Soil organic matter plays a crucial role in maintaining soil fertility and stabilizing the global carbon cycle. The application of biochar (Bc) can be converted into soil organic matter and regulate the soil organic carbon (SOC) pool through the dual mechanisms of ”introducing new carbon inputs” and ”regulating old carbon turnover”. However, the temporal distribution patterns of biochar-derived new carbon across humus fractions and their underlying mechanisms remain unclear. To address this gap, this study used chemical extraction combined with δ 13C isotope techniques to quantify SOC content, extractable carbon (EC) and non-extractable carbon (nEC) contents, and their δ 13C values after Bc addition under different incubation periods, while further investigating the increment of new carbon and its distribution in soil carbon pools. The results showed that the Bc application rate significantly regulated the increment of new carbon, with the P3 treatment (21.2 g Bc kg -1) showing the most pronounced accumulation; moreover, new carbon exhibited selective allocation among humus fractions, as both the increment and proportion of new carbon in nEC were significantly higher than those in EC at all incubation times . Meanwhile, with prolonged incubation, the increment of new carbon in nEC decreased due to the decomposition of Bc residues, whereas the proportion of new carbon allocated to humic acid (HA) increased significantly under higher Bc application rates (e.g., in the P3 treatment after 540 days, HA-associated new carbon reached 4.32%); in addition, the increment of new carbon in EC also increased markedly driven by HA-associated new carbon accumulation, which reflects the transfer of Bc-derived new carbon from nEC to HA—a carrier of long-term stable carbon sequestration. This study provides a scientific basis for optimizing Bc-based carbon sequestration strategies and enhancing soil carbon sink potential, while also enriching the understanding of microscale processes governing humus-mediated soil carbon cycling.

Limiting global warming to 1.5-2°C requires an immediate reduction in atmospheric carbon, suggesting the urgent need to conserve ecosystems with high carbon potential. Tropical forest systems, especially those that have been conserved for several years, offer immense value in both carbon storage and biodiversity conservation. This study explores the role of sacred groves, the culturally protected forest fragments, as community-managed landscapes that contribute to climate change mitigation and conserve biodiversity. The influence of elevation and grove size on floral richness and carbon storage was examined across 55 sacred groves in Kerala, India. Biomass carbon was estimated using allometric equations, and soil organic carbon was quantified using the wet digestion method, which were then summed to determine the total carbon storage. Statistical analysis revealed that carbon storage was not significantly affected by either. However, both had a significant impact on species richness, with a notable interaction between them. The results indicated that the large groves in highland areas supported the greatest species richness, while small groves in the same physiographic zone had the lowest. Soil analysis showed higher exchangeable potassium in midland groves and elevated bulk density in soils of highland groves. These results highlight the intersection of biophysical characteristics and traditional stewardship in maintaining biodiversity and influencing ecosystem functioning. As biodiversity-rich systems are known to enhance resource use efficiency and biomass accumulation, conserving sacred groves presents a scalable, traditionally embedded solution. Recognising and strengthening such nature-based, community-driven conservation practices can play a pivotal role in achieving climate and sustainability goals.

The transformation of natural ecosystems to intensive agriculture is one of the drivers of topsoil acidification. However, the extent of soil acidification throughout soil profile following land-use transformation remains insufficiently understood and poorly documented. To quantify the impacts of this land-use transformation, we conducted a paired-site investigation in southern China, comparing soil profiles (0-500 cm) from natural forests and adjacent intensively managed pomelo orchards. Within these profiles, we analyzed soil pH, exchangeable cations, and inorganic nitrogen forms, and employed statistical models to identify key drivers. Results indicated that the transformation of natural forests to pomelo orchards induced severe acidification across the entire 500 cm soil profile, with the most pronounced pH reduction (19.6%) occurring in the subsoil (160–180 cm). Paradoxically, despite this widespread acidification, exchangeable base cations (K +, Ca 2+, Mg 2+) were significantly enriched in the top 250 cm of orchard soils. Notably, soil NO 3 --N concentrations in pomelo orchards exceeded those in natural forest at all depths, while NH 4 +-N concentrations did not differ significantly between the two land-use systems. Correlation analysis revealed that soil pH in pomelo orchards had a stronger association with NO 3 --N. Clustering and partial least squares regression analysis further suggested that significant soil acidification occurred in the 0–250 cm soil layer due to NO 3 --N leaching from pomelo orchard cultivation. It can be seen that in intensive pomelo orchards, nitrogen-driven acidification overrides the ameliorative effect of base cation inputs, leading to a systemic and deep-seated acidification problem. Consequently, effective mitigation requires a shift from conventional topsoil management to integrated strategies that control nitrogen at the source and address the unique dynamics of the subsoil environment.

Arid and semi-arid regions, characterized by fragile ecosystems and concentrated land-use pressures, have become high-risk areas of cropland abandonment, posing a significant threat to regional agricultural productivity and sustainable land use. This study constructs a 10 m resolution dataset of cropland abandonment for the period 2016–2022 and, drawing on the Coupled Human–Natural Systems framework, interprets cropland abandonment and systematically investigates its spatio-temporal patterns and driving mechanisms in Inner Mongolia. This paper defines cropland abandonment as farmers, under the pressures of land degradation and environmental constraints and in order to maintain the relative stability of the coupled human–land system, reducing or ceasing cultivation to re-seek a balance between socio-economic returns and ecological carrying capacity, which constitutes a self-organizing adaptive behaviour and response mechanism to degradation. The results show that the mean annual area of abandoned cropland in Inner Mongolia is 639.67 km 2, exhibiting an overall declining trend and pronounced spatial clustering. Precipitation is the dominant natural limiting factor, while accessibility (distance) and production conditions are the main anthropogenic drivers. Further analysis shows that the synergy between mean annual precipitation and total agricultural machinery power has the strongest explanatory power, and that the explanatory power of any pairwise interaction between factors exceeds that of single factors, consistent with the CHANS framework’s expectation of non-linear human–land coupling. The study also delineates four major abandonment hotspots, conducts regional attribution of abandonment, and proposes targeted management strategies. These findings strengthen our understanding of the spatial heterogeneity and driving mechanisms of cropland abandonment in arid and semi-arid regions, and provide theoretical support and empirical evidence for the interpretation and governance of cropland abandonment.

ArticleWidth Identification and Spatiotemporal Change in the Landscape Ecotones in the Poyang Lake Sandy Land Based on an Advanced Remote Sensing Ecological IndexWangyang Wu 1,2, Junwen Tian 2, Lihui Tian 1,*, Dengshan Zhang 1, Peng Fan 2 and Shuyu Yang 21 State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China ;2 School of Earth and Planetary Sciences, East China University of Technology, Nanchang 330013, China;* Correspondence: lhtian@qhu.edu.cn; Tel.: +86-155-2830-2040

Soil salinization is a major cause of land degradation and ecological deterioration. Traditional monitoring methods are spatially limited and inefficient. This study explores the use of multi-source remote sensing to improve the accuracy and timeliness of soil salinity inversion, providing support for precise management of saline-alkali land.The research was conducted in Lihe Township, Ningxia, China. We integrated Sentinel-1 SAR, Sentinel-2 multispectral data (including reflectance and derived salinity, vegetation, and texture indices), and SRTM DEM data. Feature selection was performed using Recursive Feature Elimination (RFE), Partial Least Squares (PLS), and Out-of-Bag (OOB) estimation methods. Soil salinity inversion models were developed for three maize growth stages (D1–D3) and a bare soil period (D4) using Random Forest (RF), Support Vector Regression (SVR), and Back-Propagation Neural Network (BPNN) algorithms.The RF model achieved the best and most stable performance across all periods, with an average coefficient of determination (R 2) > 0.77 on the test set. RFE yielded the most robust feature subsets. Sensitive features evolved with crop phenology: from vegetation and salinity indices in early stages, to topographic and texture features in middle stage, and finally to original bands and specific salinity indices in late and bare soil periods. Spatially, salinity was highest in the eastern and northern regions, with the west remaining stable. Temporally, soil salinity exhibited “summer-autumn leaching and winter-spring accumulation”.The multi-period, multi-model inversion framework developed in this study offers a reliable approach for stage-specific monitoring and management of regional soil salinization.

Páramos are unique high-altitude ecosystems in the Neotropics, known for their exceptional biodiversity and critical ecosystem services, such as water regulation and carbon storage. However, these ecosystems are increasingly threatened by agricultural and livestock expansion, leading to a widespread degradation. Although spontaneous vegetation recovery by native plant species is common when abandonment of agriculture use, the dynamics of soil health restoration remain poorly understood. We examined soil characteristics, arbuscular mycorrhizal fungi (AMF) abundance, and root-associated fungal community composition based on Illumina sequencing of the ITS region in two naturally regenerating sites in the Cumbal páramo (Nariño, Colombia), representing 12 and 45 years of post-disturbance recovery. Monitoring such soil biological indicators can guide low-cost, nature-based restoration strategies and improve understanding of recovery trajectories in degraded high-mountain ecosystems. Alpha diversity of the root fungal community did not differ between sites. However, PERMANOVA revealed significant effects of host species, site, and their interaction on fungal community structure. The redundancy analysis identified CEC as the key edaphic variable influencing community composition. These findings suggest that natural regeneration rapidly restores aboveground vegetation structure and composition but only gradually and incompletely recovers soil edaphic variables. Consequently, this process primarily reshapes the composition of root-associated fungal communities rather than their diversity, with host identity and soil fertility emerging as critical factors modulating the pace and trajectory of belowground ecological recovery in páramo ecosystems. Monitoring such soil biological indicators can guide low-cost, nature-based restoration strategies and improve understanding of recovery trajectories in degraded high-mountain ecosystems.

Agriculture remains central to Ghana’s economy, providing food, employment, and income for most rural households. Yet recent intensification through mechanization and high input use has accelerated soil degradation, particularly the decline of soil organic carbon (SOC), a key indicator of soil fertility and climate regulation. This study applied the Rothamsted Carbon Model (RothC) to quantify and project SOC dynamics in Ghanaian croplands from 2001 to 2024 and to simulate trajectories to 2074 under baseline, optimistic, and pessimistic climate and vegetation productivity trends. Harmonized datasets on SOC, clay content, NDVI, and climate variables were processed at 250 m resolution in Google Earth Engine. Model outputs correlated strongly with observed SOC (r = 0.91) but yielded a negative Nash–Sutcliffe efficiency (–1.16), reflecting systematic underestimation relative to SoilGrids while remaining consistent with field measurements. National mean SOC declined from 23.79 t ha -1 in 2001 to 22.94 t ha -1 in 2024 (–3.6%), with the steepest reductions in southern high-SOC zones and slight gains in northern low-SOC areas. Across agroecological zones, losses ranged from 27–31% (p < 0.0001), primarily due to humus pool depletion, whereas inert organic matter remained stable. Lag analyses indicated immediate SOC reductions following temperature increases and delayed effects under moisture stress. Projections suggest further SOC declines of 17–35% by 2074, underscoring the need for climate-responsive and agroecologically differentiated soil carbon management strategies in Ghana. Integrating SOC monitoring into national climate and land restoration policies would enable more targeted interventions to sustain soil productivity and carbon resilience.

Land degradation in semi-arid grasslands has intensified under the combined effects of climate change and human disturbance, highlighting the need for accurate and interpretable monitoring approaches. This study proposes a process-based framework integrating unmanned aerial vehicle (UAV) imagery with deep learning to quantify desertification using the Soil Pixel Proportion (SPP)—a novel ecological indicator that quantifies the proportion of exposed soil relative to total surface area. The framework combines MSCA-U-Net for multi-scale soil–vegetation segmentation and ViT-B/16 for degradation-level classification, establishing a link between remote sensing features and ecological processes. Field validation showed strong correlations between SPP, NDVI (r = –0.76), and soil organic carbon (r = –0.68), confirming its ecological validity. After segmentation-assisted relabeling, ViT achieved an F1-score of 95.3% and maintained cross-regional accuracy of 91.7% from semi-arid to semi-humid regions. Robustness tests under cloud, shadow, and snow disturbances verified stable performance (F1 > 85%), ensuring reliable detection of early-stage degradation. The SPP-based framework provides a reliable and interpretable approach for large-scale grassland degradation assessment, offering valuable support for restoration planning and progress evaluation toward Land Degradation Neutrality (LDN) within the United Nations Convention to Combat Desertification (UNCCD) framework.

Cadmium (Cd) contamination in paddy soils poses a dual challenge to food safety and climate resilience, undermining rice productivity while influencing greenhouse gas (GHG) emissions. Although vermicompost (VC) and biochar (BC) have been widely studied as soil amendments, the comparative efficacy of pristine VC versus vermicompost-derived biochar (VC-BC) in regulating Cd dynamics, soil health and GHG emissions remain unclear. Here, we studied the potential of VC and VC-BC on Cd translocation and bioaccumulation in rice, rice growth, soil C fractions, and methane (CH 4) and nitrous oxide (N 2O) emissions across rice growth stages. Results demonstrated that both VC and VC-BC enhanced microbial biomass carbon and dissolved organic carbon, but VC-BC exhibited superior Cd immobilization, reducing grain Cd concentrations by 79% compared to 45% with VC. Unlike VC, which increased Cd bioaccumulation factors, VC-BC reduced Cd uptake while enhancing chlorophyll content, antioxidant defenses, and overall plant vigor. The dramatic effect of VC-BC, characterized by hydroxyl (-OH), carboxylate (COO -), amide (N-H), and aromatic (C=C) functional groups, enhanced Cd immobilization, reduced grain contamination supported by the porous structure identified using SEM. GHG emissions displayed stage-specific dynamics: CH 4 emissions were significantly higher during the tillering stage while N 2O emissions increased during transplanting and harvesting stage. VC-BC moderated these fluxes relative to VC. Collectively, VC-BC emerges as a climate-smart, multifunctional amendment that immobilizes Cd, sustains soil biochemical health, and mitigates environmental trade-offs in rice systems.

The relationship between karst desertification (KD) and rural functions may evolve with urbanization and the implementation of ecological engineering. However, large-scale assessments of these evolving interrelationships remain limited. In this study, we examined 85 counties in Guizhou Province using multi-factor comprehensive evaluation method and bivariate spatial autocorrelation model to estimate the spatiotemporal changes in KD, rural multifunction, and their interrelationships. The results indicate that from 2005 to 2020, the level of KD in Guizhou Province significantly decreased, with the karst desertification index (KDI) dropping from 0.669 to 0.376. Rural production, living, and ecological functions all demonstrated significant improvement. Notably, the enhancement of rural production and living functions was more pronounced, whereas the improvement in ecological function was comparatively less significant. Moreover, the degree of coupling coordination among the three rural functions continuously increased. Regarding the relationship between KD and rural functions, there was a spatially positive correlation between KD and rural production function in 2005, which subsequently shifted to a spatially negative correlation from 2015 to 2020. Overall, KD control measures have promoted the improvement of the coupling coordination degree of rural functions by restricting rural production function and enhancing living and ecological functions. Our findings provide new insights into the relationship between KD and rural functions and have significant implications for policies aimed at achieving coordinated ecological restoration and rural development.

Calcareous soils in arid regions are characterized by high alkalinity and calcium content, which constrain the accumulation and stability of soil organic carbon (SOC). This study examined the effects of continuous application of Bio-based sulfonate liquid on SOC fractions, nutrient stoichiometry, microbial community structure, and carbon metabolic functions in calcareous cotton fields, using field experiments combined with multi-omics approaches. The co-application of Bio-based sulfonate liquid and chemical fertilizers significantly enhanced cotton yield by 13.53%-20.56%, while increasing soluble organic carbon and easily oxidizable carbon by 24.30% and 19.54%, respectively. Improvements in soil aggregate stability (MWD and GWD) facilitated the physical protection of SOC. Functional groups present in the Bio-based sulfonate liquid (e.g., C=C, C-O, -COOH) enhanced soil cohesion and promoted the activities of key carbon-degrading enzymes, including cellulase, sucrase, and β-glucosidase, thereby accelerating the turnover of recalcitrant organic matter. Positive correlations were observed among soluble Ca, N, P, available nutrients, and labile SOC fractions. Multi-omics analysis revealed a significant enrichment of carbon-metabolizing microbial taxa, such as Acidobacteria, Proteobacteria, and Gemmatimonadota. Additionally, genes associated with carbon cycling (e.g., lipase, cellulose synthase A3, β-glucosidase, acid phosphatase, 6-phosphogluconate dehydratase) were markedly upregulated. Metabolic pathways related to starch, sucrose, and galactose were activated, enhancing carbon availability for microbial communities. These findings provide mechanistic insights into the chemical and biological processes regulating SOC transformation in calcareous soils, and offer a scientific basis for sustainable straw resource utilization and carbon sequestration strategies in arid agricultural systems.

Coastal soil salinization from rising seawater levels can have adverse impacts on soil function, seed germination, and plant growth. Root exudates play a key role supporting microbial activity, nutrient cycling, and plant health, yet little is known about the combined effects of salinization and artificial root exudate (ARE) addition on soils. We investigated the impacts of sodium chloride (NaCl) and AREs, alone and in combination, on soil microbial function and the growth and survival of Chamaecyparis thyoides saplings. In a three-by-three fully factorial matrix, the combined NaCl and AREs treatment increased soil phosphatase activity more than the additive effects of the individual treatments, suggesting the treatments have a synergistic effect on phosphatase activity. Sequencing revealed that salinity shaped bacterial community composition more than AREs and fungal communities assembled more stochastically than bacteria. Soil respiration increased rapidly when treated with a high concentration of AREs, but this spike was delayed in the presence of high concentrations of NaCl, suggesting a stressed microbial community. Treatments containing the higher NaCl concentration were lethal to C. thyoides saplings, with a 78% mortality rate within one week when exposed to soil salinities of ~1 dS/m. The results align with the stress gradient hypothesis, as the addition of AREs increased soil phosphatase activity more in the newly stressed salinized environment compared to unsalinized soil.

Vegetation effects on slope runoff and sediment yield depend on plant types and vertical structures, yet underlying mechanisms remain insufficiently quantified. We conducted simulated rainfall experiments (60, 90, 120 mm h -1) on a taproot grass (Coronillavaria) and a fibrous-root grass (Juncuseffusus) to assess canopy and root contributions to runoff and soil loss control. Both species significantly reduced erosion, with sediment reduction exceeding runoff reduction. Compared with bare slopes, runoff decreased by 18.47%–69.27%, and sediment yield by 66.93%–99.77%. Roots dominated the control effect, contributing 54.99%–91.54% for runoff and 54.99%–86.69% for sediment, whereas canopies contributed 3.06%–26.59% and 13.31%–45.01%, respectively. Juncuseffusus roots and canopy achieved mean runoff reduction efficiencies of 53.41% and 5.25%, markedly higher than Coronillavaria (18.40% and 3.06%). In sediment reduction, Juncuseffusus excelled at 90 mm h -1 (83.31% by roots), while Coronillavaria performed better at 60 mm h -1. Both species decreased soil erodibility (Juncuseffusus 93.13%, Coronillavaria 82.84%) and increased critical shear stress (216.35% and 152.73%). These results highlight the superior runoff and erosion control of fibrous-root species, though dense roots may pose slope-failure risks under prolonged heavy rainfall. This study provides practical guidance for vegetation-based slope stabilization and soil conservation in China’s Loess Hilly and Gully Region.

Oats had become an important crop in southwest China due to their high nutritional value and excellent adaptability to the challenging climate. Continuous oat cropping can lead to reduced oat yield and soil degradation, meanwhile, crop rotation have been proven to be an effective way to alleviate the obstacles of continuous cropping. However, the effects of different crop-oat rotation patterns on oat yield, soil chemical properties and microbial communities in southwest China remain unclear. To address this, we used high-throughput sequencing and quantitative PCR of the 16S and ITS rRNA genes to investigate microbial communities in a multi-pattern crop-oat rotation experiment that from June 2020 to June 2023. The experiment included five treatments, each with five replications: OO (oat-oat), MO (maize-oat), PO (potato-oat), BO (buckwheat-oat), and CO (cabbage-oat). Results showed that crop-oat rotation significantly affected oat yield, soil chemical properties, and microbial communities. The highest oat yield was obtained from the MO and BO treatments. Compared to the OO treatment, the BO treatment had the greatest impact on soil properties and bacterial α-diversity, while fungal α-diversity was highest in the MO and CO treatments. Crop rotation also shifted the soil microbial community structure, the dominant bacterial phyla were Actinobacteriota, Proteobacteria, Chloroflexi, and Acidobacteria, while the dominant fungal phyla were Ascomycota, Basidiomycota, and Mortierellomycota. Principal coordinate analysis (PCoA) showed significant differences in both bacterial and fungal communities between the five treatments. Redundancy analysis (RDA) indicated that soil total nitrogen (TN) and pH were the most important factors shaping the bacterial and fungal communities in oat soil, respectively. The Structural Equation Modeling analysis (SEM) revealed that crop-oat rotation affected the fungal community through its impact on soil organic carbon (SOC), thereby influenced the oat yield. Our findings suggest that buckwheat-oat rotation may be the most suitable crop rotation pattern for enhancing soil quality and oat yield in southwest China, maize-oat is not recommended due to its damage to soil nutrients and microbial communities.

Ecosystems in arid regions are facing increasing anthropogenic and environmental pressures, raising global concern about their sustainable development. Landscape ecological risk (LER) and ecological carrying capacity (ECC) are essential assessment frameworks for optimizing resource allocation and ensuring ecological security. In this study, the spatial and temporal evolution characteristics of LER and ECC in the Tianshan Mountains, a typical arid zone in Central Asia, was systematically assessed between 2000 and 2020. The PLUS model was employed to project ecological zoning patterns for 2030 and 2040, while XGBoost-SHAP was used to quantify the influence of 16 driving factors. LER was dominated by low to moderate-low risk zones (89%), while moderate-high to high risk zones rose from 0.43% to 2.82%. ECC showed a central-high and peripheral-low pattern, with zones of moderately high and high carrying capacity covering 48% of the area and increasing by 2.56%. Grasslands remained the dominant land type (48%) and expanded by 12,054.94 km 2. Cropland (39.99%) and construction land (105.85%) also increased. In contrast, water and unused land declined significantly. Ecological conservation zones remained dominant, the cultivation zone expanded sharply (+452.77%), and the restoration zone contracted (−70.84%). Projections suggest continued dominance of the conservation zone, while the restoration zone may experience strong fluctuations. Land use, temperature, precipitation, GDP, and population density were identified as key drivers of LER and ECC， with different effects in the four zones. These findings can be used to augment conservation management strategies in semi-arid grasslands.

Intensive production is sought by farmers but may harm sustainability, depending on management practices. No-Tillage System (NTS) is a conservation system and a paradigm in grain production in Brazil, but the quality of adoption is under question whilst water erosion regained strength, an underestimated issue among farmers. This study evaluated concentrations and losses of nitrogen (N) and phosphorus (P) fractions in streamwater of a rural watershed under NTS without terraces. Water was sampled daily, from December 2022 to November 2023, and losses were associated with monetary costs to replenish nutrients. Particulate forms predominated for N and P. Soluble N-NO 3 - prevailed over N-NH 4 +, but concentrations of both remained below critical environmental limit (CEL) for Brazil, while total P frequently exceeded CEL. Concentrations of N and P oscillated seasonally. The highest N losses were in October and November, and P losses peaked in August, October, and November, associated with heavy rainfall and/or low vegetative cover. Annual losses of 30.80 kg N ha -1 and 4.91 kg P ha -1 generated monetary losses of US$ 22.58 ha -1 and US$ 4.85 ha -1, respectively. The predominance of particulate N and P and the excess of total P in streamwater proved that NTS had limited effectiveness to control surface runoff without complementary practices. P losses represented eutrophication risk and, along with N losses, caused monetary impact at watershed scale, which may help enlighten farmers on the need for additional conservation practices, such as infiltration terraces and cover crops during fallow periods.

Hydrosedimentological connectivity refers to the transfer of water and sediment between landscape compartments, originating from any possible source and reaching a specific control point within a system where water serves as the transport vector. Assessing connectivity is a crucial step in comprehending the system’s behavior, enabling the prediction of its response to precipitation events and land-use changes that may arise within the catchment. Changes in land use within a catchment have a significant effect on connectivity, thereby affecting water and sediment dynamics. In this study, an analysis was conducted to examine the influence of human-induced land use changes on hydrosedimentological connectivity in a small catchment located in Campos de Cima da Serra, Rio Grande do Sul. The IHC (Index of Hydrosedimentological Connectivity) was applied to five precipitation events with varying hydrological characteristics, including rainfall magnitude, available sediments, and antecedent soil moisture. Four different scenarios were considered, maintaining the land use classes of the region but modifying their coverage. The analysis of these scenarios revealed the influence of land use on the catchment, leading to variations in the pattern of hydrosedimentological connectivity. The highest IHC values were observed in areas characterized by exposed soil (agricultural preparation) and agricultural activities. Conversely, the lowest connectivity points in the catchment were found in regions with native forest and Pinnus forest. These areas possess a significant potential for sediment retention due to the presence of plant litter. Additionally, the analysis of different precipitation events demonstrated that antecedent events and soil moisture conditions play a crucial role in estimating the hydrosedimentological connectivity of the catchment. These factors were shown to be determinants in understanding how connectivity varies over time. The findings highlight the influence of different land use scenarios on connectivity patterns and provide insights into the potential for sediment retention in specific landscape elements. Additionally, the study demonstrates the significance of considering antecedent events and soil moisture conditions when evaluating hydrosedimentological connectivity within a catchment.