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Map of field sites, full description of derivation of explanatory variables, model coefficients and additional graphs

There is considerable concern over declines in insect pollinator communities and potential impacts on the pollination of crops and wildflowers. Among the multiple pressures facing pollinators, decreasing floral resources due to habitat loss and degradation has been suggested as a key contributing factor. However, a lack of quantitative data has hampered testing for historical changes in floral resources. Here we show that overall floral rewards can be estimated at a national scale by combining vegetation surveys and direct nectar measurements. We find evidence for substantial losses in nectar resources in England and Wales between the 1930s and 1970s; however, total nectar provision in Great Britain as a whole had stabilized by 1978, and increased from 1998 to 2007. These findings concur with trends in pollinator diversity, which declined in the mid-twentieth century but stabilized more recently. The diversity of nectar sources declined from 1978 to 1990 and thereafter in some habitats, with four plant species accounting for over 50% of national nectar provision in 2007. Calcareous grassland, broadleaved woodland and neutral grassland are the habitats that produce the greatest amount of nectar per unit area from the most diverse sources, whereas arable land is the poorest with respect to amount of nectar per unit area and diversity of nectar sources. Although agri-environment schemes add resources to arable landscapes, their national contribution is low. Owing to their large area, improved grasslands could add substantially to national nectar provision if they were managed to increase floral resource provision. This national-scale assessment of floral resource provision affords new insights into the links between plant and pollinator declines, and offers considerable opportunities for conservation.

1. Ecological processes operating on large spatio-temporal scales are difficult to disentangle with traditional empirical approaches. Alternatively, researchers can take advantage of ‘natural’ experiments, where experimental control is exercised by careful site selection. Recent advances in developing protocols for designing these ‘pseudo-experiments’ commonly do not consider the selection of the focal region and predictor variables are usually restricted to two. Here, we advance this type of site selection protocol to study the impact of multiple landscape scale factors on pollinator abundance and diversity across multiple regions.\ud 2. Using datasets of geographic and ecological variables with national coverage, we applied a novel hierarchical\ud computation approach to select study sites that contrast as much as possible in four key variables, while attempting to maintain regional comparability and national representativeness. There were three main steps to the protocol: (i) selection of six 100 9 100 km2 regions that collectively provided land cover representative of the national land average, (ii) mapping of potential sites into a multivariate space with axes representing four key factors potentially influencing insect pollinator abundance, and (iii) applying a selection algorithm which maximized differences between the four key variables, while controlling for a set of external constraints.\ud 3. Validation data for the site selection metrics were recorded alongside the collection of data on pollinator populations during two field campaigns. While the accuracy of the metric estimates varied, the site selection succeeded in objectively identifying field sites that differed significantly in values for each of the four key variables. Between-variable correlations were also reduced or eliminated, thus facilitating analysis of their separate effects.\ud 4. This study has shown that national datasets can be used to select randomized and replicated field sites objectively within multiple regions and along multiple interacting gradients. Similar protocols could be used for studying a range of alternative research questions related to land use or other spatially explicit environmental variables, and to identify networks of field sites for other countries, regions, drivers and response taxa in a wide range of scenarios.

This paper presents an alternative approach for high spatial resolution vegetation productivity mapping at a regional scale, using a combination of Normalised Difference Vegetation Index (NDVI) imagery and widely distributed ground-based Above-ground Net Primary Production (ANPP) estimates. Our method searches through all available single-date NDVI imagery to identify the images which give the best NDVI–ANPP relationship. The derived relationships are then used to predict ANPP values outside of field survey plots. This approach enables the use of the high spatial resolution (30 m) Landsat 8 sensor, despite its low revisit frequency that is further reduced by cloud cover. This is one of few studies to investigate the NDVI–ANPP relationship across a wide range of temperate habitats and strong relationships were observed (R2 = 0.706), which increased when only grasslands were considered (R2 = 0.833). The strongest NDVI–ANPP relationships occurred during the spring “green-up” period. A reserved subset of 20% of ground-based ANPP estimates was used for validation and results showed that our method was able to estimate ANPP with a RMSE of 15–21%. This work is important because we demonstrate a general methodological framework for mapping of ANPP from local to regional scales, with the potential to be applied to any temperate ecosystems with a pronounced green up period. Our approach allows spatial extrapolation outside of field survey plots to produce a continuous surface product, useful for capturing spatial patterns and representing small-scale heterogeneity, and well-suited for modelling applications. The data requirements for implementing this approach are also discussed.

International audience; Atmospheric nitrogen (N) deposition has been identified as a major threat to biodiversity, but field surveys of its effects have rarely focussed on sites which are actively managed to maintain characteristic species. We analysed permanent quadrat data from 106 plots in nature reserves on calcareous grassland sites in the UK collected during a survey between 1990 and 1993 and compared the data with the results from re-survey of 48 of these plots between 2006 and 2009. N deposition showed no significant spatial association with species richness, species diversity, or the frequency of species adapted to low nutrient conditions in the 1990-1993 dataset. However, temporal analysis showed that N deposition was significantly associated with changes in Shannon diversity and evenness. In plots with high rates of N deposition, there was a decrease in species diversity and evenness, a decline in the frequency of characteristic calcareous grassland species, and a lower number of rare and scarce species. Since all sites had active management to maintain a high diversity and characteristic species, our results imply that even focussed management on nature conservation objectives cannot prevent adverse effects of high rates of N deposition. Structural equation modelling was used to compare different causal mechanisms to explain the observed effects. For change in Shannon diversity, direct effects of N deposition were the dominant mechanism and there was an independent effect of change in grazing intensity. In contrast, for change in herb species number, indirect effects on soil acidity, linked to both N and S deposition, were more important than direct effects of N deposition.