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Summary: For the 70th Anniversary of the establishment of the British Society of Soil Science, this short paper explores the idea that research on soil organic matter has remained a central theme within soil science over the past 70 years, albeit with changing emphasis and application. The number of publications on soil organic matter has increased greatly in recent decades; for example, there were almost 35 000 journal papers with this theme in the decade 2007–2016. Several topics in research on soil organic matter, such as soil fertility, have endured for a number of decades, with publications found on soil organic matter and fertility in the decade 1947–1956. A search with other keywords occurring with soil, such as climate change, biodiversity, fertility, quality, health and security, showed that several topics did not appear before the 1970s and 1980s, but since then the sub‐topics and applications have diversified. Carbon is a keyword that has become more associated with publications on soil organic matter; carbon is in over half of soil organic matter publications of the last decade. A closer examination of research on agricultural soil carbon sequestration since 1990 reveals that the focus of papers in the literature has changed over this period. A closer examination of papers on modelling shows that the next generation of soil organic matter models is developing from pseudo first‐order decay models using conceptual pools and prescribed controls of turnover time to vertically resolved, microbially explicit models representing mineral surface and plant interactions. Given its higher policy profile during the last 2 years, research on soil organic matter and soil carbon sequestration is predicted to have a bright future. Highlights: The number of publications on soil organic matter has increased greatly in recent decades. Soil fertility research has endured for many decades, whereas other topics have diversified. Soil organic matter has been increasingly associated with carbon, which has changed the focus of papers since 1990. Expanding policy attention to soil organic matter research during the last 2 years suggests a bright future. [ABSTRACT FROM AUTHOR]

Current soil‐ and land degradation seriously challenge our societies; it contributes to climate change, loss of biodiversity and loss of agricultural productions. Yet, soils are also seen as a major part of the solution, if maintained or restored to provide ecosystem services. Climate‐smart sustainable management of soils can provide options for soil health maintenance and restoration. In the European Union, the resource management and sustainability challenge are addressed in the Green Deal that, among other goals, aspires towards a healthy climate‐resilient agricultural sector that will produce sufficient products without damaging ecosystems and contribute to better biodiversity and mitigate climate change. The European Joint Programme (EJP) SOIL was set up to contribute to these goals by developing knowledge, tools and an integrated research community to foster climate‐smart sustainable agricultural soil management that provides a diversity of ecosystem service, such as adapting to and mitigating climate change, allowing sustainable food production, and sustaining soil biodiversity. This paper provides an overview of the potential of climate‐smart sustainable soil management research to the targets of the Green Deal that are related to soils most directly. The EJP SOIL EU‐wide consultation (interviews and questionnaires) and literature analysis (national and international reports and papers) done in the first year (2020–2021) generated a wealth of data. This data showed that there are specific manners to do research that are essential for it to be effective and efficient and that can actively contribute to the Green Deal targets. We concluded that research needs to be: (i) interdisciplinary, (ii) long‐term, (iii) multi‐scaled, from plot to landscape, (iv) evaluating trade‐offs of selected management options for ecosystem services and (v) co‐constructed with key stakeholders. Research on climate‐smart sustainable soil management should be developed (1) on plot scale when mobilizing soil processes and on landscape scale when addressing sediment and water connectivity and biodiversity management; and (2) address the enabling conditions through good governance, social acceptance and viable economic conditions. [ABSTRACT FROM AUTHOR]

We have read with interest an opinion paper recently published in the European Journal of Soil Science (Berthelin et al., 2022). This paper presents some interesting considerations, at least one of which is already well known to soil scientists working on soil organic carbon (SOC), that is, a large portion (80%–90%) of fresh carbon inputs to soil is subject to rapid mineralization. The short‐term mineralization kinetics of organic inputs is well‐known and accounted for in soil organic matter models. Thus, clearly, the long‐term predictions based on these models do not overlook short‐term mineralization. We point out that many agronomic practices can significantly contribute to SOC sequestration. If conducted responsibly whilst fully recognising the caveats, SOC sequestration can lead to a win‐win situation where agriculture can both contribute to the mitigation of climate change and adapt to it, whilst at the same time delivering other co‐benefits such as reduced soil erosion and enhanced biodiversity. Highlights: Rapid mineralization of organic inputs is an important factor for soil carbon sequestration.Mineralization kinetics of organic inputs are well‐known and accounted for in soil organic matter models.Many agronomic practices can contribute significantly to SOC sequestration.SOC sequestration can lead to a win‐win situation where agriculture can both contribute to the mitigation of climate change and adapt to it. [ABSTRACT FROM AUTHOR]

The structure of soil is critical for the ecosystem services it provides since it regulates many key soil processes, including water, air and solute movement, root growth and the activity of soil biota. Soil structure is dynamic, driven by external factors such as land management and climate and mediated by a wide range of biological agents and physical processes operating at strongly contrasting time‐scales, from seconds (e.g., tillage) to many decades (e.g., faunal activity and soil aggregation). In this respect, positive feedbacks in the soil–plant system may lead in the longer term to soil physical degradation or to the recovery of structurally poor soils. As far as we are aware, no existing soil‐crop model can account for such processes. In this paper, we describe a new soil‐crop model (USSF, Uppsala model of Soil Structure and Function) that accounts for the effects of soil structure dynamics on water and organic matter cycling at the soil profile scale. Soil structure dynamics are expressed as time‐varying physical (bulk density, porosity) and hydraulic properties (water retention, hydraulic conductivity) responding to the activity of biological agents (i.e., earthworms, plant roots) and physical processes (i.e., tillage, soil swell‐shrink) at seasonal to decadal time‐scales. In this first application of the model, we present the results of 30‐year scenario simulations that illustrate the potential role and importance of soil structure dynamics for the soil water balance, carbon storage in soil, root growth, and winter wheat yields on two soils (loam and clay) in the climate of central Sweden. A sensitivity analysis was also performed for these two scenarios using the Morris method of elementary effects, which revealed that the most sensitive parameters controlling soil structure dynamics in the USSF model are those determining aggregation induced by organic matter turnover and swell/shrink. We suggest that the USSF model is a promising new tool to investigate a wide range of processes and phenomena triggered by land use and climate change. Results from this study show that feedback in the soil‐crop system mediated by the dynamics of soil physical and hydraulic properties are potentially of central importance for long‐term predictions of soil water balance, crop production, and carbon sequestration under global change. [ABSTRACT FROM AUTHOR]

The importance of soils to society has gained increasing recognition over the past decade, with the potential to contribute to most of the United Nations' Sustainable Development Goals (SDGs). With unprecedented and growing demands for food, water and energy, there is an urgent need for a global effort to address the challenges of climate change and land degradation, whilst protecting soil as a natural resource. In this paper, we identify the contribution of soil science over the past decade to addressing gaps in our knowledge regarding major environmental challenges: climate change, food security, water security, urban development, and ecosystem functioning and biodiversity. Continuing to address knowledge gaps in soil science is essential for the achievement of the SDGs. However, with limited time and budget, it is also pertinent to identify effective methods of working that ensure the research carried out leads to real‐world impact. Here, we suggest three strategies for the next decade of soil science, comprising a greater implementation of research into policy, interdisciplinary partnerships to evaluate function trade‐offs and synergies between soils and other environmental domains, and integrating monitoring and modelling methods to ensure soil‐based policies can withstand the uncertainties of the future. Highlights: We highlight the contributions of soil science to five major environmental challenges since 2010.Researchers have contributed to recommendation reports, but work is rarely translated into policy.Interdisciplinary work should assess trade‐offs and synergies between soils and other domains.Integrating monitoring and modelling is key for robust and sustainable soils‐based policymaking. [ABSTRACT FROM AUTHOR]

Soil phosphorus (P) remains an ever‐increasing topic of importance, notably for its key role as a nutrient for driving food production but with parallel concerns over damaging water quality, all against a backdrop of uncertainty of long‐term rock phosphate supplies. Soil is a key interface that holds P and regulates its onward flow to plants or leakage to waters. Often overlooked are a ubiquitous group of P compounds that exist in alternative oxidation states to that of phosphate (+5). Redox cycling, and the behaviour that chemically reduced P compounds exhibit in soils, introduces alternative routes of cycling P that may become more important as the soil system itself alters, especially due to the external pressures of climate change, bringing about critical dynamics in rainfall and runoff and also wetting and drying. All of these factors are known to affect soil redox potential and consequently the oxidation state of soil P. This review considers the chemically reduced species in the P cycle, exploring their sources and sinks, while considering their importance within the primary global biogeochemical cycling of P and how this may be impacted by climate change in the temperate climate of the northern hemisphere. Highlights: This paper addresses how climate change will affect soil phosphorus cycling.This review is novel as it considers the reduced phosphorus forms when discussing P transfer in soils.Climate change is likely to increase prevalence of reduced P and free phosphate in northern hemisphere temperate soils.Phosphorus cycling relies partly on redox P processes. Their importance will increase as climate alters soils. [ABSTRACT FROM AUTHOR]

In urban areas, pre‐existing concrete‐based demolition wastes and purposely introduced crushed dolerite have been used to create artificial soils, which capture carbon (C) as carbonate minerals and offset greenhouse gas (GHG) emissions. Arbuscular mycorrhizal fungi (AMF) can enhance capture of C in artificial soils through production of glomalin‐related soil protein (GRSP), which facilitates soil organic carbon (SOC) storage and aggregation, and may also enhance precipitation of soil inorganic carbon (SIC). In this paper, we show how different mixtures of dolerite and concrete affect AMF community structure and function, GRSP fractions, and soil organic and inorganic carbon contents. We used nine demonstration plots, 1 m deep, to simulate a constructed urban soil, consisting of different proportions (0, 30, 50, 70 and 100%) of either crushed concrete demolition waste or dolerite quarry fines and sown to a species‐rich meadow mixture, to investigate AMF colonization and community structure (using DNA terminal restriction fragment length polymorphism), contents of easily‐extractable and difficultly‐extractable GRSP, and both organic and inorganic carbon contents. All artificial soils supported functioning AMF communities with different levels of GRSP, SIC and SOC. The 100% dolerite and 100% concrete soils had higher values of difficultly‐to‐extract GRSP andSOC than pure sand, whereas 100% concrete had higher AMF colonization and SOC than sand. AMF community analysis indicated that high GRSP producing species were abundant in 100% dolerite and 100% concrete. These findings demonstrate that there is potential to incorporate demolition waste or dolerite products into the land to support environmental sustainability and enhance soil C sequestration. Highlights: In constructed soils, crushed concrete and dolerite more effectively enhance GRSP and soil organic and inorganic carbon contents than sand.Use of crushed concrete and dolerite in plant‐growing substrates is a novel way to combat climate change. [ABSTRACT FROM AUTHOR]

Changes in climate patterns are dramatically influencing some agricultural areas. Arid, semi‐arid and coastal agricultural areas are especially vulnerable to climate change impacts on soil salinity. Inventorying and monitoring climate change impacts on salinity are crucial to evaluate the extent of the problem, to recognize trends and to formulate irrigation and crop management strategies that will maintain the agricultural productivity of these areas. Over the past three decades, Corwin and colleagues at the U.S. Salinity Laboratory (USSL) have developed proximal sensor and remote imagery methodologies for assessing soil salinity at multiple scales. The objective of this paper is to evaluate the impact climate change has had on selected agricultural areas experiencing weather pattern changes, with a focus on the use of proximal and satellite sensors to assess salinity development. Evidence presented in case studies for Californiaʼs San Joaquin Valley (SJV) and Minnesotaʼs Red River Valley (RRV) demonstrates the utility of these sensor approaches in assessing soil salinity changes due to changes in weather patterns. Agricultural areas are discussed where changes in weather patterns have increased root‐zone soil salinity, particularly in areas with shallow water tables (SJV and RRV), coastal areas with seawater intrusion (e.g., Bangladesh and the Gaza Strip) and water‐scarce areas potentially relying on degraded groundwater as an irrigation source (SJV and Murray‐Darling River Basin). Trends in salinization due to climate change indicate that the infrastructure and protocols to monitor soil salinity from field to regional to national to global scales are needed. Highlights: Climate change will have a negative impact on agriculture, particularly in arid regions.Proximal/remote sensors are useful to assess climate change impact on soil salinity across scales.Salt‐water intrusion, shallow water tables and degraded water reuse will increase soil salinity.Infrastructure and protocols to monitor soil salinity across multiple scales are needed. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate the suitability of the ECOSSE model to estimate soil heterotrophic respiration ( Rh) from arable land and short rotation coppices of poplar and willow. Between 2011 and 2013, we measured Rh with automatic closed dynamic chambers on root exclusion plots at one site in the UK (willow, mixed commercial genotypes of Salix spp.) and two sites in Italy (arable and poplar, Populus × Canadensis Moench, Oudemberg genotype), and compared these measured fluxes to simulated values of Rh with the ECOSSE model. Correlation coefficients ( r) between modelled and measured monthly Rh data were strong and significant, with a range between 0.81 and 0.96 for all three types of vegetation. There was no significant error and bias in the model for any site. The model was able to predict seasonal trends in Rh at all three sites even though it occasionally underestimated the flux values during warm weather in spring and summer. Because of the strong correlation between the measured and modelled values, it is unlikely that underestimation of the flux is the result of missing processes in the model. Therefore, further detailed monitoring of Rh is needed to modify the model. In this research, a limited set of input data was used to simulate Rh at the three sites. Nevertheless, overall results of the model evaluation suggest that the ECOSSE model simulates soil Rh adequately under all land uses tested and that continuous and direct measurements (such as automatic chambers installed on root-exclusion plots) are a useful tool to test model performance to simulate Rh at the site level. Highlights Model evaluation is crucial to predict soil carbon balance accurately., Modelled and measured heterotrophic respiration were compared for three land uses., The model performed well statistically for all three vegetation types., Modelled heterotrophic respiration should be evaluated by comparison to continuous measurements. [ABSTRACT FROM AUTHOR]

Organic carbon ( OC) and nitrogen ( N) storage in soil plays an important role in global climate change and in maintaining food security. Pollution of soil with heavy metals has occurred in many parts of the world, but their effects on soil OC and N have not been well addressed. Relevant data were extracted from peer-reviewed journal papers and analysed by a meta-analysis to determine how long-term heavy metal pollution affected soil OC and N status. Plant biomass decreased significantly because heavy metals in soil decreased soil OC and N concentrations by 5.0 and 17.9%, respectively, but increased the C/N ratio by 5.1%. The largest reductions in soil OC and N concentrations were in soil more strongly polluted by metals. The changes in soil OC and N with metal pollution varied with climatic conditions. More substantial decreases in OC and N concentrations were likely to occur in polluted soil with large background contents of OC and low pH. Overall, heavy metals were linked to greater reductions in soil OC and N concentrations in natural ecosystems than in agro-ecosystems. These results provided a quantitative evaluation of the effects of heavy metal pollution on the decrease in soil C and N concentrations and, therefore, on global climate change. Further consideration should be given to changes in the cycling of C and N in soil polluted with metals in natural and agro-ecosystems. [ABSTRACT FROM AUTHOR]

Current widespread and intensive soil degradation in India has been driven by unprecedented levels of population growth, large‐scale industrialization, high‐yield agriculture, urban sprawl and the spread of human infrastructure. The damage caused to managed and natural systems by soil degradation threatens livelihoods and local services and leads to national socio‐economic disruption. Human‐induced soil degradation results from land clearing and deforestation, inappropriate agricultural practices, improper management of industrial effluents and wastes, careless management of forests, surface mining, urban sprawl, and ill‐planned commercial and industrial development. Of these, inappropriate agricultural practices, including excessive tillage and use of heavy machinery, over‐grazing, excessive and unbalanced use of inorganic fertilizers, poor irrigation and water management techniques, pesticide overuse, inadequate crop residue and/or organic carbon inputs, and poor crop cycle planning, account for nearly 40% (121 Mha) of land degradation across India. Globally, human activities related to agriculture contribute to the transgression of four of the nine Planetary Boundaries proposed by Rockström et al. (2009): Climate Change, Biodiversity Integrity, Land‐system Change, and altered Phosphorus and Nitrogen Biogeochemical Flows. This review focuses on how knowledge of soil processes in agriculture has developed in India over the past 10 years, and the potential of soil science to meet the objectives of the United Nations' Sustainable Development Goal 2: Zero Hunger (End hunger, achieve food security, improved nutrition and promote sustainable agriculture), using the context of the four most relevant Planetary Boundaries as a framework. Solutions to mitigate soil degradation and improve soil health in different regions using conservation agricultural approaches have been proposed. Thus, in this review we (1) summarize the outputs of recent innovative research in India that has explored the impacts of soil degradation on four Planetary Boundaries (Climate Change, Biodiversity Loss, Land‐system Change, and altered Biogeochemical Flows of Phosphorus and Nitrogen) and vice‐versa; and (2) identify the knowledge gaps that require urgent attention to inform developing soil science research agendas in India, to advise policy makers, and to support those whose livelihoods rely on the land. [ABSTRACT FROM AUTHOR]

Floodplain ecosystems play a significant role in the global carbon (C) cycle, particularly due to their C sink potential in hardwood floodplain forests. However, in these forests, interactions between a heterogeneous micro‐relief and anthropogenic landscape changes make estimating C loss through soil CO2 efflux difficult. To determine the drivers of soil CO2 efflux, we selected six hardwood floodplain forests at the lower middle Elbe River, which were distributed among different relief positions (low‐lying or high‐elevated) in the active and former flooding zone. We measured soil CO2 effluxes over a full year using the closed‐chamber method. Based on the response of soil CO2 efflux to soil moisture and temperature, annual efflux rates were determined, which were then related to soil properties, such as pH, texture, soil organic carbon (SOC) and nitrogen (N) content. Soil CO2 efflux ranged between 1006 (±99) and 2214 (±118) gC m−2 year−1. Maximum efflux occurred in a former floodplain forest that was disconnected from Elbe River water table fluctuations. SOC‐specific soil CO2 efflux (gC gSOC−1 year−1) was smallest in low‐lying forests of the active flooding zone and reflected by the appearance of redoximorphic mottling close to the soil surface. Fine texture (<6.3 μm), SOC and N were related positively and electric conductivity, C/N and pH negatively to total soil CO2 efflux. Soil pH and fine texture were the strongest univariate predictors for total soil CO2 efflux (both R2 = 0.59). Fine texture, pH and C/N ratio explained 66% of the variance in total soil CO2 efflux according to multiple linear regression. We conclude that, in hardwood floodplain forests, soil CO2 efflux is mainly controlled by fine texture and soil pH. Fine texture can be related to soil moisture and nutrient availability and may have a positive effect on the activity of microorganisms. Highlights: Soil CO2 efflux ranged between 1006 (±99) and 2214 (±118) gC m2 year−1, whereby the maximum was measured in a disconnected floodplain forestMaximum soil CO2 efflux was measured in a disconnected floodplain forestSOC‐specific soil CO2 efflux was smallest in forests where redoximorphic mottling occurred close to the surfaceFine texture (<6.3 μm) and pH were the strongest predictors for annual soil CO2 efflux [ABSTRACT FROM AUTHOR]

Soils store vast amounts of carbon (C) on land, and increasing soil organic carbon (SOC) stocks in already managed soils such as croplands may be one way to remove C from the atmosphere, thereby limiting subsequent warming. The main objective of this study was to estimate the amount of additional C input needed to annually increase SOC stocks by 4‰ at 16 long‐term agricultural experiments in Europe, including exogenous organic matter (EOM) additions. We used an ensemble of six SOC models and ran them under two configurations: (1) with default parametrization and (2) with parameters calibrated site‐by‐site to fit the evolution of SOC stocks in the control treatments (without EOM). We compared model simulations and analysed the factors generating variability across models. The calibrated ensemble was able to reproduce the SOC stock evolution in the unfertilised control treatments. We found that, on average, the experimental sites needed an additional 1.5 ± 1.2 Mg C ha−1 year−1 to increase SOC stocks by 4‰ per year over 30 years, compared to the C input in the control treatments (multi‐model median ± median standard deviation across sites). That is, a 119% increase compared to the control. While mean annual temperature, initial SOC stocks and initial C input had a significant effect on the variability of the predicted C input in the default configuration (i.e., the relative standard deviation of the predicted C input from the mean), only water‐related variables (i.e., mean annual precipitation and potential evapotranspiration) explained the divergence between models when calibrated. Our work highlights the challenge of increasing SOC stocks in agriculture and accentuates the need to increasingly lean on multi‐model ensembles when predicting SOC stock trends and related processes. To increase the reliability of SOC models under future climate change, we suggest model developers to better constrain the effect of water‐related variables on SOC decomposition. Highlights: The feasibility of the 4‰ target was studied at 16 long‐term agricultural experiments.An ensemble of soil organic carbon models was used to estimate the uncertainty of the predictions.On average across the sites, carbon input had to increase by 119% compared to initial conditions.High uncertainty of the simulations was mainly driven by water‐related variables. [ABSTRACT FROM AUTHOR]

Erosion is a severe threat to the sustainable use of agricultural soils. However, the structural resistance of soil against the disruptive forces steppe soils experience under field conditions has not been investigated. Therefore, 132 topsoils under grass‐ and cropland covering a large range of physico‐chemical soil properties (sand: 2–76%, silt: 18–80%, clay: 6–30%, organic carbon: 7.3–64.2 g kg−1, inorganic carbon: 0.0–8.5 g kg−1, pH: 4.8–9.5, electrical conductivity: 32–946 μS cm−1) from northern Kazakhstan were assessed for their potential erodibility using several tests. An adjusted drop‐shatter method (low energy input of 60 Joule on a 250‐cm3 soil block) was used to estimate the stability of dry soil against weak mechanical forces, such as saltating particles striking the surface causing wind erosion. Three wetting treatments with various conditions and energies (fast wetting, slow wetting, and wet shaking) were applied to simulate different disruptive effects of water. Results indicate that aggregate stability was higher for grassland than cropland soils and declined with decreasing soil organic carbon content. The results of the drop‐shatter test suggested that 29% of the soils under cropland were at risk of wind erosion, but only 6% were at high risk (i.e. erodible fraction >60%). In contrast, the fast wetting treatment revealed that 54% of the samples were prone to become "very unstable" and 44% "unstable" during heavy rain or snowmelt events. Even under conditions comparable to light rain events or raindrop impact, 53–59% of the samples were "unstable." Overall, cropland soils under semi‐arid conditions seem much more susceptible to water than wind erosion. Considering future projections of increasing precipitation in Kazakhstan, we conclude that the risk of water erosion is potentially underestimated and needs to be taken into account when developing sustainable land use strategies. Highlights: Organic matter is the important binding agent enhancing aggregation in steppe topsoils.Tillage always declines aggregate stability even without soil organic carbon changes.All croplands soil are prone to wind or water erosion independent of their soil properties.Despite the semi‐arid conditions, erosion risk by water seems higher than by wind. [ABSTRACT FROM AUTHOR]

Soil respiration (RS), the soil‐to‐atmosphere CO2 flux that is a major component of the global carbon cycle, is strongly influenced by local soil temperature (Tsoil) and water content (SWC). Regional to global‐scale RS modelling thus requires this information at local scales, but few high‐quality, wall‐to‐wall (global) Tsoil and SWC data exist. As a result, such modelling efforts commonly use air temperature (Tair) and monthly precipitation (Pm) as surrogate predictors, but their site‐scale accuracy and potential bias are unknown. Here, we used monthly data from 880 sites across a wide variety of different environmental conditions (i.e., climate, ecosystem type, elevation, vegetation leaf habit and drainage conditions) to determine the suitability of Tair as a surrogate for Tsoil, and data from 507 sites to examine the suitability of Pm as a surrogate for SWC. Site‐specific linear and second‐order exponential non‐linear models were compared using model evaluation metrics (i.e., slope, p‐value of slope, root mean square error [RMSE], index of agreement and model efficiency). We found that Tsoil and Tair are highly correlated and explain similar RS variability. In contrast, Pm is not a good surrogate for SWC, even though Pm explains a similar amount of RS variability to SWC. The wide variability in the site‐specific relationships between RS and SWC means that no single relationship can be used for large‐scale modelling. The results from this study support the use of Tair in continental‐to‐global scale RS models, and highlight the urgent need for continental‐to‐global scale SWC datasets for the modelling and evaluation of future soil carbon dynamics under global climate change. Highlights: The accuracy of air temperature and precipitation as surrogates in global soil respiration modelling is unknown.Monthly air temperature and soil temperature are strongly correlated and explained similar amounts of variability in soil respiration.Relationships between precipitation and soil water content are extremely variable by region, thus precipitation is a poor surrogate in global modelling.There is a need for accurate multiscale soil moisture datasets to evaluate future soil carbon dynamics. [ABSTRACT FROM AUTHOR]

Grassed waterways are used to mitigate the offsite transport of sediment generated by soil erosion. This study used a novel trait‐based ranking approach as a method to screen potential candidate grass monocultures and mixes based on their theoretical performance in reducing (a) detachment via rainsplash, (b) detachment via scouring due to concentrated flow and (c) sediment transport and deposition processes. Selected grass species were grown under simulated UK summer and autumn establishment conditions under three different replicated rainfall scenarios: drought, normal rainfall and excess rainfall. The grass species used were the novel hybrid species Festulolium cv Prior (Fest_1) and Festulolium Bx511 (Fest_2) and a conventional mixture of Lolium perenne and Festuca rubra (Conv). Monocultures and mixtures of these species were studied. Plant traits pertinent to control of soil erosion by water were measured. Aboveground traits included plant height, percentage ground cover, aboveground biomass, stem diameter, stem area density and number of tillers. Belowground traits included total root length, root total surface area, belowground biomass, root diameter and % fine roots ≤0.25 mm. For summer conditions, the species treatments that had the highest overall soil erosion mitigation potential were Conv, Fest_1 + 2 + Conv and Fest_2. For autumn conditions, the best treatments were Fest_1 + 2, Fest_1 + 2 + Conv and Conv. The Fest 1 + 2 + Conv had more desirable traits for erosion control than mono Festulolium treatments for the autumn conditions. The conventional mixture had more desirable traits for erosion control than mono Festulolium treatments in both climate scenarios. The results indicate that the trait‐based ranking approach utilized in this study can be used to inform rapid screening of candidate grass species for soil erosion control. Highlights: How to select the most suitable grass species for soil erosion control under changing climate conditions?A novel scoring system based on plant traits associated with soil erosion mitigation was developed.Fest_1 + 2 and Conv treatments expressed traits strongly associated with maximum soil erosion mitigation.Species selection for grassed waterways should consider the establishment growing season and expected rainfall. [ABSTRACT FROM AUTHOR]

Spatially resolved estimates of change in soil organic carbon (SOC) stocks are necessary for supporting national and international policies aimed at achieving land degradation neutrality and climate change mitigation. In this work we report on the development, implementation and application of a data‐driven, statistical method for mapping SOC stocks in space and time, using Argentina as a pilot. We used quantile regression forest machine learning to predict annual SOC stock at 0–30 cm depth at 250 m resolution for Argentina between 1982 and 2017. The model was calibrated using over 5,000 SOC stock values from the 36‐year time period and 35 environmental covariates. We preprocessed normalized difference vegetation index (NDVI) dynamic covariates using a temporal low‐pass filter to allow the SOC stock for a given year to depend on the NDVI of the current as well as preceding years. Predictions had modest temporal variation, with an average decrease for the entire country from 2.55 to 2.48 kg C m−2 over the 36‐year period (equivalent to a decline of 211 Gg C, 3.0% of the total 0–30 cm SOC stock in Argentina). The Pampa region had a larger estimated SOC stock decrease from 4.62 to 4.34 kg C m−2 (5.9%) during the same period. For the 2001–2015 period, predicted temporal variation was seven‐fold larger than that obtained using the Tier 1 approach of the Intergovernmental Panel on Climate Change and United Nations Convention to Combat Desertification. Prediction uncertainties turned out to be substantial, mainly due to the limited number and poor spatial and temporal distribution of the calibration data, and the limited explanatory power of the covariates. Cross‐validation confirmed that SOC stock prediction accuracy was limited, with a mean error of 0.03 kg C m−2 and a root mean squared error of 2.04 kg C m−2. In spite of the large uncertainties, this work showed that machine learning methods can be used for space–time SOC mapping and may yield valuable information to land managers and policymakers, provided that SOC observation density in space and time is sufficiently large. Highlights: We tested the use of machine learning for space–time mapping of soil organic carbon (SOC) stock.Predictions for Argentina from 1982 to 2017 showed a 3% decrease of the topsoil SOC stock over time.The machine learning model predicted a greater temporal variation than the IPCC Tier 1 approach.Accurate machine learning SOC stock prediction requires dense soil sampling in space and time. [ABSTRACT FROM AUTHOR]

The sensitivity of peatland carbon (C) fluxes to changes in climate and hydrology are uncertain due to the complex interactions between plants and peat properties. In this study we examine how peat cores taken from under three plant functional types (PFT) (bryophyte, graminoid and ericoid) differ in their biotic and abiotic properties and how this indirectly modulates the response of C fluxes to environmental change. Peat cores taken from under three PFTs had their aboveground vegetation removed to exclude direct plant‐mediated effects, and were incubated in a temperature × water table factorial experiment at 12, 14 and 16°C (air temperature) with the water table level −25, −15 or −5 cm below the peat surface. Carbon dioxide (CO2) and methane (CH4) fluxes were measured over 11 months. Emissions of CO2 and CH4 increased with temperature, with strong positive (CH4) and negative (CO2) interactions with increasing water table level. There were significant effects of removed PFT on the environmental sensitivity of CH4, but not CO2 fluxes. CH4 emissions were greatest in peat with graminoid PFT removed at the warmest temperature but these indirect effects were not explained by peat abiotic or biotic properties, which did not differ between PFTs. These results show that climate change‐induced expansion of graminoids in northern peatlands will have direct and indirect effects on C fluxes and the stability of peatland C stores. These responses will be determined by the interactive effects of vegetation composition, hydrology and warming on methane‐cycling microbial communities. Highlights: Peatland carbon flux strength under a changing climate is influenced by PFT.Peat from under graminoid PFT emits more methane than peat from under bryophyte or ericoid PFT.Prior PFT cover influenced methane emissions, but did not affect peat abiotic or biotic properties.Increases in graminoid cover with climate change could indirectly increase peatland methane fluxes. [ABSTRACT FROM AUTHOR]

Phytoliths can act as efficient carriers of information about palaeovegetation and palaeoclimatic conditions, but the representativeness of soil phytoliths from palaeoecological sediments has not been fully understood. In this study, phytolith assemblages in topsoils and associated plant communities at 55 sites in Northeast China were compared. The results indicate that samples from herbaceous and woody communities could be reliably differentiated by topsoil phytoliths. Notably, different phytolith types exhibit varying degrees of representational bias in terms of the aboveground plant community. Some morphotypes (e.g., bilobate, rondel and lanceolate) over‐represent the richness of the corresponding plant; some morphotypes, including microhair, conical epidermal, silicified stomata and epidermal phytoliths, under‐represent the parent plant abundance; additional morphotypes (e.g., elongate, saddle and trapeziform sinuate) are consistent with the changes of associated plants. Based on the representational bias, we calibrated the percentages of topsoil phytoliths and established a phytolith‐based transfer function for precipitation in Northeast China. A palaeoclimate reconstruction in the Changbai Mountains (in the eastern part of Northeast China) based on the above phytolith‐based transfer function for precipitation shows that the region has gone through continuous climatic changes since the late glacial period: from cold and dry conditions to warm and dry conditions, then to warm and wet conditions, and finally to cool and dry conditions. The phytolith‐based reconstructed climate changes since the late glacial period correspond well to those reconstructed by other records from the same stratigraphic profile, and our phytolith‐based climatic reconstruction also confirms the reliability of abrupt cold climatic shifts at 8.2, 6.8, 5.6, 4.6 and 4.2 ka. In conclusion, our results provide the basis for the reliability of phytoliths for reconstructing climatic changes in the northern temperate region. Highlights: Calibrating soil phytolith assemblages for any quantitative palaeovegetation reconstruction using phytoliths is necessary.Phytolith morphotypes in topsoils may over‐ or under‐represent or agree with the abundance of modern plant taxa.Phytolith‐based climatic reconstruction corresponds well with the abrupt climate changes evident since the Late Glacial period and other proxy records. [ABSTRACT FROM AUTHOR]

The impacts of climate change on biodiversity can be modulated by other changing environmental conditions (e.g. induced by land‐use change). The potential interactive effects of climate change and land use have rarely been studied for soil organisms. To test the effects of changing climatic conditions and land use on soil invertebrates, we examined earthworm communities across different seasons in different grassland‐use types (intensively managed grassland, extensively managed meadow and extensively managed sheep pasture). We predicted that the strength of climate change effects would vary with season and land use. Overall, extracted earthworm populations showed the strongest variations in response to the season, indicating major differences in activity patterns and extraction efficiency, whereas climate change and different grassland‐use types had fewer and weaker effects. Future climate, characterized by slightly higher precipitation in spring and autumn but a strong reduction during the summer, had positive effects on the abundance of extracted adult earthworms in spring but then reduced the abundance of active earthworms across the remaining seasons. In contrast, the total biomass of juveniles tended to be consistently lower under future climate conditions. Earthworm species responded differently to the climate change and different grassland management types, and these species‐specific responses further varied strongly across seasons. Intensive grassland management had negative effects, due to plant community composition, whereas sheep grazing favoured earthworm populations, due to dung deposition. There were only limited interactive effects between climate and land use, which thus did not support our main hypothesis. Nevertheless, these results highlight the complex and context‐dependent responses of earthworm communities and activity patterns to climate change, with potential consequences for long‐term population dynamics and crucial ecosystem functions. Highlights: We explored earthworm communities in response to climate change, different grassland‐use types and seasonsClimate had species‐specific effects on active earthworms, but few interactions with land‐use typeIntensive grassland management decreased, but sheep grazing favoured, active earthworm populationsStrong seasonal variations in earthworm activity periods will be modulated by climate change [ABSTRACT FROM AUTHOR]

The spatial distribution of soil organic carbon is an important factor in land management decision making, climate change mitigation and landscape planning. In Scotland, where approximately one‐quarter of the soils are peat, this information has usually been obtained using field survey and mapping, with digital soil mapping only carried out recently. Here a method is presented that integrates legacy survey data, recent monitoring work for peatland restoration surveys, spatial covariates such as topography and climate, and remote sensing data. The aim of this work was to provide estimates of the depth, bulk density and carbon concentration of Scotland's soils in order to allow more effective carbon stock mapping. A neural network model was used to integrate the existing data, and this was then used to generate a map of soil property estimates for carbon stock mapping at 100‐m resolution over Scotland. Accuracy assessment indicated that the depth mapping to the bottom of the organic layer was achieved with an r2 of.67, whereas carbon proportion and bulk density were estimated with an r2 of.63 and.79, respectively. Modelling of these three properties allowed estimation of soil carbon in mineral and organic soils in Scotland to a depth of 1 m (3,498 megatons) and overall (3,688 megatons). Highlights: Scotland's soil organic carbon was mapped using a digital soil mapping approach.This provides a high‐resolution map available for scientists, regulatory bodies and policymakers.The method largely agreed with previous work but improved the spatial resolution of the mapping.Significant soil carbon stocks are held in both organic (peat) and non‐peat soils. [ABSTRACT FROM AUTHOR]

Summary: This study compares data statistically that were collected from both long‐term drained and undrained plots to test hypotheses concerning the effect of drainage on plant community, soil total nitrogen (TN), soil total carbon (TC) and stable isotopic (δ15N, δ13C) contents in a permanent grassland. In addition, the effects of soil depth, topography (elevation, slope, aspect and compound topographic index (CTI)) and spatial autocorrelation were taken into account. Data were collected in 2010 at Rowden Moor, North Wyke, Devon, UK, where, for the plots of this study, subsurface drainage was introduced in 1987. The results of a set of six linear mixed models showed that: (i) plant community did not depend on drainage, but on elevation and spatial effects, (ii) both TN and TC not only depended on drainage, but also topography and sample depth, (iii) the TC to TN ratio did not depend on drainage, but on elevation, CTI and sample depth only, (iv) δ15N values did not depend on drainage, but on topography and sample depth and (v) δ13C values depended on drainage together with topography and sample depth. Thus, drainage represented a significant effect for only TN, TC and δ13C. Furthermore, changes in soil physicochemical conditions, following the introduction of drainage in the clay soil 24 years previously, induced a shift in the plant community from a Lolium perenne L. dominated grassland with numerous patches of Juncus species, towards one with Lolium perenne and Trifolium repens L. Highlights: The effect of drainage on plant community, and C and N cycling on permanent grassland. Soil depth, topography and associated spatial effects are taken into consideration. Plant community (species diversity) depended on topography and spatial effects only. Soil chemistry depended on topography and depth, and N, C and δ13C also depended on drainage. [ABSTRACT FROM AUTHOR]

Volcanic ash soil contains large stocks of organic matter per unit area. A large proportion of organic matter is stored in the subsoil; therefore, a thorough understanding of its vertical distribution is needed to predict the effects of change in climate and land use. Faunal bioturbation is often cited as the dominant process that affects the vertical distribution of organic matter. An additional but often overlooked process is change in the volume of the soil. Such change might affect the vertical distribution of organic matter by changing the position of the soil surface, which can affect the soil-forming processes related to depth, such as weathering, decomposition, bioturbation and rooting. We calculated the change in volume with geochemical mass balance equations, and showed the effect of change in soil volume on the vertical distribution of organic matter using a dynamic model. Then we evaluated the plausibility of the model concept with an independent model for parameter identification and through a model sensitivity analysis. Results show that volume change is a major soil-forming process that determines the vertical distribution of organic matter in volcanic ash soil as the active bioturbation zone moves upwards in response to soil thickening. [ABSTRACT FROM AUTHOR]