Pastures and crops have been expanding at an accelerated rate in the forests of the Colombian Amazon since the peace accords were signed in 2016. The rapid loss of tropical rainforests is threatening the integrity of protected areas and connectivity in the Amazon and other natural regions. In the context of the post-conflict stage, a set of land use and land cover change scenarios were constructed for the Colombian Amazon for the year 2040, using expert coherent narratives. Three scenarios were designed: trend, extractivist, and sustainable development. Historic land use change and driving factors were analyzed throughout 14 transitions between the years 2002 and 2016, based on the interpretation of Landsat images and their relationship with 29 driving factors using artificial neural networks. The Markov chain model was calculated for the transitions, and the change allocation model was parameterized to spatially simulate the scenarios. The results showed that the LULC model calibration and validation were satisfactory (0.91). The sustainable development scenario that considers strong policies for the conservation of forests and implementation of sustainable production projects was the option with greater values for conserved forests and secondary vegetation in recovery, adding ~ 42 million hectares by 2040. The other scenarios showed that the Colombian Amazon will lose ~ 2 million hectares of forests in the trend scenario and ~ 4.3 million hectares in the extractivist scenario, based on the reference year (2016). In the trend scenario, pastures and crops could increase by 48%; and, in the extractivist scenario, these would increase by 117%, changing from ~ 3.9 to ~ 8.6 million hectares. We hope that the scientific contribution of this study will be relevant for informed discussion in decision-making and provide a framework for building a peaceful territory.
CITATION STYLE
Agudelo-Hz, W. J., Castillo-Barrera, N. C., & Uriel, M. G. (2023). Scenarios of land use and land cover change in the Colombian Amazon to evaluate alternative post-conflict pathways. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-29243-2
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