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Factors influencing grazing behavior in species‐rich grasslands have been little studied. Methodologies have mostly had a primary focus on grasslands with lower floristic diversity.We test the hypothesis that grazing behavior is influenced by both animal and plant factors and investigate the relative importance of these factors, using a novel combination of video technology and vegetation classification to analyze bite and step rates.In a semi‐natural, partially wooded grassland in northern Estonia, images of the vegetation being grazed and records of steps and bites were obtained from four video cameras, each mounted on the sternum of a sheep, during 41 animal‐hours of observation over five days. Plant species lists for the immediate field of view were compiled. Images were partnered by direct observation of the nearest‐neighbor relationships of the sheep. TWINSPAN, a standard vegetation classification technique allocating species lists to objectively defined classes by a principal components procedure, was applied to the species lists and 25 vegetation classes (15 open pasture and 10 woodland) were identified from the images.Taking bite and step rates as dependent variables, relative importance of animal factors (sheep identity), relative importance of day, and relative importance of plant factors (vegetation class) were investigated. The strongest effect on bite rates was of vegetation class. Sheep identity was less influential. When the data from woodland were excluded, sheep identity was more important than vegetation class as a source of variability in bite rate on open pasture.The original hypothesis is therefore supported, and we further propose that, at least with sheep in species‐rich open pastures, animal factors will be more important in determining grazing behavior than plant factors. We predict quantifiable within‐breed and between‐breed differences, which could be exploited to optimize conservation grazing practices and contribute to the sustainability of extensive grazing systems. [ABSTRACT FROM AUTHOR]

Cattle Bos taurus can perform valuable ecological functions in the maintenance of high nature value (HNV) pastoral systems. They have also attracted attention as potentially filling the ecological niches of megaherbivores, notably the extinct aurochs Bos primigenius, in rewilding initiatives. Native cattle breeds are recognized under the 1992 Rio Convention as components of biodiversity. They are used in HNV settings, but their conservation as breeds has rarely been an important consideration for their management in these contexts.The Chillingham herd has been kept under minimal management in Chillingham Park (northern England) for several centuries. Chillingham Park is not a rewilding scenario, but the long‐term study of the cattle can be informative for the design of rewilding schemes that involve cattle as megaherbivores. The pastures of the park are species‐rich seminatural grasslands.To 2004, pasture management was influenced by the need to provide herbage for a flock of sheep that was under separate ownership, as well as for the cattle. Surveys of the vegetation conducted in 1979 and 2006–2008 showed a decline of plant species richness (species per 100 m2 quadrat) from 33.8 in 1979 to 22.6 in 2006–2008. This was acceptable as the conservation priority has always been the cattle herd. With removal of the sheep from 2004, it became possible to include recovery of plant diversity as a management goal.In 2017, the cattle numbered 111 (64 in 1979). Plant species richness in 2017 had increased to 26.3 species per quadrat. It has therefore been possible at Chillingham both to conserve the cattle herd and to improve plant diversity. While providing basic information of relevance to the management of cattle in free‐ranging situations, this study also suggests a general principle, that the management of pastoral landscapes by native breeds of cattle, can deliver multiple conservation benefits. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We report the impact of an extreme weather event, the October 1987 severe storm, on fragmented woodlands in southern Britain. We analysed ecological changes between 1971 and 2002 in 143 200-m2 plots in 10 woodland sites exposed to the storm with an ecologically equivalent sample of 150 plots in 16 non-exposed sites. Comparing both years, understorey plant species-richness, species composition, soil pH and woody basal area of the tree and shrub canopy were measured., We tested the hypothesis that the storm had deflected sites from the wider national trajectory of an increase in woody basal area and reduced understorey species-richness associated with ageing canopies and declining woodland management. We also expected storm disturbance to amplify the background trend of increasing soil p H, a UK-wide response to reduced atmospheric sulphur deposition. Path analysis was used to quantify indirect effects of storm exposure on understorey species richness via changes in woody basal area and soil p H., By 2002, storm exposure was estimated to have increased mean species richness per 200 m2 by 32%. Woody basal area changes were highly variable and did not significantly differ with storm exposure., Increasing soil p H was associated with a 7% increase in richness. There was no evidence that soil p H increased more as a function of storm exposure. Changes in species richness and basal area were negatively correlated: a 3.4% decrease in richness occurred for every 0.1-m2 increase in woody basal area per plot., Despite all sites substantially exceeding the empirical critical load for nitrogen deposition, there was no evidence that in the 15 years since the storm, disturbance had triggered a eutrophication effect associated with dominance of gaps by nitrophilous species., Synthesis. Although the impacts of the 1987 storm were spatially variable in terms of impacts on woody basal area, the storm had a positive effect on understorey species richness. There was no evidence that disturbance had increased dominance of gaps by invasive species. This could change if recovery from acidification results in a soil p H regime associated with greater macronutrient availability. [ABSTRACT FROM AUTHOR]

Aim To develop a novel global spatial framework for the integration and analysis of ecological and environmental data. Location The global land surface excluding Antarctica. Methods A broad set of climate-related variables were considered for inclusion in a quantitative model, which partitions geographic space into bioclimate regions. Statistical screening produced a subset of relevant bioclimate variables, which were further compacted into fewer independent dimensions using principal components analysis ( PCA). An ISODATA clustering routine was then used to classify the principal components into relatively homogeneous environmental strata. The strata were aggregated into global environmental zones based on the attribute distances between strata to provide structure and support a consistent nomenclature. Results The global environmental stratification ( GEnS) consists of 125 strata, which have been aggregated into 18 global environmental zones. The stratification has a 30 arcsec resolution (equivalent to 0.86 km2 at the equator). Aggregations of the strata were compared with nine existing global, continental and national bioclimate and ecosystem classifications using the Kappa statistic. Values range between 0.54 and 0.72, indicating good agreement in bioclimate and ecosystem patterns between existing maps and the GEnS. Main conclusions The GEnS provides a robust spatial analytical framework for the aggregation of local observations, identification of gaps in current monitoring efforts and systematic design of complementary and new monitoring and research. The dataset is available for non-commercial use through the GEO portal (http://www.geoportal.org). [ABSTRACT FROM AUTHOR]

1. In temperate farmed landscapes conservation policies increasingly emphasize large-scale reductions in land-use intensity. Yet despite a managed reversion to more favourable abiotic conditions, depleted regional species pools may prevent the re-assembly of target communities. 2. Using national-scale survey data recorded across Great Britain in 1998, we investigated the extent to which grassland indicator plant species persisted on potential refuge habitats across a spatial gradient of intensive land cover in lowland 1-km squares. These habitats comprised road verges, field boundaries, watercourse banks and small biotope fragments. Intensive land cover comprised built land, arable and improved grassland. 3. The rate of reduction in indicator species richness across the intensive land cover gradient was significantly lower in all potential refuge features than in surrounding fields and larger areas of habitat. 4. The best refuge locations were watercourse banks and small biotopes. In both cases, indicator species richness was higher than adjacent fields at the lowest intensive land cover and stayed higher as intensive land cover increased. 5. However, as intensive land cover increased, plant traits associated with higher nutrient availability were more prominently represented among indicator species. 6. Although richer assemblages of indicator species persisted on refuge features, population sizes are likely to be small, because of species–area effects, and also vulnerable to nutrient surpluses and reduced or inappropriate disturbance. 7. Synthesis and applications. Across the British lowlands, linear landscape features and small habitat fragments can provide limited safe havens for unimproved grassland plant species. However, the identity of refuge features and their species richness and composition are likely to vary with local conditions. Three activities are therefore paramount in assessing their role in larger scale extensification schemes: (i) development of rapid ways of assessing the plant diversity and distribution of refuge features in local areas; (ii) quantification of the risks posed to the viability of residual source populations through implementation of different options for incorporating them into extensification schemes; (iii) maximization of scheme performance by targeting landscapes with sufficient residual diversity to enable increases in population size of the target species in the medium term. [ABSTRACT FROM AUTHOR]

Summary: 1. Ellenberg’s indicator values scale the flora of a region along gradients reflecting light, temperature, continentality, moisture, soil pH, fertility and salinity. They can be used to monitor environmental change. 2. Ellenberg values can be extended from central Europe, for which they were defined, to nearby parts of Europe. Given a database of quadrat samples, they can be repredicted by a simple algorithm consisting of two-way weighted averaging, followed by local regression. 3. A database of British samples was assembled from two large surveys. Ellenberg values were repredicted. 4. Except for the indicator of continentality, the correlation of repredicted and original values was in the range 0·72 (light) to 0·91 (moisture). The continentality indicator could not be adequately repredicted by the algorithm, and is unusable in Britain. 5. Discrepancies between original and repredicted values can be attributed to various causes, including wrong original values, differing ecological requirements in Britain and central Europe, biased sampling of the British range of habitats, and the occurrence of small plants in shaded or basic microhabitats within well illuminated or predominantly acid quadrats. 6. The repredicted values were generally reliable, but a small proportion was clearly wrong. Wrong values were due to either inadequate sampling of species’ realized niches in Britain or sampling with quadrats that were too large and included species that were not close associates. [ABSTRACT FROM AUTHOR]

Farmland is a major land cover type in Europe and Africa and provides habitat for numerous species. The severe decline in farmland biodiversity of the last decades has been attributed to changes in farming practices, and organic and low-input farming are assumed to mitigate detrimental effects of agricultural intensification on biodiversity. Since the farm enterprise is the primary unit of agricultural decision making, management-related effects at the field scale need to be assessed at the farm level. Therefore, in this study, data were collected on habitat characteristics, vascular plant, earthworm, spider, and bee communities and on the corresponding agricultural management in 237 farms in 13 European and two African regions. In 15 environmental and agricultural homogeneous regions, 6-20 farms with the same farm type (e.g., arable crops, grassland, or specific permanent crops) were selected. If available, an equal number of organic and non-organic farms were randomly selected. Alternatively, farms were sampled along a gradient of management intensity. For all selected farms, the entire farmed area was mapped, which resulted in total in the mapping of 11 338 units attributed to 194 standardized habitat types, provided together with additional descriptors. On each farm, one site per available habitat type was randomly selected for species diversity investigations. Species were sampled on 2115 sites and identified to the species level by expert taxonomists. Species lists and abundance estimates are provided for each site and sampling date (one date for plants and earthworms, three dates for spiders and bees). In addition, farmers provided information about their management practices in face-to-face interviews following a standardized questionnaire. Farm management indicators for each farm are available (e.g., nitrogen input, pesticide applications, or energy input). Analyses revealed a positive effect of unproductive areas and a negative effect of intensive management on biodiversity. Communities of the four taxonomic groups strongly differed in their response to habitat characteristics, agricultural management, and regional circumstances. The data has potential for further insights into interactions of farmland biodiversity and agricultural management at site, farm, and regional scale. [ABSTRACT FROM AUTHOR]