Deforestation Trajectories Research Articles

Charting the future of high forest low deforestation jurisdictions

High forest low deforestation jurisdictions (HFLDs) contain many of the world's last intact forests with historically low deforestation. Since carbon financing typically uses historical deforestation rates as baselines, HFLDs facing the prospect of future threats may receive insufficient incentives to be protected. We found that from 2002 to 2020, HFLDs (n = 310) experienced 44% higher deforestation rates than their historical baselines, and 60 HFLDs underwent periods of high deforestation (deforestation rate > 0.501%) at 0.983 ± 0.649% (mean ± SD)-a rate 7.5 times higher than the 10-y historical baseline of all HFLDs. For HFLDs to receive sufficient carbon finance requires baselines that can better reflect future deforestation trajectories of HFLDs. Using an empirical multifactorial model, we show that most contemporary HFLDs are expected to undergo higher deforestation from 2020 to 2038 than their historical baselines, with 72 HFLDs likely (>66% probability) to undergo high deforestation. Over the next 18 y, HFLDs are expected to lose 2.16 Mha y-1 of forests corresponding to 585 ± 74 MtCO2e y-1 (mean ± SE) of emissions. Efforts to protect HFLD forests from future threats will be crucial. In particular, improving baselining methods is key to ensuring that sufficient financing can flow to HFLDs to prevent deforestation.

High deforestation trajectories in Cambodia slowly transformed through economic land concession restrictions and strategic execution of REDD+ protected areas

Protected Areas (PAs) are continuously being established in tropical forests in an effort to preserve biodiversity and reduce deforestation. It was recently demonstrated that PAs are more effective at reducing forest loss than unprotected control sites across southeast Asia. The voluntary REDD+ scheme offers a new framework for the protection of high deforestation landscapes, jurisdictions, and countries backed by international carbon finance. Here we analyzed the economic drivers of deforestation in Cambodia and the effectiveness of 3 REDD+ projects vs. adjacent protected areas. We find that Economic Land Concessions were a predominant driver of deforestation in Cambodia and influenced the trajectory of illegal forest conversion in PAs. Furthermore, REDD+ projects offer significantly more protection against deforestation than adjacent PAs in two of the three analyzed cases, likely due to enhanced funding enabling implementation of targeted community activities and rigorous monitoring and enforcement.

Deforestation Trajectories on a Development Frontier in the Brazilian Amazon: 35 Years of Settlement Colonization, Policy and Economic Shifts, and Land Accumulation.

We examine deforestation processes in Apuí, a deforestation hotspot in Brazil’s state of Amazonas and present processes of land-use change on this Amazonian development frontier. Settlement projects attract agents whose clearing reflects land accumulation and the economic importance of deforestation. We used a mixed-method approach in the Rio Juma Settlement to examine colonization and deforestation trajectories for 35 years at three scales of analysis: the entire landscape, cohorts of settlement lots divided by occupation periods, and lots grouped by landholding size per household. All sizes of landholdings are deforesting much more than before, and current political and economic forces favoring the agribusiness sector foreshadow increasing rates of forest clearing for pasture establishment in Apuí. The area cleared per year over the 2013–2018 period in Apuí grew by a percentage more than twice the corresponding percentage for the Brazilian Amazon as a whole. With the national congress and presidential administration signaling impunity for illegal deforestation, wealthy actors, and groups are investing resources in land grabbing and land accumulation, with land speculation being a crucial deforestation factor. This paper is unique in providing causal explanations at the decision-maker’s level on how deforestation trajectories are linked to economic and political events (period effects) at the larger scales, adding to the literature by showing that such effects were more important than aging and cohort effects as explanations for deforestation trajectories. Additional research is needed to deepen our understanding of relations between land speculation, illegal possession of public lands, and the expansion of agricultural frontiers in Amazonia.

Spatiotemporal analysis of deforestation in the Chapare region of Bolivia using LANDSAT images

AbstractThe purpose of this study is to quantify (a) spatiotemporal deforestation patterns, and (b) the relationships between changes in the main land‐cover types in the Chapare region of Bolivia. We applied subspace classification methods to LANDSAT data from 1986, 1999, and 2018 and used grid cells at scales of 150, 300, 600, and 900 m to measure deforestation trajectories. The 150 m grids provided better detail to determine deforestation trajectories than coarser‐scale grid cells. Differences in grid‐cell scale did not influence the statistical trends in land‐cover changes significantly. Changes in forest area were negatively correlated with changes in cropland (r = −.44), grassland (r = −.34), swamp grassland (r = −.38), and regrowth (r = −.32) areas. Correlations between forest losses in cropland, grassland, and regrowth change analyses were weaker between 1999 and 2018 compared to 1986 to 1999. Forest cover declined from 6,635 km2 (1986) to 3,800 km2 (2018), and the deforestation rate increased from an annual average of 1.36% between 1986 and 1999 to 2.0% between 1999 and 2018. The key proximate drivers of forest clearance rates and patterns were increasing population, agricultural expansion, and road building. While coca is an economically important crop in Chapare, its direct and indirect effects on deforestation could not be determined unambiguously. It is probable that the expansion of agriculture will lead to further deforestation and forest fragmentation and, along with decreases in forest cover, further changes will take place between non‐forest categories.

The Rio Branco Declaration: Assessing Progress Toward a Near-Term Voluntary Deforestation Reduction Target in Subnational Jurisdictions Across the Tropics

Voluntary commitments are playing an ever-greater role in environmental governance at all scales. In the years preceding the signing of the Paris Agreement in 2015, a flurry of non-state and state actors signed on to various declarations and commitments to reduce deforestation as one globally significant climate mitigation solution. This paper focuses on the Rio Branco Declaration (RBD) and the 30 first-order subnational jurisdictions located in Brazil, Indonesia, Mexico, and Peru that signed on to it between 2014 and 2018, committing to reduce deforestation 80% by 2020, conditional upon adequate financial support from the international community. We assess each study jurisdiction’s progress toward that commitment based on deforestation data, and examine some of the potential factors supporting or slowing progress, including the existence of commensurate targets within jurisdictions’ legal frameworks and the international financial support pledged to jurisdictions. We found that progress toward achieving the target was slow and likely unattainable in most jurisdictions outside of Brazil. Among the four jurisdictions likely to achieve the target under current deforestation trajectories, only Mato Grosso has a target within its legal framework that is more ambitious than the RBD target. We found that the international response to the RBD was sluggish and likely inadequate – with only one financial pledge made in direct response to the declaration and the majority of funding to support jurisdictional efforts coming from one source. We did not find a clear relationship between international finance pledged and progress toward the RBD deforestation target; however, more often, jurisdictions that received pledges earlier have made more progress. We explore what may explain individual jurisdictions’ performance with respect to the target, including specific jurisdictional circumstances, national context, and international support. We estimate that, if current deforestation trajectories continue, the RBD signatories in our study could contribute approximately 3.7% (0.65 GtCO2e) of the greenhouse gas emissions reduction needed to keep global warming at 1.5°C, compared with a potential 5.7% (0.98 GtCO2e) if they were to all meet the RBD target.

Exploring potential impacts of mining on forest loss and fragmentation within a biodiverse region of Brazil's northeastern Amazon

Mining is a significant driver of deforestation. Not only do mines clear native forests for mineral extraction, they also often establish new infrastructure, which indirectly facilitates new access to land and further clearing. Forest loss and fragmentation have serious effects on biodiversity, yet rarely are these cumulative impacts of mining studied at the regional scale. Here, we examine potential impacts of mining in a biodiverse region of the Brazilian Amazon. The National Reserve of Copper and Associates (“Renca”) is currently off limits to mining activities but was recently threatened with a move to permit mineral exploration. We analyzed historic forest loss and fragmentation within two mining regions neighboring Renca. We also investigated historic deforestation trajectories within Renca's protected areas, to determine how well conserved these forests are against current threats. We found that mining, and other infrastructure associated with mines (i.e. roads), caused significant forest loss and fragmentation within neighboring mining sectors, and that Renca's protected areas are not currently immune to forest loss. Permitting new mines within and surrounding Renca will place additional pressure on its biodiversity. If mineral development is to proceed, huge regulatory changes will be required to effectively manage negative impacts on forests and biodiversity. Environmental Impact Assessments for new mining projects must assess and mitigate the cumulative region-wide effects on forests, while existing protected areas must be strengthened to ensure they are not directly or indirectly compromised by mining activities.

Forest Economies: A Remedy to Amazonian Deforestation?

Commonly described as the “lungs of the planet,” the Amazon rainforest represents over half of the remaining rainforest in the world, constituting an important global carbon sink and one of the most culturally- and biologically-diverse regions of the world. The past half-century has seen a worrisome amount of deforestation in this rainforest, but different regions within the Amazon, however, compare differently in terms of deforestation trajectories. What has been the role of products obtained from managing forests, such as the now globally-consumed açaí palm fruit, in reverting deforestation trends? My hypothesis is that there is a statistically significant negative correlation between such forest products and extent of deforestation. This study examines, within the historical and social context of the Amazon Delta and Estuary, the relationship between açaí agroforestry and deforestation. The focus units are the municípios (roughly equivalent to counties) that constitute the Amazon Delta and Estuary, all located in the northern Brazilian states of Amapá and Pará. Statistical data for deforestation obtained from PRODES, a Brazilian governmental project, which monitors deforestation via satellite, is used to ascertain deforestation in the region. This dataset is then correlated with census-based production data for each município for the period from 2002 to 2012. Mapping these variables onto municípios does visually demonstrate a contrast between areas of high deforestation and high açaí production; however, the relationship is not statistically significant.

Trajectory based detection of forest-change impacts on surface soil moisture at a basin scale [Poyang Lake Basin, China

Surface soil moisture plays a critical role in hydrological processes, but varies with both natural and anthropogenic influences. Land cover change unavoidably alters surface property and subsequent soil moisture, and its contribution is yet hard to isolate from the mixed influences. In combination with trajectory analysis, this paper proposes a novel approach for detection of forest-change impacts on surface soil moisture variation with an examination over the Poyang Lake Basin, China from 2003 to 2009. Soil moisture in permanent forest trajectory represents a synthetic result of natural influences and serves as a reference for isolating soil moisture alternation due to land cover change at a basin scale. Our results showed that soil moisture decreased in all forest trajectories, while the absolute decrease was lower for permanent forest trajectory (2.53%) than the whole basin (2.61%), afforestation trajectories (2.70%) and deforestation trajectories (2.81%). Moreover, afforestation has a high capacity to hold more soil moisture, but may take more than 6 years to reach its maximum capacity. Soil moisture increased from 14.09% to 14.94% for the afforestation trajectories with tree aging from 1 to 6 years. Finally, land cover change may affect soil moisture alternation toward different transformation directions. Absolute soil moisture decreases by 0.08% for the whole basin, 0.17% for afforestation and 0.28% for deforestation trajectories, accounting for 3.13%, 6.47% and 10.07% of the total decrease in soil moisture. More specifically, the transformation from woody Savannas, cropland and other lands to forest generated absolute soil moisture deceases of 0.20%, −0.08% and 0.27%, accounting for 7.26%, −3.52% and 9.57% of the decreases. On the other hand, the reverse transformation generated soil moisture deceases of 0.29%, 0.21% and 0.35%, accounting for 10.43%, 7.69% and 12.14% of the total decrease. Our findings should be valuable for evaluating the impacts of land cover change on soil moisture alternation and promoting effective management of water resources.

Offsetting the Impacts of Mining to Achieve No Net Loss of Native Vegetation

Offsets are a novel conservation tool, yet using them to achieve no net loss of biodiversity is challenging. This is especially true when using conservation offsets (i.e., protected areas) because achieving no net loss requires avoiding equivalent loss. Our objective was to determine if offsetting the impacts of mining achieves no net loss of native vegetation in Brazil's largest iron mining region. We used a land-use change model to simulate deforestation by mining to 2020; developed a model to allocate conservation offsets to the landscape under 3 scenarios (baseline, no new offsets; current practice, like-for-like [by vegetation type] conservation offsetting near the impact site; and threat scenario, like-for-like conservation offsetting of highly threatened vegetation); and simulated nonmining deforestation to 2020 for each scenario to quantify avoided deforestation achieved with offsets. Mines cleared 3570 ha of native vegetation by 2020. Under a 1:4 offset ratio, mining companies would be required to conserve >14,200 ha of native vegetation, doubling the current extent of protected areas in the region. Allocating offsets under current practice avoided deforestation equivalent to 3% of that caused by mining, whereas allocating under the threat scenario avoided 9%. Current practice failed to achieve no net loss because offsets did not conserve threatened vegetation. Explicit allocation of offsets to threatened vegetation also failed because the most threatened vegetation was widely dispersed across the landscape, making conservation logistically difficult. To achieve no net loss with conservation offsets requires information on regional deforestation trajectories and the distribution of threatened vegetation. However, in some regions achieving no net loss through conservation may be impossible. In these cases, other offsetting activities, such as revegetation, will be required.

Landscape dynamics of Amazonian deforestation between 1986 and 2007 in southeastern Peru: policy drivers and road implications

Public policies can lead to deforestation and forest fragmentation depending on the particular land uses policies seek to promote. In turn, sequences of distinct policy incentives can generate nonlinear trajectories in deforestation and habitat fragmentation. This article takes up the case of Peru, where successive presidential administrations have promoted very different land uses. I focus on Madre de Dios, a frontier region in the southeastern Peruvian Amazon, to evaluate deforestation and fragmentation from 1986 to 2007, which covers several distinct policy periods. I draw on classified Landsat TM, ETM+, and Aster images in 5-year intervals from 1986 to 2001 and bi-annual images from 2001 to 2007 to observe trajectories in forest, crops and pasture, and regrowth. The analysis permits observation of nonlinearities in changes in the land cover classes, as well as fragmentation metrics related to size, density, connectivity, and configuration of the land cover classes over time. Distinct policies show different deforestation trajectories and fragmentation values. These findings bear implications for the study of public policies and spatiotemporal land cover dynamics and offer new monitoring tools to understand the complexity of environmental change.

Trajectories of deforestation, coffee expansion and displacement of shifting cultivation in the Central Highlands of Vietnam

Production of commodities for global markets is an increasingly important factor of tropical deforestation, taking over smallholders subsistence farming. Measures to reduce deforestation and convert shifting cultivation systems towards permanent crops have recently been strengthened in several countries. But these changes have variable environmental and social impacts, including on ethnic minorities. In Vietnam, although a forest transition – i.e. shift from shrinking to expanding forest cover – occurred at the national scale, deforestation fronts and agricultural colonization for commodity crops – a.o. coffee – still dominated the Central Highlands plateaus. Previous studies suggested that the dominant land use changes in that region were on the one hand the acquisition and conversion of agricultural lands to perennial crops for external markets by capital-endowed Kinh households – the majority ethnic group in Vietnam – and on the other hand the corresponding displacement of poor households of ethnic minorities relying on shifting cultivation towards the forest margins. This study tested this hypothesis by using remote sensing to analyze land use and cover changes and deforestation trajectories in the coffee-growing area in Dak Lak and Dak Nong provinces over 2000–2010. Land use changes were linked with socioeconomic dynamics using secondary statistics and spatial modelling. Net deforestation reached −0.31%y−1 of the total area between 2000 and 2010. Deforestation was indeed mainly directly caused by shifting cultivation for annual crops, but this was partly driven indirectly by expansion of coffee and other perennial crops over agricultural lands. Displacement of shifting cultivation into the forest margins, pushed by market crops expansion, was the spatial manifestation of the marginalization of local ethnic minorities and poor migrants, pushed by capital-endowed migrants. This marginalization is a long-standing process rooted in the colonization and development strategy for the highlands followed since colonial times. Over the late 2000s, rapid deforestation was strongly reducing the benefits of national-scale forest recovery, and might shift the country back to net losses of natural forest. Implications for policies that may affect deforestation are discussed.

Level-dependent deforestation trajectories in the Brazilian Amazon from 1970 to 2001

This article demonstrates the importance of examining level-dependent deforestation trajectories that may be undetected within regional analyses. We examine Amazon-wide, sub-regional, settlement, and farm-level deforestation trajectories in the Brazilian Amazon and suggest factors that underlie level-dependent differences in spatial patterns and temporal magnitudes of deforestation from 1970 to 2001. At a sub-regional level, we find significant variation in frequency, magnitude, and intensity of deforestation associated with context-specific processes, including areas that have stopped deforesting, are rapidly reforesting, while at the same time increasing economic value of forest-based production. We use remote-sensing data from 1970 to 2001. For Amazon-wide and state-level analyses, we use data available from Brazil’s National Institute for Space Research. For sub-regional, settlement, and farm-lot levels, time-series Landsat images and aerial photographs and detailed field-based research are used to reconstruct the history of deforestation. Our analysis empirically demonstrates that understanding deforestation trajectories requires differentiating underlying causes at different levels of analysis and to be wary of overarching explanations and solutions that ignore differences in scale.

Combining land transitions and trajectories in assessing forest cover change

One restriction of landscape studies is that land use and cover change is often regarded as irreversible. A highly dynamic landscape in southern Chile was selected to show that forest cover change involves a series of complex transitions and trajectories. Using Landsat images from 1976, 1985, 1999 and 2007 an in-depth analysis of the transition matrix was conducted to separate random and systematic transitions which were grouped into trajectories using a pixel-history approach. Main trajectories were linked to fragmentation indices and farming systems through cluster analysis. Of the 247 trajectories identified, old growth forest persistence comprised 22% of the landscape, whereas deforestation trajectories comprised 20.9% and were mostly composed of changes from old growth forest to shrubland (13.9%). Trajectories of forest degradation from old growth to secondary forest comprised 19.7% of the landscape. The periods 1976–1985 and 1999–2007 concentrated the most systematic deforestation and degradation transitions. In turn, random transitions predominated between 1985 and 1999, probably in response to economic factors that acted suddenly on the landscape during the 80’s, such as the woodchip export and aquaculture booms. A close relationship between landscape fragmentation and the proportion of systematic transitions and farming systems was found; specifically, the highest entropy indices occurred in clusters which exhibited the lowest proportion of systematic transitions and the highest proportion (>70%) of peasant agricultural systems. Understanding the complexity of forest cover change trajectories is relevant for improving the prediction of possible landscape evolutions and establishing landscape management priorities.

Country ‘choices’ or deforestation paths: A method for global change analysis of human-forest interactions

Data used in quantitative studies of global tropical deforestation are typically of poor quality. These studies use either cross-sectional or panel data to measure the contribution of social and land use factors to forest decline world wide. However, there are pitfalls in the use of either type of data. Panel data studies treat each year’s observation as a distinct, reliable, data point, when a careful examination of the data reveals this assumption to be implausible. In contrast, cross-sectional studies discard most of the time series information in the data, calculating a single average deforestation rate for each country. In this paper, we argue for a middle road between these two approaches: one that does not treat the time series information as completely reliable but does not disregard it altogether. Using a well-known global forest data set (FAO’sProduction Series Yearbooks ), we argue that the most the data can reliably tell us is whether a country’s deforestation rate falls into one of four categories or country ‘path choices’. We then use the data categorised in this way in a small empirical investigation of the socio-economic causes of deforestation. This multinomial logit framework allows for the determination of the influence of independent variables on the probability that a country will follow one deforestation path vs. another. Results from the logit analysis of key social and land use indicators chosen for their importance in the literature in driving deforestation suggest that the effect of these variables will differ for countries depending on the particular set of deforestation trajectories in question.