The search for tools to perform soil surveying faster and cheaper has led to the development of technological innovations such as remote sensing (RS) and the so-called spectral libraries in recent years. However, there are no studies which collate all the RS background to demonstrate how to use this technology for soil classification. The present study aims to describe a simple method of how to classify soils by the morphology of spectra associated with a quantitative view (400-2,500 nm). For this, we constructed three spectral libraries: (i) one for quantitative model performance; (ii) a second to function as the spectral patterns; and (iii) a third to serve as a validation stage. All samples had their chemical and granulometric attributes determined by laboratory analysis and prediction models were created based on soil spectra. The system is based on seven steps summarized as follows: i) interpretation of the spectral curve intensity; ii) observation of the general shape of curves; iii) evaluation of absorption features; iv) comparison of spectral curves between the same profile horizons; v) quantification of soil attributes by spectral library models; vi) comparison of a pre-existent spectral library with unknown profile spectra; vii) most probable soil classification. A soil cannot be classified from one spectral curve alone. The behavior between the horizons of a profile, however, was correlated with its classification. In fact, the validation showed 85 % accuracy between the Morphological Interpretation of Reflectance Spectrum (MIRS) method and the traditional classification, showing the importance and potential of a combination of descriptive and quantitative evaluations

Seasonality and crab activity affects the nutrients and physicochemical parameters in mangrove soils, thus, affecting the emissions of greenhouse gases, such as nitrous oxide (N₂O). Climate change may intensify rainfall and/or enhance droughts, affecting mangroves and associated biota. Crabs are natural soil bioturbators responsible for soil aeration and turnover. We evaluated the effect of Ucides cordatus crab on N₂O emissions from mangrove soils under a semiarid climate in Northeastern Brazil. Soil and gas samples were collected over the rainy and dry seasons in crab-naturally-bioturbated and crab-exclusion mangrove plots. We measured the soil’s pH, redox potential, and the total contents of carbon, nitrogen, and sulfur. We found higher N₂O emissions in the crab-exclusion sites compared to the bioturbated sites, as well as higher N₂O emissions in the rainy season compared to the dry season. The fluxes of N₂O (µg m⁻² h⁻¹) were 47.3 ± 9.7 and 8.9 ± 0.5 for the crab-exclusion sites, and 36.5 ± 7.8 and 4.5 ± 2.1 for the bioturbated sites (wet and dry seasons, respectively). The soil turning over by macrofauna led to lower N₂O fluxes in natural crab-bioturbated areas, and seasonality was the environmental factor that contributed the most to the changes in N₂O emissions. Broadly, anthropic activities and seasonality influence nitrogen fate, N₂O emissions, and ecological services in coastal ecosystems.

Minimizing environmental impacts and increasing crop productivity depend mainly on the knowledge of chemical, physical and mineralogical characteristics of the soil attributes. However, traditional methods are timeconsuming and costly. The objective of this study was to determine and validate a method to quantify soil attributes using UV-Vis-NIR Spectroscopy as an alternative to conventional methods of soil analyses. The work comprised two main phases: (1) creation and calibration of statistical models to determine the soil attributes derived from spectral data extracted from soil samples collected in area 1, (2) validation of statistical models in area 2 and correlations between the estimated and observed values (conventional method) for each soil attribute. The equations of the attributes Fe2O3, Al2O3, and clay reached R2 > 0.80 and may be applied to a different database than the one that was used to generate the equations, provided that they belong to the same study site

Mangrove revegetation is a vital strategy to recover ecosystem services (e.g., climate regulation and pollutants retention) provided by these ecosystems. Although soils are directly or indirectly responsible for diverse ecosystem services in mangrove ecosystems, few studies have focused on the recovery of soil functions (e.g., carbon sequestration) after mangrove replanting. This study aimed to evaluate the recovery of soil processes associated with Fe, S, and C dynamics and its implications for the restoration of soil functions. Two mangrove sites under replanting initiatives were studied along the Brazilian coast (i.e., NE and SE). The study was conducted in 3- and 7-year-old replanted mangrove forests, and a comparison was made with degraded and mature mangroves. Particle size, soil C stocks, Fe forms, total Fe and S contents, degrees of pyritization of Fe, and mineralogical assemblages were assessed. Seven years after replanting, soil C stocks increased by 42% and 29% in mangrove soils from the NE and SE sites, respectively. In addition, significant increases were observed in fine particles, reactive Fe, and pyrite contents in replanted plots. These new conditions promoted organic matter accumulation, stabilization, and potential metal retention. Our findings highlight the potential of revegetation programs for recovering soil processes and essential soil functions.

Unstable soil aggregates can easily be dispersed when mechanical energy is applied, denominated as readily dispersible clay (RDC) which is usually measured by turbidimetry. Faster methods that require minimum preparation at reduced costs are needed, such as the spectroscopy technique. Nevertheless, the technique has not yet been tested on soils. Electromagnetic radiation has strong interaction with soil physical elements (sand, silt, and clay) and with selective elements of the clay fraction, such as mineralogy. Thus, this study assessed the potential of 400–16,680 nm range (visible – Vis; near-infrared – NIR; short-wave infrared – SWIR; and medium infrared – MIR) spectroscopy to estimate RDC in some tropical soils. We also evaluated the wavelengths and regions that contribute to this prediction. We collected 68 samples from the underlying horizon of three different soils from three important states in Brazil The soil analyses were performed (physical and chemical) in the laboratory. RDC quantification was compared with the Vis-NIR-SWIR and MIR wavelengths models. The random forest (RF) algorithm was used to generate the prediction in the soil database. For RDC, the Vis-NIR-SWIR and MIR configuration presented a better relationship (coefficient of correlation (r) = 0.659 and root of the mean square error (RMSE) = 0.469%), although the results were similar when the regions were evaluated separately (Vis-NIR-SWIR – 350 to 2500 nm and MIR 2500 to 16,680 nm). RDC determination is more related to bands from 1980 to 2040, 6840 to 7360, and 7750 to 9820 nm. Spectroscopy showed its importance in RDC quantification, as it is fast and does not require soil preparations. The results show that spectral wavelengths are appropriate to assist on the estimative of RDC in the studied soils and may provide a basis for future research.