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Funder: Royal Society for the Protection of Birds, Agri‐environment schemes (AES) are the primary policy mechanism for addressing farmland biodiversity declines across Europe. Despite previous studies on the impacts of AES on biodiversity, there is little empirical evidence on the scale of provision required to reverse declines. Across three regions of lowland England with contrasting farm systems (arable, pastoral, mixed), we estimated avian population growth rates (PGRs) on farmland with high AES provision (‘higher‐tier’: average bird‐friendly option cover = 7.4%), low AES provision (‘lower‐tier’: 2.3%) and no bird‐friendly AES (‘no AES’). Ten‐year PGRs were derived for 24 species and three multi‐species groups comprising farmland‐associated species (‘farmland birds’), species of conservation concern (‘priority birds’) and species restricted to farmland (‘specialist birds’). We used PGRs to simulate the proportion of the regional farmland landscape that would have to be assigned to higher‐ and lower‐tier agreements to stabilise or increase populations. In the arable and pastoral regions, 13/23 and 13/22 species, respectively, had more positive PGRs under higher‐tier AES than on no AES farmland (none had more negative PGRs), compared to 4/22 (positive) and 1/22 (negative) in the mixed region. Only two to four species per region exhibited more positive PGRs under lower‐tier AES compared to no AES farmland. Multi‐species PGRs in the arable and pastoral regions increased from no AES (strong decline), to lower‐tier (decline or stability) to higher‐tier (moderate or strong increase). There was no overall AES effect in the mixed region. To increase regional farmland bird populations by 10% over 10 years, 47% and 26% of the farmed landscape would need to be devoted to higher‐tier agreements in arable and pastoral landscapes respectively. This falls to 34% and 17% when higher‐tier is targeted at localities supporting higher abundances of target species, and to 29% and 10% when 30% of the farmed landscape is also devoted to lower‐tier. Priority and specialist birds require higher provision levels. Policy implications. Where farmland bird recovery is an AES objective, farms should prioritise higher‐tier agreement delivery over lower‐tier. Farmland bird responses to AES provision are likely to vary regionally, but careful targeting will reduce the amount needed in the landscape.

Lower diversity of plant and animal farmland species are usually reported where cropland has been aggregated into larger fields, which raises prospects of curbing declines in European farmland biodiversity and associated ecosystem services by halting trends to field size increases associated to agricultural intensification, without having to set aside arable land for conservation. Here, we consider the factors underlying trade‐offs between farmer income and biodiversity as mediated by field size at local and landscape scales, and how these trade‐offs may be overcome. Field sizes are still increasing, facilitated by increasing farm sizes and land consolidation. Decreases in working time and fuel expenses when fields are larger, uptake of larger machinery and subsidies favoring larger farms provide incentives to manage land in larger units, putting farmland biodiversity further at risk. Yet, field size‐mediated ecological–economic trade‐offs are largely ignored in policy and research. We recommend internalizing the ecological effects of changes in landscape‐scale field size into land consolidation scheme design, ensuring that EU Common Agricultural Policy post‐2020 rewards farmers that maintain and recreate fine‐grained landscapes where these are essential for farmland biodiversity targets, and reducing economic–ecological trade‐offs by stimulating agricultural research and innovation for economically efficient yet biodiversity‐friendly farming in fine‐grained landscapes.

1. Bee populations and other pollinators face multiple, synergistically acting threats, which have led to population declines, loss of local species richness and pollination services, and extinctions. However, our understanding of the degree, distribution and causes of declines is patchy, in part due to inadequate monitoring systems, with the challenge of taxonomic identification posing a major logistical barrier. Pollinator conservation would benefit from a high-throughput identification pipeline.\ud \ud 2. We show that the metagenomic mining and resequencing of mitochondrial genomes (mitogenomics) can be applied successfully to bulk samples of wild bees. We assembled the mitogenomes of 48 UK bee species and then shotgun-sequenced total DNA extracted from 204 whole bees that had been collected in 10 pan-trap samples from farms in England and been identified morphologically to 33 species. Each sample data set was mapped\ud against the 48 reference mitogenomes.\ud \ud 3. The morphological and mitogenomic data sets were highly congruent. Out of 63 total species detections in the morphological data set, the mitogenomic data set made 59 correct detections (93�7% detection rate) and detected\ud six more species (putative false positives). Direct inspection and an analysis with species-specific primers suggested that these putative false positives were most likely due to incorrect morphological IDs. Read frequency\ud significantly predicted species biomass frequency (R2 = 24�9%). Species lists, biomass frequencies, extrapolated\ud species richness and community structure were recovered with less error than in a metabarcoding pipeline.\ud \ud 4. Mitogenomics automates the onerous task of taxonomic identification, even for cryptic species, allowing the\ud tracking of changes in species richness and istributions. A mitogenomic pipeline should thus be able to contain\ud costs, maintain consistently high-quality data over long time series, incorporate retrospective taxonomic revisions and provide an auditable evidence trail. Mitogenomic data sets also provide estimates of species counts within samples and thus have potential for tracking population trajectories.

The recent growth in bioenergy crop cultivation, stimulated by the need to implement measures to reduce net CO2 emissions, is driving major land-use changes with consequences for biodiversity and ecosystem service provision. Although the type of bioenergy crop and its associated management is likely to affect biodiversity at the local (field) scale, landscape context and its interaction with crop type may also influence biodiversity on farms. In this study, we assessed the impact of replacing conventional agricultural crops with two model bioenergy crops (either oilseed rape Brassica napus or Miscanthus à  giganteus) on vascular plant, bumblebee, solitary bee, hoverfly and carabid beetle richness, diversity and abundance in 50 sites in Ireland. We assessed whether within-field biodiversity was also related to surrounding landscape structure. We found that local- and landscape-scale variables correlated with biodiversity in these agricultural landscapes. Overall, the differences between the bioenergy crops and the conventional crops on farmland biodiversity were mostly positive (e.g. higher vascular plant richness in Miscanthus planted on former conventional tillage, higher solitary bee abundance and richness in Miscanthus and oilseed rape compared with conventional crops) or neutral (e.g. no differences between crop types for hoverflies and bumblebees). We showed that these crop type effects were independent of (i.e. no interactions with) the surrounding landscape composition and configuration. However, surrounding landscape context did relate to biodiversity in these farms, negatively for carabid beetles and positively for hoverflies. Although we conclude that the bioenergy crops compared favourably with conventional crops in terms of biodiversity of the taxa studied at the field scale, the effects of large-scale planting in these landscapes could result in very different impacts. Maintaining ecosystem functioning and the delivery of ecosystem services will require a greater understanding of impacts at the landscape scale to ensure the sustainable development of climate change mitigation measures. This research was funded by the SIMBIOSYS Project (http://www.tcd.ie/research/simbiosys/, 2007-B-CD-1-S1) as part of the Science, Technology, Research and Innovation for the Environment (STRIVE) Programme, financed by the Irish Government under the National Development Plan 2007–2013, administered on behalf of the Department of the Environment, Heritage and Local Government by the Irish Environmental Protection Agency. peer-reviewed

Major conservation efforts in human‐dominated systems, such as farmland, have focused on the establishment of subsidies and compensation promoting low‐impact management practices to reverse the impacts of conservation threats in the short term (reactive approaches). In this study, we discuss how a different way of framing conservation policy (proactive approaches) could lead to fundamentally different long‐term conservation outcomes. We define proactive approaches as those not necessarily including measures directly addressing the threats affecting biodiversity, but promoting transitions from current scenarios in which species are threatened to new states in which the threat is no longer present. We illustrate reactive and proactive approaches using as a case study two contrasting conservation frameworks for a vulnerable farmland bird, the Montagu's harrier (Circus pygargus ) in northeastern Spain. This example shows that reactive approaches can lead to “conservation traps,” which we defined as situations where the application of biologically focused actions in response to conservation problems results in an unsustainable need to perpetuate the implementation of those actions. Our aim is to offer a fresh perspective on biodiversity conservation in human‐dominated systems and to stimulate alternative, more holistic approaches in conservation promoting transitions to new states not requiring long‐term active and costly conservation action. This work is a contribution to the project BIONOVEL (CGL2011‐ 29539/BOS) and the project Steppeahead, funded by CSIC, Fundación General CSIC, and Banco Santander.