Peruvian Amazon disappearing: Transformation of protected areas during the last two decades (2001-2019) and potential future deforestation modelling using cloud computing and MaxEnt approach

被引:13
作者
Sanchez, Alexander Cotrina [1 ]
Bandopadhyay, Subhajit [2 ]
Briceno, Nilton B. Rojas [1 ]
Banerjee, Polash [3 ]
Guzman, Cristobal Torres [1 ]
Oliva, Manuel [1 ]
机构
[1] Univ Nacl Toribio Rodriguez de Mendoza Amazonas, Inst Invest Desarrollo Sustentable Ceja Selva IND, Chachapoyas 0100, Peru
[2] Poznan Univ Life Sci, Fac Environm & Mech Engn, Dept Ecol & Environm Protect, Lab Bioclimatol, PL-60649 Poznan, Poland
[3] Sikkim Manipal Inst Technol, Dept Comp Sci & Engn, Majitar 737136, Sikkim, India
关键词
Amazon; Peruvian Amazon; Deforestation; Protected Areas; Maximum Entropy; Peru; LAND-USE CHANGE; SPECIES DISTRIBUTIONS; BRAZILIAN AMAZON; CLIMATE-CHANGE; FOREST; FIRE; CONSERVATION; IMPACT; CONSUMPTION; VALIDATION;
D O I
10.1016/j.jnc.2021.126081
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Despite several measures that have been taken to promote the conservation of the Peruvian Amazon, several reports exhibited that forest cover loss was still occurring. To combat against deforestation and landscape change, the Peru government has created Protected Areas (PAs) to maintain floral diversity, conserve forests and environmental services. Along with tremendous anthropogenic pressures, billions of dollars have been spent every year to promote and save the PAs, yet rigorous quantified evaluation and interpretation of such PAs are lacking. Considering such knowledge gap, we have quantified the forest loss under the PAs and their buffer areas over the last 20 years (2001-2019) have been performed using Google Earth Engine. Furthermore, the potential deforestation risk zones were identified using the Maximum Entropy based predictive modelling. Outcome showed that the forest cover losses within the PAs were 114,463 ha and 782,781 ha within the buffer zones in the last 20 years. Additionally, high deforestation risk zones were mainly found in the central and southwestern parts of the Peruvian Amazon and interestingly close to the navigable riverbanks. We have received high prediction accuracy (AUC 0.964) and further validated with high-resolution PlanetScope imageries. This study will be useful for policy interventions and conservation measures.
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页数:15
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