James Hutton Institute

Enhanced Rock Weathering (ERW) is a climate mitigation strategy that accelerates natural rock weathering processes to sequester atmospheric carbon dioxide. Applying crushed basalt to agricultural soils releases base cations (Ca2+, Mg2+) that form stable carbonates or leach as bicarbonate to the ocean. In addition to carbon sequestration, basalt weathering provides crop nutrients, potentially improving yields and quality. This study evaluated the effects of basalt application on crop growth and soil carbon sequestration through a two-year field experiment, with a focus on elemental dynamics.A field experiment was conducted from 2023 to 2024 at an experimental field in Hokkaido University (43.07° N, 141.34° E; gray lowland soil), using soybean (Glycine max (L.) Merrill.) in the first year and maize (Zea mays L.) in the second. Five treatments with three replications were established: a control, three basalt application rates (5, 10, and 20 wt.% incorporated into the top 15 cm; BA5, BA10, BA20), and a lime application (0.15 wt.%). While basalt was applied only in 2023, lime was reapplied in 2024 to match the soil pH of BA10. In 2023, soil and plant samples were collected at the flowering (R2), seed development (R6) and R8 stages. In 2024, soil and plant samples were collected at the vegetative (V9), reproductive (R1), and harvest (R6) stages. We measured plant dry weight, elemental concentrations, and grain yield. Soil analyses included pH, exchangeable cations, available silicon (Si), and mineralogical composition via X-ray powder diffraction (XRPD). Total carbon budgets were calculated by integrating plant and soil data.Soil pH increased similarly in both basalt and lime treatments. Basalt application significantly increased soil exchangeable magnesium (Mg) and sodium (Na) concentrations throughout the entire cultivation period. Additionally, available Si concentrations significantly increased in 2024. In contrast, exchangeable calcium (Ca) concentration showed no significant change with basalt application, increasing only in the limed plots. This likely reflects the high initial exchangeable calcium concentration in the original soil. XRPD showed a decrease in Ca-plagioclase in 2024 compared to pre-cultivation soil in 2023, with the greatest decrease observed in BA20. This reduction occurred primarily in planted plots, suggesting that crop roots may enhance basalt weathering. While basalt application showed no growth-promoting effects on soybean, it significantly increased maize plant height at V9, leaf dry weight at R1, and stem cross-sectional area at R6. In soybean, shoot manganese (Mn) and nickel (Ni) concentrations decreased in both basalt and lime treatments. In maize, shoot Mn concentration decreased in the lime treatment, while shoot Mg concentration increased significantly and shoot Si concentration showed an increasing trend in basalt treatments. Soil exchangeable Mg concentration was positively correlated with shoot dry weight.Overall, basalt application had no negative effects on crop growth and can be beneficial depending on the crop species. The growth-promoting effects arise not only from pH neutralization but also from the supply of essential elements such as Mg and Si released through weathering. Mineralogical evidence indicates that basalt weathering progressed over two years, suggesting potential carbon sequestration through ERW in agricultural soils.

Pharmaceuticals are increasingly recognised as a class of emerging contaminants of concern in rivers. Their continuous release from human use and variable removal in sewage treatment works (STWs) can produce ecologically relevant concentrations and contribute to antimicrobial resistance. We developed a probabilistic catchment-scale model based on a Bayesian Belief Network (BN) to quantify pharmaceutical concentrations and the probability of exceeding predicted no-effect concentrations (PNECs) at a monthly time step. The BN embeds a stochastic mass-balance linking monthly prescribing rates, excretion fractions, STW removal efficiencies and river discharge to produce posterior distributions of concentrations for 16 pharmaceuticals at 20 monitoring points in a medium size Scottish catchment. Model inputs were derived from Scotland’s National Health Service (NHS) prescribing records, a literature compilation of excretion and removal data, and a calibrated SWAT hydrological model. Simulated posterior concentration distributions generally agreed with observations and were typically within one order of magnitude for most compounds, indicating satisfactory performance. Highest exceedance probabilities were predicted for azithromycin, diclofenac, ibuprofen and clarithromycin, particularly at heavily impacted sites and during low-flow summer months. Scenario analyses show that future drier summers (UKCP18 RCP8.5) increase exceedance probabilities, and that substantial reductions in prescribing or markedly improved STW removal efficiencies are needed to reduce risks for high-impact compounds. The BN framework transparently captures uncertainty, supports diagnostic inference to prioritise interventions and is readily extensible to include additional sources (e.g. combined storm overflow and septic tanks) and pollutant mixture risk assessment.

Rewilding is a complex and increasingly important topic that bridges nature conservation with economic sustainability, and wider social issues. It is aimed at restoring natural ecosystems by reintroducing native species and allowing natural processes to prevail. Rewilding contributes to biodiversity aims and multiplies opportunities associated with putting nature on a path to recovery. However, its other dimensions are uncertain. The challenges may arise as to (i) connecting rewilding with stakeholders’ other values and interests; (ii) achieving more efficient spatial integration/segregation of land use systems and specifically regarding (iii) the linking of biodiversity conservation and rewilding with place-based practices and social innovation initiatives in mountain regions of Europe. This is the focus of this paper, which has Scotland as a case study.Nearly 200 projects are dedicated to rewilding in Scotland (Armour, 2025). Discussions around the reintroduction of lynx, for example, indicate the importance to operate following transparent positions, involving stakeholders who need to come to an agreement on ‘best’ solutions. We analyse how the Scottish policy framework supports rewilding and associated stakeholder perceptions to enable such solutions to be achieved. Using an innovative combination of research methods, we examine public/stakeholder perceptions associated with rewilding and key trade-offs in-between. The integration of participatory, analytical and visualization tools, refined and applied at the James Hutton Institute has proven useful for assisting decision making by incorporating prevalent attitudes/perceptions of end users into the design of relevant policies, spatial plans and management practices associated with rewilding.Our findings provide evidence that although in Scotland economic considerations remain strong, the cultural, health/wellbeing, and intrinsic values that people associate with nature are receiving increasing recognition. Decisions on undertaking rewilding are likely to benefit from developing social innovations and bringing deliberative approaches into monetary valuation of the societal benefits/costs of socio-ecological systems’ transformation. The findings also show that there is an understanding that the promotion of rewilding in some localities in Scotland, and especially in the Highlands, opens a pathway towards leveraging and multiplying forest benefits for society and the environment, potentially offering lessons that extend to other marginalised mountain regions of Europe.

ABSTRACT Aim European grasslands rank among the most species‐rich ecosystems at small spatial scales, yet their biodiversity and functioning face significant threats from climate change and land‐use intensification. Functional traits more effectively explain ecosystem functions (EFs) than species identity or diversity. This study examines how future climate and land cover changes will shape grassland functional composition, addressing gaps in trait‐environment relationships and large‐scale functional predictions. Location Europe. Time Period 1971–2000 and 2081–2100. Major Taxa Studied 4406 distinct grassland plant species. Methods We used Boosted Regression Trees to model trait‐environment relationships based on vegetation plot data from sPlotOpen, GrassPlot, and the Nordic‐Baltic Grassland Vegetation Database (NBGVD). We mapped the 17 trait community‐weighted means (CWMs) and three functional richness (FRic) metrics under historical conditions and two future climate scenarios to assess temporal and spatial changes in grassland functional composition. Results The trait–environment relationships are highly trait‐dependent: structural and size‐related traits such as plant height, leaf area and seed number were consistently well‐predicted, whereas other traits were less well predicted. Mean annual temperature emerged as the strongest predictor of grassland functional composition. Climate and land cover change were predicted to drive significant spatial shifts in trait CWMs and FRic. Specifically, leaf area was predicted to decline in the Baltic Sea region and Pannonian Basin, while plant height was expected to increase across Europe. Seed number was predicted to rise at higher latitudes and in mountainous regions. Moreover, FRic was expected to decrease in temperate grasslands but increase at high latitudes and mountainous regions. Main Conclusions Our findings reveal distinct spatial patterns in functional shifts, reflecting plant adaptation to future environmental conditions. The increase in FRic at high latitudes and mountainous regions also signals ecosystem transitions that may pose additional threats to further complicate grassland conservation efforts.

Peatlands have the capacity to sequester large quantities of carbon and can therefore play an important role in climate change mitigation. However, anthropogenic activities alter their hydrological regimes, converting them from net CO2 sinks into net sources. In England and elsewhere, lowland peatlands have been heavily drained and modified for agricultural land use, resulting in some of the most productive farmland in the UK. Estimates of CO2 emissions and water use from the area are scarce, but these data are required to understand the consequences of maintaining agricultural output whilst simultaneously reducing GHG emissions. In this paper, we compiled a uniquely comprehensive dataset of CO2 and H2O flux measurements from flux towers on cropped lowland peat, and coupled this with crop calorific values to estimate carbon and water use intensities of food production on peat. Our results showed that croplands on peat emitted 23.1 ± 10.4 ton CO2 ha-1 y-1 (mean ± SD). Sites with peat depth > 40 cm emitted 25.1 ± 9.2 ton CO2 ha-1, while wasted peat sites emitted 11.8 ± 4.8 ton CO2 ha-1. Effective water table depth and organic carbon content were the main drivers of variation in annual net ecosystem production and ecosystem respiration across sites; crop type partly followed these gradients, so may not be a direct driver of variations in emissions. ET was less variable across site-years and depended on the phenology of crop production. When considering CO2 emissions and water use per calorie produced, lettuce and celery rotations were the most C and water use intensive crops, with values an order of magnitude larger than cereal crops. Overall, this paper highlights the scale of CO2 emissions from managed peatlands and the importance of balancing GHG emissions and water use with ongoing food production from these economically important areas.

Abstract Habitat loss and nutrient enrichment are major drivers of plant species declines. However, local extinction risks vary widely and are shaped by life‐history trait syndromes. Genomic life‐history traits, which are simple, stable and widely available, offer a promising yet underexplored approach to improving extinction risk assessments and informing conservation efforts. Using a spatial comparison approach, we analysed 256 semi‐natural grassland plant communities in four Swedish agricultural landscapes to examine whether genomic life‐history traits such as ploidy, genome size and chromosome number mediate differences in plant community diversity and composition along independent gradients of grassland fragment size and phosphorus availability. Our findings show that plant diversity and community composition are increasingly dominated by larger genome species both as grassland fragments become smaller and as more phosphorus becomes available. While all genomic life‐history traits proved important, ploidy plays a particularly significant role in explaining differences between observed plant communities. Ploidy mediated deterministic plant community changes along both environmental gradients. Diploid species are especially vulnerable to local extinction, whereas polyploids demonstrate resilience to habitat loss and benefit from increased phosphorus availability, likely leading to the competitive exclusion of diploids. Synthesis . By revealing how genomic traits shape plant community responses to land‐use change and nutrient pollution—two key drivers of extinction—our study introduces a predictive, genomic trait‐based framework for assessing local extinction risks in fragmented landscapes.

Beneath the Earth's surface lies a network of interconnected caves, voids, and systems of fissures forming in rocks of sedimentary, igneous, or metamorphic origin. Although largely inaccessible to humans, this hidden realm supports and regulates services critical to ecological health and human well-being. Subterranean ecosystems are integral to major biogeochemical cycles, sustain diverse surface habitats, and serve as the primary source of irrigation and drinking water. They also offer non-material benefits, including scientific discovery, education, and cultural practices. Yet, these contributions often go unrecognised, partly due to the lack of a unified synthesis of ecosystem services across terrestrial, freshwater, and marine subterranean compartments. This gap limits effective communication of their value to scientists, practitioners, and the public. Through a systematic expert-based review, we show that subterranean ecosystems contribute to up to 75% of classified ecosystem services. Notably, many of these contributions are described only qualitatively, lacking numerical or economic quantification. Next, we list examples of the main ecosystem services provided by subterranean systems to offer a global overview of their multifaceted value and vulnerability to environmental change. We believe this synthesis provides researchers and practitioners with concrete examples to communicate more effectively the importance of subterranean ecosystems to diverse audiences.

Introduction Wood borer pests represent a growing threat to forestry worldwide, with potential for an increase in climate change induced outbreaks that could significantly impact ecosystem functioning. Methods This study reviews the current state-of-the-art in bark beetle modeling as presented in peer-reviewed English language scientific papers and reviews cited in Clarivate Analytics Web of Science (WoS) Core Collection in the period from 2006 to 2023, but earlier influential papers cited in reviews from this period are also in scope. We categorize studies by modeling methodology, by host and by modeled processes. Results Ash, pine, and spruce hosts account for 88% of studies, the majority of which focus on the continental USA, British Columbia, Canada and Central Europe. In terms of methodology, statistical methods are the most commonly employed technique, and the majority of articles model just one or two key processes with pest demography and environmental factors being the most studied across different hosts. Commonalities in methods used across pest-host systems include: use of phenology-like models; application of static species distribution models (SDMs) to understand climate impacts; modeling of spread via local and long-range kernels; and use of economic cost-benefit analysis as a tool to guide management. Discussion We identify several gaps in current research including quantifying economic consequences of wood borer pests and the need for greater understanding of ecological impacts and resilience. Agent- and individual-based models may also provide useful tools for understanding the complexity of socio-ecological system dynamics. However, such developments should be in tandem with wider use of techniques for parameter estimation and uncertainty quantification, including Bayesian inference in particular of the dynamics of spatial spread. A related challenge is better quantification of pathways - including trade - for entry by invasive pests, coupled with a greater understanding of potential vulnerabilities of forest systems to environmental drivers like climate change, coupled with potentially multiple endemic, emerging and novel pests. Addressing these challenges would enable both better mitigation of risks associated with wood borer beetle infestations and better management of outbreaks when they do occur.

<title>Abstract</title> As a nearly universal rule governing parasitology, parasites form aggregated distributions where a minority of hosts are responsible for harboring a majority of the parasite burden in any given population. For 30 years ectoparasitic <italic>Varroa destructor</italic> mites are described as preferring non-reproductive female nurse bees of its host, Western honey bee, <italic>Apis mellifera</italic> , while otherwise largely leaving the distribution of <italic>Varroa</italic> undescribed. As a result, <italic>Varroa-</italic> vectored disease transmission dynamics, sampling methodology and research have largely been worker centric. For the first time we investigate the intracolony distribution and dispersal patterns of <italic>Varroa</italic> on sex and age cohorts of its honey bee host in natural colonies and in laboratory choice experiments, and demonstrate that <italic>Varroa</italic> overwhelmingly prefer young adult males (drones), over any other cohort. We show <italic>Varroa</italic> form highly aggregated distributions on the drone cohort early in the season when infestation levels are low, and distribute broadly onto the worker cohort later in the season when infestation levels are high. In 1978 Anderson and May first proposed the theoretical framework that parasites would have little destabilizing effect on the host population until the degree of aggregation was low, or approached a Poisson distribution. The distribution patterns of <italic>Varroa</italic> are in alignment with their theoretical work, and maybe the underlying mechanism responsible for historical losses of honey bee colonies observed over the last decade.