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Natural pest and weed regulation are essential for agricultural production, but the spatial distribution of natural enemies within crop fields and its drivers are mostly unknown. Using 28 datasets comprising 1204 study sites across eight Western and Central European countries, we performed a quantitative synthesis of carabid richness, activity densities and functional traits in relation to field edges (i.e. distance functions). We show that distance functions of carabids strongly depend on carabid functional traits, crop type and, to a lesser extent, adjacent non-crop habitats. Richness of both carnivores and granivores, and activity densities of small and granivorous species decreased towards field interiors, whereas the densities of large species increased. We found strong distance decays in maize and vegetables whereas richness and densities remained more stable in cereals, oilseed crops and legumes. We conclude that carabid assemblages in agricultural landscapes are driven by the complex interplay of crop types, adjacent non-crop habitats and further landscape parameters with great potential for targeted agroecological management. In particular, our synthesis indicates that a higher edge–interior ratio can counter the distance decay of carabid richness per field and thus likely benefits natural pest and weed regulation, hence contributing to agricultural sustainability.

Birds are useful indicators of overall biodiversity, which continues to decline globally, despite targets to reduce its loss. The aim of this paper is to understand the importance of different spatial drivers for modelling bird distributions. Specifically, it assesses the importance of satellite‐derived measures of habitat productivity, heterogeneity and landscape structure for modelling bird diversity across Great Britain. Random forest (RF) regression is used to assess the extent to which a combination of satellite‐derived covariates explain woodland and farmland bird diversity and richness. Feature contribution analysis is then applied to assess the relationships between the response variable and the covariates in the final RF models. We show that much of the variation in farmland and woodland bird distributions is explained (R2 0.64–0.77) using monthly habitat‐specific productivity values and landscape structure (FRAGSTATS) metrics. The analysis highlights important spatial drivers of bird species richness and diversity, including high productivity grassland during spring for farmland birds and woodland patch edge length for woodland birds. The feature contribution provides insight into the form of the relationship between the spatial drivers and bird richness and diversity, including when a particular spatial driver affects bird richness positively or negatively. For example, for woodland bird diversity, the May 80th percentile Normalized Difference Vegetation Index (NDVI) for broadleaved woodland has a strong positive effect on bird richness when NDVI is >0.7 and a strong negative effect below. If relationships such as these are stable over time, they offer a useful analytical tool for understanding and comparing the influence of different spatial drivers.

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.

•1. Declines in farmland biodiversity remain evident despite over three decades of research and implementation of agri-environment schemes (AES). Although positive effects of AES are often demonstrated locally or in the short term, studies exploring longer term trends in biodiversity often show contradictory results. Evidence for the potential of AES to drive beneficial changes in populations remains sparse, especially for mobile taxa such as birds and butterflies. •2. We analysed the abundance of 12 widespread bird and 9 butterfly species from a 10-year study of AES intervention in a farmland landscape in southern England. We compared estimates of annual population growth rates from our study landscape with rates derived from large-scale national monitoring schemes in equivalent landscapes without substantial AES. •3. Species trends in our study landscape were frequently stable or increasing, in contrast to concurrent declining trends in equivalent landscapes without AES. These differences were significant for total abundance of granivorous species and for chaffinch Fringilla coelebs, blue tit Cyanistes caeruleus and great tit Parus major individually. For butterflies, differences in trends were significantly more positive for gatekeeper Pyronia tithonus and green-veined white Pieris napi, while small white P. rapae showed a trend that was significantly more negative in our study landscape. •4. Synthesis and applications. Our results demonstrate that, for some bird and butterfly species, the higher abundances associated with areas of AES uptake within a typical commercial farmland landscape can co-occur with positive or stable population trends over long time scales and that these trends can show significant differences from those in equivalent landscapes without substantial AES interventions. Our results suggest that previously observed inconsistencies in AES benefits may in part reflect a lack of long-term studies with accurate data on AES uptake and quality (i.e

The Glastir Monitoring and Evaluation Programme (GMEP) ran from 2013 until 2016 and was probably the most comprehensive programme of ecological study ever undertaken at a national scale in Wales. The programme aimed to (1) set up an evaluation of the environmental effects of the Glastir agri-environment scheme and (2) quantify environmental status and trends across the wider countryside of Wales. The focus was on outcomes for climate change mitigation, biodiversity, soil and water quality, woodland expansion, and cultural landscapes. As such, GMEP included a large field-survey component, collecting data on a range of elements including vegetation, land cover and use, soils, freshwaters, birds, and insect pollinators from up to three-hundred 1 km survey squares throughout Wales. The field survey capitalised upon the UK Centre for Ecology & Hydrology (UKCEH) Countryside Survey of Great Britain, which has provided an extensive set of repeated, standardised ecological measurements since 1978. The design of both GMEP and the UKCEH Countryside Survey involved stratified-random sampling of squares from a 1 km grid, ensuring proportional representation from land classes with distinct climate, geology and physical geography. Data were collected from different land cover types and landscape features by trained professional surveyors, following standardised and published protocols. Thus, GMEP was designed so that surveys could be repeated at regular intervals to monitor the Welsh environment, including the impacts of agri-environment interventions. One such repeat survey is scheduled for 2021 under the Environment and Rural Affairs Monitoring & Modelling Programme (ERAMMP). Data from GMEP have been used to address many applied policy questions, but there is major potential for further analyses. The precise locations of data collection are not publicly available, largely for reasons of landowner confidentiality. However, the wide variety of available datasets can be (1) analyse

Aim: Hotspots of human activity are focal points for ecosystem disturbance and non‐native introduction, from which invading populations disperse and spread. As such, connectivity to locations used by humans may influence the likelihood of invasion. Moreover, connectivity in freshwater ecosystems may follow the hydrological network. Here we tested whether multiple forms of connectivity to human recreational activities promotes biological invasion of freshwater ecosystems. Location: England, UK. Time period: 1990–2018. Major taxa studied: One hundred and twenty‐six non‐native freshwater birds, crustaceans, fish, molluscs and plants. Methods: Machine learning was used to predict spatial gradients in human recreation and two high risk activities for invasion (fishing and water sports). Connectivity indices were developed for each activity, in which human influence decayed from activity hotspots according to Euclidean distance (spatial connectivity) or hydrological network distance (downstream, upstream and along‐channel connectivity). Generalized linear mixed models identified the connectivity type most associated to invasive species richness of each group, while controlling for other anthropogenic and environmental drivers. Results: Connectivity to humans generally had stronger positive effects on invasion than all other drivers except recording effort. Recreation had stronger influence than urban land cover, and for most groups high risk activities had stronger effects than general recreation. Downstream human connectivity was most important for invasion by most of the groups, potentially reflecting predominantly hydrological dispersal. An exception was birds, for which spatial connectivity was most important, possibly because of overland dispersal capacity. Main conclusions: These findings support the hypothesis that freshwater invasion is partly determined by an interaction between human activity and species dispersal in the hydrological network. By comparing altern

1. Increasing landscape heterogeneity by restoring semi‐natural elements to reverse farmland biodiversity declines is not always economically feasible or acceptable to farmers due to competition for land. We hypothesized that increasing the heterogeneity of the crop mosaic itself, hereafter referred to as crop heterogeneity, can have beneficial effects on within‐field plant diversity. 2. Using a unique multi‐country dataset from a cross‐continent collaborative project covering 1,451 agricultural fields within 432 landscapes in Europe and Canada, we assessed the relative effects of compositional and configurational crop heterogeneity on within‐field plant diversity components. We also examined how these relationships were modulated by the position within the field. 3. We found strong positive effects of configurational crop heterogeneity on within‐field plant alpha and gamma diversity in field interiors. These effects were as high as the effect of semi‐natural cover. In field borders, effects of crop heterogeneity were limited to alpha diversity. We suggest that a heterogeneous crop mosaic may overcome the high negative impact of management practices on plant diversity in field interiors, whereas in field borders, where plant diversity is already high, landscape effects are more limited. 4. Synthesis and applications. Our study shows that increasing configurational crop heterogeneity is beneficial to within‐field plant diversity. It opens up a new effective and complementary way to promote farmland biodiversity without taking land out of agricultural production. We therefore recommend adopting manipulation of crop heterogeneity as a specific, effective management option in future policy measures, perhaps adding to agri‐environment schemes, to contribute to the conservation of farmland plant diversity.

The ability to predict spatial variation in biodiversity is a long-standing but elusive objective of landscape ecology. It depends on a detailed understanding of relationships between landscape and patch structure and taxonomic richness, and accurate spatial modelling. Complex heterogeneous environments such as cities pose particular challenges, as well as heightened relevance, given the increasing rate of urbanisation globally. Here we use a GIS-linked Bayesian Belief Network approach to test whether landscape and patch structural characteristics (including vegetation height, green-space patch size and their connectivity) drive measured taxonomic richness of numerous invertebrate, plant, and avian groups. We find that modelled richness is typically higher in larger and better-connected green-spaces with taller vegetation, indicative of more complex vegetation structure and consistent with the principle of ‘bigger, better, and more joined up’. Assessing the relative importance of these variables indicates that vegetation height is the most influential in determining richness for a majority of taxa. There is variation, however, between taxonomic groups in the relationships between richness and landscape structural characteristics, and the sensitivity of these relationships to particular predictors. Consequently, despite some broad commonalities, there will be trade-offs between different taxonomic groups when designing urban landscapes to maximise biodiversity. This research demonstrates the feasibility of using a GIS-coupled Bayesian Belief Network approach to model biodiversity at fine spatial scales in complex landscapes where current data and appropriate modelling approaches are lacking, and our findings have important implications for ecologists, conservationists and planners.

Agricultural landscape homogenization has detrimental effects on biodiversity and key ecosystem services. Increasing agricultural landscape heterogeneity by increasing seminatural cover can help to mitigate biodiversity loss. However, the amount of seminatural cover is generally low and difficult to increase in many intensively managed agricultural landscapes. We hypothesized that increasing the heterogeneity of the crop mosaic itself (hereafter “crop heterogeneity”) can also have positive effects on biodiversity. In 8 contrasting regions of Europe and North America, we selected 435 landscapes along independent gradients of crop diversity and mean field size. Within each landscape, we selected 3 sampling sites in 1, 2, or 3 crop types. We sampled 7 taxa (plants, bees, butterflies, hoverflies, carabids, spiders, and birds) and calculated a synthetic index of multitrophic diversity at the landscape level. Increasing crop heterogeneity was more beneficial for multitrophic diversity than increasing seminatural cover. For instance, the effect of decreasing mean field size from 5 to 2.8 ha was as strong as the effect of increasing seminatural cover from 0.5 to 11%. Decreasing mean field size benefited multitrophic diversity even in the absence of seminatural vegetation between fields. Increasing the number of crop types sampled had a positive effect on landscape-level multitrophic diversity. However, the effect of increasing crop diversity in the landscape surrounding fields sampled depended on the amount of seminatural cover. Our study provides large-scale, multitrophic, cross-regional evidence that increasing crop heterogeneity can be an effective way to increase biodiversity in agricultural landscapes without taking land out of agricultural production.

Agricultural intensification is one of the main causes for the current biodiversity crisis. While reversing habitat loss on agricultural land is challenging, increasing the farmland configurational heterogeneity (higher field border density) and farmland compositional heterogeneity (higher crop diversity) has been proposed to counteract some habitat loss. Here, we tested whether increased farmland configurational and compositional heterogeneity promote wild pollinators and plant reproduction in 229 landscapes located in four major western European agricultural regions. High-field border density consistently increased wild bee abundance and seed set of radish (Raphanus sativus), probably through enhanced connectivity. In particular, we demonstrate the importance of crop–crop borders for pollinator movement as an additional experiment showed higher transfer of a pollen analogue along crop–crop borders than across fields or along semi-natural crop borders. By contrast, high crop diversity reduced bee abundance, probably due to an increase of crop types with particularly intensive management. This highlights the importance of crop identity when higher crop diversity is promoted. Our results show that small-scale agricultural systems can boost pollinators and plant reproduction. Agri-environmental policies should therefore aim to halt and reverse the current trend of increasing field sizes and to reduce the amount of crop types with particularly intensive management.

Small, 1st and 2nd-order, headwater streams and ponds play essential roles in providing natural flood control, trapping sediments and contaminants, retaining nutrients, and maintaining biological diversity, which extend into downstream reaches, lakes and estuaries. However, the large geographic extent and high connectivity of these small water bodies with the surrounding terrestrial ecosystem makes them particularly vulnerable to growing land-use pressures and environmental change. The greatest pressure on the physical processes in these waters has been their extension and modification for agricultural and forestry drainage, resulting in highly modified discharge and temperature regimes that have implications for flood and drought control further downstream. The extensive length of the small stream network exposes rivers to a wide range of inputs, including nutrients, pesticides, heavy metals, sediment and emerging contaminants. Small water bodies have also been affected by invasions of non-native species, which along with the physical and chemical pressures, have affected most groups of organisms with consequent implications for the wider biodiversity within the catchment. Reducing the impacts and restoring the natural ecosystem function of these water bodies requires a three-tiered approach based on: restoration of channel hydromorphological dynamics; restoration and management of the riparian zone; and management of activities in the wider catchment that have both point-source and diffuse impacts. Such activities are expensive and so emphasis must be placed on integrated programmes that provide multiple benefits. Practical options need to be promoted through legislative regulation, financial incentives, markets for resource services and voluntary codes and actions.

1. Public data archiving (PDA) is widely advocated as a means of achieving open data standards, leading to improved data preservation, increased scientific reproducibility, and transparency, as well as additional data use. 2. Public data archiving was primarily conceived to archive data from short‐term, single‐purpose scientific studies. It is now more widely applied, including to large‐scale citizen science biodiversity recording and monitoring schemes which combine the efforts of volunteers with professional scientists. 3. This may affect the financial security of such schemes by reducing income from data and analytical services. Communication between scheme organizers and researchers may be disrupted, reducing scientific quality and impeding scheme development. It may also have an impact on the participation of some volunteers. 4. Synthesis and applications. In response to the challenges of public data archiving for citizen science biodiversity recording and monitoring schemes, the archive function of scheme organizations should be better recognized by those promoting open data principles. Increased financial support from the public sector or from commercial or academic data users may offset financial risk. Those in favour of public data archiving should do more to facilitate communication between nonscheme users and the originating schemes, while a more flexible approach to data archiving may be required to address potential impacts on volunteer participation.

Spatial environmental heterogeneity (EH) is an important factor determining species richness among many taxa across spatial scales. Increased EH may support higher diversity mainly by providing a higher number of ecological niches. However, the shapes of the EH-diversity relationships and their influence on diversity measures at landscape scales are poorly understood. We used random forests regression models to assess the relationships between different components of EH and bird species richness across Great Britain. Bird data were obtained using BTO/JNCC/RSPB Breeding Bird Survey methods across 335 UK Countryside Survey (CS) 1-km squares in 2000. Data on components of EH, including; vegetation, habitat diversity, and habitat structure were collected in associated field surveys. Using the results of our EH component-bird richness models, we applied the case of the likely decline of the ash tree, a species of conservation concern and a key component of British landscape complexity, to create predictive scenarios of future bird richness. We found that EH components had a strong positive effect on bird richness and identified six key components that explained over 70% of variance in bird richness. Bird richness responses were strongly dependent on the specific EH components and were generally non-linear, especially for habitat structural variables, such as lines of trees and hedges. Our predictive scenarios showed a decrease in bird species richness only for simulated ash tree decreases within the habitat structural variables of over 90%, and only for areas where this tree species was a particularly abundant component of the landscape. Our findings, showing that bird richness responses differ for EH components, and that non-linear responses are common, could help the ‘design’ of landscapes that enhance bird diversity. In particular, our study indicates that, in some cases, increasing the occurrence of key structural components of habitat (such as ensuring a minimum of

Healthy natural resources underpin significant economic sectors in Wales including agriculture, fisheries, tourism and forestry, they also make a significant contribution across Cabinet policies including the health and well-being agenda. In order to develop policies that build social, economic and environmental resilience and to evaluate policy implementation, a robust natural resources monitoring framework is required. Current monitoring activities are of varying quality, not sufficiently aligned to the new legislative and policy landscape, disjointed and when considered as a whole, potentially not as cost-effective as they could be. This project was tasked with identifying options and developing recommendations for an integrated natural resources monitoring framework for Wales reflecting the ambitions and integrating principles of the Environment Act and Well Being of Future Generations Act. The monitoring community, the Welsh Government and Natural Resources Wales Core Evidence Group, the project team, stakeholders and partners, have agreed on a set of recommendations.

1. The importance of habitat for biodiversity is well established, but the two most commonly used methods to measure habitat (field survey and remote sensing) have seldom been explicitly compared. 2. We compare high-resolution sample-based field survey (Countryside Survey) with medium-resolution remotely sensed habitat data (the highest resolution of Land Cover Map available) for Great Britain. Variation in abundance of 60 bird species from 335 1 km squares was modelled using habitat predictors from the two methods. Model comparisons assessed the explanatory power of (i) field survey vs. remotely sensed data and (ii) coarse information on habitat areas (Broad Habitats) vs. fine-grained information on Landscape Features. 3. Field survey data (combining Broad Habitat and Landscape Feature predictors) explained more variation in bird abundance than remotely sensed data (comprising Broad Habitat predictors only) for 57 species and had significantly higher mean explanatory power, averaged across 60 species models. The relative explanatory power of remote sensing, as a proportion of that provided by field data, was measured at 73%, aver aged across 60 species models. Predictions from field survey Broad Habitat data were more accurate than those from either remotely sensed Broad Habitat data or field survey Landscape Feature data, averaged across 60 species models. 4. High-resolution data generate more reliable models of predicted local population responses to land use change than lower resolution remotely sensed data. Collection of field data is typically costly in time, labour and resources, making use of remote sensing more feasible for assessment at larger spatial extents if data of equivalent value are produced, but the cost–benefit threshold between the two is likely to be context specific. However, integration of field survey with remotely sensed data provides accurate predictions of bird distributions, which suggests that both forms of data should be considered for future biod

The Welsh Government has commissioned a comprehensive new ecosystem monitoring and evaluation programme to monitor the effects of Glastir, its new land management scheme, and to monitor progress towards a range of international biodiversity and environmental targets. A random sample of 1 km squares stratified by landcover types will be used both to monitor change at a national level in the wider countryside and to provide a backdrop against which intervention measures are assessed using a second sample of 1 km squares located in areas eligible for enhanced payments for advanced interventions. Modelling in the first year has forecast change based on current understanding, whilst a rolling national monitoring programme based on an ecosystem approach will provide an evidence-base for on-going, adaptive development of the scheme by Welsh Government. To our knowledge, this will constitute the largest and most in-depth ecosystem monitoring and evaluation programme of any member state of the European Union.