Deforestation and Reforestation of Latin America and the Caribbean (2001–2010)
TL;DR: In this paper, the authors presented a wall-to-wall, annual maps of change in woody vegetation and other land-cover classes between 2001 and 2010 for each of the 16,050 municipalities in Latin American and the Caribbean region (LAC).
Abstract: Forest cover change directly affects biodiversity, the global carbon budget, and ecosystem function. Within Latin American and the Caribbean region (LAC), many studies have documented extensive deforestation, but there are also many local studies reporting forest recovery. These contrasting dynamics have been largely attributed to demographic and socio-economic change. For example, local population change due to migration can stimulate forest recovery, while the increasing global demand for food can drive agriculture expansion. However, as no analysis has simultaneously evaluated deforestation and reforestation from the municipal to continental scale, we lack a comprehensive assessment of the spatial distribution of these processes. We overcame this limitation by producing wall-to-wall, annual maps of change in woody vegetation and other land-cover classes between 2001 and 2010 for each of the 16,050 municipalities in LAC, and we used nonparametric Random Forest regression analyses to determine which environmental or population variables best explained the variation in woody vegetation change. Woody vegetation change was dominated by deforestation (541,835 km 2 ), particularly in the moist forest, dry forest, and savannas/shrublands biomes in South America. Extensive areas also recovered woody vegetation (+362,430 km 2 ), particularly in regions too dry or too steep for modern agriculture. Deforestation in moist forests tended to occur in lowland areas with low population density, but woody cover change was not related to municipality-scale population change. These results emphasize the importance of quantitating deforestation and reforestation at multiple spatial scales and linking these changes with global drivers such as the global demand for food.
Citations
More filters
TL;DR: Tropical forests house over half of Earth’s biodiversity and are an important influence on the climate system, but ongoing pressures, together with an intensification of global environmental change, may severely degrade forests in the future unless new “development without destruction” pathways are established alongside climate change–resilient landscape designs.
Abstract: Tropical forests house over half of Earth’s biodiversity and are an important influence on the climate system. These forests are experiencing escalating human influence, altering their health and the provision of important ecosystem functions and services. Impacts started with hunting and millennia-old megafaunal extinctions (phase I), continuing via low-intensity shifting cultivation (phase II), to today’s global integration, dominated by intensive permanent agriculture, industrial logging, and attendant fires and fragmentation (phase III). Such ongoing pressures, together with an intensification of global environmental change, may severely degrade forests in the future (phase IV, global simplification) unless new “development without destruction” pathways are established alongside climate change–resilient landscape designs.
542 citations
TL;DR: Both the successes and failures of the global food system are reviewed, addressing ongoing debates on pathways to environmental health and food security and calling on plant biologists to lead this effort and help steer humanity toward a safe operating space for agriculture.
Abstract: The eighteenth-century Malthusian prediction of population growth outstripping food production has not yet come to bear. Unprecedented agricultural land expansions since 1700, and technological innovations that began in the 1930s, have enabled more calorie production per capita than was ever available before in history. This remarkable success, however, has come at a great cost. Agriculture is a major cause of global environmental degradation. Malnutrition persists among large sections of the population, and a new epidemic of obesity is on the rise. We review both the successes and failures of the global food system, addressing ongoing debates on pathways to environmental health and food security. To deal with these challenges, a new coordinated research program blending modern breeding with agro-ecological methods is needed. We call on plant biologists to lead this effort and help steer humanity toward a safe operating space for agriculture.
483 citations
TL;DR: A novel approach and the results achieved by a multi-disciplinary network called MapBiomas to reconstruct annual land use and land cover information between 1985 and 2017 for Brazil, based on random forest applied to Landsat archive using Google Earth Engine are described.
Abstract: Brazil has a monitoring system to track annual forest conversion in the Amazon and most recently to monitor the Cerrado biome. However, there is still a gap of annual land use and land cover (LULC) information in all Brazilian biomes in the country. Existing countrywide efforts to map land use and land cover lack regularly updates and high spatial resolution time-series data to better understand historical land use and land cover dynamics, and the subsequent impacts in the country biomes. In this study, we described a novel approach and the results achieved by a multi-disciplinary network called MapBiomas to reconstruct annual land use and land cover information between 1985 and 2017 for Brazil, based on random forest applied to Landsat archive using Google Earth Engine. We mapped five major classes: forest, non-forest natural formation, farming, non-vegetated areas, and water. These classes were broken into two sub-classification levels leading to the most comprehensive and detailed mapping for the country at a 30 m pixel resolution. The average overall accuracy of the land use and land cover time-series, based on a stratified random sample of 75,000 pixel locations, was 89% ranging from 73 to 95% in the biomes. The 33 years of LULC change data series revealed that Brazil lost 71 Mha of natural vegetation, mostly to cattle ranching and agriculture activities. Pasture expanded by 46% from 1985 to 2017, and agriculture by 172%, mostly replacing old pasture fields. We also identified that 86 Mha of the converted native vegetation was undergoing some level of regrowth. Several applications of the MapBiomas dataset are underway, suggesting that reconstructing historical land use and land cover change maps is useful for advancing the science and to guide social, economic and environmental policy decision-making processes in Brazil.
473 citations
University of Connecticut1, International Institute of Minnesota2, University of Alabama3, Wageningen University and Research Centre4, University of Regina5, University of Puerto Rico6, National Autonomous University of Mexico7, Brown University8, University of São Paulo9, Smithsonian Tropical Research Institute10, Leipzig University11, Federal University of Pernambuco12, Tulane University13, University of Stirling14, Clemson University15, University of Alberta16, National Institute of Amazonian Research17, Colorado Mesa University18, State University of New York at Purchase19, World Agroforestry Centre20, Aarhus University21, Columbia University22, University of Minnesota23, University of California, Santa Barbara24, Pedagogical and Technological University of Colombia25, University of Maryland, College Park26, Yale-NUS College27, National University of Singapore28, Puerto Rico Department of Agriculture29, University of Amsterdam30, Museu Paraense Emílio Goeldi31, Louisiana State University32
TL;DR: This study estimates the age and spatial extent of lowland second-growth forests in the Latin American tropics and model their potential aboveground carbon accumulation over four decades to guide national-level forest-based carbon mitigation plans.
Abstract: Regrowth of tropical secondary forests following complete or nearly complete removal of forest vegetation actively stores carbon in aboveground biomass, partially counterbalancing carbon emissions from deforestation, forest degradation, burning of fossil fuels, and other anthropogenic sources. We estimate the age and spatial extent of lowland second-growth forests in the Latin American tropics and model their potential aboveground carbon accumulation over four decades. Our model shows that, in 2008, second-growth forests (1 to 60 years old) covered 2.4 million km2 of land (28.1% of the total study area). Over 40 years, these lands can potentially accumulate a total aboveground carbon stock of 8.48 Pg C (petagrams of carbon) in aboveground biomass via low-cost natural regeneration or assisted regeneration, corresponding to a total CO2 sequestration of 31.09 Pg CO2. This total is equivalent to carbon emissions from fossil fuel use and industrial processes in all of Latin America and the Caribbean from 1993 to 2014. Ten countries account for 95% of this carbon storage potential, led by Brazil, Colombia, Mexico, and Venezuela. We model future land-use scenarios to guide national carbon mitigation policies. Permitting natural regeneration on 40% of lowland pastures potentially stores an additional 2.0 Pg C over 40 years. Our study provides information and maps to guide national-level forest-based carbon mitigation plans on the basis of estimated rates of natural regeneration and pasture abandonment. Coupled with avoided deforestation and sustainable forest management, natural regeneration of second-growth forests provides a low-cost mechanism that yields a high carbon sequestration potential with multiple benefits for biodiversity and ecosystem services.
419 citations
TL;DR: It is shown that secondary succession in tropical landscapes is a multifactorial phenomenon affected by a myriad of forces operating at multiple spatio‐temporal scales, and succession must be examined using more comprehensive explanatory models.
Abstract: Old-growth tropical forests are being extensively deforested and fragmented worldwide. Yet forest recovery through succession has led to an expansion of secondary forests in human-modified tropical landscapes (HMTLs). Secondary forests thus emerge as a potential repository for tropical biodiversity, and also as a source of essential ecosystem functions and services in HMTLs. Such critical roles are controversial, however, as they depend on successional, landscape and socio-economic dynamics, which can vary widely within and across landscapes and regions. Understanding the main drivers of successional pathways of disturbed tropical forests is critically needed for improving management, conservation, and restoration strategies. Here, we combine emerging knowledge from tropical forest succession, forest fragmentation and landscape ecology research to identify the main driving forces shaping successional pathways at different spatial scales. We also explore causal connections between land-use dynamics and the level of predictability of successional pathways, and examine potential implications of such connections to determine the importance of secondary forests for biodiversity conservation in HMTLs. We show that secondary succession (SS) in tropical landscapes is a multifactorial phenomenon affected by a myriad of forces operating at multiple spatio-temporal scales. SS is relatively fast and more predictable in recently modified landscapes and where well-preserved biodiversity-rich native forests are still present in the landscape. Yet the increasing variation in landscape spatial configuration and matrix heterogeneity in landscapes with intermediate levels of disturbance increases the uncertainty of successional pathways. In landscapes that have suffered extensive and intensive human disturbances, however, succession can be slow or arrested, with impoverished assemblages and reduced potential to deliver ecosystem functions and services. We conclude that: (i) succession must be examined using more comprehensive explanatory models, providing information about the forces affecting not only the presence but also the persistence of species and ecological groups, particularly of those taxa expected to be extirpated from HMTLs; (ii) SS research should integrate new aspects from forest fragmentation and landscape ecology research to address accurately the potential of secondary forests to serve as biodiversity repositories; and (iii) secondary forest stands, as a dynamic component of HMTLs, must be incorporated as key elements of conservation planning; i.e. secondary forest stands must be actively managed (e.g. using assisted forest restoration) according to conservation goals at broad spatial scales.
400 citations
Cites background from "Deforestation and Reforestation of ..."
...SS can also occur in areas with relatively low productivity, such as those present at high elevations (e.g. cooler temperatures, steeper slopes), that are not appropriate for large-scale mechanized agriculture (Aide et al., 2013)....
[...]
...In summary, despite the reduction in the annual net loss of old-growth forests observed in several tropical developing countries (Aide & Grau, 2004; Aide et al., 2013; Hansen et al., Biological Reviews 92 (2017) 326–340 © 2015 Cambridge Philosophical Society 2013), the frequency and intensity of…...
[...]
...…shaping SS are indirect consequences of proximate (e.g. economic activity, policy, road culture, social institutions, governance) and underlying societal (e.g. population density, percentage of economically active population) drivers (e.g. Ostrom, 2009; Aide et al., 2013; Quezada et al., 2014)....
[...]
...…occurs mainly in areas of high human population density, where forests have been extensively transformed into agricultural landscapes under the effect of societal drivers (e.g. increasing global demand for food), but where migration of people has led to the abandonment of lands (Aide et al., 2013)....
[...]
...Unfortunately, despite this research effort, the intermingled biophysical and societal factors and drivers that govern the probability of abandoned private lands experiencing SS are often complex and poorly understood (Lambin & Meyfroidt, 2011; Aide et al., 2013; Ellis, 2013)....
[...]
References
More filters
[...]
TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Abstract: Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them. Using a random selection of features to split each node yields error rates that compare favorably to Adaboost (Y. Freund & R. Schapire, Machine Learning: Proceedings of the Thirteenth International conference, aaa, 148–156), but are more robust with respect to noise. Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the splitting. Internal estimates are also used to measure variable importance. These ideas are also applicable to regression.
79,257 citations
"Deforestation and Reforestation of ..." refers methods in this paper
...We used the Random Forests (RF) tree-based classifier (Breiman 2001), implemented using the R statistical program and the ‘randomForest’ package (v. 4.6–2)....
[...]
TL;DR: In this paper, the authors evaluated the performance and validity of the MODIS vegetation indices (VI), the normalized difference vegetation index (NDVI) and enhanced vegetation index(EVI), produced at 1-km and 500-m resolutions and 16-day compositing periods.
6,563 citations
"Deforestation and Reforestation of ..." refers result in this paper
...Although rural population changes can impact land change (Carr 2009, Izquierdo et al. 2011, Robson & Berkes 2011), other studies using our land-change dataset, and which included rural population change at the municipality scale in Mexico (Bonilla-Moheno et al. in press) and Bolivia (Redo et al.…...
[...]
6,448 citations
TL;DR: It is the combination of relatively high prediction accuracy and its collection of desired features that makes Random Forest uniquely suited for modeling in cheminformatics.
Abstract: A new classification and regression tool, Random Forest, is introduced and investigated for predicting a compound's quantitative or categorical biological activity based on a quantitative description of the compound's molecular structure. Random Forest is an ensemble of unpruned classification or regression trees created by using bootstrap samples of the training data and random feature selection in tree induction. Prediction is made by aggregating (majority vote or averaging) the predictions of the ensemble. We built predictive models for six cheminformatics data sets. Our analysis demonstrates that Random Forest is a powerful tool capable of delivering performance that is among the most accurate methods to date. We also present three additional features of Random Forest: built-in performance assessment, a measure of relative importance of descriptors, and a measure of compound similarity that is weighted by the relative importance of descriptors. It is the combination of relatively high prediction accu...
2,634 citations
"Deforestation and Reforestation of ..." refers methods in this paper
...We used Random Forests (RF) regression (Svetnik et al. 2003) to determine which environmental or population variables best explained the variation in woody vegetation change....
[...]
28 Nov 2003
TL;DR: In this article, the authors highlight the complexity of land-use/cover change and propose a framework for a more general understanding of the issue, with emphasis on tropical regions, and argue that a systematic analysis of local-scale land use change studies, conducted over a range of timescales, helps to uncover general principles that provide an explanation and prediction of new land use changes.
Abstract: We highlight the complexity of land-use/cover change and propose a framework for a more general understanding of the issue, with emphasis on tropical regions. The review summarizes recent estimates on changes in cropland, agricultural intensification, tropical deforestation, pasture expansion, and urbanization and identifies the still unmeasured land-cover changes. Climate-driven land-cover modifications interact with land-use changes. Land-use change is driven by synergetic factor combinations of resource scarcity leading to an increase in the pressure of production on resources, changing opportunities created by markets, outside policy intervention, loss of adaptive capacity, and changes in social organization and attitudes. The changes in ecosystem goods and services that result from land-use change feed back on the drivers of land-use change. A restricted set of dominant pathways of land-use change is identified. Land-use change can be understood using the concepts of complex adaptive systems and transitions. Integrated, place-based research on land-use/land-cover change requires a combination of the agent-based systems and narrative perspectives of understanding. We argue in this paper that a systematic analysis of local-scale land-use change studies, conducted over a range of timescales, helps to uncover general principles that provide an explanation and prediction of new land-use changes.
2,491 citations