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Context Declining biodiversity in agricultural landscapes has increased the need for research and monitoring of insect abundance and diversity at the landscape level. Objectives We investigated the accuracy of different spatial sampling designs in estimating landscape-level abundance and species richness of carabids in agricultural landscapes and, further, which sample size per landscape section was required and whether dominating land use or landscape subdivision affected accuracy and required sample size. Methods We developed a simulation model that created raster maps of agricultural landscapes, compiled local carabid communities (species composition and abundances) within raster cells and simulated the sampling of carabids with pitfall traps using different spatial sampling designs and sample sizes between 4 and 49 sampling points per landscape section. Spatial sampling designs included random, systematic grid-based, stratified and clustered schemes. Results To estimate landscape-level abundance, area-proportional stratified random sampling was most accurate followed by systematic grid-based designs. A sample size of 25 appeared to be the best trade-off between accuracy and sampling cost. Accuracy was not affected substantially by landscape characteristics in most cases. With respect to species richness, all designs except for clustered sampling had comparable accuracies, but even 49 samples were not sufficient to detect 80% of the species. Conclusion Systematic grid-based designs are generally recommendable for sampling of carabids in agricultural landscapes and, in case a carabid-specific habitat classification is available, area-proportional stratified random sampling provides optimal accuracy for estimating landscape-level abundance. For assessment of species richness, large sample size is more important than spatial sampling design.

Determination of sample size (the number of replications) is a key step in the design of an observational study or randomized experiment. Statistical procedures for this purpose are readily available. Their treatment in textbooks is often somewhat marginal, however, and frequently the focus is on just one particular method of inference (significance test, confidence interval). Here, we provide a unified review of approaches and explain their close interrelationships, emphasizing that all approaches rely on the standard error of the quantity of interest, most often a pairwise difference of two means. The focus is on methods that are easy to compute, even without a computer. Our main recommendation based on standard errors is summarized as what we call the 1-2-3 rule for a difference of two treatment means.

Context Pollinator declines and functional homogenization of farmland insect communities have been reported. Mass-flowering crops (MFC) can support pollinators by providing floral resources. Knowledge about how MFC with dissimilar flower morphology affect functional groups and functional trait compositions of wild bee communities is scarce. Objective We investigated how two morphologically different MFC, land cover and local flower cover of semi-natural habitats (SNH) and landscape diversity affect wild bees and their functional traits (body size, tongue length, sociality, foraging preferences). Methods We conducted landscape-level wild bee surveys in SNH of 30 paired study landscapes covering an oilseed rape (OSR) (Brassica napus L.) gradient. In 15 study landscapes faba beans (Vicia faba L.) were grown, paired with respective control landscapes without grain legumes. Results Faba bean cultivation promoted bumblebees (Bombus spp. Latreille), whereas non-Bombus densities were only driven by the local flower cover of SNH. High landscape diversity enhanced wild bee species richness. Faba bean cultivation enhanced the proportions of social wild bees, bees foraging on Fabaceae and slightly of long-tongued bumblebees. Solitary bee proportions increased with high covers of OSR. High local SNH flower covers mitigated changes of mean bee sizes caused by faba bean cultivation. Conclusions Our results show that MFC support specific functional bee groups adapted to their flower morphology and can alter pollinators` functional trait composition. We conclude that management practices need to target the cultivation of functionally diverse crops, combined with high local flower covers of diverse SNH to create heterogeneous landscapes, which sustain diverse pollinator communities.

Worldwide pollinator declines lead to pollination deficits in crops and wild plants, and managed bees are frequently used to meet the increasing demand for pollination. However, their foraging can be affected by flower availability and colony size. We investigated how mass-flowering oilseed rape (OSR) can influence the pollen resource use of small and large honey bee (Apis mellifera L.) and bumble bee (Bombus terrestris L.) colonies. Colonies were placed adjacent to strawberry fields along a gradient of OSR availability in the landscapes. We used ITS2 metabarcoding to identify the pollen richness based on ITS2 amplicon sequencing and microscopy for quantification of target pollen. Bumble bees collected pollen from more different plant genera than honey bees. In both species, strawberry pollen collection decreased with high OSR availability but was facilitated by increasing strawberry flower cover. Colony size had no effect. The relationship between next-generation sequencing-generated ITS2 amplicon reads and microscopic pollen counts was positive but pollen type-specific. Bumble bees and, to a lesser degree, honey bees collected pollen from a wide variety of plants. Therefore, in order to support pollinators and associated pollination services, future conservation schemes should sustain and promote pollen plant richness in agricultural landscapes. Both bee species responded to the availability of flower resources in the landscape. Although honey bees collected slightly more strawberry pollen than bumble bees, both can be considered as crop pollinators. Metabarcoding could provide similar quantitative information to microscopy, taking into account the pollen types, but there remains high potential to improve the methodological weaknesses.

Context: Declining biodiversity in agricultural landscapes has increased the need for research and monitoring of insect abundance and diversity at landscape level.Objectives: We investigated the accuracy of different spatial sampling designs in estimating landscape-level abundance and species richness of carabids in agricultural landscapes and, further, which sample size per landscape section was required and whether dominating land use or landscape subdivision affected accuracy and required sample size.Methods: We developed a simulation model that created raster maps of agricultural landscapes, compiled local carabid communities (species composition and abundances) within raster cells and simulated the sampling of carabids with pitfall traps using different spatial sampling designs and sample sizes between 4 and 49 sampling points per landscape section. Spatial sampling designs included random, systematic grid-based, stratified and clustered schemes.Results: To estimate landscape-level abundance, area-proportional stratified random sampling was most accurate followed by systematic grid-based designs. A sample size of 25 appeared to be the best trade-off between accuracy and sampling cost. Accuracy was not affected substantially by landscape characteristics in most cases. With respect to species richness, all designs except for clustered sampling had comparable accuracies, but even 49 samples were not sufficient to detect 80 % of the species.Conclusions: Systematic grid-based designs are generally recommendable for sampling of carabids in agricultural landscapes and, in case a carabid-specific habitat classification is available, area-proportional stratified random sampling provides optimal accuracy for estimating landscape-level abundance. For assessment of species richness, large sample size is more important than spatial sampling design.

1. Concerns about insect declines are growing and the provisioning of ecosystem services like pollination may be threatened. To safeguard biodiversity, greening measures were introduced within the reform of the EU's Common Agricultural Policy. One measure commonly applied by farmers is the cultivation of nitrogen fixing crops. Although underlying studies are largely missing, this measure is criticized as providing no significant biodiversity benefit. 2. Using a landscape-scale approach, we selected 30 paired study landscapes (1 km × 1 km) in Germany, that is, 15 study landscapes with faba bean (FB) fields (Vicia faba L .) a nd 15 w ithout a ny g rain l egumes. F lower-visiting w ild b ees were recorded with transect walks at the field margins of different crops using a stratified sampling approach. We analysed the effect of FB cultivation and landscape composition on the abundance and species richness of wild bees as well as on the functional composition of the bee communities. 3. Bumblebee densities (Bombus spp. Latreille) were more than twice as high in FB compared to control landscapes after the flowering of the beans. Non-Bombus wild bee densities, however, were not affected by FB cultivation, but were enhanced by increasing amounts of semi-natural habitats (SNH). 4. After the beans' blooming had ceased, FB landscapes had a higher proportion of wild bees collecting pollen from Fabaceae than control landscapes. The communityweighted means for bee size, measured as intertegular distance, were not affected by FB cultivation, but we found smaller species and species with shorter tongues with an increasing percentage of SNH. 5. Synthesis and applications. The cultivation of faba bean Vicia faba L . s trongly increased bumblebee densities throughout the season. This indicates that also on-field greening measures can support biodiversity. Nevertheless, since only functional groups adapted to faba bean benefit, measures to promote seminatural habitats in agricultural landscapes need to be implemented. We conclude that the combination of on- and off-field measures is essential to maintain farmland biodiversity and the Common Agricultural Policy should furthermore promote both.

Downy mildew of common sage (Salvia officinalis), caused by Peronospora salviae-officinalis, has become a serious problem in sage production worldwide. The effect of temperature was determined for conidia germination and disease development. In vitro, conidial germination rate was highest at temperatures between 10 °C and 20 °C and was strongly reduced at temperatures above 25, but conidia were also able to germinate at 2 °C. Temperatures between 15 and 20 °C were most favourable for infection and disease progress in infection experiments in climate chambers, with highest sporulating leaf area observed at 15 and 20 °C, and highest symptomatic leaf area at 20 °C. P. salviae-officinalis is still able to infect sage plants at 5 °C, but sporulation was only observed at higher temperatures. Oospores developed 14 days after inoculation at 15 °C, and 8 days after inoculation at 20 and 25 °C. The infection trials also showed that dark incubation is not a prerequisite for successful infection of sage. Furthermore, P. salviae-officinalis needs two events of leaf wetness or high humidity to complete its asexual life cycle. First, a leaf wetness event of at least three hours is needed for conidial germination and penetration of the host. Second, high humidity of at least 90% is needed at the end of the infection cycle for sporulation. Seed washing revealed the presence of P. salviae-officinalis oospores in seed lots of sage suggesting that infested seeds might play a major role in the fast spread of sage downy mildew, which is an important finding for phytosanitary or quarantine measures.

Pesticides used in seed coatings can influence seed consumption by birds and, therefore, actual exposure risk for them. A quantification of such effects on consumption is currently not regarded as a refinement factor in environmental risk assessments, although it is a possible option and should be considered, for example, for comparing exposure risk of different pesticides. It can highlight avoidance behavior, preventing birds from taking up lethal or sublethal pesticide doses. To formulate a standard, we developed an indoor test procedure based on established pen test methods, including 2- and no-choice phases with hunger periods. During testing, the highest standards of animal welfare were applied. Statistical approaches were used to determine the most appropriate number of replicates and for analysis. The effect on consumption of seeds is expressed as the ratio of consumed treated to untreated seeds. This consumption factor can be applied in avian risk assessments for seed treatments equivalent to an avoidance factor. We present, as an example, an application of the procedure to obtain a seed- and species-specific consumption factor for oilseed rape seeds (Brassica napus) provided untreated and treated with fungicides to greenfinches (Carduelis chloris) and Japanese quail (Coturnix japonica). Overall, bird constitution was not negatively affected by the test procedure in either species. The test procedure was suitable for showing differences in expected consumption patterns, such as greater avoidance of treated seeds in 2-choice than in no-choice tests. However, the consumption differed between species and fungicide treatments, allowing us to rank avoidance effects of different fungicides. Using the presented standard procedure to generate comparable pesticide- and species-specific consumption factors for more species and seed treatments may result in refinement of default values and reduce animal trials in different designs in the future. Environ Toxicol Chem 2020;39:359���370. �� 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Norway rats (Rattus norvegicus) need to be controlled to prevent transmission of pathogens and damages to stored products and material, leading to considerable economic risks and losses. Given increasing resistance in Norway rats, the most persistent, bio-accumulative and toxic anticoagulant rodenticides are widely used for management, which presents hazards to the environment especially for non-target species. We investigated how sanitary measures improved management of Norway rats on 12 paired livestock farms in a region of Germany with a high population of resistant rats for reducing application of rodenticides. We recorded food intake, and tracked activity and resistance frequency during the pre-treatment, treatment and post-treatment periods.In the post-treatment period, farms using sanitary measures had a higher control success with 13% more bait boxes without feeding than farms not using sanitary measures. In addition, the reoccurrence of rats was delayed by 85 days. With increasing accessibility to buildings and more precise positioning of the boxes, control success improved, especially when rats could not spread from water-bearing ditches through the sewer system, and when rat-hunting animals were present. Resistant animals were more common indoors than outdoors, and there were more resistant rats recorded before and during treatment than in the post-treatment period.The control success was substantially higher and reoccurrence was delayed using sanitary measures on farms. Sanitary measures can reduce resistance indirectly due to delayed re-colonization and establishment of resistant populations inside buildings. Hence, sanitary measures help to reduce economic losses, rodenticides required for rat management and environmental risk especially in the resistance area. © 2022 The Authors. Pest Management Science published by John WileySons Ltd on behalf of Society of Chemical Industry.

Grapevine (Vitis vinifera L.) is an economically important crop that needs to comply with high quality standards for fruit, juice and wine production. Intense plant protection is required to avoid losses caused by fungal infections. Grapevine cultivars with loose cluster architecture enable to reduce protective chemical treatments due to their enhanced resilience against fungal infections such as Botrytis cinerea induced grey mold. A recent study identified transcription factor gene VvGRF4 as determinant of inflorescence structure in exemplary samples of loose and compact quasi-isogenic ‘Pinot Noir’ clones. Here, we extended the analysis to 12 differently clustered ‘Pinot Noir’ clones originating from five different clonal selection programs. Differential gene expression of these clones was studied in three different locations over three seasons in demonstrative vineyards. Two phenotypically contrasting clones were grown at all three locations and served for standardization of downstream analyses. Differential gene expression data were correlated to the phenotypic variation of cluster architecture sub-traits. A consistent differential gene expression of VvGRF4 in relation to loose clusters was verified over the different environments and in the extended set of ‘Pinot Noir’ clones. In addition, 14 more genes with consistent expression differences between loosely and compactly clustered clones independent from season and location were identified. These genes show annotations related to cellular growth, cell wall extension, cell division and auxin metabolism. They include two more transcription factor genes.

In grapevine breeding, loose grape bunch architecture is one of the most important selection traits, contributing to an increased resilience towards Botrytis bunch rot. Grape bunch architecture is mainly influenced by the berry number, berry size, the total berry volume, and bunch width and length. For an objective, precise, and high-throughput assessment of these architectural traits, the 3D imaging sensor Artec® Spider was applied to gather dense point clouds of the visible side of grape bunches directly in the field. Data acquisition in the field is much faster and non-destructive in comparison to lab applications but results in incomplete point clouds and, thus, mostly incomplete phenotypic values. Therefore, lab scans of whole bunches (360°) were used as ground truth. We observed strong correlations between field and lab data but also shifts in mean and max values, especially for the berry number and total berry volume. For this reason, the present study is focused on the training and validation of different predictive regression models using 3D data from approximately 2000 different grape bunches in order to predict incomplete bunch traits from field data. Modeling concepts included simple linear regression and machine learning-based approaches. The support vector machine was the best and most robust regression model, predicting the phenotypic traits with an R2 of 0.70–0.91. As a breeding orientated proof-of-concept, we additionally performed a Quantitative Trait Loci (QTL)-analysis with both the field modeled and lab data. All types of data resulted in joint QTL regions, indicating that this innovative, fast, and non-destructive phenotyping method is also applicable for molecular marker development and grapevine breeding research.

The cultivation of mass-flowering crops (MFC) can promote pollinators by providing floral resources. However, there is missing knowledge about the effect of MFC cultivation history on bees and their pollination services in agricultural landscapes. We investigated how bee densities in oilseed rape (Brassica napus L.) (OSR) fields were affected by past (cultivation area of the preceding three years) and current MFC area coverages in the surrounding landscape. Moreover, we analyzed how insect pollination, its possible interaction with the plants` pod numbers and MFC covers influence yield components of individual OSR plants and calculated yields (t/ha). To test this, we conducted pollinator surveys and a pollinator exclusion experiment in one oilseed rape field in 17 agricultural landscapes in Germany. We found that wild bee densities were positively affected by past MFC covers and negatively impacted by current OSR covers, indicating enhanced pollinator populations due to previous MFC cultivation and contemporary pollinator dilution. In contrast, honeybees showed opposite responses to past and present MFC cultivation. Furthermore, seed weight per plant of open pollinated plants was positively correlated with past MFC covers. Pollinator exclusion decreased the seed number per pod and increased thousand-seed weight, while yields were unaffected. Pod number interacted with insect pollination in shaping yields, such that pollinator exclusion led to a steeper increase of yield with higher pod numbers. Insect pollination compensated for low pod numbers by increasing the plants` seed number per pod and ultimately yields. Our findings demonstrate a beneficial effect of high MFC covers in the past on bee densities and potentially yield components in the current year. Our study highlights the need for further research on how past and present landscape composition in terms of MFC cultivation interactively affect pollinator communities and their pollination services in agricultural landscapes.

New strategies for a reliable assessment of baking quality of wheat are required since the protein content is a widely discussed indicator in this respect. In this study, the indicator value of the protein content for baking quality was evaluated using almost 600 wheat samples representing different quality and varieties. NIRS calibrations were developed to estimate bread volume at different levels of processing. Bread volume increased with increasing protein content in a wide curvilinear relationship with an R 2 of 0.59. At protein contents above 12% representing the relevant range for trading, the R 2 dropped to 0.15. Different wheat varieties showed differential responses (i.e. linear and non-linear) in bread volume to increasing protein content. The performance of NIRS calibrations for bread volume were best at the processing level of dough (R 2 0.81) and good at the level of whole grains (R 2 0.70). Hence, the protein content is not a reliable indicator for baking quality on its own. Bread volume was predicted better by NIRS calibrations than by protein content. A strategy is presented paying attention to the variety specific interplay between baking quality and protein content with implications for the variety registration system, trading, breeding and nitrogen fertilisation.

Land-use change is one of the primary drivers of species loss, yet little is known about its effect on other components of biodiversity that may be at risk. Here, we ask whether, and to what extent, landscape simplification, measured as the percentage of arable land in the landscape, disrupts the functional and phylogenetic association between primary producers and consumers. Across seven European regions, we inferred the potential associations (functional and phylogenetic) between host plants and butterflies in 561 semi-natural grasslands. Local plant diversity showed a strong bottom-up effect on butterfly diversity in the most complex landscapes, but this effect disappeared in simple landscapes. The functional associations between plant and butterflies are, therefore, the results of processes that act not only locally but are also dependent on the surrounding landscape context. Similarly, landscape simplification reduced the phylogenetic congruence among host plants and butterflies indicating that closely related butterflies become more generalist in the resources used. These processes occurred without any detectable change in species richness of plants or butterflies along the gradient of arable land. The structural properties of ecosystems are experiencing substantial erosion, with potentially pervasive effects on ecosystem functions and future evolutionary trajectories. Loss of interacting species might trigger cascading extinction events and reduce the stability of trophic interactions, as well as influence the longer-term resilience of ecosystem functions. This underscores a growing realization that species richness is a crude and insensitive metric and that both functional and phylogenetic associations, measured across multiple trophic levels, are likely to provide additional and deeper insights into the resilience of ecosystems, and the functions they provide.

In response to strong selection, new mutations can arise quickly and sweep through populations, particularly, if survival and reproduction depend on certain allele copies for adaptation to rapidly changing environments, like resistance against deadly diseases or strong toxins. Since the 1950s, resistance to anticoagulant rodenticides in several rodents has emerged through single nucleotide mutations in the vitamin-K-epoxid-reductase-complex-subunit-1 (VKORC1) gene, often located in its exon 3. Detection of high prevalence and concentrations of anticoagulant rodenticides in non-target vertebrates, including carnivorous Mustelidae, let us assume that secondary exposure by feeding on poisoned prey may also cause selection along the food chain and we hypothesized that VKORC1-based resistance might also have evolved in rodents’ predators. Using newly-developed mustelid-specific primers for direct sequencing of genomic DNA, we studied VKORC1-DNA-polymorphisms in 115 mustelids of five species (Martes martes, M. foina, Mustela nivalis, M. erminea, M. putorius), obtained from northern Denmark, yielding six sites with nonsynonymous and several synonymous amino acid polymorphisms in exon 3. Comparison of these VKORC1-genotypes with hepatic rodenticide residues (obtained by HPLC combined with fluorescence or mass spectrometry) in 83 individuals (except M. martes), using generalized linear models, suggested that anticoagulant levels depended on species and specific polymorphisms. Although most VKORC-1 polymorphisms may present standing genetic variation, some are situated in resistance-mediating membrane parts of the VKORC1-encoded protein, and might be a result of selection due to exposure to anticoagulant poisons. Our new molecular markers might allow detecting indirect effects of anticoagulant rodenticides on rodent predator populations in the future.

Worldwide, small rodents are main prey items for many mammalian and avian predators. Some rodent species have pest potential and are managed with anticoagulant rodenticides (ARs). ARs are consumed by target and non-target small mammals and can lead to secondary exposure of predators. The development of appropriate risk mitigation strategies is important and requires detailed knowledge of AR residue pathways. From July 2011 to October 2013 we collected 2397 regurgitated barn owl (Tyto alba) pellets to analyze diet composition of owls on livestock farms in western Germany. 256 of them were fresh pellets that were collected during brodifacoum baiting. Fresh pellets and 742 liver samples of small mammals that were trapped during baiting in the same area were analyzed for residues of ARs. We calculated exposure risk of barn owls to ARs by comparing seasonal diet composition of owls with AR residue patterns in prey species. Risk was highest in autumn, when barn owls increasingly preyed on Apodemus that regularly showed AR residues, sometimes at high concentrations. The major prey species (Microtus spp.) that was consumed most frequently in summer had less potential to contribute to secondary poisoning of owls. There was no effect of AR application on prey composition. We rarely detected ARs in pellets (2 of 256 samples) but 13% of 38 prey individuals in barn owl nests were AR positive and substantiated the expected pathway. AR residues were present in 55% of 11 barn owl carcasses. Fluctuation in non-target small mammal abundance and differences in AR residue exposure patterns in prey species drives exposure risk for barn owls and probably other predators of small mammals. Exposure risk could be minimized through spatial and temporal adaption of AR applications (avoiding long baiting and non-target hot spots at farms) and through selective bait access for target animals.

Loose cluster architecture is an important aim in grapevine breeding since it has high impact on the phytosanitary status of grapes. This investigation analyzed the contributions of individual cluster sub-traits to the overall trait of cluster architecture. Six sub-traits showed large impact on cluster architecture as major determinants. They explained 57% of the OIV204 descriptor for cluster compactness rating in a highly diverse cross-population of 149 genotypes. Genetic analysis revealed several genomic regions involved in the expression of this trait. Based on the linkage of phenotypic features to molecular markers, QTL calculations shed new light on the genetic determinants of cluster architecture. Eight QTL clusters harbor overlapping confidence intervals of up to four co-located QTLs. A physical projection of the QTL clusters by confidence interval-flanking markers onto the PN40024 reference genome sequence revealed genes enriched in these regions.

Summary 1. The magnitude of the benefits derived from organic farming within contrasting managed landscapes remains unclear and, in particular, the potential scale-dependent response of insect parasitoids is relatively unexplored. Identifying the scale at which parasitoids are affected by organic farming will be an important step to enhance their conservation. 2. We sampled tachinid parasitoids at the centre and margin of arable and grassland fields on paired organic and conventional farms located in landscapes with different proportions of organic land. A total of 192 fields were sampled in two biogeographical regions of the UK. 3. We found that the positive effect of organic farming on tachinid parasitoid diversity can be observed at multiple spatial scales. At the local scale, we found higher abundance and species richness of tachinid parasitoids on organic than on conventional farms and on field margins than on field centres. At the landscape scale, the diversity of tachinids was higher in landscapes with higher proportions of organic land. At both scales, the positive effect of organic farming was clear for arable fields, while it was almost neutral for grasslands. 4. Synthesis and applications. Any attempt to enhance parasitoid diversity in agricultural landscapes needs to consider the local management in relation to the habitat type, location within the field and agricultural management in the surrounding landscape. To restore parasitoid diversity, the promotion of organic agriculture should aim to increase both the total extent of organic farming and the connectivity of individual farms. As the benefits of organic farming to biodiversity clearly spread beyond individual farm boundaries, any assessment of organic farming should consider these positive externalities.

Increasing crop productivity to meet rising demands for food and energy, but doing so in an environmentally sustainable manner, is one of the greatest challenges for agriculture to date. In Ireland, Miscanthus x giganteus has the potential to become a major feedstock for bioenergy production, but the economic feasibility of its cultivation depends on high yields. Miscanthus fields can have a large number of gaps in crop cover, adversely impacting yield and hence economic viability. Predominantly positive effects of Miscanthus on biodiversity reported from previous research might be attributable to high crop patchiness, particularly during the establishment phase. The aim of this research was to assess crop patchiness on a field scale and to analyse the relationship between Miscanthus yield and species richness and abundance of selected taxa of farmland wildlife. For 14 Miscanthus fields at the end of their establishment phase (4–5 years after planting), which had been planted either on improved grassland (MG) or tilled arable land (MT), we determined patchiness of the crop cover, percentage light penetration (LP) to the lower canopy, Miscanthus shoot density and height, vascular plants and epigeic arthropods. Plant species richness and noncrop vegetation cover in Miscanthus fields increased with increasing patchiness, due to higher levels of LP to the lower canopy. The species richness of ground beetles and the activity density of spiders followed the increase in vegetation cover. Plant species richness and activity density of spiders on both MT and MG fields, as well as vegetation cover and activity density of ground beetles on MG fields, were negatively associated with Miscanthus yield. In conclusion, positive effects of Miscanthus on biodiversity can diminish with increasing productivity. This matter needs to be considered when assessing the relative ecological impacts of developing biomass crops in comparison with other land use

Spatial targeting of conservation actions is indispensable to protect and maintain farmland biodiversity and associated ecosystem services. To implement region-specific conservation actions, information on the spatial distribution of farmland biodiversity and its major drivers is a prerequisite. Here, we model the spatial distribution of species-rich farmland (defined by a minimum number of indicator plant species) and landscape elements (e.g. hedgerows, ditches, patches of woodland or scrub) at the national level by combining field-based survey data from a biological monitoring programme with agri-environmental variables. Adopting factor analysis and mixed effect models, we show that the percentage cover of species-rich farmland and landscape elements can be predicted by a combination of factors describing the intensity of arable farming, topography, low-input grassland farming, landscape structure and the intensity of livestock farming. Our results demonstrate that the relative importance of these factors differed between species-rich farmland and landscape elements. The share of species-rich farmland was highest in upland and structurally complex grassland-dominated regions where extensive livestock production is practised; whereas landscape elements were most likely to occur within flat regions where edge density tends to be high. In a policy context, our generated maps contribute to identifying priority regions for conservation actions. It is proposed that in regions with high coverage of species-rich farmland priority should be given to sustaining low-input grassland farming by keeping farmers in business and preventing farmland abandonment. We conclude that this modelling approach could be adapted for application in other European countries to facilitate spatial targeting of conservation actions.

Summary 1. A substantial proportion of the global land surface is used for agricultural production. Agricultural land serves multiple societal purposes; it provides food, fuel and fibre and also acts as habitat for organisms and supports the services they provide. Biodiversity conservation and food production need to be balanced: production needs to be sustainable, while conservation cannot be totally at the expense of crop yield. 2. To identify the benefits (in terms of biodiversity conservation) and costs (in terms of reduction in yields) of agricultural management, we examined the relationship between crop yield and abundance and species density of important taxa in winter cereal fields on both organic and conventional farms in lowland England. 3. Of eight species groups examined, five (farmland plants, bumblebees, butterflies, solitary bees and epigeal arthropods) were negatively associated with crop yield, but the shape of this relationship varied between taxa. It was linear for the abundance of bumblebees and species density of butterflies, concave up for the abundance of epigeal arthropods and butterflies and concave down for species density of plants and bumblebees. 4. Grain production per unit area was 54% lower in organic compared with conventional fields. When controlling for yield, diversity of bumblebees, butterflies, hoverflies and epigeal arthropods did not differ between farming systems, indicating that observed differences in biodiversity between organic and conventional fields are explained by lower yields in organic fields and not by different management practices per se. Only percentage cover and species density of plants were increased by organic field management after controlling for yield. The abundance of solitary wild bees and hoverflies was increased in landscapes with high amount of organic land. 5. Synthesis and applications. Our results indicate that considerable gains in biodiversity require roughly proportionate reductions in yield in highly productive agricultural systems. They suggest that conservation efforts may be more cost effective in low-productivity agricultural systems or on non-agricultural land. In less productive agricultural landscapes, biodiversity benefit can be gained by concentrating organic farms into hotspots without a commensurate reduction in yield.

In this paper we present a multi-disciplinary analysis of the potential impacts of undertaking similar environmental actions on multiple farms in a small geographic area, using organic farming as a proxy for a co-ordinated approach. Recent papers have called for more co-ordinated efforts between farmers in terms of their environmental actions, but there has been limited applied research demonstrating the environmental benefits or the economic and social implications to farmers of this approach. Comparative analysis of biodiversity, soil and water, and farm profitability were undertaken in England on 32 matched farms in areas of low and high organic farming concentration; qualitative interviews were also conducted with 48 farmers living in two of the eight areas. Findings demonstrate higher overall levels of biodiversity on organic farms (particularly in “hotspot” areas) but this was not universal across the species groups investigated. Higher water infiltration rates were found in organic grasslands, which could prove to be a useful measure to combat flooding. In terms of the technical efficiency of producing these environmental gains, conventional and organic farms in hotspot areas demonstrated equivalent efficiency from a financial perspective. Socio-cultural research identified the different amounts of trust farmers have in their neighbours, based in part on their performance as ‘good farmers’. We discuss the neighbourhood effect with a multi-disciplinary approach and conclude that encouraging local farmer co-ordination can have clear environmental benefits without high economic cost, but must be undertaken with caution – specifically regarding the trade-offs between benefits, local geophysical and social characteristics, and assumptions made about inter-farmer trust.

Organic farming aims to be wildlife-friendly, but it may not benefit wildlife overall if much greater areas are needed to produce a given quantity of food. We measured the density and species richness of butterflies on organic farms, conventional farms and grassland nature reserves in 16 landscapes. Organic farms supported a higher density of butterflies than conventional farms, but a lower density than reserves. Using our data, we predict the optimal land-use strategy to maintain yield whilst maximizing butterfly abundance under different scenarios. Farming conventionally and sparing land as nature reserves is better for butterflies when the organic yield per hectare falls below 87% of conventional yield. However, if the spared land is simply extra field margins, organic farming is optimal whenever organic yields are over 35% of conventional yields. The optimal balance of land sparing and wildlife-friendly farming to maintain production and biodiversity will differ between landscapes.

Summary 1. Habitat fragmentation can affect pollinator and plant population structure in terms of species composition, abundance, area covered and density of flowering plants. This, in turn, may affect pollinator visitation frequency, pollen deposition, seed set and plant fitness. 2. A reduction in the quantity of flower visits can be coupled with a reduction in the quality of pollination service and hence the plants’ overall reproductive success and long-term survival. Understanding the relationship between plant population size and ⁄ or isolation and pollination limitation is of fundamental importance for plant conservation. 3. We examined flower visitation and seed set of 10 different plant species from five European countries to investigate the general effects of plant populations size and density, both within (patch level) and between populations (population level), on seed set and pollination limitation. 4. We found evidence that the effects of area and density of flowering plant assemblages were generally more pronounced at the patch level than at the population level. We also found that patch and population level together influenced flower visitation and seed set, and the latter increased with increasing patch area and density, but this effect was only apparent in small populations. 5. Synthesis. By using an extensive pan-European data set on flower visitation and seed set we have identified a general pattern in the interplay between the attractiveness of flowering plant patches for pollinators and density dependence of flower visitation, and also a strong plant species-specific response to habitat fragmentation effects. This can guide efforts to conserve plant–pollinator interactions, ecosystem functioning and plant fitness in fragmented habitats.

Summary 1 Given the current debate on the global food crisis, conservation in Europe is expected to shift from maximizing biodiversity at the expense of yield to conserving biodiversity under food production constraints. Organic farming is potentially of great importance for environmentally sustainable farming. Understanding the distribution of organic farms and the environmental, social and cultural correlates is necessary to predict the way in which this may change over time. 2 We collated data from 30 variables describing the topography, climate, soils, farm size/type, human population characteristics and farm business in the English agricultural landscape. Factor analysis reduced these variables to six orthogonal axes, which describe the suitability of land for arable farming, the degree of ruralization (distance to urban centres and population density), the farm size and type, the soil hydrology and texture, and the amount of woodland (forestry). 3 An analysis of the distribution of organic farms showed that they are spatially aggregated at the regional and neighbourhood scales and that their presence in a 10 × 10-km grid square can be predicted from the farm size/type. 4 Analysis of the concentration of organic farms showed that about a third of the variance in their occurrence across the country can be predicted by a statistical model including the six landscape axes and a term to account for spatial aggregation. 5 Synthesis and applications. Our results show that a combination of environmental variables associated with a lower agricultural potential predisposes farmers to convert to organic farming, which further promotes conversion of farmers in the neighbourhood. Organic farming as a ‘wildlife friendly’ method is more likely to occur in agriculturally less-favoured areas where economic incentives for conversion to organic farming do not need to be high and the loss of production due to conversion will be comparatively small. This suggests that an efficient conservation strategy, which takes the global demand for food into account, would be to promote organic farming as an agri-environment scheme in landscapes that are already rich in organic farms at the expense of those existing high-production landscapes that are not.

1. Most studies in applied ecology use measures of alpha-diversity measures, i.e. the mean diversity on a site, to compare biodiversity effects of different management schemes. The total or alpha-diversity within a region, however, need not be correlated with the mean alpha-diversity within any site of the region. Thus, analyses of alpha-diversity alone may misrepresent the contributions of other diversity components (beta) to total diversity (gamma). 2. We apply a biodiversity-partitioning approach to species richness from a comparison between paired organic and conventional wheat fields in 21 sites from three regions in Germany, where we recorded plants, bees, carabids, staphylinids and spiders in the centre and edge of the fields. 3. Relative values of alpha- and beta-diversity depended on taxon. Both between-site and between-region beta-diversity were very high (in total 60-85%). alpha-Diversity and between-site beta-diversity was larger on the edge than in the centre of fields for all taxa. 4. alpha-Diversity, between-site beta-diversity of plants and bees and between-region beta-diversity of bees were higher in organic than in conventional fields, providing local as well as larger-scale species richness benefits. alpha-Diversity did not differ between management types for the epigaeic arthropods. Lower between-site beta-diversity was found for spiders in organic fields than in conventional fields, resulting in higher total species richness in conventionally managed wheat. 5. Similarity in composition of landscapes surrounding the study fields was correlated with similarity in species composition for epigaeic arthropods in conventional fields. For this group of organisms the variability of landscapes in the sample contributed to increasing beta-diversity. 6. Synthesis and applications. Diversity accounts for the major part of species richness in agro-ecosystems. Implementing an agri-environment scheme such as organic agriculture may result in either an additional increase of total diversity, as could be shown for plants and bees, or in a decrease in total diversity as was the case for the spiders. Therefore, beta-diversity needs to be included in the evaluation of different management schemes for conservation. For plant and bees it is recommended to implement agri-environment schemes in contrasting landscapes and in different regions to maximize total species richness benefits.

Organic farming is predicted to enhance diversity in agroecosystems. This study addresses the question of whether the often observed positive effect of organic farming on arable weed and pollinator diversity results in a significant shift in arable weed community structure towards a higher proportion of insect pollinated species in organic crop fields. To examine whether plant community patterns were consistent with this hypothesis, arable weed communities were compared with respect to the type of pollination (i.e. insect pollination versus non-insect pollination) in the edges and centres of 20 organic and 20 conventional wheat fields. Plant species numbers of both pollination types were much higher in organic than in conventional fields and higher in the field edge than in the field centre. A comparison of the proportions of both pollination types to all plant species revealed that the relative number of insect pollinated species was higher in organic than in conventional fields and higher at the field edge than in the field centre, whereas the relative number of non-insect pollinated species was higher in conventional fields and in the field centre. Our results show that insect pollinated plants benefit disproportionately from organic farming, which appeared to be related to higher pollinator densities in organic fields, whereas in the centres of conventional fields non-insect pollinated plants dominate presumably due to a limitation of pollinators. Hence, disruption of plant-pollinator interactions due to agricultural intensification may cause important shifts in plant community structure.

A key challenge for both ecological researchers and biodiversity managers is the measurement and prediction of species richness across spatial scales. Typically, biodiversity is assessed at fine scales (e.g. in quadrats or transects) for practical reasons, but often we are interested in coarser-scale (field, regional, global) diversity issues. Moreover, the pressures affecting biodiversity patterns are often scale specific, making multiscale assessment a crucial methodological priority. As species richness is not additive, it is difficult to translate from the scale of measurement to the scale(s) of interest. A number of methods have been proposed to tackle this problem, but most are too model specific or too rigid to allow general application. Here, we present a general framework (and a specific implementation of it) that allows such scale translations to be performed. Building on the intrinsic relationships among patterns of species richness, abundance and spatial turnover, we introduce a framework that links and predicts the profile of the species-area relationship and the species-abundance distributions across scales when a limited number of fine-scale scattered samples are available. Using the correlation in species' abundances between pairs of samples as a function of the distance between them, we are able to link the effects of aggregation, similarity decay, species richness and species abundances across scales. Our approach allows one to draw inferences about biodiversity scaling under very general assumptions pertaining to the nature of interactions, the geographical distributions of individuals and ecological processes. We demonstrate the accuracy of our predictions using data from two well-studied forest stands and also demonstrate the potential value of such methods by examining the effects of management on farmland insects across scales. The framework has important applications to biodiversity research and conservation practice.

Agri-environment schemes are an increasingly important tool for the maintenance and restoration of farmland biodiversity in Europe but their ecological effects are poorly known. Scheme design is partly based on non-ecological considerations and poses important restrictions on evaluation studies. We describe a robust approach to evaluate agri-environment schemes and use it to evaluate the biodiversity effects of agri-environment schemes in five European countries. We compared species density of vascular plants, birds, bees, grasshoppers and crickets, and spiders on 202 paired fields, one with an agri-environment scheme, the other conventionally managed. In all countries, agri-environment schemes had marginal to moderately positive effects on biodiversity. However, uncommon species benefited in only two of five countries and species listed in Red Data Books rarely benefited from agri-environment schemes. Scheme objectives may need to differentiate between biodiversity of common species that can be enhanced with relatively simple modifications in farming practices and diversity or abundance of endangered species which require more elaborate conservation measures.

Summary 1 There is growing concern about declining species diversity in agro-ecosystems caused by agricultural intensification at the field and landscape scales. Species diversity of arable weeds is classically related to local abiotic factors and resource conditions. It is believed to be enhanced by organic farming but the surrounding landscape may also be important. 2 This study assessed the ruderal vegetation, seed bank and seed rain in 24 winter wheat fields to examine the relative importance of organic vs. conventional farming and landscape complexity for weed species diversity. Diversity was partitioned into its additive components: alpha, beta and gamma diversity. Percentage arable land in a circular landscape sector of 1-km radius around each study site was used as an indicator of landscape complexity. 3 Weed species diversity in the vegetation, seed rain and seed bank was higher in organic than in conventional fields. Increasing landscape complexity enhanced species diversity more strongly in the vegetation of conventional than organic fields, to the extent that diversity was similar in both farming systems when the landscape was complex. Species diversity of the seed bank was increased by landscape complexity irrespective of farming system. 4 Overall diversity was largely determined by the high heterogeneity between and within the fields (beta diversity). Only in very few cases could higher weed species diversity in complex landscapes and/or organic farming be related to species dependence on landscape or farming system. 5 Synthesis and applications. Local weed species diversity was influenced by both landscape complexity and farming system. Species diversity under organic farming systems was clearly higher in simple landscapes. Conventional vegetation reached similar diversity levels when the surrounding landscape was complex through the presence of refugia for weed populations. Consequently, agri-environment schemes designed to preserve and enhance biodiversity should not only consider the management of single fields but also of the surrounding landscape.

Patterns of plant diversity are often related to local site conditions and to competitive interactions, but landscape context may also be important for local plant species richness. This is shown here by analysing the relationship between landscape complexity and local species richness of arable weeds in wheat fields. The fields were located in 18 landscapes characterised by a gradient in landscape complexity from structurally complex to structurally simple (39–94% arable land). We quantified local site conditions, field management intensity and landscape characteristics, and used principle component analyses to ordinate the environmental variables. The percentage of arable land was negatively correlated with perimeter–area ratio, habitat-type diversity and topographical heterogeneity, but landscape characteristics did not correlate with local site conditions and field management intensity. The number of plant species was mainly related to landscape characteristics and to a lesser extent to field management intensity (nitrogen fertilisation), whereas local soil characteristics did not contribute to the explanation of arable weed richness. In a geographic scale analysis using circular landscape sectors ranging from 1 km up to 5 km diameter, the predictive power of landscape complexity for local plant species richness was strongest at 2 km indicating a scale-dependent relationship between landscape context and plant species richness. Our results support the hypothesis that local plant species richness in arable fields is greatly influenced by processes operating at the landscape scale. Seed rain from ruderal source habitats and disturbed edges may be the most important underlying process.

summary 1. Ecological theory predicts that the effectiveness of local agri-environmental management to enhance species richness at field scales will be the highest at intermediate levels of landscape complexity because of nonlinear effects of landscape context on field-scale diversity. 2. We examined how landscape complexity determined effectiveness of local agri-environmental management in terms of effects on species richness of birds, plants, spiders and bees in 232 extensive and intensive paired fields (112 arable fields and 120 grasslands) from 18 regions located in six European countries. 3. As predicted, landscape complexity enhanced field-scale species richness in a mostly nonlinear (sigmoidal) way, with earlier species richness increases in extensive than in intensive fields along landscape complexity gradients. Length of semi-natural boundaries (for arable fields) and proportion of unfarmed habitat (for grasslands) were the landscape features influencing species richness. 4. The relationships between effectiveness of local management and landscape complexity for all taxa were best described with hump-shaped curves, indicating the highest effectiveness at intermediate landscape complexities. 5. Synthesis and applications. We used models to investigate how and why effects of local management intensity on species richness vary along wide gradients of landscape complexity. We conclude that landscape-scale management options should take priority over local extensification measures within agri-environmental programmes. These programmes should follow a hierarchical multi-scale approach directed to address landscape-scale constraints on local diversity.

There is increasing recognition that ecosystems and their services need to be managed in the face of environmental change. However, there is little consensus as to the optimum scale for management. This is particularly acute in the agricultural environment given the level of public investment in agri-environment schemes (AES). Using a novel multiscale hierarchical sampling design, we assess the effect of land use at multiple spatial scales (from location-within-field to regions) on farmland biodiversity. We show that on-farm biodiversity components depend on farming practices (organic vs. conventional) at farm and landscape scales, but this strongly interacts with fine- and coarse-scale variables. Different taxa respond to agricultural practice at different spatial scales and often at multiple spatial scales. Hence, AES need to target multiple spatial scales to maximize effectiveness. Novel policy levers may be needed to encourage multiple land managers within a landscape to adopt schemes that create landscape-level benefits.

Worldwide agriculture is one of the main drivers of biodiversity decline. Effective conservation strategies depend on the type of relationship between biodiversity and land-use intensity, but to date the shape of this relationship is unknown. We linked plant species richness with nitrogen (N) input as an indicator of land-use intensity on 130 grasslands and 141 arable fields in six European countries. Using Poisson regression, we found that plant species richness was significantly negatively related to N input on both field types after the effects of confounding environmental factors had been accounted for. Subsequent analyses showed that exponentially declining relationships provided a better fit than linear or unimodal relationships and that this was largely the result of the response of rare species (relative cover less than 1%). Our results indicate that conservation benefits are disproportionally more costly on high-intensity than on low-intensity farmland. For example, reducing N inputs from 75 to 0 and 400 to 60 kg ha −1 yr −1 resulted in about the same estimated species gain for arable plants. Conservation initiatives are most (cost-)effective if they are preferentially implemented in extensively farmed areas that still support high levels of biodiversity.

Biodiversity studies that guide agricultural subsidy policy have generally compared farming systems at a single spatial scale: the field. However, diversity patterns vary across spatial scales. Here, we examined the effects of farming system (organic vs. conventional) and position in the field (edge vs. center) on plant species richness in wheat fields at three spatial scales. We quantified alpha-, beta-, and gamma-diversity at the microscale in 800 plots, at the mesoscale in 40 fields, and at the macroscale in three regions using the additive partitioning approach, and evaluated the relative contribution of beta-diversity at each spatial scale to total observed species richness. We found that alpha-, beta-, and gamma-diversity were higher in organic than conventional fields and higher at the field edge than in the field center at all spatial scales. In both farming systems, beta-diversity at the meso- and macroscale explained most of the overall species richness (up to 37% and 25%, respectively), indicating considerable differences in community composition among fields and regions due to environmental heterogeneity. The spatial scale at which beta-diversity contributed the most to overall species richness differed between rare and common species. Total richness of rare species (present inor = 5% of total samples) was mainly explained by differences in community composition at the meso- and macroscale (up to 27% and 48%, respectively), but only in organic fields. Total richness of common species (present inor = 25% of total samples) was explained by differences in community composition at the micro- and mesoscale (up to 29% and 47%, respectively), i.e., among plots and fields, independent of farming system. Our results show that organic farming made the greatest contribution to total species richness at the meso (among fields) and macro (among regions) scale due to environmental heterogeneity. Hence, agri-environment schemes should exploit this large-scale contribution of beta-diversity by tailoring schemes at regional scales to maximize dissimilarity between conservation areas using geographic information systems rather than focusing entirely at the classical local-field scale, which is the current practice.