Drivers of tropical deforestation: a global review of methodological approaches and analytical scales

Bernhard, Katie P.; Shapiro, Aurélie C.; Hunt, Carter A.

doi:10.1007/s10531-023-02747-z

Cited by 1 publication

(4 citation statements)

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“…First, the drivers of deforestation literature highlights the role of small-scale agriculture as a driver of forest change in Sub-Saharan Africa (SSA). In SSA, despite substantial efforts towards protection, small-scale agriculture remains a primary proximate driver of both deforestation and degradation [6][7][8]11,20,42,[45][46][47]. Other common drivers include subsistence extraction activities like fuelwood collection, infrastructure development, small-scale and industrial mining, and natural or anthropogenic fires, many of which are frequently found in combination [2,11,42,48,49].…”

Section: Literature Reviewmentioning

confidence: 99%

“…In addition to the proximate causes of forest change in the tropics and SSA, there are underlying conditions enacted from local to global scales that influence forest and land cover change [42,45,[50][51][52][53]. Conflict [30,[54][55][56], political instability, and weak institutions [54,57,58] impact forest cover through inconsistent application of environmental policy or increasing pressure to extract natural resources.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Institutional, governance, conflict, and other social, political, and economic factors that influence forest change also segue into factors that influence protected areas effectiveness [18,31,61]. Conflict, for example, can have varying influences on forest cover, in some cases increasing degradation and, in other cases, reducing degradation via internal displacement and reduced pressure on a forest system [42,43,49,55,61]. Yet conflict has resulted in enforcement challenges and de-prioritization for Central African protected areas in regions of the DRC and in conflicted areas of CMR and CAR (Figure 2) [62].…”

Section: Literature Reviewmentioning

confidence: 99%

“…As this literature continues to develop, several innovative open-source and cloudbased geospatial applications have advanced in recent years, enabling access to advanced processing capabilities for vast collections of high-resolution satellite imagery in the cloud [6,[33][34][35][36][37][38][39][40][41][42]. The increased availability, accessibility, and quality of earth observation (EO) data opens doors to understanding the factors that influence protected area effectiveness through forest and land cover changes in new and under-studied contexts and creates opportunities to address challenges for ecosystems and sustainable development via spatial and land use planning [6,10,34,37,43,44].…”

Section: Introductionmentioning

confidence: 99%

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Transboundary Central African Protected Area Complexes Demonstrate Varied Effectiveness in Reducing Predicted Risk of Deforestation Attributed to Small-Scale Agriculture

Bernhard,

Shapiro,

d’Annunzio

et al. 2024

Remote Sensing

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The forests of Central Africa constitute the continent’s largest continuous tract of forest, maintained in part by over 200 protected areas across six countries with varying levels of restriction and enforcement. Despite protection, these Central African forests are subject to a multitude of overlapping proximate and underlying drivers of deforestation and degradation, such as conversion to small-scale agriculture. This pilot study explored whether transboundary protected area complexes featuring mixed resource-use restriction categories are effective in reducing the predicted disturbance risk to intact forests attributed to small-scale agriculture. At two transboundary protected area complex sites in Central Africa, we used Google Earth Engine and a suite of earth observation (EO) data, including a dataset derived using a replicable, open-source methodology stemming from a regional collaboration, to predict the increased risk of deforestation and degradation of intact forests caused by small-scale agriculture. For each complex, we then statistically compared the predicted increased risk between protected and unprotected forests for a stratified random sample of 2 km sites (n = 4000). We found varied effectiveness of protected areas for reducing the predicted risk of deforestation and degradation to intact forests attributed to agriculture by both the site and category of protected areas within the complex. Our early results have implications for sustainable agriculture development, forest conservation, and protected areas management and provide a direction for future research into spatial planning. Spatial planning could optimize the configuration of protected area types within transboundary complexes to achieve both forest conservation and sustainable agricultural production outcomes.

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