Monitoring and classifying cropland productivity degradation to support implementing land degradation neutrality: The case of China

Deforestation impacts on dengue incidence in the Brazilian Amazon

The present study aimed to contribute to the diagnosis and advance the knowledge of the impacts of land use change and climate change on the tropical longleaf forest biome at the continental scale in South America (Biome 1 according to the WWF classification) for realizing scientific progress in the search for convincing strategies and actions by different actors for the preservation of forests in the continent. The status and climate of the area, which harbors the tropical longleaf forests of South America, were assessed. Moreover, volumetric soil moisture (VSM) was evaluated through maps and simulation using the autoregressive integrated moving average model (ARIMA). Furthermore, future climate scenarios were predicted based on El Niño–Southern Oscillation phenomena, meteorological systems, and scientific evidence, such as the shared socioeconomic pathways (SSPs) and sociopolitical dynamics evident in the region from the case analysis of the Brazilian states of Acre and Rio de Janeiro. An increase was noted in the temperature and range of precipitation variation in the biome. ARIMA analysis indicated changes of up to 0.24 m3 m−3 and an increased range of future VSM values. The December–January–February (DJF) quarter recorded the highest VSM median with the measurement scale of 0.05 to 0.44 m3 m−3, while the June–July–August (JJA) quarter recorded the lowest value. The regions of the biome with the lowest VSM values included southern Amazon (Ecuador, Peru, and the Brazilian states of Acre, Mato Grosso, Pará, and Maranhão), Brazilian Atlantic Forest, Southeast Region, and the Brazilian state of Bahia.

https://www.mdpi.com/2073-4433/14/4/755/pdf?version=1682085143

Past and Future Responses of Soil Water to Climate Change in Tropical and Subtropical Rainforest Systems in South America

Modeling transport and fate of metals for risk assessment in the Parauapebas river

Honeybees and hive products have long been recognized as excellent bio-indicators, as they provide valuable information on the state of the environments concerned. As yet, however, no tool is capable of contextually assessing the level of pollution of different environmental matrices in order to create maps of areas in which to place hives. In this paper, a possible method of creating a regional map to support the implementation of targeted monitoring plans on beekeeping is described. We obtained and identified related-activity pressure factors, which were subsequently combined by means of a multi-criteria approach through the analytic hierarchy process method (AHP). The different levels used were drawn up by first attributing qualitative values; these were converted into quantitative values through scoring elaborations and pair comparisons and then elaborated and standardized by means of different techniques in order to create an index with a spatial distribution of five risk classes throughout the region. To verify the correct execution of the procedure, a consistency ratio method was implemented on this index and validated the reliability of the application as the main source of information for sampling activities on beekeeping products. Creation of the specific environmental risk index enabled us to construct a map displaying the areas of greatest impact on beekeeping activities and a representation of the cumulative effects generated by the different pollutants in the air, water, soil and subsoil compartments. This index may, therefore, constitute an essential tool to support beekeepers in choosing sites for their apiaries.

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Application of a Quality-Specific Environmental Risk Index for the Location of Hives in Areas with Different Pollution Impacts

Degradation of South American biomes: What to expect for the future?

Tropical forests stand out among forest domains, due to their wide diversity of flora and fauna. However, these areas concentrate a large number of the forest fires that occur annually on the planet. In this context, the present study performs spatial modeling of the normalized multi-band drought index (NMDI) in the Central Atlantic Forest Corridor during past (2001-2020) and future (2021-2040) periods to identify the relationship between drought and forest fires. Fire foci data, soil moisture, and data from the MOD09A1 product were used to obtain the NMDI. Rainfall and mean air temperature data from the past and for different future scenarios (SSP126 and SSP585) were also used. The autoregressive integrated moving average model (ARIMA) was used for modeling the NMDI. The results found indicate a recurrence of fire in the CAFC during the period of 2001–2020. Future data indicate reductions in rainfall and an increase in temperature in the CAFC area. The NMDI data indicate that the central region of the corridor is the driest and, among the priority areas for conservation, the Ilha do Lameirão Municipal ecological station has the lowest index values. Future modeling indicates the drought intensifying in the coming years in the corridor area. The CAFC is an extremely important area for the maintenance of Atlantic Forest remnants; however, this area continues to suffer disturbances and without the adoption of public policies, these disturbances could compromise the conservation of natural resources.

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Future spatial modeling of vegetation in the Central Atlantic Forest Corridor, Brazil

Vegetation resilience prognosis: A past and future approach from hydrometeorological and remote sensing data for eight government regions of Rio de Janeiro, Brazil

R. O. de Santana

Papers

Degradation of South American biomes: What to expect for the future?

Future spatial modeling of vegetation in the Central Atlantic Forest Corridor, Brazil

Vegetation resilience prognosis: A past and future approach from hydrometeorological and remote sensing data for eight government regions of Rio de Janeiro, Brazil

Dairy production in a region of the Brazilian Atlantic Forest: interactions between climate, fire, vegetation, and pasture degradation