The recurrence and severity of wildfire is on the rise due to factors like global warming and human activities. Mediterranean regions are prone to significant wildfire events, which cause extensive damage to ecosystems and soil properties. This study focuses on the municipality of Allande in south-western Asturias (Spain), a region highly affected by recurrent wildfires. In this regard, we sought to examine how the recurrence of such fires influences soil organic carbon fractionation and other soil parameters, such as nitrogen fractionation, pH, and cation exchange capacity. The study involved six sampling plots with between varying fire recurrence levels, from 0 to 4 events between 2005 and 2022. The results revealed some significant effects of wildfires recurrence on soil texture, inorganic elemental composition and CEC, but not on pH and CE. In soil affected by recurrent fires, labile carbon fractions (cold-water extractable & hot-water extractable), and fulvic acid concentrations decreased by up to 36%, 5%, and 45%, respectively in comparison with undisturbed soil. In contrast, humic acid concentration remained stable or increased in soils damaged by fire. Additionally, nitrogen species in soil were observed to decrease significantly in high recurrence scenarios, especially nitrate. On the basis of our findings, we conclude that wildfires impact the distinct fractions of organic carbon and nitrogen in soils and that this effect is aggravated by increasing recurrence.

Climate change and associated shifts in temperature and precipitation patterns have become an increasing concern as drivers of ongoing biodiversity loss. The Mediterranean region is particularly vulnerable, being both a biodiversity hotspot and a region very prone to desertification. Freshwater mussels are amongst the most threatened invertebrate taxa worldwide. Unio tumidiformis is an endemic and endangered species restricted to the southern Iberian Peninsula, living in temporary Mediterranean-type streams. Freshwater mussels need a fish host for successful larval transformation, meaning U. tumidiformis must belong to the genus Squalius. The main objective of this study was to evaluate the vulnerability of U. tumidiformis to climate change, by studying its population genetics and evolutionary history, its current and future habitat suitability, and that of its hosts. Genetic population structure and diversity were assessed using Single-Nucleotide Polymorphisms through Genotyping by Sequencing and used to infer species evolutionary history. The species potential distribution was modeled using an ensemble forecasting approach, and future shifts in habitat suitability were assessed with the projected climate data layers from Worldclim. Most populations showed extreme genetic differentiation (Fst up to 0.745), even from close neighboring ones. Upper Guadiana populations were more diverse and less differentiated. We hypothesize that U. tumidiformis originated in Upper Guadiana and followed the same colonization routes as their hosts with numerous founder effects and bottlenecks. Our results also predicted a reduction of 99% of climatically suitable areas for U. tumidiformis in the Iberian Peninsula until 2040. For the fish hosts, a maximum 42% reduction in suitable areas was estimated throughout the century, with remaining adequate habitats in the north. Our results suggest that difficult conservation options are necessary, prioritizing the preservation of populations, translocations to the northern area of its historical range and stream engineering to increase resilience to droughts.

Mediterranean temporary streams are characterized by high hydrological variability that climate change is expected to intensify, increasing drought frequency and severity. These conditions represent a major threat to freshwater mussels, an imperiled group with limited mobility and strict habitat and host requirements. This study explored key factors shaping freshwater mussel community structure, including the spatial distribution, species composition and abundance of coexisting species, in two temporary streams of the Guadiana river basin (southwestern Iberian Peninsula). Pool systems in both streams were characterized and compared under average dry season and extreme drought conditions using aerial imagery, whereas mussel abundance patterns and host–mussel relationships were assessed in the larger and more hydrologically stable stream. Results showed that drought severity had different effects on pool refugia persistence, longitudinal distribution and host fish availability between streams. The smaller stream experienced extensive pool desiccation during extreme drought, causing widespread mussel mortality, whereas the larger stream retained numerous pools that allowed mussel persistence. Mussel abundance showed no relationship with pool size. However, Unio tumidiformis abundance was positively associated with native fish abundance, particularly in upstream reaches. These results highlight hydrological stability and host availability as key drivers of freshwater mussel persistence in Mediterranean temporary streams.

The studied specimens were collected with a plankton net with pore mesh of 45 µm, preserved with 4% formalin, and these were analyzed and dissected with the aid of a stereomicroscope. Microphotographic images and measurements were made with NIS-Elements G software.

Traditional methods to acquire (geo)chemical data of Soil Organic Carbon (SOC) in soil rely on manual sampling, time-consuming and laborious chemical analyses, and subsequent mapping by geostatistical interpolation methods. In this study, we propose the use of UAV-RS and Sentinel-2 images, still partially supported by field sampling, for assessing and mapping different fractions of SOC using a regression study through Machine Learning (ML) techniques. This approach is exemplified in the postmining degraded soils of a vast former coal-mining area affected mainly by high degradation of Organic Matter (O.M).Geochemical analyses by means of a TOC analyzer were conducted to monitor SOC fractions. Soil samples were dried and sieved through a 2-mm mesh to eliminate large particles. Two labile fractions of carbon (CLAB) were obtained through cold-water extraction (CCWE) and hot-water extraction (CHWE); also, two removable carbon fractions (CREM), humic and fulvic acids (CHA and CFA), were extracted; finally, the remaining recalcitrant organic carbon (CREC) was measured in the residue of the previous extractions. TOC was estimated as the sum of CLAB, CREM and CREC.Spectral data were systematically recorded across a surface area covering 64 hectares within former open pits, involving natural, restored, and degraded zones. A UAV-RS P4-Multispectral platform, equipped with a camera featuring six individual sensors (RGB, blue, green, red, red-edge, and near-infrared), was used; five distinct bands between the visible and near-infrared spectra were obtained. Simultaneously, Sentinel-2 data were employed to acquire spectral information from satellite-borne sensors, thereby obtaining 12 single bands (aerosol, blue, green, red, 3 red edge, 2 NIR, water vapor, cirrus, and 2 SWIR). Given the limitations of information derived from individual bands, spectral indices—combinations of multiple bands through algebraic operations—were employed. Subsequently, two ML algorithms, specifically Random Forest (RF) and Partial Least Square (PLS), were applied to identify the most fitted model for each SOC fraction.Results revealed that the utilization of non-parametric algorithms, specifically RF, yields a superior goodness of fit compared to parametric algorithms like PLS. The most favourable statistical outcomes were observed for fractions of non-labile organic carbon, with the optimal statistics achieved for CREC, attaining an R2 value of 0.70 and an RPD value of 1.83. When comparing data from UAV and Sentinel-2 sources, better results were found for UAV, this strongly suggesting that, in this study, spatial resolution holds greater relevance than spectral resolution.This research was funded by the projects NATURESOIL (AEI/Spain, TED2021-130375B-I00) and Atlantic Risk Management Plan in Water and Soil (RiskAquaSoil 272-2016, Interreg Atlantic Area, EU).