ABSTRACT
Phosphorus (P) is a critical nutrient for primary production in terrestrial and aquatic ecosystems. As P mineral reserves are finite and non-renewable, there is an increasing discussion on its sustainable utilization to safeguard food security for future generations. Understanding the spatial distribution of soil P is central in advancing effective phosphorus management and fostering sustainable agricultural practices. This study aims to digitally map the stocks of available P (AP) and total P (TP) in Brazil at a fine resolution (30 m). Using the Random Forest machine learning algorithm and a database of topsoil (0-20 cm) with 28,572 samples for AP and 3154 for TP, we predicted P stocks based on environmental covariates related to soil formation processes. By dividing Brazil into two sub-regions, representing areas with native coverage and anthropogenic ones, we built independent predictive models for each sub-region. Our results show that Brazil has a TP stock of 531 Tg and an AP stock of 17.4 Tg. The largest soil TP stocks are in the Atlantic Forest biome (73.8 g.m2), likely due to higher organic carbon stocks in this biome. The largest AP stocks were in the Caatinga biome (2.51 g.m2) because of younger soils with low P adsorption capacity. We also found that fertilizer use significantly increased AP stocks in agricultural areas compared to native ones. Our results indicated that AP stocks strongly influenced Brazil's agricultural production, with a correlation coefficient ranging from 0.20 for coffee crops to 0.46 for soybean. The maps generated in this study are expected to contribute to the sustainable use of P in agriculture and environmental systems.
ABSTRACT
Bioclimatic envelope models have been extensively used to predict the vegetation dynamics in response to climate changes. However, they are prone to the uncertainties arising from General Circulation Models (GCMs), classification algorithms and predictors, with low-resolution results and little detail at the regional level. Novel research has focused on the improvement of these models through a combination of climate and soil predictors to enhance ecological consistency. In this framework, we aimed to apply a joint edaphoclimatic envelope to predict the current and future vegetation distribution in the semiarid region of Brazil, which encompasses several classes of vegetation in response to the significant environmental heterogeneity. We employed a variety of machine learning algorithms and GCMs under RCP 4.5 and 8.5 scenarios of Coupled Model Intercomparison Project Phase 5 (CMIP5), in 1 km resolution. The combination of climate and soil predictors resulted in higher detail at landscape-scale and better distinction of vegetations with overlapping climatic niches. In forecasts, soil predictors imposed a buffer effect on vegetation dynamics as they reduced shifts driven solely by climatic drift. Our results with the edaphoclimatic approach pointed to an expansion of the dry Caatinga vegetation, ranging from an average of 16% to 24% on RCP 4.5 and RCP8.5 scenarios, respectively. The shift in environmental suitability from forest to open and dry vegetation implies a major loss to biodiversity, as well as compromising the provision of ecosystem services important for maintaining the economy and livelihoods of the world's largest semiarid population. Predicting the most susceptible regions to future climate change is the first step in developing strategies to mitigate impacts in these areas.
ABSTRACT
BACKGROUND: The Cerrado is the second largest biome in Brazil and the most biodiverse tropical savannah in the world and acts as a great sequester of atmospheric carbon. The lack of studies related to the quantification of its total biomass compromises the understanding of the dynamics of CO2 in this biome. Thus, it is relevant to develop studies aiming at obtaining accurate estimates of the carbon stock in the different phytophysiognomies that make the Cerrado, to include them in appropriate forest management models. Based on the hypothesis that the amount of carbon stored can vary according to the vegetation typology and vegetation compartments, the aerial stock of dry biomass and carbon were estimated in different compartments (arboreal, herbaceous-shrub and litter). The study was developed in open Brazilian savannah and soils on the sandstone and discussed the effect of fire on this phytophysiognomy. For the arboreal compartment were adjusted mathematical models to fit the biomass equations to estimate the individual stock of the trees in this compartment. The results of the stocks were discussed considering the effect of fire on the phytophysiognomy. RESULTS: Based on the precision and extra distribution measures, the Schumacher-Hall (non-logarithmic) equation presented better results to estimate the individual biomass and carbon stocks of the open Brazilian savannah trees. The aboveground biomass was 12.88 Mg ha-1, corresponding to a total carbon stock of 5.91 Mg ha-1, where most of the stocks are in the herbaceous-shrub compartment (44%). The arboreal compartment accounts for the smallest part of the stocks, followed by the litter. CONCLUSIONS: The observed values are in the interval verified for other areas of savannah studied in Brazil. The values verified for the open Brazilian savannah in sandy soils are at the lower limit of this range, due to the nutrient-poor nature of this type of soil. The distribution of stocks in the different compartments above the ground points to the fragility of this environment to the random fire effect, common in the region. That shows the need for conservation measures for vegetation maintenance and soil protection to preserve adequate nutrient cycling in the ecosystem.
ABSTRACT
ABSTRACT Remote sensing allows for identification of regularities and irregularities in land use and land coverage (LULC) change in relation to environmental legislation. The aim of this study was to delimit scenarios in the permanent preservation areas (PPAs) according to the Brazilian forestry law, with or without consolidated uses in the basin of Capivari River and the State of Rio de Janeiro in the Atlantic Forest biome. Mapping and analysis were performed on LULC in areas of permanent preservation using the following data: RapidEye-REIS satellite scenes acquired in 2012 and Bhattacharyya distance classifier and hydrography of the basin and digital elevation model (1:25.000) using Spring and ArcGIS software. The legal scenarios adopted were as follows: I) Federal Law N°. 4,771/1965 and the National Council for the Environment (CONAMA) N°. 303/2002; II) Federal Law N°. 12,651/2012; and III) Federal Law N°. 12,651/2012 and N°. 12,727/2012. The classification presented an excellent overall accuracy of 91.15% and a Kappa Index of 0.86 in relation to the samples of the six multipurpose classes having the anthropic uses of agriculture, burned pasture, exposed soil and urbanization, which were present with conflicting uses for Scenarios I, II and III. The new forest legislation for the PPAs of Scenario III impacted the reduction of 68% compared to Scenario I, which corroborates with the concerns on the conservation of water and soil resources.
RESUMO O sensoriamento remoto permite a identificação das regularidades e irregularidades do uso e cobertura do solo em relação à legislação ambiental e pode ser decisivo em tomadas de decisões para intervenção. O objetivo do trabalho foi delimitar cenários em áreas de preservação permanentes com e sem usos consolidados na bacia hidrográfica do Rio Capivari, Estado do Rio de Janeiro-Brasil, no bioma da Mata Atlântica. Foram realizados no mapeamento e a análise do uso e ocupação das áreas de preservação permanente, através dos seguintes dados: cenas do satélite RapidEye-REIS de 2012, classificador Bhattacharya Distance e hidrografia da bacia e modelo digital de elevação (1:25.000), e os softwares Spring 5.2.7 e ARCGis 10.3.1. Os cenários adotados foram: I) Lei Federal n.º 4.771/1965 e Resolução do Conselho Nacional de Meio Ambiente (CONAMA) n.° 303/2002; II) Lei Federal n.º 12.651/20120; e III) Leis Federais n.º 12.651/2012 e n.º 12.727/2012. A classificação apresentou excelente acurácia de 91,15% para exatidão global e o índice Kappa de 0,86 em relação as amostras de treinamento das seis classes de usos múltiplos, tendo os usos antrópicos de Agropecuária, Queimadas, Solo Exposto e Urbanização, os quais estiveram presentes com usos conflitivos para Cenários I, II e III. A nova legislação florestal para as APPs do Cenário III impactou na redução em 68% em relação ao Cenário I, onde corrobora a preocupação na conservação dos recursos hídricos e edáficos, e o cumprimento da legislação.
ABSTRACT
A equação universal de perda de solo (USLE) vem sendo utilizada para valorar os serviços ambientais de praticas conservacionistas e uso do solo em sub-bacias na quantificação da erosão e aporte de sedimentos. Neste sentido este trabalho objetivou comparar os resultados de perda de solo e de valoração ambiental obtido a partir da USLE com os valores mensurados no exutório de duas sub-bacias. A perda total de solo foi calculada utilizando técnicas de geoprocessamento e transformada em aporte de sedimentos e comparado ao aporte de sedimento observado no exutório da sub-bacias. A produção de sedimentos calculada e observada foi valorada considerando o custo de remoção de sedimentos do sistema de captação de água das microbacias. De forma geral, o modelo utilizado não apresentou bom ajuste para a quantificação do aporte de sedimentos nas sub-bacias Glória e Palmital, superestimando os valores medidos nas respectivas áreas. De acordo com a valoração ambiental pelo custo de retirada de sedimentos observou-se que a microbacia com maior cobertura florestal reduz o aporte de sedimentos e gera mais serviços ambientais reduzindo os custos de retirada de sedimentos na captação de água.
The Universal Soil Loss Equation (USLE) has been used to appraise the environmental services of the conservation practices and land use in sub - watersheds in the quantification of erosion and sediment delivery. In this sense this study compares the results of soil loss and environmental valuation obtained from the USLE model with the values measured in the discharge of water of both watersheds. The total soil loss was calculated using GIS techniques and transformed into sediment delivery and then compared to the production of sediment observed in the discharge watersheds. The sediment production rate was calculated and valued considering the cost of sediment removal from water catchment system. In general, the model used did not show goodfit for quantification of sediment delivery in sub - watersheds Gloria and Palmital, overestimating the values measured in the respective areas. According to evaluation by environmental cost of removing sediment was observed that the more sub watershed forest cover reduces the accumulation of sediments creates more environmental services and reducing the costs of removal of sediment in the water uptake.
