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Spatiotemporal Assessment of Deforestation and Forest Degradation Indicates Spillover Effects From Mining Activities and Related Biodiversity Offsets in Madagascar
Context
For nearly three years, the COVID-19 pandemic has disrupted human well-being and livelihoods, communities, and economies in myriad ways with consequences for social-ecological systems across the planet. The pandemic represents a global shock in multiple dimensions that has already, and is likely to continue to have, far-reaching effects on land systems and on those depending on them for their livelihoods.
Objectives
We focus on the observed effects of the pandemic on landscapes and people composing diverse land systems across the globe.
Methods
We highlight the interrelated impacts of the pandemic shock on the economic, health, and mobility dimensions of land systems using six vignettes from different land systems on four continents, analyzed through the lens of socio-ecological resilience and the telecoupling framework. We present preliminary comparative insights gathered through interviews, surveys, key informants, and authors’ observations and propose new research avenues for land system scientists.
Results
The pandemic’s effects have been unevenly distributed, context-specific, and dependent on the multiple connections that link land systems across the globe.
Conclusions
We argue that the pandemic presents concurrent “natural experiments” that can advance our understanding of the intricate ways in which global shocks produce direct, indirect, and spillover effects on local and regional landscapes and land systems. These propagating shock effects disrupt existing connections, forge new connections, and re-establish former connections between peoples, landscapes, and land systems.
Madagascar's unique biota is heavily affected by human activity and is under intense threat. Here, we review the current state of knowledge on the conservation status of Madagascar's terrestrial and freshwater biodiversity by presenting data and analyses on documented and predicted species-level conservation statuses, the most prevalent and relevant threats, ex situ collections and programs, and the coverage and comprehensiveness of protected areas. The existing terrestrial protected area network in Madagascar covers 10.4% of its land area and includes at least part of the range of the majority of described native species of vertebrates with known distributions (97.1% of freshwater fishes, amphibians, reptiles, birds, and mammals combined) and plants (67.7%). The overall figures are higher for threatened species (97.7% of threatened vertebrates and 79.6% of threatened plants occurring within at least one protected area). International Union for Conservation of Nature (IUCN) Red List assessments and Bayesian neural network analyses for plants identify overexploitation of biological resources and unsustainable agriculture as the most prominent threats to biodiversity. We highlight five opportunities for action at multiple levels to ensure that conservation and ecological restoration objectives, programs, and activities take account of complex underlying and interacting factors and produce tangible benefits for the biodiversity and people of Madagascar.
Growing demand for minerals continues to drive deforestation worldwide. Tropical forests are particularly vulnerable to the environmental impacts of mining and mineral processing. Many local- to regional-scale studies document extensive, long-lasting impacts of mining on biodiversity and ecosystem services. However, the full scope of deforestation induced by industrial mining across the tropics is yet unknown. Here, we present a biome-wide assessment to show where industrial mine expansion has caused the most deforestation from 2000 to 2019. We find that 3,264 km2 of forest was directly lost due to industrial mining, with 80% occurring in only four countries: Indonesia, Brazil, Ghana, and Suriname. Additionally, controlling for other nonmining determinants of deforestation, we find that mining caused indirect forest loss in two-thirds of the investigated countries. Our results illustrate significant yet unevenly distributed and often unmanaged impacts on these biodiverse ecosystems. Impact assessments and mitigation plans of industrial mining activities must address direct and indirect impacts to support conservation of the world’s tropical forests.
Despite the continuous growth in renewable sources of energy, coal remains the primary
source of energy security in developing countries and accounted for 1.1 Gt of CO2 annually. The present study was conducted to examine the dynamic land cover changes, deforestation, and carbon (C) emissions in the mined landscape of Central India. Geospatial techniques coupled with field measurements were conjunctively employed for quantifying land use and vegetation changes from the period of 2001 to 2020. The unchecked mining (6.4–30 Km2) along with the rapid expansion of agriculture (586.7–642.5 Km2) were identified as major drivers of deforestation, which resulted in the net loss of 115.3 Km2 area under intact Sal dominant forest. The mining and associated activities increased the fragmentation of intact forest that had not only decreased density, basal area, and diversity of vegetation but also a huge loss of biomass of ~2.5 Tg that contributed to a net loss of 1.08 Tg C (~3.98 Tg of CO2) in the past twenty years. The study explored the use of land management options and confirmed that C offset ensued from land use changes without hampering coal production for the next two decades. The scenarios will provide valuable information to the policymakers for devising sustainable coal mining by underpinning the ecological compensation for deforestation while promoting cleaner production technologies through decarbonization to counteract emissions, which could help in achieving ambitious goals set by India for planned C reduction targets as Intended Nationally Determined Commitments under Paris Agreement (2015).
Mining sites are areas where mining and restoration coexist and are constantly changing. The vegetation condition can reflect the process of surface mining and restoration, while quantifying the impacts of different mining patterns and surrounding environments on vegetation is the key to balancing mining activities and ecological restoration. In this study, long-term monitoring from 1986 to 2020 was implemented by the LandTrendr algorithm to reveal the ecological impacts of two concentrated and contiguous surface mining sites with different mining patterns (scattered and aggregated mining) and surrounding environments in Inner Mongolia, China. The results show that it is reasonable to use the LandTrendr algorithm for long-term monitoring of surface mining sites, and that the ecological impacts of different surface mining sites in ecologically fragile areas have the same regularity. As the duration increases, the magnitude of disturbance decreases, and the magnitude of recovery first decreases and then reaches a natural fluctuation state after 20 years of recovery. Different mining patterns and surrounding environments bring different ecological impacts. Scattered mining areas are more likely to produce natural recovery while the restored ecosystem is more stable. The performance of mining development disturbance is more obvious in places with better ecological environment, while the effect of ecological restoration is also more significant. This study can provide guidance for the rational planning of mining and restoration activities in ecologically fragile areas.
There is little robust, quantitative information on the impacts of the COVID-19 pandemic on the extinction crisis. Focusing on Madagascar, one of the world’s most threatened biodiversity hotspots, we explore whether the cessation of on-site protected-area management activities due to the pandemic were associated with increased burning inside protected areas. We identify monthly excess fire anomalies by comparing observed fires with those predicted on the basis of historical and contemporary fire and weather data for all of Madagascar’s protected areas for every month 2012–2020. Through to 2019, excess fire anomalies in protected areas were few, short in duration and, in some years, coincident with social disruption linked to national elections. By contrast, in 2020, COVID-19 meant on-site management of Madagascar’s protected areas was suspended from March to July. This period was associated with 76–248% more fires than predicted, after which burning returned to normal. At a time when international biodiversity conservation faces unprecedented challenges, our results highlight the importance of on-site management for maintaining protected-area integrity. The COVID-19 pandemic has affected a range of human activities, but its effect on land management is less clear. This study finds an increase in fires inside Madagascar’s protected areas during periods when management stopped due to COVID-19 lockdowns.
Global climate change is continuing to occur at an alarming rate. In addition to increases in global weather extremes, melting of polar ice caps, and subsequent sea level rises, climate change is known to directly impact the life cycles and ecolo-gies of many animals and plants. While climate change is projected to result in substantial geographic range and habitat contractions for many species in future, the effects of climate change on many habitats of conservation concern remain poorly understood. In this study, we investigated how future climate change is projected to impact the occurrence and distribution of four major forest types of Madagascar, a global biodiversity hotspot and conservation priority, over the next 60 years. We also compared how climate change effects vary among the four forest types under a "mitigation" climate forecast and under a "business-as-usual" trajectory. As expected, our models suggest that future climate change will affect the distribution of the four forest types under both trajectories, and forest occurrence is likely to decrease if mean temperatures, temperature seasonality, and precipitation rates increase as predicted. The exception is that forest gain is predicted to occur in the northwest of Madagascar, resulting in a small increase in transitional forest area under the "business-as-usual" climate change trajectory. Our study highlights that unmitigated climate change will have a negative impact on Madagascar's forests during the period up to the year 2080, and climate change therefore needs to be mitigated. Madagascar remains a global conservation priority, and urgent conservation action and protective legislation are required to safeguard the future of its native forest.
Meeting the UN Sustainable Development Goals requires reconciling development with biodiversity conservation. Governments and lenders increasingly call for major industrial developments to offset unavoidable biodiversity loss but there are few robust evaluations of whether offset interventions ensure no net loss of biodiversity. We focus on the biodiversity offsets associated with the high-profile Ambatovy mine in Madagascar and evaluate their effectiveness at delivering no net loss of forest. As part of their efforts to mitigate biodiversity loss, Ambatovy compensate for forest clearance at the mine site by slowing deforestation driven by small-scale agriculture elsewhere. Using a range of methods, including extensive robustness checks exploring 116 alternative model specifications, we show that the offsets are on track to avert as much deforestation as was caused by the mine. This encouraging result shows that biodiversity offsetting can contribute towards mitigating environmental damage from a major industrial development, even within a weak state, but there remain important caveats with broad application. Our approach could serve as a template to facilitate other evaluations and so build a stronger evidence-base of the effectiveness of no net loss interventions. Despite the growing use of biodiversity offsets from major industrial projects, little is known about how effective they are. This study shows that the offsets associated with the Ambatovy mine in Madagascar trying to compensate for deforestation at the mine site are on track to achieve no net loss of forest.
The Amazon Basin is undergoing extensive environmental degradation as a result of deforestation and the rising occurrence of fires. The degradation caused by fires is exacerbated by the occurrence of anomalously dry periods in the Amazon Basin. The objectives of this study were: (i) to quantify the extent of areas that burned between 2001 and 2019 and relate them to extreme drought events in a 20-year time series; (ii) to identify the proportion of countries comprising the Amazon Basin in which environmental degradation was strongly observed, relating the spatial patterns of fires; and (iii) examine the Amazon Basin carbon balance following the occurrence of fires. To this end, the following variables were evaluated by remote sensing between 2001 and 2019: gross primary production, standardized precipitation index, burned areas, fire foci, and carbon emissions. During the examined period, fires affected 23.78% of the total Amazon Basin. Brazil had the largest affected area (220,087 fire foci, 773,360 km2 burned area, 54.7% of the total burned in the Amazon Basin), followed by Bolivia (102,499 fire foci, 571,250 km2 burned area, 40.4%). Overall, these fires have not only affected forests in agricultural frontier areas (76.91%), but also those in indigenous lands (17.16%) and conservation units (5.93%), which are recognized as biodiversity conservation areas. During the study period, the forest absorbed 1,092,037 Mg of C, but emitted 2908 Tg of C, which is 2.66-fold greater than the C absorbed, thereby compromising the role of the forest in acting as a C sink. Our findings show that environmental degradation caused by fires is related to the occurrence of dry periods in the Amazon Basin.
We applied a participatory mapping approach supported by very high-resolution satellite imagery to reconstruct spatially explicit, year-to-year land use transitions in two highly biodiverse, data-scarce forest frontier landscapes in northeastern Madagascar. We explored these transitions in the light of major continuous trends and discrete events highlighted by local farmers as influencing their land use decisions. Our results suggest that the process of establishing protected areas first reinforced ongoing deforestation, but later led to a significant reduction of forest loss rates. Recent cash crop booms appear to have induced agricultural intensification processes in our study landscapes, while also putting additional pressure on forests, as people may be encouraged to clear forest for cash crop cultivation. These findings are crucial to understanding rapid land use change processes in forest frontier contexts in the humid tropics, and especially to informing natural resource governance and development initiatives in complex mosaic landscapes. ARTICLE HISTORY
Worldwide mining activities are one of the major anthropogenic activities that have caused high forest cover loss (FCL). In this study, we have quantified FCL in Odisha State due to mining activities analyzing Hansen Global Forest Change (HGFC) time series data for the period of 2001-2019 in Google Earth Engine platform. Our analysis suggests that Nabarangpur, Puri, Kendrapara, and Kalahandi districts lost more than 20% of their forest cover during this period. Rayagada and Koraput were the top two districts that recorded the highest FCL with mean change rates of 13.81 km 2 /year and 7.17 km 2 /year, respectively. The results point out that mining operations have grown in recent years in Odisha State, and the increase in these activities has contributed to the increase in FCL. This study offers a cost-effective methodology to monitor FCL in mining areas which will eventually contribute to the protection of forest biodiversity and forest dwelling tribal population.
Ecological restoration has emerged as a key strategy for conserving tropical forests and habitat specialists, and monitoring faunal recovery using indicator taxa like birds can help assess restoration success. Few studies have examined, however, whether active restoration (AR) achieves better recovery of bird communities than natural regeneration, or how bird recovery relates to habitat affiliations of species in the community.
In rainforests restored over the past two decades in a fragmented landscape (Western Ghats, India), we examined whether bird species richness and community composition recovery in 23 actively restored (AR) sites were significantly better than recovery in paired naturally regenerating (NR) sites, relative to 23 undisturbed benchmark (BM) rainforests. We measured eight habitat variables and tested whether bird recovery tracked habitat recovery, whether rainforest and open‐country birds showed contrasting patterns, and assessed species‐level responses to restoration.
We recorded 92 bird species in 460 point‐count surveys. Rainforest bird species richness was highest in BM, intermediate in AR and lowest in NR. Contrastingly, open‐country bird species richness was least in BM, intermediate in AR and highest in NR.
Bird community composition varied significantly across treatment types with composition in AR in transition from NR to BM. Bird community dissimilarity between sites was positively related to dissimilarity in habitat structure and floristics, and geographical distance between sites. Variance partitioning indicated that structural and floristic dissimilarity explained 90% of the variation in community composition.
Indicator species analysis revealed significant associations of 34 species with one or more treatment types. Species associated with BM and AR treatment types were all rainforest species, while only 38% of species associated with AR and NR treatment types were rainforest species.
Synthesis and applications. We show that active restoration (AR) of degraded fragments benefits rainforest birds and reduces the infiltration of open‐country birds, and highlight the importance of considering rainforest and open‐country species separately. In human‐modified tropical rainforest landscapes, AR of degraded fragments fosters partial recovery and complements protection of mature forests for bird conservation.
Free-to-read at: https://rdcu.be/cw7ua; Portuguese and Spanish versions of this paper are provided at: https://github.com/celsohlsj/ngeo_correspondence
While deforestation has traditionally been the focus for forest canopy disturbance detection, forest degradation must not be overlooked. Both deforestation and forest degradation influence carbon loss and greenhouse gas emissions and thus must be included in activity data reporting estimates, such as for the Reduced Emissions from Deforestation and Degradation (REDD+) program. Here, we report on efforts to develop forest degradation mapping capacity in Nepal based on a pilot project in the country’s Terai region, an ecologically complex physiographic area. To strengthen Nepal’s estimates of deforestation and forest degradation, we applied the Continuous Degradation Detection (CODED) algorithm, which uses a time series of the Normalized Degradation Fraction Index (NDFI) to monitor forest canopy disturbances. CODED can detect low-grade degradation events and provides an easy-to-use graphical user interface in Google Earth Engine (GEE). Using an iterative process, we were able to create a model that provided acceptable accuracy and area estimates of forest degradation and deforestation in Terai that can be applied to the whole country. We found that between 2010 and 2020, the area affected by disturbance was substantially larger than the deforested area, over 105,650 hectares compared to 2753 hectares, respectively. Iterating across multiple parameters using the CODED algorithm in the Terai region has provided a wealth of insights not only for detecting forest degradation and deforestation in Nepal in support of activity data estimation but also for the process of using tools like CODED in applied settings. We found that model performance, measured using producer’s and user’s accuracy, varied dramatically based on the model parameters specified. We determined which parameters most altered the results through an iterative process; those parameters are described here in depth. Once CODED is combined with the description of each parameter and how it affects disturbance monitoring in a complex environment, this degradation-sensitive detection process has the potential to be highly attractive to other developing countries in the REDD+ program seeking to accurately monitor their forests.
Forest degradation through logging is pervasive throughout the world's tropical forests, leading to changes in the three‐dimensional canopy structure that have profound consequences for wildlife, microclimate and ecosystem functioning. Quantifying these structural changes is fundamental to understanding the impact of degradation, but is challenging in dense, structurally complex forest canopies.
We exploited discrete‐return airborne LiDAR surveys across a gradient of logging intensity in Sabah, Malaysian Borneo, and assessed how selective logging had affected canopy structure (Plant Area Index, PAI, and its vertical distribution within the canopy).
LiDAR products compared well to independent, analogue models of canopy structure produced from detailed ground‐based inventories undertaken in forest plots, demonstrating the potential for airborne LiDAR to quantify the structural impacts of forest degradation at landscape scale, even in some of the world's tallest and most structurally complex tropical forests.
Plant Area Index estimates across the plot network exhibited a strong linear relationship with stem basal area (R² = 0.95). After at least 11–14 years of recovery, PAI was ~28% lower in moderately logged plots and ~52% lower in heavily logged plots than that in old‐growth forest plots. These reductions in PAI were associated with near‐complete lack of trees >30‐m tall, which had not been fully compensated for by increasing plant area lower in the canopy. This structural change drives a marked reduction in the diversity of canopy environments, with the deep, dark understorey conditions characteristic of old‐growth forests far less prevalent in logged sites. Full canopy recovery is likely to take decades.
Synthesis and applications. Effective management and restoration of tropical forests requires detailed monitoring of the forest and its environment. We demonstrate that airborne LiDAR can effectively map the canopy architecture of the complex tropical forests of Borneo, capturing the three‐dimensional impact of degradation on canopy structure at landscape scales, therefore facilitating efforts to restore and conserve these ecosystems.
Accurate characterization of tropical moist forest changes is needed to support conservation policies and to quantify their contribution to global carbon fluxes more effectively. We document, at pantropical scale, the extent and changes (degradation, deforestation, and recovery) of these forests over the past three decades. We estimate that 17% of tropical moist forests have disappeared since 1990 with a remaining area of 1071 million hectares in 2019, from which 10% are degraded. Our study underlines the importance of the degradation process in these ecosystems, in particular, as a precursor of deforestation, and in the recent increase in tropical moist forest disturbances (natural and anthropogenic degradation or deforestation). Without a reduction of the present disturbance rates, undisturbed forests will disappear entirely in large tropical humid regions by 2050. Our study suggests that reinforcing actions are needed to prevent the initial degradation that leads to forest clearance in 45% of the cases.
Owing to high rates of land and forest degradation, there is consensus that forest landscape restoration is a global priority with the Bonn Challenge and the New York Declaration on Forests committing to restore about 350 Million hectares by 2030, globally. However, there is a need for incentives that motivate these restoration efforts and disincentives aimed at restricting activities that result in further land degradation. We provide insights and understanding of the incentives and disincentives measures applied within the forest restoration systems through a case study in the Shinyanga region of Tanzania. Incentives that have promoted forest landscape restoration in Shinyanga include; conservation benefits, education and information, Reducing Emissions from Deforestation and forest Degradation (REDD+), well-defined property rights & increasing land prices and awards while disincentives include; penalties, quotas and permits. Intrinsic incentives that are derived from self-desire within an individual such as conservation benefits and education & information were more preferred within Shinyanga region compared to extrinsic incentives which relied more on external factors such as REDD+ and awards. Nonetheless, a combination of both incentives and disincentives has led to the success of restoration in Shinyanga; positive incentives worked better for privately owned lands while regulatory disincentives worked better for communally owned restoration lands. High levels of social equity and trust have enabled the functioning of these incentives while a robust governance structure at the local level has been instrumental in enforcing the disincentives. There is need for government and all stakeholders to maintain and enhance the gains from restoration, especially empowering communities further, for these incentives to work.
This article presents an analysis of the potential forest damage that occurred due to the COVID-19 pandemic in rural communities on the Forest Management Unit (FMUs). It focused on forest utilization and deforestation before and during the epidemic. Base on The data on online surveys using Google form instruments, Zoom meetings, and in-depth telephone interviews with the informants. The data of the research were analyzed descriptively using the mind mapping method. The data analysis shows that social and economic impacts potentially enhance the threat of forest resource utilization-increasing pressure on the forest due to the increase in forest product demand. Even though the government made efforts to minimize forest degradation and prevent illegal logging, the communities didn't follow the policy because there were no alternative solutions. The timber logging is carried out into a threat to forest degradation when it's not immediately prevented. The FMU needs to improve access to rural living near the forest to increase their forest income. These solutions are crucial for reducing illegal logging activities and forest degradation in the pandemic.
Land cover has been designated by the Global Climate Observing System (GCOS) as an Essential Climate Variable due to its integral role in many climate and environmental processes. Land cover and change affect regional precipitation patterns, surface energy balance, the carbon cycle and biodiversity. Accurate information on land cover and change is essential for climate change mitigation programs such as UN-REDD+. Still, uncertainties related to land change are large, in part due to the use of traditional land cover and change mapping techniques that use one or a few remotely sensed images, preventing a comprehensive analysis of ecosystem change processes. The opening of the Landsat archive and the initiation of the Copernicus Program have enabled analyses based on time series data, allowing the scientific community to explore global land cover dynamics in ways that were previously limited by data availability. One such method is the Continuous Change Detection and Classification algorithm (CCDC), which uses all available Landsat data to model temporal-spectral features that include seasonality, trends, and spectral variability. Until recently, the CCDC algorithm was restricted to academic environments due to computational requirements and complexity, preventing its use by local practitioners. The situation has changed with the recent implementation of CCDC in the Google Earth Engine, which enables analyses at global scales. What is still missing are tools that allow users to explore, analyze and process CCDC outputs in a simplified way. In this paper, we present a suite of free tools that facilitate interaction with CCDC outputs, including: (1) time series viewers of CCDC-generated time segments; (2) a spatial data viewer to explore CCDC model coefficients and derivatives, and visualize change information; (3) tools to create land cover and land cover change maps from CCDC outputs; (4) a tool for unbiased area estimation of key climate-related variables like deforestation extent; and (5) an API for accessing the functionality underlying these tools. We illustrate the usage of these tools at different locations with examples that explore Landsat time series and CCDC coefficients, and a land cover change mapping example in the Southeastern USA that includes area and accuracy estimates.
Although deforestation rates in the Brazilian Amazon are well known, the extent of the area affected by forest degradation is a notable data gap, with implications for conservation biology, carbon cycle science, and international policy. We generated a long-term spatially quantified assessment of forest degradation for the entire Brazilian Amazon from 1992 to 2014. We measured and mapped the full range of activities that degrade forests and evaluated the relationship with deforestation. From 1992 to 2014, the total area of degraded forest was 337,427 square kilometers (km 2), compared with 308,311 km 2 that were deforested. Forest degradation is a separate and increasing form of forest disturbance, and the area affected is now greater than that due to deforestation.
Renewable energy production is necessary to halt climate change and reverse associated biodiversity losses. However, generating the required technologies and infrastructure will drive an increase in the production of many metals, creating new mining threats for biodiversity. Here, we map mining areas and assess their spatial coincidence with biodiversity conservation sites and priorities. Mining potentially influences 50 million km2 of Earth’s land surface, with 8% coinciding with Protected Areas, 7% with Key Biodiversity Areas, and 16% with Remaining Wilderness. Most mining areas (82%) target materials needed for renewable energy production, and areas that overlap with Protected Areas and Remaining Wilderness contain a greater density of mines (our indicator of threat severity) compared to the overlapping mining areas that target other materials. Mining threats to biodiversity will increase as more mines target materials for renewable energy production and, without strategic planning, these new threats to biodiversity may surpass those averted by climate change mitigation. Renewable energy production is necessary to mitigate climate change, however, generating the required technologies and infrastructure will demand huge production increases of many metals. Here, the authors map mining areas and assess spatial coincidence with biodiversity conservation sites, and show that new mining threats to biodiversity may surpass those averted by climate change mitigation.
Madagascar is recognized both for its unparalleled biodiversity and the high level of threat suffered by this biodiversity, associated in particular with anthropogenic deforestation. Despite sustained efforts to fight poverty and curb deforestation, forest cover in Madagascar is rapidly decreasing. To try to explain why it is so difficult to stop deforestation in Madagascar, we analyzed the recent deforestation process in Western Madagascar through satellite image analysis and field surveys. We show that deforestation has increased from less than 0.9%/yr on 2000-2010 to more than 2%/yr on 2010-2017. We identified two major causes of deforestation, which were not associated with subsistence agriculture: slash-and-burn agriculture for the cultivation of cash crops (maize and peanut), and uncontrolled fires to create open pasture. Maize production is mainly at the destination of the domestic market and is used in particular for livestock feeding. Peanut production has boomed since 2013 and more than half of it is now exported towards Asiatic countries. The money earned by farmers is principally invested into zebu herd acquisition. Trade of agricultural commodities benefits several intermediaries, some of whom have political responsibilities thus creating conflicts of interest. On the other hand, agents from institutions in charge of the management of the protected areas have no means to enforce laws against deforestation. In the absence of an efficient strategy to stop deforestation, we predicted that 38-93% of the forest present in 2000 will have disappeared in 2050. Forest loss, apart from biodiversity loss and climate-change global issues, will be at the expense of local population. In order to stop deforestation, international aid should be used to improve local governance to enforce environmental laws and pressure should be put on trading companies to buy certified agricultural commodities that are not derived from deforestation.
Forest degradation affects forest structure, composition and diversity, carbon stocks, functionality and ecosystem processes. It is known to contribute significantly to global carbon emissions, but there is uncertainty about the relative size of these emissions. This is largely because while deforestation, or long-term forest clearance, has been successfully monitored using remote sensing technology, there are more difficulties in using remote sensing to quantify forest degradation, in which the area remains as forest, but with an altered structure, composition and function. A major challenge in estimating emissions from forest degradation is that in addition to identifying the areas affected, the amount of biomass loss over time in a given area must be estimated. Contributory challenges to mapping, monitoring and quantifying forest degradation include the complexity of the concept of degradation, limitations in the spatial and temporal resolution of remote sensing sensors, and the inherent complexity of detecting degradation caused by different disturbance processes and forest uses. We take the innovative approach of dividing the studies reviewed by the specific type of forest disturbance that is being monitored (selective logging, fires, shifting cultivation and fuelwood extraction etc.), since these different activities will result in different signatures in the canopy and thus may determine the type of remote sensing technology that may best be applied.
Despite its contributions to the development of the country, the mining sector in Sierra Leone, has been attributed to a multitude of impacts on the environment. This article focuses on assessing the environmental impacts of mining in mining edge communities in Sierra Leone. A survey of 360 people from three mining edge communities (Sierra Rutile Limited (SRL), Bonthe district; Octea Mining Company (OMC), Kono district and Sierra Leone Mining Company (SLM), Port Loko district) was conducted. Key informant interviews, focus groups, and secondary data sources-Government policies and regulatory documents, government's Mines Department annual reports-provided data for this article. Data were analyzed using the Statistical Analysis System with a mean separation done at α = 0.05 (SAS version 9.4). As a result of mining operations, the rates of deforestation, land degradation and destruction of farmlands, inadequate availability of clean water, poor air quality and noise pollution were the main impacts exacerbated by rutile, iron ore and diamond mining. Strategies as recommended by the local communities to be put in place, to restore ecological function in the mining edge communities include, the Environmental Protection Agency (EPA), the Mines and Mineral Agency, and other responsible authorities addressing weakness in mining and environmental policies, thereby strengthening enforcement and monitoring regulations relating to mining operations; and companies embarking on rehabilitation, reclamation, and restoration measures to ensure environmental sustainability.
The development and utilization of mining resources are basic requirements for social and economic development. Both open-pit mining and underground mining have impacts on land, ecology, and the environment. Of these, open-pit mining is considered to have the greatest impact due to the drastic changes wrought on the original landform and the disturbance to vegetation. As awareness of environmental protection has grown, land reclamation has been included in the mining process. In this study, we used the Shengli Coalfield in the eastern steppe region of Inner Mongolia to demonstrate a mining and reclamation monitoring process. We combined the Google Earth Engine platform with time series Landsat images and the LandTrendr algorithm to identify and monitor mining disturbances to grassland and land reclamation in open-pit mining areas of the coalfield between 2003 and 2019. Pixel-based trajectories were used to reconstruct the temporal evolution of vegetation, and sequential Landsat archive data were used to achieve accurate measures of disturbances to vegetation. The results show that: (1) the proposed method can be used to determine the years in which vegetation disturbance and recovery occurred with accuracies of 86.53% and 78.57%, respectively; (2) mining in the Shengli mining area resulted in the conversion of 89.98 km2 of land from grassland, water, etc., to barren earth, and only 23.54 km2 was reclaimed, for a reclamation rate of 26.16%; and (3) the method proposed in this paper can achieve fast, efficient identification of surface mining land disturbances and reclamation, and has the potential to be applied to other similar areas.
Environmental policies that impose restrictions within one location may be undermined or reinforced by ‘spillover effects,’ the movement of actors, processes, or knowledge to other locations. Such spillovers are an important consideration in the design of interventions seeking to reduce commodity driven deforestation. In these settings, global markets and mobile actors can move deforestation and conservation behaviors over large distances, complicating efforts to measure and manage spillovers. Here we quantify forest loss and conservation spillovers from the Roundtable on Sustainable Palm Oil (RSPO) certification system in Indonesian Borneo (Kalimantan). We examine whether spillovers from certification are transmitted through corporate groups (i.e. to non-certified, RSPO member-held plantations) or local agricultural markets (i.e. to lands near certified mills). We find that, from 2009 to 2016, spillovers from RSPO certification reduced deforestation within Indonesia’s forest estate, but increased deforestation in areas zoned for agricultural use. The private RSPO certification system has complemented public conservation by aligning de facto land cover with central government land zoning policy. Despite these benefits, aggregate avoided deforestation attributed to direct and spillover effects was statistically and substantively insignificant when compared to the total deforestation occurring inside all of Kalimantan’s oil palm concessions. While certification has reduced illegal deforestation, stronger sector-wide action appears necessary to ensure that oil palm production is no longer a driver of forest loss.
Governing land use to achieve sustainable outcomes is challenging, because land systems manifest complex land use spillovers-i.e. processes by which land use changes or direct interventions in land use (e.g. policy, program, new technologies) in one place have impacts on land use in another place. The ERL issue 'Focus on Leakage: Informing Land-Use Governance in a Tele-coupled World' builds on discussions in an international expert workshop conducted in Berlin in November 2017 to explore innovative ways to improve our understanding of how governance interventions, new technologies and other factors can affect land-use change both directly and indirectly through spillovers. This editorial starts by clarifying the definitions and relationships between land-use spillover, indirect land use change- A form of spillover where land use change in one place is caused by land use change in another place-leakage- A form of land use spillover, which is caused by an environmental policy (e.g. a conservation or restoration intervention), and the spillover reduces the overall benefits and effectiveness of this intervention-, and land use displacement processes. We then use this terminology to summarize the individual contributions of this special issue and conclude with lessons learned as well as directions for future research.
Large-scale land acquisitions (LSLAs) have received considerable scholarly attention over the last decade, and progress has been made towards quantifying their direct impacts. There is also a growing recognition of the importance of indirect effects of LSLAs, such as 'spillover' or indirect land-use change (iLUC), and the substantial challenges they pose for attribution and quantification. In fact, the relative contributions of direct and indirect LUC associated with LSLAs are unknown. This study aims to address these knowledge gaps using Economic Land Concessions (ELCs) in Cambodia, now the most targeted country for LSLAs in Southeast Asia. We leverage findings on archetypical pathways of direct and indirect LUC in Cambodia, developed through previous mixed-methods synthesis efforts, to quantify remotely sensed forest loss to specific ELCs. During 2000-2016, Cambodia roughly 1611 kha of forest, or 22% of total forest cover. Although ELCs (as of 2016) contained roughly 16% of Cambodia's forest cover (2000), forest lost within ELC boundaries accounted for nearly 30% (476 kha) of total forest lost by 2016. Furthermore, iLUC contributed an additional 49-174 kha of forest loss (3.0%-10.7% of all forest lost in Cambodia) over the same period. Thus, iLUC contributed to Cambodia's total forest loss at the rate of 11.4%-40.8% of direct LUC caused by ELCs. Such findings suggest that the total amount of LUC caused by LSLAs may well be underestimated globally. This and related synthesis research efforts can be valuable approaches for better targeting remote sensing analyses to specific locations and time periods needed to disentangle and quantify forest loss due to direct and indirect land change processes.
Protected areas in Guatemala provide habitat for diverse tropical ecosystems, contain ancient archeological sites, sequester carbon, and support economic activity through eco‐tourism. However, many of the forests in these protected areas have been converted to other uses or degraded by human activity, and therefore are considered “paper parks”. In this study, we analyzed time series of satellite data to monitor deforestation, degradation, and natural disturbance throughout Guatemala from 2000 to 2017. A recently developed methodology, Continuous Degradation Detection (CODED), was used to detect forest disturbances of varying size and magnitude. Through sample‐based statistical inference, we estimated that 854 137 ha (± 83 133 ha) were deforested and 1 012 947 ha (±139 512 ha) of forest was disturbed but not converted during our study period. Forest disturbance in protected areas ranged from under 1% of a park's area to over 95%. Our estimate of the extent of deforestation is similar to previous studies, however, degradation and natural disturbance affect a larger area. These results suggest that the total amount of forest disturbance can be significantly underestimated if degradation and natural disturbance are not taken into account. As a consequence, we found that the protected areas of Guatemala are more affected by disturbance than previously realized. Landsat time series analysis is used in this paper to monitor forest disturbance in Guatemala. The results indicate that forest conversion (deforestation) and disturbances in forests remaining forest (degradation) are occurring throughout the country's protected areas. We demonstrate how the omission of degradation would lead to great underestimation of the disturbed area of the country, and as a consequence the protected areas of Guatemala are more at risk of disturbance than previously realized.
Efforts to reduce deforestation are increasing worldwide through the implementation of climate change mitigation schemes and have recently been promoted as one of the goals of the United Nations' 2015-2030 Sustainable Development Goals. However, existing strategies are associated with high costs, low effectiveness, and potential adverse economic impact on tropical countries and local people. Moreover, because the underlying causes of deforestation are not clearly understood, the policy options that would be most effective in halting deforestation are not known. Therefore, in this study, I examine the main factors influencing forest area change by synthesizing the results of a multinational data analysis, a Malaysian socioeconomic survey, and Indonesian household surveys on deforestation that were conducted between 1990 and 2014. I reveal that poverty has a strong impact on forest area change and that high agricultural rent accelerates deforestation. I then use logical equations based on my own findings and those of previous studies to represent the relationships between deforestation, poverty, agricultural rent, and forest scarcity. From these equations, I derive clear and reasonable explanations for the causes of deforestation and assess the effectiveness of various policies and Reducing Emissions from Deforestation and Forest Degradation strategies to halt deforestation. I suggest that poverty-reduction strategies can represent sound and effective methods for reducing tropical deforestation. These findings will facilitate development of sustainable strategies that will both reduce deforestation over long term and reconcile forest conservation with social welfare.
No net loss (NNL) biodiversity policies mandating the application of a mitigation hierarchy (avoid, minimize, remediate, offset) to the ecological impacts of built infrastructure are proliferating globally. However, little is known about their effectiveness at achieving NNL outcomes. We reviewed the English‐language peer‐reviewed literature (capturing 15,715 articles), and identified 32 reports that observed ecological outcomes from NNL policies, including >300,000 ha of biodiversity offsets. Approximately one‐third of NNL policies and individual biodiversity offsets reported achieving NNL, primarily in wetlands, although most studies used widely criticized area‐based outcome measures. The most commonly cited reason for success was applying high offset multipliers (large offset area relative to the impacted area). We identified large gaps between the global implementation of offsets and the evidence for their effectiveness: despite two‐thirds of the world's biodiversity offsets being applied in forested ecosystems, we found none of four studies demonstrated successful NNL outcomes for forested habitats or species. We also found no evidence for NNL achievement using avoided loss offsets (impacts offset by protecting existing habitat elsewhere). Additionally, we summarized regional variability in compliance rates with NNL policies. As global infrastructural expansion accelerates, we must urgently improve the evidence‐base around efforts to mitigate development impacts on biodiversity.
In several low- and middle-income countries rich in non-fuel mineral resources, mining makes significant contributions to national economic development as measured by the revised Mining Contribution Index (MCI-Wr). Ten countries among the 20 countries where mining contributes most (highest MCI-Wr score) have moved up one or two steps in the World Bank’s country classification between 1996 and 2016. In particular, African countries have benefitted. Socio-economic development indicators also show signs of progress for African mineral-rich countries. This paper provides an update and expansion of an earlier study within the framework of the United Nations University (UNU) World Institute for Development Economics Research (WIDER) initiative Extractives for Development. Based on the detailed data available for the sector, such as production, export, prices, mineral rents, exploration expenditure and government revenues, an analysis is carried out of the current situation for 2016, and trends in mining’s contribution to economic development for the years 1996–2016. The contribution of minerals and mining to GDP and exports reached a maximum at the peak of the mining boom in 2011. Naturally, the figures for mining’s contribution had declined for most countries by 2016, but importantly the levels were still considerably higher than in 1996. The results of this survey contradict the widespread view that mineral resources create a dependency that might not be conducive to economic and social development. In addition, this paper presents an attempt to use already available socio-economic indicators for African mineral-rich countries to measure socio-economic developments. One preliminary conclusion of this survey is that mining countries perform better than oil-producing countries and non-mineral countries in Africa as measured by these indices of human development and governance.
Madagascar’s recently elected president ran on a platform of improving the economy and raising people out of poverty. We suggest that addressing the precipitous decline of biodiversity will help to deliver this commitment, and we lay out ways in which President Rajoelina could firmly put the country on a trajectory towards sustainable growth.
Mining poses serious and highly specific threats to biodiversity. However, mining can also be a means for financing alternative livelihood paths that, over the long-term, may prevent biodiversity loss. Complex and controversial issues associated with mining and biodiversity conservation are often simplified within a narrow frame oriented towards the negative impacts of mining at the site of extraction, rather than posed as a series of challenges for the conservation science community to embrace. Here, we synthesize core issues that, if better understood, may ensure coexistence between mining and conservation agendas. We illustrate how mining impacts biodiversity through diverse pathways and across spatial scales. We argue that traditional, site-based conservation approaches will have limited effect in preventing biodiversity loss against an increasing mining footprint, but opportunities to improve outcomes (e.g. through long-term strategic assessment and planning) do exist. While future mineral supply is uncertain, projections suggest demand will grow for many metals and shift mining operations towards more dispersed and biodiverse areas. Initiating dialogue between mining companies, policy-makers and conservation organizations is urgent, given the suite of international agendas simultaneously requiring more minerals but less biodiversity loss. & 2018 The Author(s) Published by the Royal Society. All rights reserved.
While deforestation rates decline globally they are rising in the Western Amazon. Artisanal-scale gold mining (ASGM) is a large cause of this deforestation and brings with it extensive environmental, social, governance, and public health impacts, including large carbon emissions and mercury pollution. Underlying ASGM is a broad network of factors that influence its growth, distribution, and practices such as poverty, flows of legal and illegal capital, conflicting governance, and global economic trends. Despite its central role in land use and land cover change in the Western Amazon and the severity of its social and environmental impacts, it is relatively poorly studied. While ASGM in Southeastern Peru has been quantified previously, doing so is difficult due to the heterogeneous nature of the resulting landscape. Using a novel approach to classify mining that relies on a fusion of CLASlite and the Global Forest Change dataset, two Landsat-based deforestation detection tools, we sought to quantify ASGM-caused deforestation in the period 1984–2017 in the southern Peruvian Amazon and examine trends in the geography, methods, and impacts of ASGM across that time. We identify nearly 100,000 ha of deforestation due to ASGM in the 34-year study period, an increase of 21% compared to previous estimates. Further, we find that 10% of that deforestation occurred in 2017, the highest annual amount of deforestation in the study period, with 53% occurring since 2011. Finally, we demonstrate that not all mining is created equal by examining key patterns and changes in ASGM activity and techniques through time and space. We discuss their connections with, and impacts on, socio-economic factors, such as land tenure, infrastructure, international markets, governance efforts, and social and environmental impacts.
The Nacala corridor in Mozambique is one of the main host regions for large-scale agricultural investments (LAIs) in Africa. LAI companies produce crops for export, with scarcely known impacts on small-scale farmers and the environment. We conducted 101 interviews with small-scale farmers living near an LAI to elicit their perceptions of the LAI’s impacts on their own land use and the environment. Additionally, we used remote sensing to assess land use change between 2000 and 2015 in two study areas in Guruè and Monapo districts. The results show that LAIs caused deforestation both directly and indirectly. The main environmental impact perceived by farmers was that LAIs had blocked their access to rivers. Positive spillovers did occur, but could not compensate for the negative impacts experienced. A peaceful coexistence of LAIs and small-scale farmers in the Nacala corridor is only possible if existing injustices around the occupation of land are resolved.
Biodiversity offsets seek to counterbalance loss of biodiversity due to major developments by generating equivalent biodiversity benefits elsewhere, resulting, at least in theory, in ‘no net loss’ (or even a ‘net positive gain’) in biodiversity. While local costs of major developments themselves receive significant attention, the local costs of associated biodiversity offsets have not. In low income countries, where local populations often depend heavily on natural resources and access to land for their livelihoods, the conservation restrictions introduced around biodiversity offsets can have significant local costs. We consider the international standards which underpin the development of biodiversity offsets around the world and look at the biodiversity offset programme of the Ambatovy nickel mine in eastern Madagascar: a company at the vanguard of biodiversity offset development. Using document review and interviews with key international and national stakeholders (as well as previous fieldwork on local impacts of the Ambatovy biodiversity offset) we identify a mismatch between policies which make clear commitments to avoiding harm to local people, and somewhat weaker implementation on the ground. We explore this policy-practice gap and suggest that it is due to: 1) different interpretations of the meaning of international standards, 2) weak incentives for companies to comply with policies, 3) separation of responsibilities for social and environmental impacts of interventions in operating companies, 4) assumptions that conservation is a ‘good thing’ causing reduced scrutiny of biodiversity offsets relative to other activities of major developments. Biodiversity offsets are resulting in a rapid increase in protected areas funded by corporations (and their international lenders). Many conservation projects in low income countries have local costs. The existence of stringent standards which recognise these costs in the case of biodiversity offset projects is very positive. Biodiversity offsets have the potential to be a successful addition to the conservationist’s toolkit but the real challenges of addressing the local costs of this novel conservation approach need to be resolved.
Approximately 2.5 × 106 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year-1), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year-1). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest.
The present study attempts to understand land use land cover change dynamics in an area subjected to opencast and underground coal mining for the last few decades in Kotma Coalmines of Anuppur district in Madhya Pradesh, India through geospatial techniques. Land Use and Land Cover (LULC) change detection analysis was performed digitally classifying Landsat 5 (2001) as well as Landsat 8 (2020) satellite data using maximum likelihood algorithm. Results revealed that area under Dense native vegetation decreased drastically (13.74 sq. km) with the gradual and consistent expansion in the activities of coal mines which showed the highest increase in area over time (15.84 sq. km). Bivariate regression analysis showed the positive empirical relationships between vegetation indices and soil physico‐chemical parameters. Studies suggested soil and vegetation is degraded over the large mining areas consistently over a long time period. Despite the continuous reforestation activities on mined areas, the decline area under dense vegetation and sparse vegetation over the twenty‐year time‐scale indicates that the reclamation activities are still in its’ infancy. Land Degradation Vulnerability Index (LDVI) map was generated to understand the extent of decadal land degradation trends and it shows that 8.60 % of the area is highly vulnerable to degradation. The LDI inputs will help the planners to develop alternate strategies to tackle vulnerability zones for safe mining. Monthly estimation of various meteorological parameters was also recorded to generate heat plots for the period 2001‐2020. The study concludes that monitoring and assessment of fragile ecosystems are indispensable for holistic environmental management.
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The Amazon forest’s main protection against fire is its capacity to create a moist understory microclimate. Roads, deforestation, droughts, and climate change have made this natural firebreak less effective. The southern Amazon, in particular, has become more flammable and vulnerable to wildfires during recent droughts. The drought of 1997/98 first showed that fires could escape from agricultural fields and burn standing primary forests that were once considered impenetrable to fire. The spread of forest fires during other 21st-century droughts suggests that this pattern may well be the new normal. With the landscape becoming more flammable, reducing sources of ignition and the negative effects of deforestation is crucial for avoiding severe degradation of Amazon forests. Unfortunately, recent increases in deforestation suggest that Brazil is moving in the opposite direction. Keeping pace with the rapid changes in the region’s fire regimes would require innovation; cooperation across political boundaries; and interagency communication on a scale never seen before. While Brazil’s past success in reducing deforestation suggests that it could be an effective leader in this regard, its sluggish response to the 2019 fires tells quite a different story. But the fact remains that the future of the Amazon depends on decisive action now.
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.
Anthropogenic and natural forest disturbance cause ecological damage and carbon emissions. Forest disturbance in the Amazon occurs in the form of deforestation (conversion of forest to non‐forest land covers), degradation from the extraction of forest resources, and destruction from natural events. The crucial role of the Amazon rainforest in the hydrologic cycle has even led to the speculation of a disturbance ‘tipping point’ leading to a collapse of the tropical ecosystem. Here we use time series analysis of Landsat data to map deforestation, degradation, and natural disturbance in the Amazon Ecoregion from 1995 to 2017. The map was used to stratify the study area for selection of sample units that were assigned reference labels based on their land cover and disturbance history. An unbiased statistical estimator was applied to the sample of reference observations to obtain estimates of area and uncertainty at biennial time intervals. We show that degradation and natural disturbance, largely during periods of severe drought, have affected as much of the forest area in the Amazon Ecoregion as deforestation from 1995 to 2017. Consequently, an estimated 17% (1,036,800 ±24,800 km2, 95% confidence interval) of the original forest area has been disturbed as of 2017. Our results suggest that the area of disturbed forest in the Amazon is 44‐60% more than previously realized, indicating an unaccounted for source of carbon emissions and pervasive damage to forest ecosystems.
An ensemble of time series algorithms improves land change monitoring. The methodology combines the Continuous Change Detection and Classification (CCDC; Zhu & Woodcock, 2014) and Cumulative Sum of Residuals (CUSUM) algorithms for break detection and the Chow Test (Chow, 1960) for removing false positives (or breaks in time series not representing land change). The algorithms included are based on fundamentally different approaches to change detection and therefore offer unique advantages. The ensemble, or the combination of the three algorithms, was applied to 3 Landsat scenes in the United States and the results were assessed based on their ability to correctly discern structural breaks from stable time periods. The CUSUM test was shown to detect significant breaks 84.18% of the time and the Chow Test correctly removed breaks in 87.4% of the breaks analyzed. The ensemble produced results with lower frequency of errors of omission and commission (Type-I and Type-II errors) than a single algorithm approach. These results indicate that using a combination of break detection algorithms can be an improvement over typical approaches that utilize only one algorithm.
The REDD+ mechanism of UNFCCC was established to reduce greenhouse gases emissions by means of financial incentives. Of importance to the success of REDD+ and similar initiatives is the provision of credible evidence of reductions in the extent of land change activities that release carbon to the atmosphere (e.g. deforestation). The criteria for reporting land change areas and associated emissions within REDD+ stipulate the use of sampling-based approaches, which allow for unbiased estimation and uncertainty quantification. But for economic compensation for emission reductions to be feasible, agreements between participating countries and donors often require reporting every year or every second year. With the rates of land change typically being very small relative to the total study area, sampling-based approaches for estimation of annual or bi-annual areas have proven problematic, especially when comparing area estimates over time. In this paper, we present a methodology for monitoring and estimating areas of land change activity at high temporal resolution that is compliant with international guidelines. The methodology is based on a break detection algorithm applied to time series of Landsat data in the Colombian Amazon between 2001 and 2016. A biannual stratified sampling approach was implemented to (1) remove the bias introduced by the change detection and classification algorithm in mapped areas derived from pixel-counting; and (2) provide confidence intervals for area estimates obtained from the reference data collected for the sample. Our results show that estimating the area of land change, like deforestation, at annual or bi-annual resolution is inherently challenging and associated with high degrees of uncertainty. We found that better precision was achieved if independent sample datasets of reference observations were collected for each time interval for which area estimates are required. The alternative of selecting one sample of continuous reference observations analyzed for inference of area for each time interval did not yield area estimates significantly different from zero. Also, when large stable land covers (primary forest in this case, occupying almost 90% of the study area) are present in the study area in combination with small rates of land change activity, the impact of omission errors in the map used for stratifying the study area will be substantial and potentially detrimental to usefulness of land change studies. The introduction of a buffer stratum around areas of mapped land change reduced the uncertainty in area estimates by up to 98%. Results indicate that the Colombian Amazon has experienced a small but steady decrease in primary forest due to establishment of pastures, with forest-to-pasture conversion reaching 103 ± 30 kha (95% confidence interval) in the period between 2013 and 2015, corresponding to 0.22% of the study area. Around 29 ± 17 kha (95% CI) of pastureland that had been abandoned shortly after establishment reverted to secondary forest within the same period. Other gains of secondary forest from more permanent pastures averaged about 12 ± 11 kha (95% CI), while losses of secondary forest averaged 20 ± 12 kha (95% CI).
Tropical forest loss currently contributes 5 to 15% of anthropogenic carbon emissions to the atmosphere. The large uncertainty in emissions estimates is a consequence of many factors, including differences in definitions of forests and degradation, as well as estimation methodologies. However, a primary factor driving uncertainty is an inability to properly account for forest degradation. While remote sensing offers the only practical way of monitoring forest disturbances over large areas, and despite recent improvements in data quality and quantity and processing techniques, remote sensing approaches are still limited in their ability to detect forest degradation. In this paper, a system is presented that uses time series of Landsat data and spectral mixture analysis to detect both degradation and deforestation in forested landscapes. The Landsat data are transformed into spectral endmember fractions and are used to calculate the Normalized Degradation Fraction Index (NDFI; Souza et al., 2005). The spectrally unmixed data are used for disturbance monitoring and land cover classification via time series analysis. To assess the performance of the system, maps of deforestation and degradation were used to stratify the study area for collection of sample data to which unbiased estimators were applied to produce accuracy and area estimates of degradation and deforestation from 1990 to 2013. The approach extends previous research in spectral mixture analysis for identifying forest degradation to the temporal domain. The method was applied using the Google Earth Engine and tested in the Brazilian State of Rondônia. Degradation and deforestation were mapped with 88.0% and 93.3% User's Accuracy, and 68.1% and 85.3% Producer's Accuracy. Area estimates of degradation and deforestation were produced with margins of error of 13.9% and 5.3%, respectively, over the 24 year time period. These results indicate that for Rondônia a decreasing trend in deforestation after 2004 corresponds to an increase in degradation during the same time period.