Diego Soto-Gómez

Accurate correction of daily satellite-derived precipitation estimates in data-scarce tropical regions remains a critical challenge for climate monitoring, agriculture, and public health. Satellite products such as CHIRPS offer broad spatial coverage but exhibit systematic biases relative to ground-based observations particularly in complex terrain under bimodal tropical regimes influenced by ENSO. We propose a Functional Generalised Additive Mixed Model (FGAMM) that corrects CHIRPS-derived precipitation estimates by treating the annual accumulated precipitation curve as a functional response and the satellite accumulation curve as a functional covariate, while incorporating station-level random effects and the Southern Oscillation Index. This functional formulation targets the systematic, slowly varying bias between satellite and ground-station accumulation, the quantity most relevant for water-balance applications such as reservoir management and agricultural planning rather than day-to-day storm nowcasting. Applied to 62 IDEAM stations in the Valle del Cauca department of Colombia (2012–2020), the FGAMM achieves a mean cross-validation RMSE of 0.68 mm/day (95% bootstrap CI: 0.61–0.75), a substantially lower error than linear regression, SVM, and Random Forest within this dataset, where the gap is statistically significant across all competing methods. This magnitude of advantage is not reproduced when applying the same fitting-and-differencing pipeline, via a simplified concurrent approximation, to an independent national-network dataset; we discuss the methodological factors that likely contribute to this discrepancy—including an inherent smoothness asymmetry between the penalised-spline FGAMM fit and the unconstrained benchmark models, and differences in validation design between the two checks—in the Discussion, and treat the true size of the FGAMM’s advantage as an open question pending a fully controlled comparison. Corrected estimates are currently restricted to the calibrated station locations; because CHIRPS provides near-global daily coverage from 1981 to the present, we discuss how the same modelling approach could in principle be applied to other tropical or subtropical regions with a sparse reference station network, including areas of Latin America, sub-Saharan Africa, and South Asia where station density is similarly limited.

Persistent organochlorine pesticides such as hexachlorocyclohexane (HCH) persist in European soils decades after their ban, impacting human health, soil quality, and microbial communities. We compared bacterial community composition (16S rDNA metabarcoding) and mineralogical profiles across three contaminated sites: Sabiñánigo (Spain), Bitterfeld (Germany), and Colleferro (Italy), including flood–dry cycle samples from Spain. Heatmap and correlation analyses revealed strong associations between specific taxa and physicochemical and mineralogical parameters, including exchangeable Na+, Mg2+, and silicate matrices, indicating ecological selection by soil properties. Spanish soils, especially under flood–dry cycles, were dominated by Sphingobium and Comamonadaceae, suggesting enhanced HCH mobility and potential degradation under fluctuating hydrological conditions. Italian soils were enriched in Thiobacillus and Geothrix, reflecting coupling between microbial activity and iron redox processes. German soils showed high microbial evenness, with Acidothermus and Conexibacter correlated with higher cation exchange capacity, indicating the influence of intrinsic soil properties on community structure. Although HCH is neutral, its bioavailability is likely controlled by interactions with organic matter and mineral surfaces rather than CEC alone. Integrated tripartite networks linking minerals, bacteria, and enzymes revealed site-specific structures: German soils showed highest modularity, Italian soils highest connectivity and multifunctionality, and Spanish soils strong compartmentalization between mineral, microbial, and enzymatic modules. Betweenness centrality identified key integrative enzymes, suggesting that mineral–microbe associations can be decoupled from enzymatic networks. Overall, mineralogical composition acts as the dominant ecological filter shaping microbial assembly and functional organization in contaminated soils.

Accurate daily precipitation prediction in data-scarce tropical regions remains a critical challenge for climate monitoring, agriculture, and public health. Satellite products such as CHIRPS offer broad spatial coverage but exhibit systematic biases relative to ground-based observations—particularly in complex terrain under bimodal tropical regimes influenced by ENSO. We propose a Functional Generalized Additive Mixed Model (FGAMM) that corrects CHIRPS-derived precipitation estimates by treating the annual accumulated precipitation curve as a functional response and the satellite accumulation curve as a functional covariate, while incorporating station-level random effects and the Southern Oscillation Index. Applied to 62 IDEAM stations in the Valle del Cauca department of Colombia (2012–2020), the FGAMM achieves a mean cross-validation RMSE of 0.68 mm/day (95% bootstrap CI: 0.61–0.75), outperforming linear regression, SVM, and Random Forest by a factor of more than four; the performance gap is statistically significant across all competing methods. Because CHIRPS provides near-global daily coverage from 1981 to the present, the methodology is directly transferable to any tropical or subtropical region with a sparse reference station network, including areas of Latin America, sub-Saharan Africa, and South Asia where station density is similarly limited.

InBestSoil (IBS) project has been funded under the call "Incentives and business models for soil health" from the EU Missions program (Horizon Europe) — Grant Agreement n° 1010910990. The University of Vigo leads the project within a consortium of 19 partners from 10 countries with a 48-month duration.The IBS aims to quantify the economic benefits of the different ecosystem services that healthy soils can provide and analyze the costs and benefits of the interventions to improve soil health. This economic valuation will facilitate investments in soil health and the generation of new businesses, incentives, and policies that help us to reclaim degraded soils or improve the quality of existing ones.In IBS, we analyzed nine case studies across Europe with different land uses (agricultural, forestry, urban, and mining) across four different biogeographic regions (Boreal, Continental, Atlantic and Mediterranean). These long-term experiments have been running for years into an established network of stakeholders and businesses created to exploit improved soil quality benefits. In each case study, we will assess the outcome of soil reclamation actions by examining the actual soil quality indicators and comparing them with the antecedent indicators before the restoration process. Then, we will conduct an economic valuation of the soil quality differences by considering the potential income from the enhanced ecosystem services that have proved effective in improving soil quality indicators.To develop a multi-actor approach, we will gather data and opinions from stakeholders about every relevant item in this transformation, i.e., from selecting soil indicators to creating new incentives and policies. These consultations will be done at each step of the project through a collaborative platform developed specifically for the IBS. The IBS partners come from a wide range of sectors (from universities to distribution companies of organic products), allowing us to create an extensive network of stakeholders to share information, feedback experiences, and diffusion of results.With this information, we will first try to scale up by exporting to other areas the business models that were created around our case studies. Second, we will use the information obtained through the economic valuation to develop new business models. Finally, we will try to integrate the information obtained to develop a set of incentive support systems and new policies. Acknowledgments: This study has been funded by the Horizon Europe Project InBestSoil (GA 101091099).

The assessment of remediation on metal-polluted soils is usually focused on total and/or bioavailable metal content. However, these chemical variables do not provide direct information about reductions in heavy metals pressure on soil microorganisms. We propose the use of bacterial communities to evaluate the efficiency of three remediation techniques: crushed mussel shell (CMS) and pine bark (PB) as soil amendments and EDTA-washing. A soil sample was polluted with different doses of Cu, Ni, and Zn (separately). After 30 days of incubation, the remediation techniques were applied, and bacterial community tolerance to heavy metals determined. If bacterial communities develop tolerance, it is an indicator that the metal is exerting toxicity on them. Soil bacterial communities developed tolerance to Cu, Ni, and Zn in response to metal additions. After remediation, bacterial communities showed decreases in bacterial community tolerance to Cu, Ni, and Zn for all remediation techniques. For Cu and Ni, soil EDTA-washing showed the greatest reduction of bacterial community tolerance to Cu and Ni, respectively, while for Zn the soil amendment with PB was the most effective remediation technique. Thus, bacterial community tolerance to heavy metals successfully detect differences in the effectiveness of the three remediation techniques.

The use of tree monoculture systems in Mediterranean areas can accentuate problems already existing in the area, resulting from lack of moisture, low levels of organic matter and high temperatures. In these crops, the soil in the alleys remains bare practically all year, so that in addition to the above limitations, there is an increase in erosion owing to direct exposure to meteorological agents. Owing to climate change, all these disadvantages may be aggravated over time. To improve soil conditions in orchard alleys, various techniques such as mulching, reduced tillage, cover crops or alley cropping can be used. These techniques aim to reduce erosion, improve soil structure and water conditions, and increase the amount of organic matter while slowing down soil mineralization. Alley cropping can also provide complementary commodities for farmers, with important economic benefits. Thus, the objective of this study was to assess if two different crop diversifications applied in mandarin alleys from the Mediterranean region can enhance soil fertility after three crop cycles. For this, three different treatments were applied: i) a mandarin monoculture with bare alley soil all year (MM); ii) a multiple cropping of vetch/barley and then fava bean (AC1) repeated every year in the alleys; and iii) a rotation of fava bean, purslane and cowpea (AC2). Three soil samplings were carried out in February 2019, 2020 and 2021 at 0-10 cm and 10-30 cm depth. Samples were characterized for properties related to fertility: total nitrogen, exchangeable NH4+, NO3-, cation exchange capacity (CEC), exchangeable Ca, Mg and K, soluble B, and available P, Cu, Zn, Fe and Mn. Results showed that in AC1, a significant increase in CEC and exchangeable Ca was observed, while NO3- and B slightly decreased. In AC2, there was a decrease in NH4+ and NO3- concentrations, with significant increases in B and P. In addition, in AC1 and AC2, there was an increase trend in total nitrogen. With regard to bioavailable metals, their behavior was similar in all treatments, with a general decrease along time; only the amount of bioavailable Zn increased. Regarding mandarin yield, there was a slight decrease with crop diversification. However, in 2021, a low mandarin yield was recorded in all treatments caused by Alternaria spp. In AC1, this decrease was partly compensated by the alley crops, corresponding to 26% of the overall land production. In AC2, cowpea production was lower < 2% of land production, so it did not compensate for the losses caused by Alternaria spp. It can be concluded that the AC1 diversification works better than AC2, as it helps to improve soil CEC and increases overall land production, reducing the dependence on a single crop in case of perturbations, such as pests/diseases.Acknowledgements: This study has been funded by H2020 project Diverfarming (GA 728003).