Abstract

Abstract

This study aims to map the changes in land use and land cover between 1970 and 2018, analyzing the influence of the protected area s (PAs) in the Cerrado biome, specifically in the area of the Jalapão Mosaic. Images from the Landsat 1-MSS, 5-TM, and 8-OLI satellites were used and processed in SPRING and ArcGIS software. The analyses were based on three approaches: (1) the boundary of the Jalapão Mosaic, (2) the PAs, and (3) a comparison between the PAs and their surroundings. The Jalapão Mosaic results demonstrated that 26% (≅ 8410 km²) of the area was burned, and 15.5% (4971 km²) was anthropized in at least one of the analyzed periods. Among the PAs, the Serra Geral do Tocantins Ecological Station (Integral Protection) presented the largest burned area (43.7% ≅ 3095 km²); however, there was no significant increase in the anthropized areas due to fire. Meanwhile, the anthropized areas in the Rio Preto and Serra da Tabatinga Environmental Protection Areas (Sustainable Use) increased by 27.5% and by 75%, respectively, due to agricultural expansion. By analyzing the two groups of PAs and their surroundings, it was observed that the loss of natural vegetation was restrained and fires were less intense in the Integral Protection Units; in the Sustainable Use Units, there was a significant increase in the anthropized areas. Furthermore, over 70% of the anthropized areas occurred in the surrounding areas, thus showing the importance of creating PAs.

Abstract

Brazil has experienced huge areas of forest loss over recent decades with an estimated removal of 80 MHa of natural forest since 1990. Deforestation creates substantial greenhouse emissions that have historically dominated all other sectors. Effective governance has reduced deforestation and net land-use emissions have fallen by 74% since the mid-2000s. Anthropogenic carbon removal from secondary forest regrowth and protected areas has increased by 62%, which has helped drive the reduction in net emissions, offsetting gross emissions which have fallen by 44%. Major Brazilian biomes, such as the Atlantic Forest are net-sinks and the Amazon was near net-zero in 2010. Deforestation has increased over the last 10-years and now stands at a decadal high in the Amazon region. These increases in deforestation put Brazil at risk of missing its original National Determined Contribution; however, the recent revision has substantially increased the 2005 baseline and therefore the overall target. Carbon removals in the forest sector play an increasingly important role in reducing emissions and achieving the NDC. The Brazilian target of achieving 12 MHa of reforestation and restoration has the potential to further offset emissions through enhanced regrowth. However, the natural carbon sinks of Brazil are weakening. The Amazon forest is the single largest Brazilian biome for natural carbon uptake but when combined with land-use emissions has seen a net loss over the last 30 years. The natural sink remains large, but ecosystem resilience is declining driven by global and local climate change linked to rising international emissions and changing circulation patterns associated with local deforestation and degradation. These combine to make realizing the huge potential for carbon removal more challenging. It remains evident that forest protection and avoided degradation and disturbance is the best way to mitigate emissions and reduce climate impacts.

Abstract

Recent publications indicate that the Amazon may be acting more as a carbon source than a sink in some regions. Moreover, the Amazon is a source of moisture for other regions in the continent, and deforestation over the years may be reducing this function. In this work, we analyze the impacts of elevated CO₂ (eCO₂) and land use change (LUC) on gross primary productivity (GPP) and evaporation in the southern Amazon (7°S 14°S, 66°W 51°W), which suffered strong anthropogenic influence in the period of 1981‒2010. We ran four dynamic global vegetation models (DGVMs), isolating historical CO₂, constant CO₂, LUC, and potential natural vegetation scenarios with three climate variable data sets: precipitation, temperature, and shortwave radiation. We compared the outputs to five “observational” data sets obtained through eddy covariance, remote sensing, meteorological measurements, and machine learning. The results indicate that eCO₂ may have offset deforestation, with GPP increasing by ∼13.5% and 9.3% (dry and rainy seasons, respectively). After isolating the LUC effect, a reduction in evaporation of ∼4% and ∼1.2% (dry and rainy seasons, respectively) was observed. The analysis of forcings in subregions under strong anthropogenic impact revealed a reduction in precipitation of ∼15 and 30 mm, and a temperature rise of 1°C and 0.6°C (dry and rainy seasons, respectively). Differences in the implementation of plant physiology and leaf area index in the DGVMs introduced some uncertainties in the interpretation of the results. Nevertheless, we consider that it was an important exercise given the relevance.

Abstract

An improved version of the Integrated Land Surface Model (INLAND), incorporating the physical, ecological and hydrological parameters and processes pertaining to two subclasses of tropical forest in the central Amazon basin, a poorly drained flat plateau and a well-drained adjacent broad valley, is used to simulate the hydrological, energy and CO₂ fluxes. The model is forced with observed meteorological data. The experimental output data from the model runs are compared with observational data at the two locations. The seasonal variabilities of water table depth at the valley site and the soil moisture at the plateau site are satisfactorily simulated. The two locations exhibit large differences in energy, carbon and water fluxes, both in the simulations and in the observations. Results validate the INLAND model and indicate the need for incorporating sub-grid scale variability in the relief, soil type and vegetation type attributes to improve the representation of the Amazonian ecosystems in land-surface models.

Abstract

Anthropogenic transformations, which have become intensified by land use and land cover changes and industrialization, have contributed to increased anthropogenic pressure on biodiversity. These disturbances contribute toward fragmentating habitats at different scales and putting species at risk, in addition to compromising the main biogeochemical cycles. To better understand the spatiotemporal dynamics of anthropogenic pressure on Brazilian biomes, this study sought to develop a composite index to identify and analyze the degree and distribution of anthropogenic-based pressure on biodiversity, and identify internally homogeneous and heterogeneous regions regarding the dynamics of this pressure in different scenarios. To that end, we carried out an analysis of the impact of select anthropogenic factors. Specifically, we analyzed future scenarios involving land use and land cover changes in line with the global structure Shared Socio-Economic Pathways (SSPs) and Representative Concentration Pathways (RCPs), according to the narratives SSP1/RCP 1.9, SSP2/ RCP 4.5 and SSP3/RCP 7.0. We used cluster and spatial analyses to determine the spatial dynamics of the index and, consequently, the regions most susceptible to anthropogenic pressure. The results demonstrate intensified pressure on biodiversity in areas that have already been subject to a considerable degree of disturbances, especially the Cerrado, Caatinga, and Atlantic Forest biomes. In all scenarios, the region with the highest average pressure index, i.e., Region 4, which has an average pressure index of 0.57, corresponds to 30% of Brazilian territory. This method made it possible to determine the level of pressure in each region and, subsequently, identify the regions that have been most affected by human actions in an effort to guide priority actions and local policies. However, it should be noted that this approach should be complemented with additional information, such as soil erosion, field recognition, and socioeconomic information.

The future of land use and cover change in Brazil, particularly due to deforestation and forest restoration processes, is critical for the future of global climate and biodiversity, given the richness of its five biomes. These changes in Brazil depend on the interlink between global factors due to its role as one of the main exporters of commodities globally and the national to local institutional, socioeconomic, and biophysical contexts. Aiming to develop scenarios that consider the balance between global (e.g., GDP growth, population growth, per capita consumption of agricultural products, international trade policies, and climatic conditions) and local factors (e.g., land use, agrarian structure, agricultural suitability, protected areas, distance to roads, and other infrastructure projects), a new set of land-use change scenarios for Brazil were developed that aligned with the global structure Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathway (RCPs) developed by the global change research community. The narratives of the new scenarios align with SSP1/RCP 1.9 (Sustainable development scenario), SSP2/RCP 4.5 (Middle of the road scenario), and SSP3/RCP 7.0 (Strong inequality scenario). The scenarios were developed by combining the LuccME spatially explicit land change allocation modeling framework and the INLAND surface model to incorporate the climatic variables in water deficit. Based on detailed biophysical, socioeconomic, and institutional factors for each biome in Brazil, we have created spatially explicit scenarios until 2050, considering the following classes: forest vegetation, grassland vegetation, planted pasture, agriculture, a mosaic of small land uses, and forestry. The results aim to detail global models regionally. They could be used regionally to support decision-making and enrich the global analysis.

Abstract

The 2030 Agenda framework represents an opportunity for the co-development of local indicators and shares the same principles of cross-sectoral integration and universality as the water–energy–food nexus. This research aimed to develop a quantitative-collaborative methodology for constructing indicators and indexes for the sustainability of the Cerrado and Caatinga Brazilian biomes, considering the connection and synergies between the Nexus perspective and the 2030 Agenda’s SDG–target framework. The study was applied in 2,512 municipalities that make up the total of the mentioned biomes. The methodology consists of four major blocks: i) identification and construction of indicators based on the association of them with one or more 2030 Agenda’s targets, in a collaborative way from expert groups; ii) generation of weights by an indicator considering leverage, according to the number of target assignments, and importance, attributed by experts for each indicator to the target; iii) generation of sustainable development goal indexes, considering the performance of the SDGs; Nexus performance, considering different weights between the SDGs; Nexus synergistic, the standard deviation between the SDGs; and Nexus overall, a combination of the last two; and iv) sensitivity analysis for performance indexes considering the assignment of zero values to the governance indicators. In general, the regions of MATOPIBA, northern and western of Cerrado and the Caatinga, are, on average, the areas of greatest vulnerability. The targets that respond to this inequality are related to eradicating hunger, sustainable and climate-resilient production systems, universal access to water, water quality, efficiency of multiple water uses, access to energy, and the participation of renewable energies. We found that in areas of better average nexus performance, there is also greater inequality between nexus dimensions; therefore, the Nexus overall index is penalized. The federal units and areas with the worst Nexus dimension performances and with insufficient governance measures are north and northwest of Bahia and municipalities bordering the State of Tocantins—food; Maranhão and Piauí, northeast of Mato Grosso, northwest of Goiás, Rio Grande do Norte and Paraíba—water; and Maranhão, extreme southeast of Pará, and more sparsely in Paraíba—energy.

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract