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11 results for “farmland biodiversity”
Dataset for: Multi-scale approach to biodiversity proxies of biological control service in European farmlands
<p>Dataset for the BiodivERsA COFUND Woodned project. Information on which spatio-temporal factors are simultaneously affecting crop pests and their natural enemies is required to improve conservation biological control practices. The study was conducted in 80 winter wheat crop fields distributed in three regions of North-western Europe (Brittany, Hauts-de-France and Wallonia), along intra-regional gradients of landscape complexity. Five taxa : aphids, slugs, spiders, carabids, and parasitoids were sampled for two consecutive years. We analysed the influence of regional, landscape and local factors on the abundance and species richness of crop-dwelling organisms, as proxies of the service/disservice they provide. Firstly, there was higher biocontrol potential in areas with mild winter climatic conditions. Secondly, natural enemy communities were less diverse and had lower abundances in landscapes with high crop and wooded continuities, contrary to slugs and aphids. Finally, field boundaries with grass strips were more favourable to spiders and carabids than boundaries formed by hedges, while the opposite was found for crop pests, with the latter being less abundant towards the centre of the fields. These results are quite unexpected because they show that hedgerows and woodlots should not be the unique cornerstones of agro-ecological landscape design strategies. We point out that combining woody and grassy habitats to take full advantage of the features and ecosystem services they both provide may promote sustainable agricultural ecosystems. It may be possible to both reduce pest pressure and promote natural enemies by accounting for taxa-specific antagonistic responses to multi-scale environmental characteristics.</p>
Reassessing science communication for effective farmland biodiversity conservation.
<p>Data set and code for analysing a communication case study about biodiversity conservation and farming in the European decision-making environment. It includes: (1) a literature corpus, consisting of 5988 digital press releases and news texts, covering the period of 2015-2020, from 40 different organizations involved in European farming and food decision-making processes; (2) R code scripts for analysis and graphic representation.</p>
Disentangling direct and indirect drivers of farmland biodiversity at landscape scale
<p><span>To stop the ongoing decline of farmland biodiversity there are increasing claims for a paradigm shift in agriculture, namely from conserving and restoring farmland biodiversity at field scale (α-diversity) to doing it at landscape scale (γ-diversity). However, knowledge on factors driving farmland γ-diversity is currently limited. Here, we quantified farmland γ-diversity in 123 landscapes and analysed direct and indirect effects of abiotic and land-use factors shaping it using structural equation models. The direction and strength of effects of factors shaping γ-diversity were only partially consistent with what is known about factors shaping α-diversity, and indirect effects were often stronger than direct effects or even opposite. Thus, relationships between factors shaping α-diversity cannot simply be up-scaled to γ-diversity, and also indirect effects should no longer be neglected. Finally, we show that local mitigation measures benefit farmland γ-diversity at landscape scale and are therefore a useful tool for designing biodiversity-friendly landscapes. </span></p>
Disentangling direct and indirect drivers of farmland biodiversity at landscape scale
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Data from: Testing scale-dependent effects of semi-natural habitats on farmland biodiversity
The effectiveness of conservation interventions for maximizing biodiversity benefits from agri-environment schemes (AESs) is expected to depend on the quantity of seminatural habitats in the surrounding landscape. To verify this hypothesis, we developed a hierarchical sampling design to assess the effects of field boundary type and cover of seminatural habitats in the landscape at two nested spatial scales. We sampled three types of field boundaries with increasing structural complexity (grass margin, simple hedgerow, complex hedgerow) in paired landscapes with the presence or absence of seminatural habitats (radius 0.5 km), that in turn, were nested within 15 areas with different proportions of seminatural habitats at a larger spatial scale (10 × 10 km). Overall, 90 field boundaries were sampled across a Mediterranean region (northeastern Italy). We considered species richness response across three different taxonomic groups: vascular plants, butterflies, and tachinid flies. No interactions between type of field boundary and surrounding landscape were found at either 0.5 and 10 km, indicating that the quality of field boundary had the same effect irrespective of the cover of seminatural habitats. At the local scale, extended-width grass margins yielded higher plant species richness, while hedgerows yielded higher species richness of butterflies and tachinids. At the 0.5-km landscape scale, the effect of the proportion of seminatural habitats was neutral for plants and tachinids, while butterflies were positively related to the proportion of forest. At the 10-km landscape scale, only butterflies responded positively to the proportion of seminatural habitats. Our study confirmed the importance of testing multiple scales when considering species from different taxa and with different mobility. We showed that the quality of field boundaries at the local scale was an important factor in enhancing farmland biodiversity. For butterflies, AESs should focus particular attention on preservation of forest patches in agricultural landscapes within 0.5 km, as well as the conservation of seminatural habitats at a wider landscape scale.
Data from: How much would it cost to monitor farmland biodiversity in Europe?
To evaluate progress on political biodiversity objectives, biodiversity monitoring provides information on whether intended results are being achieved. Despite scientific proof that monitoring and evaluation increase the (cost) efficiency of policy measures, cost estimates for monitoring schemes are seldom available, hampering their inclusion in policy programme budgets. Empirical data collected from 12 case studies across Europe were used in a power analysis to estimate the number of farms that would need to be sampled per major farm type to detect changes in species richness over time for four taxa (vascular plants, earthworms, spiders and bees). A sampling design was developed to allocate spatially, across Europe, the farms that should be sampled. Cost estimates are provided for nine monitoring scenarios with differing robustness for detecting temporal changes in species numbers. These cost estimates are compared with the Common Agricultural Policy (CAP) budget (2014–2020) to determine the budget allocation required for the proposed farmland biodiversity monitoring. Results show that the bee indicator requires the highest number of farms to be sampled and the vascular plant indicator the lowest. The costs for the nine farmland biodiversity monitoring scenarios corresponded to 0·01%–0·74% of the total CAP budget and to 0·04%–2·48% of the CAP budget specifically allocated to environmental targets. Synthesis and applications. The results of the cost scenarios demonstrate that, based on the taxa and methods used in this study, a Europe-wide farmland biodiversity monitoring scheme would require a modest share of the Common Agricultural Policy budget. The monitoring scenarios are flexible and can be adapted or complemented with alternate data collection options (e.g. at national scale or voluntary efforts), data mobilization, data integration or modelling efforts.
An increase in food production in Europe could dramatically affect farmland biodiversity
<p><strong>Supplementary Data. Detailed average yield per region, and organic and non-organic management systems per crop type in MJ/ha (</strong><strong>+/- standard error) </strong><strong>in ten European farmland regions</strong>. Details on regions and country abbreviations are given in Supplementary Table 1.</p>
Data from: Testing scale-dependent effects of semi-natural habitats on farmland biodiversity
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Data from: How much would it cost to monitor farmland biodiversity in Europe?
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Data from: A national-scale model of linear features improves predictions of farmland biodiversity
1. Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically-relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies. 2. We assessed whether a novel spatial dataset mapping linear and woody linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites respectively. 3. Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. 4. Synthesis and applications. This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems, and also can potentially be used to assess habitat connectivity. 10-Mar-2017
Data from: A national-scale model of linear features improves predictions of farmland biodiversity
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