacionadas con las variables de cobertura y fragmentación forestal. Se realizaron análisis de regresión lineal basados en la teoría de juegos cooperativos para comprender la importancia de las variables predictoras en la predicción del número de fragmentos forestales y el porcentaje de cobertura forestal en los modelos. Encontramos que el tamaño, la concentración, la dispersión y la geometría de la población contribuyeron a comprender la deforestación, así como la estructura del paisaje. Sin embargo, la fragmentación forestal y la extensión de la cobertura forestal no están necesariamente definidas por los mismos aspectos de la población. Los modelos sugieren que el cambio en la cobertura forestal está impulsado principalmente por la concentración de la población en la RE, mientras que la fragmentación forestal está altamente influenciada por la dispersión de la población. El papel de las condiciones externas (bosques circundantes y áreas protegidas) también fue relevante. Nuestro estudio destaca la importancia de incorporar medidas de distribución espacial de los bosques en la investigación sobre Población y Medio Ambiente, más allá del enfoque habitual en la extensión forestal. También muestra la importancia de trabajar con variables demográficas espaciales, yendo más allá del enfoque convencional centrado en el tamaño de la población.
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