Abstract
Tropical forests are disappearing at an alarming rate. In Central America, a hectare of forest is cleared for agriculture every 5 min. This study was conducted in a forested 4,000 ha watershed of central Honduras to find deforestation causes based on socio-economic characteristics of population. First, a multitemporal analysis of Landsat TM imagery was conducted to determine deforestation rates and agricultural–forest boundaries. A GIS buffer procedure allowed determining which households were at the deforestation front and which households were located at the rest of the area (control). GIS techniques were used to extract biophysical information such as slope, elevation, land cover, temperature, precipitation, etc. Then, we set up a data base with more than 50 socioeconomic variables (level of education, income, children per family, major economic activity, use of conservation practices, etc.). Around 500 households, distributed all over the watershed, were visited, interviewed and GPS-located. A multivariate statistical analysis allowed an exploratory analysis to eliminate non useful and redundant variables and then to determine what variables appear to be important predictors of deforestation behavior among rural families. A resulting logistic regression model showed that household with lower annual income heads and with less use of conservation practices were more statistically prone to clear the forest (α = 0.001). The study uncovered the complexity of this problem and confirmed the need of using GIS–remote sensing techniques to combine socioeconomic and environmental data in several time–space dimensions to find the causes and trends of tropical deforestation.
Resumen
Los bosques tropicales están desapareciendo a un ritmo alarmante. En América Central, una hectárea de bosque es deforestada con fines agrícolas cada cinco minutos. Este estudio se realizó en una cuenca forestal de 4.000 hectáreas en el centro de Honduras con el objetivo de encontrar las causas de deforestación basado en las características socioeconómicas de la población. En primer lugar, un análisis multitemporal de imágenes Landsat TM se llevó a cabo para determinar las tasas de deforestación y las fronteras agrícolas-forestales. Un procedimiento búfer de Sistemas de Información Geográficos, SIG permitió determinar que los hogares estaban en el frente la deforestación y que los hogares se encuentra en el resto de la zona (de control). Las técnicas de SIG se utilizaron para extraer la información biofísica como la pendiente, la altitud, la cobertura del suelo, temperatura, precipitación, etc. Se estableció una base de datos con más de 50 variables socioeconómicas (nivel de educación, ingresos, niños por familia, importancia económica la actividad principal, el uso de prácticas de conservación, etc.). Alrededor de 500 familias, repartidas por toda la cuenca, fueron visitadas, se entrevistaron y se ubicó su posición con un Sistema de Posicionamiento Global (GPS). Un análisis estadístico multivariado permitió un análisis exploratorio para eliminar las variables irrelevantes y redundantes y luego determinar qué variables parecían ser predictoras importantes del comportamiento de la deforestación de las familias rurales. Un modelo resultante de regresión logística mostró que los hogares con menores ingresos anuales y con un menor uso de prácticas de conservación fueron estadísticamente más propensos a cortar el bosque (α = 0,001). El estudio puso de manifiesto la complejidad de este problema y confirmó la necesidad de la utilización de los SIG, de las técnicas de teledetección para combinar los datos socioeconómicos y ambientales en varias dimensiones de espacio-tiempo para encontrar las causas y tendencias de la deforestación tropical.
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Acknowledgments
We thank Noe Perez and Ramon Alvarez for their contributions to the development of this research. We also thank Alexander Hernandez and Carlos Meza for their technical support. ESNACIFOR students provided the field logistical support. The USAID mission in Honduras, through the Forestry Development Project, provided the financial means to this study. We also appreciate the contributions of many families of the study area who shared their personal information with us.
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Rivera, S., Martinez de Anguita, P., Ramsey, R.D. et al. Spatial Modeling of Tropical Deforestation Using Socioeconomic and Biophysical Data. Small-scale Forestry 12, 321–334 (2013). https://doi.org/10.1007/s11842-012-9214-2
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DOI: https://doi.org/10.1007/s11842-012-9214-2