Socioecological system and potential deforestation in Western Amazon forest landscapes

• Published in: The Science of the total environment Vol. 644; pp. 1044 - 1055
• Main Authors: Bonilla-Bedoya, S., Estrella-Bastidas, Anabel, Molina, Juan Ramón, Herrera, Miguel Ángel
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 10-12-2018
• Subjects: Amazon forest landscapes; Human and environment relationships; Land use management; Sustainable forest management; Amazon forest landscapes; Human and environment relationships; Land use management; Sustainable forest management
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2018.07.028

The ecosystem services provided by tropical forests are affected by deforestation. Territorial management strategies aim to prevent and mitigate forest loss. Therefore, modeling potential land use changes is important for forest management, monitoring, and evaluation. This study determined whether there are relationships between forest vulnerability to deforestation (potential deforestation distribution) and the forest management policies applied in the Ecuadorian Amazon.
Proxy and underlying variables were used to construct a statistical model, based on the principle of maximum entropy that could predict potential land use changes. Entropy can be seen as a measure of uncertainty for a density function. Receiver operating characteristics (ROC) analysis and the Jackknife Test were used to validate the model. The importance of input variables in the model was determined through: Percent Contribution (PC) and Permutation Importance (PI). The results were compared with prevailing regional forest management strategies.
The socioeconomic variables that provided the largest amount of information in the overall model (AUC = 0.81) and that showed most of the information not present in other variables were: “Protected areas-Intangible zone” (PC = 24%, PI = 12.4%), “timber harvesting programs” (PC = 21.7%, PI = 4.7%), “road network” (PC = 18.9%, PI = 7.7%), and “poverty rate” (PC = 3.7%, PI = 6.1%). Also, the biophysical variable “temperature” (PC = 7,9%, PI = 22.3%) provided information in the overall model.
The results suggested the need for changes in forest management strategies. Forest policies and management plans should consider integrating and strengthening protected areas and intangible zones, as well as restricting timber harvesting in native forest and establishing forest areas under permanent management. Furthermore, the results also suggested that financial incentive programs to reduce deforestation have to be evaluated because their present distribution is inefficient. In this context, conservation incentive plans need to be revised so that they focus on areas at deforestation risk.
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•Modeling deforestation could improve forest landscape planning and management.•Maximum entropy models as effective estimators in land use change studies, forest management, and deforestation distribution.•Mixed variables quantified the relationship between deforestation potential distribution and regional forest management.•Legal timber harvesting, protected areas, oil extraction and road network boost Western Amazon landscape deforestation.