The effect of agricultural intensification and population growth in the local climate. A case study of the Ecuadorian Amazon.

Among the most important transitions in land use change detected in the Ecuadorian Amazon, two stand out: i) agricultural intensification/rotation and ii) the expansion of populated areas. Both are the result of rural development in recent decades on the slope hills of Ecuador towards the Amazon. The changes registered in the landscape are the consequence of an intensification of forestry, agricultural, livestock and mining activities, which has negatively impacted ecosystems, causing loss/mobilization of fauna and biodiversity. Consequently, ecosystems have also been affected by changes in local climatic characteristics with different degrees of affectation. Local changes in temperature, soil moisture, relative humidity, and wind speed are studied in detail in order to improve decision-making regarding conservation and remediation actions for the Amazon biome. In this study, based on land use and cover maps, spatiotemporal analysis of the evolution of the two transitions was carried out, coupled with an analysis of time series of climatic variables. Contrast analysis with long persistence was carried out in the surroundings of changed patches to confirm the climatic variation because of the transition according to LULCC. A landscape ecology approach was used to support and characterise the analysis of transitions and their relationship with the dynamic characteristics and trends of climatic variables. As a preliminary result, a detected set of points with the greatest territorial dynamics associated with local climate change. This set of patches is valuable to prioritize actions in the short term.

Acknowledgements

The authors acknowledge the support of the Master in Climate Change, Agriculture and Sustainable Rural Development (MACCARD), co-funded by the Erasmus + Programme of the European Union. The authors also acknowledge support from European Union NextGenerationEU and RD 289/2021 and the support of Project No. PGC2018-093854-B-I00 of the Ministerio de Ciencia, Innovación y Universidades de España.

 

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