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1. Natural Capital Accounts for woodland, farmland and freshwater broad habitats were produced by ERAMMP in collaboration with the Office of National Statistics in 2017. These accounts estimated the combined partial asset value for these habitats to be £30.5 billion for 2014. A new monetary account has now been created for Mountain, Moor and Heath (MMH) habitat. This account estimates the MMH asset value to be £3 billion for 2018. 2. It is noted in all the reports produced that Office for National Statistics produced Natural Capital accounts remain experimental and future publications will be subject to methodological improvements. Also, it should be noted that all accounts only represent partial or a minimum valuation as methods are not available for all services. 3. This partial asset value for MMH is a relatively small asset figure – but it underlines how cheaply the products of the environment are rather than how important they are. The price is an important signal of levels of trade. If we are to decouple economic production and growth from environmental impact then the raw price ought to remain low with most value added upstream in the supply chain. If we were to look at the final consumer value of products from Welsh upland agriculture, it would be significantly higher. 4. For all of these accounts, the condition of the various broad habitats are not included explicitly as these are not typically represented in the reporting of many natural capital accounts by the Office of National Statistics. This means the rich set of condition data from the GMEP and ERAMMP National Field Survey and many other sources have not been exploited. These condition data are particularly important for assessing the underpinning resilience of ecosystems to sudden shocks. In addition, as standalone indicators these condition metrics help us to track the outcomes of policy (and other) interventions in improving the health of our ecosystems. 5. To test out the value of assessing condi

This project assessed the impacts of 741 potential land management actions, suitable for agricultural land in England, on the Farming & Countryside Programme’s Environmental Objectives (and therefore Environment Act targets and climate commitments) through 53 relevant environmental and cultural service indicators. The project used a combination of expert opinion and rapid evidence reviews, which included 1000+ pages of evidence in 10 separate reports with reference to over 2400 published studies, and an Integrated Assessment comprising expert-derived qualitative impact scores. The project has ensured that ELM schemes are evidence-based, offer good value for money, and contribute to SoS priorities for farming.

Soil organic carbon (SOC) concentration is the fundamental indicator of soil health, underpinning food production and climate change mitigation. SOC storage is highly sensitive to several dynamic environmental drivers, with approximately one third of soils degraded and losing carbon worldwide. Digital soil mapping illuminates where hotspots of SOC storage occur and where losses to the atmosphere are most likely. Yet, attempts to map SOC often disagree. Here we compare national scale SOC concentration map products to reveal agreement of data in mineral soils, with progressively poorer agreement in organo-mineral and organic soils. Divergences in map predictions from each other and survey data widen in the high SOC content land types we stratified. Given the disparities are highest in carbon rich soils, efforts are required to reduce these uncertainties to increase confidence in mapping SOC storage and predicting where change may be important at national to global scales. Our map comparison results could be used to identify SOC risk where concentrations are high and should be conserved, and where uncertainty is high and further monitoring should be targeted. Reducing inter-map uncertainty will rely on addressing statistical limitations and including covariates that capture convergence of physical factors that produce high SOC contents.

The thin layer of soil at the earth’s surface supports life, storing water and nutrients for plant uptake. These processes occur in the soil pore space, often half the soil volume, but our understanding of how this volume responds to environmental change is poor. Convention, has been to predict soil porosity, or its reciprocal bulk density (BD), from soil texture using pedotransfer functions (PTFs). A texture based approach, invariant to environmental change, prevents feedback from land use or climate change to soil porosity. Moreover, PTFs are often limited to mineral soils with < 20% soil organic matter (SOM) content. Here, we develop an analytical model to predict soil porosity, or BD, as a function of SOM. We test it on two comprehensive, methodologically consistent, temperate national-scale topsoil data sets (0–15 cm) (Wales, n = 1385; Great Britain, n = 2570). The purpose of the approach is to generate an analytical function suitable for predicting soil porosity change with SOM content, while providing insight into the main grain-scale factors determining the porosity emergence. The newly developed function covering the entire SOM gradient allows for impacts of land use, management or climate change to feedback on soil porosity or bulk density through decadal dynamic changes in SOM.

The purpose of this work was to provide more in-depth analysis of the field survey data collected under the GMEP project between 2013 – 2016 to inform both future analysis of Glastir outcomes and the design of the Sustainable Farm Scheme in Wales.

The Glastir Monitoring and Evaluation Programme (GMEP, https://gmep.wales/) was at the forefront of the ecosystem approach to monitoring the impact of Pillar II schemes across the European Union - as recognised by the European Commission’s Monitoring and Evaluation Help Desk. GMEP also recruited a large sample of counterfactual “wider Wales” sites, thus enabling additional all Wales reporting. GMEP and other assimilated data represents a significant source of robust, timely and spatially relevant evidence which can contribute to SoNaRR. To facilitate use of GMEP data in SoNaRR, we present new analyses of national monitoring data which has been co-developed with SoNaRR technical leads at Natural Resources Wales (NRW).

Farmscoper is a decision support tool that can be used to assess diffuse agricultural pollutant loads on a farm and quantify the impacts of farm mitigation methods on these pollutants. The farm systems within the tool can be customised to reflect management and environmental conditions representative of farming across England and Wales. The tool contains over 100 mitigation methods, including many of those in the latest Defra Mitigation Method User Guide.

The potential impact of Brexit on the farming sector and wider environment is just one of the many challenges facing the Welsh Government. There are a range of decision and modelling tools which can be used to explore potential outcomes and the areas at risk where the environmental regulatory floor needs to be enhanced or social transition programmes put in place. To meet this challenge in Wales, a partnership between the Welsh Government, their stakeholders and a consortium of research organisations led by the UK Centre for Ecology and Hydrology (UKCEH) was formed. This partnership, called ERAMMP, (https://erammp.wales/en) combined expert knowledge and a range of decision and modelling tools to examine potential changes in agricultural land use that might result from Brexit, and to explore potential benefits of new land management options.

The potential impact of Brexit on the farming sector and wider environment is just one of the many challenges facing the Welsh Government. There are a range of decision and modelling tools which can be used to explore potential outcomes and the areas at risk where the environmental regulatory floor needs to be enhanced or social transition programmes put in place. The same tools can also be used to explore a range of ‘what if’ scenarios for different land management options which could be included in new Payment for Ecosystem Service (PES) schemes or in national land management payment schemes to replace CAP. To meet this challenge in Wales, a partnership between the Welsh Government, their stakeholders and a consortium of research organisations led by the Centre for Ecology and Hydrology (CEH) was formed. This partnership, called ERAMMP, (https://erammp.wales/en) combined expert knowledge and a range of decision and modelling tools to examine potential changes in agricultural land use that might result from Brexit, and to explore potential benefits of new land management options.

This review was commissioned by Welsh Government (WG) from the Environment and Rural Affairs Monitoring and Modelling Programme (ERAMMP) to provide key evidence of potential benefits and disbenefits of woodland creation, woodland expansion and managing undermanaged woodland, to provide an evidence base to inform the development of a National Forest for Wales. During the commissioning process, WG emphasised that the evidence provided must reflect the collective views of the community by reviewing the literature in an objective way highlighting where evidence is contradictory or weak. Within the time available, evidence of causality of impacts, the likely timescales and magnitude of these impacts should be also be presented, for both positive and negative impacts of woodland expansion and management of undermanaged woodlands. This Evidence Pack should also build on the evidence put forward in the ERAMMP Sustainable Farm Scheme (SFS) (https://erammp.wales/en/resources) which included a range of assessments of the value of intervention measures which promoted trees within a landscape setting for a range of environmental, economic and social outcomes. The required rapid production of the review in four months meant an expert approach of key evidence was expected rather than a systematic review. Key topics to cover were selected, in partnership with WG, focussing on issues that could fundamentally change decision-making going forward. The final agreed list was arranged under a series of high-level subject headings, and the individual reviews published as ERAMMP Reports 33 to 38 and include; Biodiversity; Managing Undermanaged Woodland; Future-proofing our Woodland; Climate Change Mitigation; Ecosystem Services, and Economics and Natural Capital Accounting. An Integrated Assessment was also commissioned to provide a synthesis of cross-cutting themes and dependencies between topics. These ERAMMP reports are all provided as Annexes to this report.

Understanding how species richness is distributed across landscapes and which variables may be used as predictors is important for spatially targeting management interventions. This study uses finely resolved data over a large geographical area to explore relationships between land-use intensity, habitat heterogeneity and species richness of multiple taxa. It aims to identify surrogate landscape metrics, valid for a range of taxa, which can be used to map and monitor High Nature Value farmland (HNV). Results show that variation in species richness is distributed along two axes: land-use intensity and habitat heterogeneity. At low intensity land-use, species rich groups include wetland plants, plant habitat indicators, upland birds and rare invertebrates, whilst richness of other species groups (farmland birds, butterflies, bees) was associated with higher land-use intensity. Habitat heterogeneity (broadleaved woodland connectivity, hedgerows, habitat diversity) was positively related to species richness of many taxa, both generalists (plants, butterflies, bees) and specialists (rare birds, woodland birds, plants, butterflies). The results were used to create maps of HNV farmland. The proportion of semi-natural vegetation is a useful metric for identifying HNV type 1. HNV type 2 (defined as a mosaic of low-intensity habitats and structural elements) is more difficult to predict from surrogate variables, due to complex relationships between biodiversity and habitat heterogeneity and inadequacies of current remotely sensed data. This approach, using fine-scaled field survey data collected at regular intervals, in conjunction with remotely sensed data offers potential for extrapolating modelled results nationally, and importantly, can be used to assess change over time.

New analysis was carried out to explore the reported loss of topsoil-C between 2007 and 2016 in the ‘Habitat’ category in the final GMEP report. This ‘Habitat’ category is defined as all habitats except woodlands, arable and improved grassland. The GMEP survey squares were selected using Countryside Survey protocols stratified according to Land Classes. The final GMEP survey sample from 2012-2016 consists of 7% previously surveyed Countryside Survey squares. Further analysis was needed to explore, and account for, unintended shifts in environmental variables which could have contributed to the reported topsoil carbon decline. The results indicate: 1. The reported change in the ‘Habitat’ category is driven by trends in upland habitats (median elevation of 400m). 2. In upland habitats, soil carbon is positively associated with dwarf shrub cover (particularly ericoid e.g. heather cover), Sphagnum, presence of peat, elevation and moisture conditions. 3. The coverage of dwarf shrubs was lower in GMEP than in Countryside Survey 2007, mostly due to lower cover of ericoids i.e. heather. This is consistent with decreasing soil carbon in upland habitats. Other variables (i.e. potential drivers) did not differ between surveys, or direction of change was inconsistent with reported C trends. 4. Re-analysis of Countryside Survey data (1978-2007) provides evidence that shifts over time from dwarf shrub to grass-dominated habitats are associated with a decline in topsoil carbon. 5. Overall, this suggest a potential role of ongoing vegetation change in upland habitats (i.e. conversion of dwarf shrub to grass-dominated) contributing to topsoil carbon loss. Further work is needed to: • Confirm recent vegetation change in upland habitats using independent data e.g. satellite data; • Explore relationships between specific plant species and topsoil carbon in Countryside Survey where we have a high number of true repeat samples; This work highlights the importance of the findings of the n

The aim of the Natural Resources Wales (NRW) and other monitoring activities review is to recommend where the key opportunities exist to address evidence gaps, better align activities and reduce duplication. This should not duplicate the intensive work involving more than 40 organisations and over 100 individuals which resulted in the ‘Options for a New Integrated Natural Resource Monitoring Framework for Wales’ 1 review which identified more than 180 monitoring schemes and provided 6 independent reviews of new opportunities for the monitoring community.

A reduction in the number of GMEP squares to be revisited in the ERAMMP field survey is required to meet budgetary constraints whilst ensuring the survey will deliver the most robust evidence base which is responsive to such issues as the actual uptake of different Glastir interventions by contract-holders/land-managers and the capture of those within the baseline GMEP survey. An approach was needed which would maximise outputs matched to policy priorities for assessing national trends, provide evidence for the outcomes of Glastir interventions and optimise where changes were most likely to be detected. The target is to reduce survey squares from 300 to 240 1km squares.

Atmospheric pollution by reactive nitrogen (N) can have profound effects on ecosystem functioning and biodiversity. Numerous mechanisms are involved, and response times vary among habitats and species. This complex picture can make it difficult to convey the benefits of controlling N pollution to policy developers and the public. In this study we evaluate pressure, midpoint, and endpoint metrics for N pollution, considering those currently in use and proposing some improved metrics. Pressure metrics that use the concept of a critical load (CL) are useful, and we propose a new integrated measure of cumulative exposure above the CL that allows for different response times in different habitats. Biodiversity endpoint metrics depend greatly on societal values and priorities and so are inevitably somewhat subjective. Species richness is readily understood, but biodiversity metrics based on habitat suitability for particular taxa may better reflect the priorities of nature conservation specialists. Midpoint metrics indicate progress towards desired endpoints – the most promising are those based on empirical evidence. Moss tissue N enrichment is responsive to lower N deposition rates, and we propose a new Moss Enrichment Index (MEI) based on species-specific ranges of tissue N content. At higher N deposition rates, mineral N leaching is an appropriate midpoint indicator. Biogeochemical models can also be used to derive midpoint metrics which illustrate the large variation in potential response times among ecosystem components. Metrics have an important role in encouraging progress towards reducing pollution, and need to be chosen accordingly.

The majority of the Earth’s terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12–17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon–climate feedback that could accelerate climate change.

Field experiments that expose terrestrial ecosystems to climate change factors by manipulations are expensive to maintain, and typically only last a few years. Plant biomass is commonly used to assess responses to climate treatments and to predict climate change impacts. However, response to the treatments might be considerably different between the early years and a decade later. The aim of this data analysis was to develop and apply a method for evaluating changes in plant biomass responses through time, in order to provide a firm basis for discussing how the ‘short-term’ response might differ from the ‘long-term’ response. Across 22 sites situated in the northern hemisphere, which covered three continents, and multiple ecosystems (grasslands, shrublands, moorlands, forests, and deserts), we evaluated biomass datasets from long-term experiments with exposure to elevated CO2 (eCO2), warming, or drought. We developed methods for assessing biomass response patterns to the manipulations using polynomial and linear (piecewise) model analysis and linked the responses to site-specific variables such as temperature and rainfall. Polynomial patterns across sites indicated changes in response direction over time under eCO2, warming, and drought. In addition, five distinct pattern types were confirmed within sites: ‘no response’, ‘delayed response’, ‘directional response’, ‘dampening response’, and ‘altered response’ patterns. We found that biomass response direction was as likely to change over time as it was to be consistent, and therefore suggest that climate manipulation experiments should be carried out over timescales covering both short- and long-term responses, in order to realistically assess future impacts of climate change.

Site-occupancy models that predict habitat suitability for plant species in relation to measurable environmental factors can be useful for conservation planning. Such models can be derived from large-scale presence–absence datasets on the basis of environmental observations or, where only floristic data are available, using plant trait values averaged across a plot. However, the estimated modelled relationship between species presence and environmental variables depends on the type of statistical model adopted and hence can introduce additional uncertainty. Authors used an ensemble-modelling approach to constrain and quantify the uncertainty because of the choice of statistical model, applying generalised linear models (GLM), generalised additive models (GAM), and multivariate adaptive regression splines (MARS). Niche models were derived for over 1000 species of vascular plants, bryophytes and lichens, representing a large proportion of the British flora and many species occurring in continental Europe. Each model predicts habitat suitability for a species in response to climate variables and trait-based scores (evaluated excluding the species being modelled) for soil pH, fertility, wetness and canopy height. An R package containing the fitted models for each species is presented which allows the user to predict the habitat suitability of a given set of conditions for a particular species. Further functions within the package are included so that these habitat suitability scores can be plotted in relation to individual explanatory variables. A simple case study shows how the R package (MultiMOVE) can be used quickly and efficiently to answer questions of scientific interest, specifically whether climate change will counteract any benefits of sheep-grazing for a particular plant community. The package itself is freely available via http://doi.org/10.5285/94ae1a5a-2a28-4315-8d4b-35ae964fc3b9.

Plant production is a key process in semi-natural ecosystems, affecting resource provision, carbon storage, and habitat suitability for species of conservation concern. There is debate over whether nitrogen (N) or phosphorus (P) limits productivity more widely, and whether the pattern of limitation has been affected by widespread atmospheric N pollution. In a national-scale survey, floristic composition was used to derive mean Ellenberg N score (EN) for use as an independent metric of productivity. Much of the variation in EN within extensively-managed habitats could be explained by bulk-soil properties such as total C and moisture contents, reflecting the axis from wet, organic, infertile soils to drier, mineral, fertile soils. However, this main axis of variation was also explained well by bicarbonate-extractable P stock, and P stock was included in the best 88 of 255 possible models for all habitats, or the best 55 of 255 models for extensively-managed habitats. The stock of mineralisable N was much less well able to explain variation in the productivity metric, particularly in extensively-managed habitats. This suggests that P availability is a more widespread constraint to the productivity of semi-natural ecosystems in the UK than is N availability.

We combined published and new radiocarbon and ancillary data for uncultivated topsoils (typically 15 cm depth), to make two databases, one for the United Kingdom (133 sites), and one global (114 sites). Forest topsoils are significantly higher in radiocarbon than non-forest soils, indicating greater enrichment with ‘‘bomb carbon’’ and therefore faster C turnover, if steady-state conditions are assumed. Steady-state modelling, taking into account variations in atmospheric 14CO2, including the effects of 20th century nuclear weapons testing and radioactive decay, was used to quantify soil carbon turnover rates. Application of a model with variable slow (20 year mean residence time, MRT) and passive (1,000 year MRT) carbon pools partitioned the topsoil C approximately equally, on average, between the two pools when the entire data set was considered. However, the mean slow:passive ratio of 0.65:0.35 for forest soil was highly significantly different (p\0.001) from the 0.40:0.60 ratio for non-forest soils. Values of the slow and passive fractions were normally distributed, but the non-forest fractions showed greater variation, with approximately twice the relative standard deviations of the forest values. Assuming a litter input of 500 g C m-2 a-1, average global C fluxes (g C m-2 a-1) of forest soils are estimated to be 298 (through a fast pool ofMRT1 year), 200 (slow pool) and 2.0 (passive pool), while for non-forest soils, respective average fluxes of 347, 150 and 3.3 g C m-2 a-1 are obtained. The results highlight the widespread global phenomenon of topsoil C heterogeneity, and indicate key differences between forest and non-forest soils relevant for understanding and managing soil C.