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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 km2) and arable (~1.1 million km2) lands are currently threatened by one, two, and three drivers of degradation, while 10–11% of pan-European agricultural/arable landscapes are cumulatively affected by four and at least five concurrent processes. We also explore the complex pattern of spatially interacting processes, emphasizing the major combinations of land degradation pathways across continental and national boundaries. Our results will enable policymakers to develop knowledge-based strategies for land degradation mitigation and other critical European sustainable development goals..

A unifying modelling of multiple land degradation pathways in Europe | Nature Communications

Soil health is expected to be of key importance for plant growth and ecosystem functioning. However, whether soil health is linked to primary productivity across environmental gradients and land-use types remains poorly understood. To address this gap, we conducted a pan-European field study including 588 sites from 27 countries to investigate the link between soil health and primary productivity across three major land-use types: woodlands, grasslands and croplands. We found that mean soil health (a composite index based on soil properties, biodiversity and plant disease control) in woodlands was 31.4% higher than in grasslands and 76.1% higher than in croplands. Soil health was positively linked to cropland and grassland productivity at the continental scale, whereas climate best explained woodland productivity. Among microbial diversity indicators, we observed a positive association between the richness of Acidobacteria, Firmicutes and Proteobacteria and primary productivity. Among microbial functional groups, we found that primary productivity in croplands and grasslands was positively related to nitrogen-fixing bacteria and mycorrhizal fungi and negatively related to plant pathogens. Together, our results point to the importance of soil biodiversity and soil health for maintaining primary productivity across contrasting land-use types.

Soil health is associated with higher primary productivity across Europe | Nature Ecology & Evolution

Fire-induced geomorphic changes, such as enhanced erosion and debris-flow activity, are expected to increase with climate change owing to increases in fire activity and rainfall intensification. In this Review, we summarize how landscape attributes, rainfall and burn severity influence post-fire geomorphic responses over a range of temporal and spatial scales. Sub-hourly rainfall intensity and burn severity control the magnitude of many post-fire geomorphic process rates through their influence on ground cover and rainfall-runoff partitioning. Post-fire debris flows (PFDFs) make a substantial contribution to the post-fire sediment cascade, transporting sediment from hillslopes to channels, adjacent floodplains and alluvial fans. By the late twenty-first century, PFDF activity is estimated to increase in 68% of areas in which PFDFs have occurred in the past and decrease in only 2% of locations. Once altered by fire, geomorphic state variables — such as infiltration capacity, canopy cover, ground cover and sediment availability — can recover to their pre-fire value or be shifted to a new value. Improved understanding of the factors that influence these post-fire trajectories could support targeted management and intervention strategies. Additionally, monitoring that extends beyond the first 1–3 years after fire and deeper integration of ecohydrological processes into geomorphic models are needed to improve forecasts of post-fire geomorphic responses.

Fire effects on geomorphic processes | Nature Reviews Earth & Environment

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 (0.1° × 0.1° spatial resolution) integrating satellite (CMORPH and IMERG) and reanalysis (ERA5-Land) derived rainfall erosivity estimates with gauge rainfall erosivity observations collected from approximately 6,200 locations across the globe. We used a machine learning-based Gaussian Process Regression (GPR) model to assimilate multi-source rainfall erosivity estimates alongside geoclimatic covariates to prepare a unified high-resolution mean annual rainfall erosivity product. It has been shown that the proposed rainfall erosivity product performs well during cross-validation with gauge records and inter-comparison with the existing global rainfall erosivity datasets. Furthermore, this dataset offers a new global rainfall erosivity perspective, addressing the limitations of existing datasets and facilitating large-scale hydrological modelling and soil erosion assessments.

GloRESatE: A dataset for global rainfall erosivity derived from multi-source data | Scientific Data

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. The framework integrates long-term (2001–2020) mean annual rainfall erosivity estimates from IMERG (Global Precipitation Measurement (GPM) mission’s Integrated Multi-satellitE Retrievals for GPM) with station data from GloREDa (Global Rainfall Erosivity Database, n = 3,286 stations). The merged mean annual rainfall erosivity was disaggregated into mean monthly values based on monthly rainfall erosivity fractions derived from the original IMERG data. Global mean monthly rainfall erosivity was distinctly seasonal; erosivity peaked at ~ 200 MJ mm ha−1 h−1 month−1 in June–August over the Northern Hemisphere and ~ 700 MJ mm ha−1 h−1 month−1 in December–February over the Southern Hemisphere, contributing to over 60% of the annual rainfall erosivity over large areas in each hemisphere. Rainfall erosivity was ~ 4 times higher during the most erosive months than the least erosive months (December–February and June–August in the Northern and Southern Hemisphere, respectively). The latitudinal distributions of monthly and seasonal rainfall erosivity were highly heterogeneous, with the tropics showing the greatest erosivity. The intra-annual variability of monthly rainfall erosivity was particularly high within 10–30° latitude in both hemispheres. The monthly rainfall erosivity maps can be used for improving spatiotemporal modeling of soil erosion and planning of soil conservation measures.

An integrated modeling approach for estimating monthly global rainfall erosivity | Scientific Reports

Increasing soil organic carbon (SOC) confers benefits to soil health, biodiversity, underpins carbon sequestration and ameliorates land degradation. One recommendation is to increase SOC such that the SOC to clay ratio (SOC/clay) exceeds 1/13, yet normalising SOC levels based on clay alone gives misleading indications of soil structure and the potential to store additional carbon. Building on work by Poeplau & Don (2023) to benchmark observed against predicted SOC, we advance an alternative indicator: the ratio between observed and “typical” SOC (O/T SOC) for pan-European application. Here, “typical” SOC is the average concentration in different pedo-climate zones, PCZs (which, unlike existing SOC indicators, incorporate land cover and climate, alongside soil texture) across Europe, determined from mineral (<20 % organic matter) topsoils (0–20 cm) sampled during 2009–2018 in LUCAS, Europe's largest soil monitoring scheme (n = 19,855). Regression tree modelling derived 12 PCZs, with typical SOC values ranging 5.99–39.65 g kg−1. New index classes for comparison with SOC/clay grades were established from the quartiles of each PCZ's O/T SOC distribution; these were termed: “Low” (below the 25th percentile), “Intermediate” (between the 25th and 50th percentiles), “High” (between the 50th and 75th percentiles), and “Very high” (above the 75th percentile). Compared with SOC/clay, O/T SOC was less sensitive to clay content, land cover, and climate, less geographically skewed, and better reflected differences in soil porosity and SOC stock, supporting 2 EU Soil Health Mission objectives (consolidating SOC stocks; improving soil structure for crops and biota). These patterns held for 2 independent datasets, and O/T SOC grades were sensitive enough to reflect land management differences across several long-term field experiments. O/T SOC used in conjunction with several other physical, chemical and biological soil health indicators can help support the EU Soil Monitoring Law and achieve several United Nations Sustainable Development Goals.

Benchmarking soil organic carbon (SOC) concentration provides more robust soil health assessment than the SOC/clay ratio at European scale - ScienceDirect

The present European Union (EU) Sewage Sludge Directive (86/278/EEC) is undergoing modifications aimed at enhancing its applicability in the agricultural sector. The Directive's existing limit values for heavy metal concentrations in soils are in the process of being revised. However, to comprehensively understand their effects on EU agricultural lands, additional evaluations are necessary. This is particularly important given that ecological risk assessments are often performed on a site-specific basis, potentially overlooking broader regional implications. The main objective of the current work is to introduce a methodological approach to quantify the impact of sewage sludge (SS) application on agricultural soils in the EU and the United Kingdom. Concentrations of heavy metals (HMs) (Cd, Cu, Hg, Ni, Pb and Zn) in agricultural land from Land Use/Land Cover Area Frame Survey (LUCAS) 2009 topsoil database were used as a baseline. Maximum quantities of SS that can be safely applied to agricultural lands were obtained by a modeling procedure was used to determine the maximum safe quantities of SS that can be applied to agricultural lands for each country within the European Member States and the United Kingdom. Accumulation of HMs in soils was modelled by using a representative SS composition, distributed over 10 successive years at 5 Mg ha−1 year−1 rate. Ecological risk impact was assessed by using both the single ecological risk index (Er) and the integrated potential ecological risk index (RI). Maximum quantities of SS applied on agricultural soils in EU + UK were estimated to be 45 Mg ha−1 at the country level. We found that 19% of agricultural land (around 28,471,900 ha) in the EU + UK shows a higher RI than moderate risk after long time application of the representative SS. We show that the combination of the HM concentrations from the LUCAS topsoil survey and assumptions on the SS composition and soil HM partitioning can be used to define the actual and potential soil pollution rate in EU + UK. We demonstrate that the proposed methodology can be used by policymakers, farmers, regional authorities and other stakeholders, with possible adaptions based on local in-depth soil and SS knowledge.

Ecological risk assessment of heavy metals from application of sewage sludge on agricultural soils in Europe - Yunta - 2024 - European Journal of Soil Science - Wiley Online Library

Soil protists have vital roles as major microbiome predators in soil functioning and plant performance. Protists are also suggested to be the most responsive microbial group to external changes, such as anthropogenic land use types. While protists were long used as models for biogeography such as to investigate if ‘everything is everywhere’ among microbes, their biogeography at the taxonomic level has never been explored in depth at the continental scale and linked to anthropogenic drivers. Here we evaluated how land-use types affect the diversity and structure of soil protist communities across 885 locations in Europe based on the European Commission's Land Use and Coverage Area frame Survey (LUCAS). We observed higher α-diversity of soil protists but lower community structure dissimilarity (β-diversity) in croplands compared with woodlands, with grasslands in an intermediate position. The diversity of protist groups with a broader spatial niche was higher in croplands, whereas taxa with a narrower niche increased in woodlands. The importance of climate factors on α-diversity variations reduced as land use intensity increased, but the opposite trend was observed for the effect of soil properties. Our study suggests that there is an interaction between land use type, environmental effects, and spatial niche attributes of soil protist groups, highlighting the importance of land-use type on the dynamics of protist communities.

https://www.sciencedirect.com/science/article/pii/S0038071724001482

Soil microbial biomass and activity strongly depend on land use, vegetation cover, climate, and soil physicochemical properties. In most cases, this dependence was assessed by one-to-one correlations while by employing network analysis, information about network robustness and the balance between stochasticity and determinism controlling connectivity, was revealed. In this study, we further elaborated on the hypothesis of Smith et al. (2021) that cropland soils depended more on climate variables and therefore are more vulnerable to climate change. We used the same dataset with that of Smith et al. (2021) that contains seasonal microbial, climate and soil variables collected from 881 soil points representing the main land uses in Europe: forests, grassland, cropland. We examined complete (both direct and indirect relationships) and incomplete networks (only direct relationships) and recorded higher robustness in the former. Partial Least Square results showed that on average more than 45% of microbial attributes' variability was predicted by climate and habitat drivers denoting medium to strong effect of habitat filtering. Network architecture slightly affected by season or land use type; it followed the core/periphery structure with positive and negative interactions and no hub nodes. Microbial attributes (biomass, activity and their ratio) mostly belong to core block together with Soil Organic Carbon (SOC), while climate and soil variables to periphery block with the exception of cropland networks, denoting the higher dependence between microbial and climate variables in these latter. All complete networks appeared robust except for cropland and forest in summer, a finding that disagrees with our initial hypothesis about cropland. Networks' connectivity was controlled stronger by stochasticity in forest than in croplands. The lack of human interventions in forest soils increase habitat homogeneity enhancing the influence of stochastic agents such as microbial unlimited dispersal and/or stochastic extinction. The increased stochasticity implies the necessity for proactive management actions.

Connections between soil microbes, land use and European climate: Insights for management practices - ScienceDirect

Soil loss by water erosion represents a key threat to land degradation worldwide. This study employs an integrated quantitative modelling approach to estimate the long-term global sustainability impacts of soil erosion. The global biophysical model estimates a mean increase of soil erosion rates of between 30-66% over the period 2015-2070 under alternative climate-economic scenarios, assuming different greenhouse gas concentration trajectories. In a subsequent step, projected soil erosion rates are converted into land productivity losses and inputted into an economic global simulation model to identify those regional hotspots where the greatest market tensions are expected to occur.The headline result is that soil erosion presents a major challenge to food security in vulnerable regions (Africa and some tropical regions). Indeed, for certain crops (particularly oilseeds) the threat of shortages is potentially significant. Secondly, exploring different long-term socioeconomic-environmental pathways quantitatively confirms the merits of sustainable management practises in coping with anticipated market and environmental stresses arising from soil erosion. Finally, free (and fair) trade is essential to allow less affected regions to expand (marginally) their production, thereby cushioning the market tensions that are expected to occur in more acutely affected areas of the world.

Remaining Loyal to Our Soil: A Prospective Integrated Assessment of Soil Erosion on Global Food Security by Martina Sartori, Emanuele Ferrari, Robert M'Barek, G. Philippidis, Kirsten Boysen-Urban, Pasquale Borrelli, Luca Montanarella, Panos Panagos :: SSRN

The use of cover crops (CCs) is a promising cropland management practice with multiple benefits, notably in reducing soil erosion and increasing soil organic carbon (SOC) storage. However, the current ability to represent these factors in land surface models remains limited to small scales or simplified and lumped approaches due to the lack of a sediment-carbon erosion displacement scheme. This precludes a thorough understanding of the consequences of introducing a CC into agricultural systems. In this work, this problem was addressed in two steps with the spatially distributed CE-DYNAM model.First, the historical effect of soil erosion, transport, and deposition on the soil carbon budget at a continental scale in Europe was characterized since the early industrial era, using reconstructed climate and land use forcings. Then, the impact of two distinct policy-oriented scenarios for the introduction of CCs were evaluated, covering the European cropping systems where surface erosion rates or nitrate susceptibility are critical. The evaluation focused on the increase in SOC storage and the export of particulate organic carbon (POC) to the oceans, compiling a continental-scale carbon budget. The results indicated that Europe exported 1.95 TgC/year of POC to the oceans in the last decade, and that CCs can contribute to reducing this amount while increasing SOC storage. Compared to the simulation without CCs, the additional rate of SOC storage induced by CCs peaked after 10 years of their adoption, followed by a decrease, and the cumulative POC export reduction stabilized after around 13 years. The findings indicate that the impacts of CCs on SOC and reduced POC export are persistent regardless of their spatial allocation adopted in the scenarios. Together, the results highlight the importance of taking the temporal aspect of CC adoption into account and indicate that CCs alone are not sufficient to meet the targets of the 4‰ initiative. Despite some known model limitations, which include the lack of feedback of erosion on the net primary productivity and the representation of carbon fluxes with an emulator, the current work constitutes the first approach to successfully couple a distributed routing scheme of eroded carbon to a land carbon model emulator at a reasonably high resolution and continental scale. SHORT ABSTRACT: A spatially distributed model coupling erosion, transport, and deposition to the carbon cycle was developed. Then, it was used to simulate the impact of cover crops on both erosion and carbon, to show that cover crops can simultaneously increase organic carbon storage and reduce particulate organic carbon export to the oceans. The results seemed persistent regardless of the spatial distribution of cover crops.

Including land management in a European carbon model with lateral transfer to the oceans - PubMed