Rapid expansion of human impact on natural land in South America since 1985.

Across South America, the expansion of commodity land uses has underpinned substantial economic development at the expense of natural land cover and associated ecosystem services. Here, we show that such human impact on the continent's land surface, specifically land use conversion and natural land cover modification, expanded by 268 million hectares (Mha), or 60%, from 1985 to 2018. By 2018, 713 Mha, or 40%, of the South American landmass was impacted by human activity. Since 1985, the area of natural tree cover decreased by 16%, and pasture, cropland, and plantation land uses increased by 23, 160, and 288%, respectively. A substantial area of disturbed natural land cover, totaling 55 Mha, had no discernable land use, representing land that is degraded in terms of ecosystem function but not economically productive. These results illustrate the extent of ongoing human appropriation of natural ecosystems in South America, which intensifies threats to ecosystem-scale functions.

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity.

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process-oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large-scale remote-sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate-change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation.

Land cover mapping of the tropical savanna region in Brazil.

The Brazilian tropical savanna (Cerrado), encompassing more than 204 million hectares in the central part of the country, is the second richest biome in Brazil in terms of biodiversity and presents high land use pressure. The objective of this study was to map the land cover of the Cerrado biome based on the segmentation and visual interpretation of 170 Landsat Enhanced Thematic Mapper Plus satellite scenes acquired in 2002. The following land cover classes were discriminated: grasslands, shrublands, forestlands, croplands, pasturelands, reforestations, urban areas, and mining areas. The results showed that the remnant natural vegetation is still covering about 61% of the biome, however, on a highly asymmetrical basis. While natural physiognomies comprise 90% of the northern part of the biome, only 15% are left in its southern portions. Shrublands were the dominant natural land cover class, while pasturelands were the dominant land use class in the Cerrado biome. The final Cerrado's land cover map confirmed the intensive land use pressure in this unique biome. This paper also showed that Landsat-like sensors can provide feasible land cover maps of Cerrado, although ancillary data are required to help image interpretation.

Seleção de áreas de interesse ecológico através de sensoriamento remoto e de otimização matemática: um estudo de caso no município de Cocalinho, MT / Selection of areas of ecological importance through remote sensing and mathematics optimization: a case study in the municipality of Cocalinho, Mato Grosso

A criação de unidades de conservação tem sido a principal estratégia para preservar a biodiversidade. O recente emprego de técnicas como o sensoriamento remoto e a otimização matemática, aliados a dados biológicos, ajudam a definir as áreas prioritárias para conservação, indicando a representação máxima da biodiversidade com base em medidas de complementaridade. O presente trabalho objetivou selecionar áreas de interesse ecológico, com base na heterogeneidade de hábitats, através da integração de imagens de satélite com dados biológicos, em Cocalinho, MT. As 66 parcelas quadradas estabelecidas foram comparadas com base na heterogeneidade e na representatividade mínima (ha) dos ambientes em cada parcela, através do programa SITES. O parque de cerrado é a fitofisionomia predominante em Cocalinho (38,44 por cento). A região central do município concentrou o maior agrupamento de parcelas, indicando a maior heterogeneidade de hábitats do local. Oficialmente, 6 por cento da área total do município estão protegidos em duas unidades de conservação na categoria de Refúgios de Vida Silvestre. Esses refúgios foram demarcados em locais com cobertura vegetal homogênea e sem considerar a composição faunística e florística. O modelo usado neste estudo pode ser uma boa abordagem a ser empregada no processo de indicação de novas unidades de conservação no bioma Cerrado ou em outros biomas do Brasil.