Publications by authors named "Pasquale Borrelli"

Effective implementation of Sustainable Land Management (SLM) remains a major challenge worldwide because of its weak integration within the domains of science, policy, and development practice. Based on global analyses of soil erosion risk and the degree of implementation of SLM research, policies, and practices at the country level, we propose a transdisciplinary framework to address soil erosion through SLM. In the analysis, we used indices of the policy-development, science-policy, and science-development interfaces to evaluate the overall science-policy-development interface (SPDI) in 236 countries.

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After the successful mapping of gully erosion channels in the 2018 Eurostat Land Use/Cover Area Frame (topsoil) statistical survey (LUCAS, n = 24,759 locations), the methodology was further expanded across the full LUCAS 2022 survey (n = 399,591 locations). This expert-based assessment identifies the presence or absence of gully erosion forms at each LUCAS location. Its goal is to improve understanding of gully erosion geography in the EU and develop forecasting methods to support soil health indicators proposed by the new Directive on Soil Monitoring and Resilience (COM(2023)416) and Common Agricultural Policy monitoring.

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Introduction: Whether Alzheimer's disease pathology involves white matter pathways connecting the locus coeruleus (LC) to the entorhinal cortex (EC) is unclear. In this cross-sectional observational study, we investigated the microstructural integrity of the LC-EC pathway in relation to amyloid, tau, and neurodegeneration (ATN) biomarkers along the cognitive spectrum from normal cognition to dementia.

Methods: One hundred twenty-four participants underwent clinical assessment, diffusion-weighted imaging, structural magnetic resonance imaging (N), amyloid (A), and tau (T) positron emission tomography.

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Numerous hydrological applications, such as soil erosion estimation, water resource management, and rain driven damage assessment, demand accurate and reliable rainfall erosivity data. However, the scarcity of gauge rainfall records and the inherent uncertainty in satellite and reanalysis-based rainfall datasets limit rainfall erosivity assessment globally. Here, we present a new global rainfall erosivity dataset (0.

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Article Synopsis
  • - This research presents a new method using deep learning and active learning to create accurate global maps of land susceptibility to wind erosion, employing models like RNN and GRU alongside various interpretation techniques.
  • - Thirteen environmental factors were analyzed, and through optimization, eight significant factors (such as wind speed and soil moisture) were selected to predict wind erosion risk.
  • - The findings show that the GRU-AL model was the most effective, categorizing global land into different levels of susceptibility, with significant insights into how factors like soil carbon and precipitation interact with erosion risk predictions.
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Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Public access to the training methodology for these solutions remains absent.

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Land degradation is a complex socio-environmental threat, which generally occurs as multiple concurrent pathways that remain largely unexplored in Europe. Here we present an unprecedented analysis of land multi-degradation in 40 continental countries, using twelve dataset-based processes that were modelled as land degradation convergence and combination pathways in Europe's agricultural (and arable) environments. Using a Land Multi-degradation Index, we find that up to 27%, 35% and 22% of continental agricultural (~2 million km) and arable (~1.

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Modeling monthly rainfall erosivity is vital to the optimization of measures to control soil erosion. Rain gauge data combined with satellite observations can aid in enhancing rainfall erosivity estimations. Here, we presented a framework which utilized Geographically Weighted Regression approach to model global monthly rainfall erosivity.

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Deforestation reduces the capacity of the terrestrial biosphere to take up toxic pollutant mercury (Hg) and enhances the release of secondary Hg from soils. The consequences of deforestation for Hg cycling are not currently considered by anthropogenic emission inventories or specifically addressed under the global Minamata Convention on Mercury. Using global Hg modeling constrained by field observations, we estimate that net Hg fluxes to the atmosphere due to deforestation are 217 Mg year (95% confidence interval (CI): 134-1650 Mg year) for 2015, approximately 10% of global primary anthropogenic emissions.

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Article Synopsis
  • New EU policies post-2020 focus on soil conservation, influenced by the CAP 2023-2027, a proposed Soil Monitoring Law, and the 'A Soil Deal for Europe' mission.
  • Over 330 participants from 63 countries attended a 2022 EU Soil Observatory workshop on soil erosion, discussing key topics such as management practices and nutrient cycles.
  • The follow-up resulted in 15 manuscripts, with 9 selected for publication, highlighting challenges in soil erosion research amid the EU Green Deal's aims.
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Future phosphorus (P) shortages could seriously affect terrestrial productivity and food security. We investigated the changes in topsoil available P (AP) and total P (TP) in China's forests, grasslands, paddy fields, and upland croplands during the 1980s-2010s based on substantial repeated soil P measurements (63,220 samples in the 1980s, 2000s, and 2010s) and machine learning techniques. Between the 1980s and 2010s, total soil AP stock increased with a small but significant rate of 0.

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Numerous drivers such as farming practices, erosion, land-use change, and soil biogeochemical background, determine the global spatial distribution of phosphorus (P) in agricultural soils. Here, we revised an approach published earlier (called here GPASOIL-v0), in which several global datasets describing these drivers were combined with a process model for soil P dynamics to reconstruct the past and current distribution of P in cropland and grassland soils. The objective of the present update, called GPASOIL-v1, is to incorporate recent advances in process understanding about soil inorganic P dynamics, in datasets to describe the different drivers, and in regional soil P measurements for benchmarking.

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USLE-type models are widely used to estimate average annual soil loss at large scales, with the erodibility factor (K) being the sole component that accounts for soil's susceptibility to erosion. The factor includes the information on permeability in the equation, however, most definitions of the K factor consider the soil hydrological influence only very crudely and indirectly. Thus, the direct impact of surface runoff infiltration and drainage on soil erosion is largely neglected.

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Article Synopsis
  • - The Global Rainfall Erosivity Database (GloREDa) is a first-of-its-kind open-access platform that provides rainfall erosivity values from nearly 4000 global stations, gathered through collaboration among researchers and organizations from 65 countries.
  • - The database includes hourly and sub-hourly rainfall records, offers annual and mean monthly erosivity data for most stations, and is hosted in the European Soil Data Centre (ESDAC) for long-term accessibility and future data enhancements.
  • - Using machine learning techniques, researchers have generated predicted global monthly erosivity datasets at a 1 km resolution, which can aid in modeling soil erosion, sediment distribution, climate impacts, and natural disaster assessments.
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As a network of researchers we release an open-access database (EUSEDcollab) of water discharge and suspended sediment yield time series records collected in small to medium sized catchments in Europe. EUSEDcollab is compiled to overcome the scarcity of open-access data at relevant spatial scales for studies on runoff, soil loss by water erosion and sediment delivery. Multi-source measurement data from numerous researchers and institutions were harmonised into a common time series and metadata structure.

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Purpose: The use of topological metrics to derive quantitative descriptors from structural connectomes is receiving increasing attention but deserves specific studies to investigate their reproducibility and variability in the clinical context. This work exploits the harmonization of diffusion-weighted acquisition for neuroimaging data performed by the Italian Neuroscience and Neurorehabilitation Network initiative to obtain normative values of topological metrics and to investigate their reproducibility and variability across centers.

Methods: Different topological metrics, at global and local level, were calculated on multishell diffusion-weighted data acquired at high-field (e.

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Land conservation and increased carbon uptake on land are fundamental to achieving the ambitious targets of the climate and biodiversity conventions. Yet, it remains largely unknown how such ambitions, along with an increasing demand for agricultural products, could drive landscape-scale changes and affect other key regulating nature's contributions to people (NCP) that sustain land productivity outside conservation priority areas. By using an integrated, globally consistent modelling approach, we show that ambitious carbon-focused land restoration action and the enlargement of protected areas alone may be insufficient to reverse negative trends in landscape heterogeneity, pollination supply, and soil loss.

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Climate change can affect all levels of society and the planet. Recent studies have shown its effects on sediment fluxes in several locations worldwide, which can impact ecosystems and infrastructure such as reservoirs. In this study, we focused on simulating sediment fluxes using projections of future climate change for South America (SA), a continent with a high sediment transport rate to the oceans.

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As agricultural land area increases to feed an expanding global population, soil erosion will likely accelerate, generating unsustainable losses of soil and nutrients. This is critical for Kenya where cropland expansion and nutrient loading from runoff and erosion is contributing to eutrophication of freshwater ecosystems and desertification. We used the Revised Universal Soil Loss Equation (RUSLE) to predict soil erosion rates under present land cover and potential natural vegetation nationally across Kenya.

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Global efforts to deliver internationally agreed goals to reduce carbon emissions, halt biodiversity loss, and retain essential ecosystem services have been poorly integrated. These goals rely in part on preserving natural (e.g.

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Sustainable land management (SLM) is widely recognized as the key to reducing rates of land degradation, and preventing desertification. Many efforts have been made worldwide by various stakeholders to adopt and/or develop various SLM practices. Nevertheless, a comprehensive review on the spatial distribution, prospects, and challenges of SLM practices and research is lacking.

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Chemical contamination from point source discharges in developed (resource-rich) countries has been widely regulated and studied for decades; however, diffuse sources are largely unregulated and widespread. In the European Union (EU), large dischargers report releases of some chemicals, yet little is known of total emissions (point and diffuse) and their relative significance. We estimated copper loadings from all significant sources including industry, sewage treatment plants, surface runoff (from traffic, architecture, and atmospheric deposition), septic tanks, agriculture, mariculture, marine transport (antifoulant leaching), and natural processes.

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Despite phosphorus (P) being crucial for plant nutrition and thus food security, excessive P fertilization harms soil and aquatic ecosystems. Accordingly, the European Green Deal and derived strategies aim to reduce P losses and fertilizer consumption in agricultural soils. The objective of this study is to calculate a soil P budget, allowing the quantification of the P surpluses/deficits in the European Union (EU) and the UK, considering the major inputs (inorganic fertilizers, manure, atmospheric deposition, and chemical weathering) and outputs (crop production, plant residues removal, losses by erosion) for the period 2011-2019.

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Background: Advances in climate change research contribute to improved forecasts of hydrological extremes with potentially severe impacts on human societies and natural landscapes. Rainfall erosivity density (RED), i.e.

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Healthy soil is the foundation underpinning global agriculture and food security. Soil erosion is currently the most serious threat to soil health, leading to yield decline, ecosystem degradation and economic impacts. Here, we provide high-resolution (ca.

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