The soil quality index (SQI) serves as a general ecological restoration indicator, however, statistics approaches that accurately assess the minimum data set (MDS) for SQI remain susceptible. The ...present study aims to evaluate the short-term reclamation results at the Ferro-Carvão stream and propose a system for ecological restoration monitoring, by selecting influential attributes and indexing soil quality. We hypothesized that the reclamation activities at the Ferro-Carvão stream, referred to as the “Marco zero” (MZ) area, can bring its soil quality to levels comparable to those of the native area. We collected soil samples at 0–20 and 20–40 cm depths from transects of MZ and reference sites (R1 and R2). Principal component analysis showed the MDS for each soil depth. Permutational analysis of variance, in conjunction with Nonmetric Multidimensional Scaling, exposed relationships between transects of areas. An additive non-linear factorial algorithm allowed SQI assessment. The results indicated a similar soil quality between transects of areas at 0–20 cm depth, whereas a dissimilarity at 20–40 cm. To sum up, reclamation activities allowed MZ-constructed Technosol to present a soil quality similar to native areas. The soil quality assessment at both depths offered insights into reclamation activities' immediate and long-term impacts on the Ferro-Carvão stream. This robust framework effectively monitors ecological restoration progress and guides future efforts in post-mining and post-dam collapse sites.
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•The constructed Technosol equaled the soil quality of natural and riparian forests.•Using stockpiled topsoil and managing soil pH and fertility are valued reclamation activities.•Soil quality assessment is an effective tool for monitoring ecological restoration.•Soil quality is depth-dependent, it declines with increasing soil depth.
•The chemical weathering intensity in Maritime Antarctica is modeled.•A geophysical survey and lithological characteristics as input data.•Proximal geophysical sensors and terrain attributes are ...combined for modeling.•Use of leave-one-out-cross-validation method in modeling.•Periglacial processes control the distribution of geophysical variables.
The chemical weathering intensity in Antarctica is underestimated. As the chemical weathering intensity increases, hydrological, geochemical and geophysical changes occur in the different environmental spheres and at their interfaces through reactions and energy flows. Thus, once chemical weathering rates are understood and estimated, they can be used to predict and assess changes and trends in different environmental spheres. Few studies on the chemical weathering intensity have been performed in Antarctica. We used radiometric and magnetic properties associated with terrain attributes and the chemical degree of alteration of the igneous rock to model the chemical weathering intensity in Maritime Antarctica by using machine learning. Then, we related the chemical weathering intensity and geophysical variables with periglacial processes. To do this, gamma-spectrometric and magnetic readings were carried out using proximal-field sensors at 91 points located on different lithologies in a representative area of Maritime Antarctica. A qualitative analysis of chemical alteration for the different lithologies was carried out based on field observations and rock properties, and the levels of the chemical weathering degree were established. The geophysical data associated with terrain attributes were used as input data in the modeling of the weathering intensity. Then, the levels of the rock weathering degree were used as the “y” variable in the models. The results indicated that the C5.0 algorithm had the best performance in predicting the weathering intensity, and the most important variables were eTh, 40K, 40K/eTh, 40K/eU, the magnetic susceptibility and terrain attributes. The contents of radionuclides and ferrimagnetic minerals in different lithologies, concomitantly with the intensity at which chemical weathering occurs, determine the contents of these elements. However, the stability and distribution of these elements in a cold periglacial environment are controlled by periglacial processes. The chemical weathering intensity prediction model using gamma-spectrometric and magnetic data matched the in situ estimate of the chemical degree of alteration of the rock. The pyritized andesites showed the highest intensities of weathering, followed by tuffites, diorites, andesitic basalts and basaltic andesites, and the lowest weathering intensity was shown by undifferentiated marine sediments. This work highlighted the suitability of using machine learning techniques and proximal-field sensor data to study the chemical weathering process on different rocks in these important and inhospitable areas of the cryosphere system.
Global soil carbon maps are essential to understanding the global carbon cycle and supporting policy decisions, but their uncertainty in remote areas with limited data remains a significant ...challenge. Assessing and quantifying soil carbon at a regional level can shed light on existing uncertainties in global maps, providing more dependable information for stakeholders. Therefore, we aimed to model and map the soil organic carbon (SOC) stock in the Western Amazon, state of Rondônia, which witnessed a loss of 30% of its native coverage in the last 35 years. We used information from almost three thousand soil profiles that have not been included in the modeling of global and national existing soil maps. SOC stocks were stratified at 0–5, 5–15, 15–30, 30–60, and 60–100 cm depths and we selected the environmental predictors based on correlation < |0.95| and importance (recursive feature elimination). To reduce uncertainties and select the best model, we tested six different machine learning algorithms and ran the models 100 times for each depth with different subsets of samples, resulting in maps of mean, quantiles (Q05 and Q95), and uncertainty (Coefficient of variation). The Random Forest model presented the best performance, and the soil class was one of the predictors that most influenced the SOC stock, especially in the superficial layers (0–30 cm). The largest SOC stocks are in the southern region (protected areas), at low altitudes and places with seasonal flooding dynamics, and the smallest values are found in the central region, associated with the high-weathered Latossolos. Our results show that national and global maps overestimate SOC stocks (up +100 Mg C ha−1) in the central region with lower SOC stocks, and underestimate (− 400 Mg C ha−1) in the southern region with higher SOC stocks. These higher SOC stocks are concentrated in protected areas, but this information was hidden until now since global and national SOC maps could not identify these hotspots. Although global and national maps are handy for first assessment in locations without specific information, regional soil sampling and mapping should be used in hotspots of soil carbon sequestration and land use changes to ensure the continuous protection of these areas.
As florestas plantadas destacam-se no contexto da mitigação de gases de efeito estufa, pois são estoques renováveis que dão perenidade aos estoques de carbono. Objetivou-se quantificar o estoque de ...biomassa e carbono na parte aérea em plantio comercial de paricá (Schizolobium parahyba var. amazonicum) em Rolim de Moura, Rondônia. Selecionaram-se árvores distribuídas em cinco classes de diâmetro à altura do peito (DAP), definidas pelo inventário florestal. As árvores foram abatidas e tiveram os compartimentos fuste, casca, galhos e folhas separados. Para densidade básica, os maiores valores foram encontrados nas classes de DAP entre 19,4 e 28,2 cm (380 kg m-3 e 345 kg m-3). O plantio acumulou 41,94 Mg ha-1 de biomassa total e as classes intermediárias (10,6 até 19,4 cm) representaram 84% dessa biomassa. Em relação aos compartimentos, observou-se que tanto a biomassa quanto o teor de carbono acumulados foram crescentes na seguinte ordem: fuste > galho > folha > casca. A biomassa de fuste representou 72,2% do total estimado no plantio. O estoque de carbono total encontrado para o plantio foi em torno de 16,6 Mg ha-1, que foi distribuído em 74,9% para o fuste, 6,3% para casca, 10,4% para galhos e 8,3% para folhas. O plantio de paricá apresentou acúmulos consideráveis de biomassa e carbono e pode contribuir para programas de crédito de carbono.
Palavras-chave: serviços ecossistêmicos; gases de efeito estufa; silvicultura tropical.
Biomass and carbon in commercial paricá plantations in the Amazon
ABSTRACT: Planted forests stand out in the context of greenhouse gas mitigation, because they are renewable stocks that provide perpetuity to carbon stocks. The objective was to quantify the aboveground biomass and carbon stock in a commercial plantation of paricá (Schizolobium parahyba var. amazonicum) in Rolim de Moura, Rondônia. Trees were selected in five diameters at breast height (DBH) classes, defined by the forest inventory. The trees were cut down and the stem, bark, twigs and leaves were separated. For basic density, the highest values were found in DBH classes between 19.4 and 28.2 cm (380 kg m-3 and 345 kg m-3). The plantation accumulated 41.94 Mg ha-1 of total biomass and the intermediate classes (10.6 to 19.4 cm) represented 84% of this biomass. The biomass and carbon content accumulated in each compartment increased in the following order: stem > twig > leaf > bark. The stem biomass represented 72.2% of the total estimated in the plantation. The total carbon stock found for the plantation was around 16.6 Mg ha-1, which was distributed in 74.9% for the stem, 6.3% for bark, 10.4% for branches and 8.3% for leaves. The paricá plantation presented considerable accumulations of biomass and carbon and can contribute to carbon credit programs.
Keywords: ecosystem services; greenhouse gases; tropical forestry.
Plantios de árvores proporcionam aumento dos estoques de carbono do solo, mas estudos envolvendo espécies nativas da Amazônia são incipientes. Objetivou-se avaliar a variação espacial dos atributos ...físicos e estoque de carbono orgânico no solo em plantio de paricá. Na área de estudo, coletaram-se amostras de solo nas profundidades de 0 a 20 cm e de 20 a 40 cm e os parâmetros analisados foram: textura do solo, macroporosidade, microporosidade, densidade aparente do solo, resistência mecânica do solo à penetração, teores e os estoques de carbono orgânico do solo. Interpolou-se os dados pelo inverso do quadrado da distância. A variação espacial dos atributos físicos do solo no plantio foi influenciada pela textura. Houve baixa amplitude da variação espacial dos teores e estoques de carbono orgânico do solo. O plantio de paricá apresentou eficiência na fixação de carbono no solo em profundidade.
Palavras-chave: silvicultura; sequestro de carbono; física do solo; mudança climática.
Spatial variation of physical attributes and soil carbon stocks in a Schizolobium amazonicum plantation in the amazon
ABSTRACT: Tree plantations provide an increase in soil carbon stocks, but studies involving native Amazonian species are incipient. The objective was to evaluate the spatial variation of physical attributes and soil organic carbon stock in a paricá plantation. In the study area, soil samples were collected at depths of 0 to 20 cm and 20 to 40 cm and the parameters analyzed were: soil texture, macroporosity, microporosity, soil bulk density, mechanical soil resistance to penetration, and soil organic carbon content and stocks. The data were interpolated by the inverse of the square of the distance. The spatial variation of soil physical attributes at planting was influenced by texture. There was a low range of spatial variation in soil organic carbon content and stocks. Paricá planting was efficient in fixing soil carbon at depth.
Keywords: silviculture; carbon sequestration; soil physics; climate change.