Questions Earth observation is an important tool in biological monitoring. Previous studies have shown that variation in grassland canopy reflectance can explain gradients in plant community composition. However, there is a need for methods that allow the interpretation of the overall spectral signal of complex grassland vegetation in terms of existing knowledge about individual species' habitat preferences. Can community-level grassland canopy reflectance be interpreted in terms of the distribution patterns and habitat preferences of individual plant species? Location The island of & Ouml;land, Sweden. The sites represent a succession from grazed grassland on previously arable fields to old semi-natural pastures. Methods We collected data on plant species occurrences and mean hyperspectral reflectance (414-2351 nm) during peak vegetation season in 104 (4 m & times; 4 m) field plots. We simplified the spectral data into orthogonal components using Principal Component Analysis. Joint species distribution modelling was used to analyse 100 species' relationships with the components. Information on species' habitat preferences was included to explain species' model-responses. Results Grassland canopy reflectance was associated with variation in the occurrences of individual plant species (41 species with Tjur's D > 0.15, 15 species with D > 0.30), particularly species with distinct habitat preferences. The main gradient in the reflectance data-representing features in the red, blue, SWIR and NIR spectra-was associated with species' preferences for mineral nitrogen availability. In contrast, species' phosphate preferences showed stronger associations with reflectance in the green and red-edge spectra. Conclusions Data on individual species and their habitat preferences can be used to interpret patterns of variation in community-level canopy reflectance in grazed grasslands. Vegetation in phosphorus-poor grasslands-which are valuable for biodiversity conservation-showed a consistent pattern (characterised by features in the green and red-edge) in the spectral data.

Questions To what extent does the long-term process of grassland succession reflect changes in nutrient availability or other effects of grassland history? Plant communities in ancient, semi-natural pastures include many species associated with nutrient-poor soils. However, semi-natural pasture communities can also develop on previously arable sites - as nutrient levels decline over time. In Europe, Ellenberg N-values represent species' overall nutrient preferences and are often used as a proxy for soil nutrient availability. But how well do N-values actually reflect species' relationships with measured nutrient concentrations during grassland succession? Location A successional series of grazed, previously arable to ancient, grasslands on the Baltic island of oland, Sweden. Methods We collected data on community composition and soil nutrient (phosphorus, ammonium, nitrate) concentrations. We used Bayesian joint-community modelling to parameterize species' relationships with nutrients and grassland age, and quantified the relative contributions of the variables. Species responses were then compared with Ellenberg N-values. Results Phosphorus was the best explanatory variable for most species. However, species occurrences were not simply explained by gradients in particular nutrients, but by combinations of different nutrients and grassland age. There was overall agreement between N-values and species' nutrient responses - although the occurrences of species with identical N-values may be explained by different nutrients. Species with high and low N-values represent more reliable nutrient indicators than intermediate-N species, but their occurrences also reflect other factors that, as with nutrients, depend on the grassland age. Conclusions Our results confirm that Ellenberg N provides a robust indication of the overall nutrient preferences of individual grassland species. However, in grassland sites developing on previously arable land - where nutrient availability is strongly associated with habitat age - N-values may represent an integrated response not only to nutrients but also to other historical processes that drive grassland community assembly.

The NDVI is a remotely sensed vegetation index that is frequently used in ecological studies. There is, however, a lack of studies that evaluate the ability of the NDVI to detect fine‐scale variation in grassland plant community composition and species richness. Ellenberg indicators characterize the environmental preferences of plant species—and community‐mean Ellenberg values have been used to explore the environmental drivers of community assembly. We used variation partitioning to test the ability of satellite‐based NDVI to explain community‐mean Ellenberg nutrient (mN) and moisture (mF) indices, and the richness of habitat‐specialist species in dry grasslands of different ages. The grasslands represent a gradient of decreasing soil nutrient status. If community composition is determined by the responses of individual species to the underlying environmental conditions and if, at the same time, community composition determines the optical characteristics of the vegetation canopy, then positive relationships between the NDVI and mN and mF are expected. Many grassland specialists are intolerant of nutrient‐rich soils. If specialist richness is negatively related to soil‐nutrient levels, then a negative association between the NDVI and specialist richness is expected. However, because grassland community composition is not only influenced by abiotic variables but also by other spatial and temporal drivers, we included spatial variables and grassland age in the statistical analyses. The NDVI explained the majority of the variation in mF, and also contributed to a substantial proportion of the variation in mN. However, variation in specialist richness and the lowest values of mN were explained by grassland age and spatial variables—but were poorly explained by the NDVI. Synthesis and applications. The NDVI showed a good ability to detect variation in plant community composition, and should provide a valuable tool for assessing fine‐scale environmental variation in grasslands or for monitoring changes in grassland habitat properties. However, because the concentration of grassland specialists not only depends on environmental variables but also on the age and spatial context of the grasslands, the NDVI is unlikely to allow the identification of grasslands with high numbers of specialist species.

Small remnants of non-arable habitat within the farmland mosaic are considered important for the conservation of farmland biodiversity, but their contribution to landscape-scale species richness is poorly understood. In the present study, we examined the relative contributions of different habitat types to the landscape-scale species richness of vascular plants within farmland of varying landscape complexity. We also analysed pollen collected by bees to examine the extent to which the different habitat types contributed towards the provisioning of floral resources for three taxa (Bombus terrrestris, Megachile sp. and Osmia bicornis). We found that plant species richness increased with landscape complexity (defined as the proportion of semi-natural habitats). The relative contribution of small fragments of non-arable habitat to total plant species richness was high within all landscape types, especially in relation to the small area they covered. The importance of small non-arable fragments for the provisioning of floral resources to bees varied over time and between taxa. Bombus terrestris used the different habitat types differently during different parts of the growing season: arable fields were important early in the season, leys late in the season, and small non-arable habitat fragments during the mid-season when no mass-flowering crops were in bloom. In contrast, Megachile sp. and O. bicornis mainly foraged on plants occurring within grasslands. We conclude that small fragments of non-arable habitat are important for plant species richness at the landscape-scale and that their importance for plants may cascade to the bees that use them as foraging resources. Consequently, it is important to consider the entire landscape mosaic when taking actions to conserve farmland species.

Semi-natural grasslands with grazing management are characterized by high fine-scale species richness and have a high conservation value. The fact that fine-scale surveys of grassland plant communities are time-consuming may limit the spatial extent of ground-based diversity surveys. Remote sensing tools have the potential to support field-based sampling and, if remote sensing data are able to identify grassland sites that are likely to support relatively higher or lower levels of species diversity, then field sampling efforts could be directed towards sites that are of potential conservation interest. In the present study, we examined whether aerial hyperspectral (414–2501 nm) remote sensing can be used to predict fine-scale plant species diversity (characterized as species richness and Simpson’s diversity) in dry grazed grasslands. Vascular plant species were recorded within 104 (4 m × 4 m) plots on the island of Öland (Sweden) and each plot was characterized by a 245-waveband hyperspectral data set. We used two different modeling approaches to evaluate the ability of the airborne spectral measurements to predict within-plot species diversity: (1) a spectral response approach, based on reflectance information from (i) all wavebands, and (ii) a subset of wavebands, analyzed with a partial least squares regression model, and (2) a spectral heterogeneity approach, based on the mean distance to the spectral centroid in an ordinary least squares regression model. Species diversity was successfully predicted by the spectral response approach (with an error of ca. 20%) but not by the spectral heterogeneity approach. When using the spectral response approach, iterative selection of important wavebands for the prediction of the diversity measures simplified the model but did not improve its predictive quality (prediction error). Wavebands sensitive to plant pigment content (400–700 nm) and to vegetation structural properties, such as above-ground biomass (700–1300 nm), were identified as being the most important predictors of plant species diversity. We conclude that hyperspectral remote sensing technology is able to identify fine-scale variation in grassland diversity and has a potential use as a tool in surveys of grassland plant diversity.

Europe is one of the world's largest food producers, and climate change may pose a serious threat to food security in the region. In the present study, we assess the potential impact of climate change on the Colorado Potato Beetle (CPB), Leptinotarsa decemlineata (Say)-a severe pest of potato (Solanum tuberosum, L.). We also investigate the possible impact of climate change on the phenological development of potato. The main focus is on factors that may limit the northward expansion of the CPB, and the number of generations per year in areas where the insect pest is already present. These factors include lack of temperature sum for completed development before winter, and lack of food (i.e. potato) due to mismatches in insect-host plant phenological synchrony.We use a gridded observational dataset and an ensemble of bias corrected regional climate model data for the period of 1981-2099, representing RCP8.5, as input to a potato and CPB phenological model. The results show that in the future, CPB individuals with a low developmental threshold (+10 degrees C) can complete maturity of two generations per year before potato is harvested in most parts of Europe. A third generation of CPB may not be able to complete maturation due to lack of food in south and central Europe, while temperature becomes a limiting factor further north. In north-eastern Europe, the initiation of a first generation may be delayed due to lack of food in spring. CPBs with a high developmental threshold (+12 degrees C) will emerge later from winter hibernation, and food availability will therefore not be a problem in spring. However, individuals with a high developmental threshold face a greater risk of regeneration failure caused by harvesting of potato in autumn. The potential lack of food in autumn may also increase the strength of selection towards a low developmental threshold in northern populations. The combined analysis of CPB and potato phenology indicated that climate change can lead to increased pressure from the CPB in most potato growing areas. (C) 2016 Elsevier B.V. All rights reserved.

Species-based ecological indices, such as Ellenberg indicators, reflect plant habitat preferences and can be used to describe local environment conditions. One disadvantage of using vegetation data as a substitute for environmental data is the fact that extensive floristic sampling can usually only be carried out at a plot scale within limited geographical areas. Remotely sensed data have the potential to provide information on fine-scale vegetation properties over large areas. In the present study, we examine whether airborne hyperspectral remote sensing can be used to predict Ellenberg nutrient (N) and moisture (M) values in plots in dry grazed grasslands within a local agricultural landscape in southern Sweden. We compare the prediction accuracy of three categories of model: (I) models based on predefined vegetation indices (VIs), (II) models based on waveband-selected VIs, and (III) models based on the full set of hyperspectral wavebands. We also identify the optimal combination of wavebands for the prediction of Ellenberg values. The floristic composition of 104 (4 m x 4 m grassland) plots on the Baltic island of Ol and was surveyed in the field, and the vascular plant species recorded in the plots were assigned Ellenberg indicator values for N and M. A community-weighted mean value was calculated for N (mN) and M (mM) within each plot. Hyperspectral data were extracted from an 8 m x 8 m pixel window centred on each plot. The relationship between field-observed and predicted mean Ellenberg values was significant for all three categories of prediction models. The performance of the category II and III models was comparable, and they gave lower prediction errors and higher R-2 values than the category I models for both mN and mM. Visible and near-infrared wavebands were important for the prediction of both mN and mM, and shortwave infrared wavebands were also important for the prediction of mM. We conclude that airborne hyperspectral remote sensing can detect spectral differences in vegetation between grassland plots characterised by different mean Ellenberg N and M values, and that remote sensing technology can potentially be used to survey fine-scale variation in environmental conditions within a local agricultural landscape. (C)2016 Elsevier Ltd. All rights reserved.

Uncultivated field margins are one of the most frequent non-crop habitat types in contemporary, high-intensity agricultural landscapes and may therefore be important for the persistence of many farmland species. Managing field margins in a way that preserves, and preferably enhances, their value for biodiversity is therefore important. In the present study, we evaluate how the flora of uncultivated field margins is affected by the removal of woody vegetation as prescribed by an agri-environment scheme (AES) under the Swedish Rural Development Program 2007-2013. We used generalized linear mixed models and detrended correspondence analysis to compare the flora of open (cleared) and more overgrown field margins, located within agricultural landscapes of different complexity, in Scania, S. Sweden. As expected, there was a negative effect of management on woody species. However, the local (1 m(2)) and transect (100 m) level richness of non-woody species did not differ significantly between management categories, and there were no differences in the within-transect variability of non-woody species (local beta diversity) or the species composition (0.25 m(2) plots) in managed and unmanaged field margins. Our results show that the removal of woody vegetation from uncultivated field margins, as prescribed by the evaluated AES, is unlikely to benefit non-woody plant species. The species composition of the sampled field margins suggests that inclusion of appropriate field layer management alone is unlikely to be sufficient to improve habitat conditions for grassland species unless measures are taken to counteract eutrophication. Landscape type, on the other hand, influenced both the total richness and the richness of each of the species groups that were considered to be of particular conservation value in the present study: field margins in the complex agricultural landscapes were significantly richer than those in the simple ones. Maintaining non-crop habitat at the landscape scale is likely to be a necessary first step in the prevention of a further decline of farmland plants. (C) 2014 Elsevier B.V. All rights reserved.

Potato (Solanum tuberosum) is one of the main food crops in northern Europe, considered to be the fourth most important crop on a global scale after rice, wheat and maize. Climate change leading to longer growing seasons may call for adjustments in timing of planting and harvesting, and in this modeling study we assess potential effects of a warmer climate on potato crop phenology and temperature stress. A phenological potato model was parameterized with three planting dates to assess management impact on the timing of emergence and maturation of both early and late potato. Estimates on phenological development and occurrence of temperature stress were analyzed by comparing two developmental thresholds (0 degrees C and +2 degrees C) and three temperature response functions. The potato model was driven by observed gridded climate data and two sets of bias corrected climate model data, representing RCP4.5 and RCP8.5 for the period 1991-2100.The future simulations indicated that a wanner climate and earlier planting may move the timing of harvest up to 1 month earlier, however, potato emergence early in the year will be associated with an increased risk of frost damage in most parts of northern Europe. The areas of west Europe most prone to frost damage today may experience a risk of frost damage in response to climate change. The simulation of early potato development was sensitive to the setting of the developmental threshold, while late potato development was sensitive to the optimum temperature setting. While a linear temperature response function is essentially sufficient for current climate conditions in northern Europe, optimum and upper thresholds should be considered in climate change impact assessments. The potato model runs with temperature data corrected according to quantile-mapping indicated in general a slightly higher risk of temperature stress than the corresponding runs with temperature data corrected by linear scaling. (C) 2015 Elsevier B.V. All rights reserved.

The Colorado potato beetle Leptinotarsa decemlineata is an insect pest that can cause a substantial reduction of the potato harvest if left uncontrolled. The aim of this study was to assess the impact of a warmer climate on the Colorado potato beetle in Europe, since temperature influences the beetles' activity and development from egg to adult, and thereby the potential distribution. The study focuses in particular on the potential northward spread in the Scandinavian countries. In this region, the current climate is not warm enough to sustain the completed development of one generation in all years, and the region does not host a permanent population. Temperature data for 1961-2050 from 4 regional climate models and gridded observed data for 1961-1990 (reference period) were used for model calculations. We simulated the earliest timing of completed development of the first and second generations of the Colorado potato beetle, and assessed the geographical and inter-annual variation in the number of generations per year. The model simulations indicated a shift in the northern limit for establishment of a permanent Colorado potato beetle population by 2020-2050 in comparison with 1961-1990. In particular, the model showed a substantial increase in the frequency of years in which the temperature requirement for development of one generation was fulfilled in the transient zone, i.e. the southern part of Scandinavia. In addition, 2 generations per year may occur more frequently at the current distribution border at 55 degrees N, increasing the risk of northward migration to the Scandinavian countries.

Plant communities differ in their species composition, and, thus, also in their functional trait composition, at different stages in the succession from arable fields to grazed grassland. We examine whether aerial hyperspectral (414–2501 nm) remote sensing can be used to discriminate between grazed vegetation belonging to different grassland successional stages. Vascular plant species were recorded in 104.1 m2 plots on the island of Öland (Sweden) and the functional properties of the plant species recorded in the plots were characterized in terms of the ground-cover of grasses, specific leaf area and Ellenberg indicator values. Plots were assigned to three different grassland age-classes, representing 5–15, 16–50 and >50 years of grazing management. Partial least squares discriminant analysis models were used to compare classifications based on aerial hyperspectral data with the age-class classification. The remote sensing data successfully classified the plots into age-classes: the overall classification accuracy was higher for a model based on a pre-selected set of wavebands (85%, Kappa statistic value = 0.77) than one using the full set of wavebands (77%, Kappa statistic value = 0.65). Our results show that nutrient availability and grass cover differences between grassland age-classes are detectable by spectral imaging. These techniques may potentially be used for mapping the spatial distribution of grassland habitats at different successional stages.

Plant species beta diversity is influenced by spatial heterogeneity in the environment. This heterogeneity can potentially be characterised with the help of remote sensing. We used WorldView-2 satellite data acquired over semi-natural grasslands on The Baltic island of Öland (Sweden) to examine whether dissimilarities in remote sensing response were related to fine-scale, between-plot dissimilarity (beta diversity) in non-woody vascular plant species composition within the grasslands. Fieldwork, including the on-site description of a set of 30 2 m × 2 m plots and a set of 30 4 m × 4 m plots, was performed to record the species dissimilarity between pairs of same-sized plots. Spectral data were extracted by associating each plot with a suite of differently sized pixel windows, and spectral dissimilarity was calculated between pairs of same-sized pixel windows. Relationships between spectral dissimilarity and beta diversity were analysed using univariate regression and partial least squares regression. The study revealed significant positive relationships between spectral dissimilarity and fine-scale (2 m × 2 m and 4 m × 4 m) between-plot species dissimilarity. The correlation between the predicted and the observed species dissimilarity was stronger for the set of large plots (4 m × 4 m) than for the set of small plots (2 m × 2 m), and the association between spectral and species data at both plot scales decreased when pixel windows larger than 3 × 3 pixels were used. We suggest that the significant relationship between spectral dissimilarity and species dissimilarity is a reflection of between-plot environmental heterogeneity caused by differences in grazing intensity (which result in between-plot differences in field-layer height, and amounts of biomass and litter). This heterogeneity is reflected in dissimilarities in both the species composition and the spectral response of the grassland plots. Between-plot dissimilarities in both spectral response and species composition may also be caused by between-plot variations in edaphic conditions. Our results indicate that high spatial resolution satellite data may potentially be able to complement field-based recording in surveys of fine-scale species diversity in semi-natural grasslands.

A warmer climate may increase the risk of attacks by insect pests on agricultural crops, and questions on how to adapt management practice have created a need for impact models. Phenological models driven by climate data can be used for assessing the potential distribution and voltinism of different insect species, but the quality of the simulations is influenced by a range of uncertainties. In this study, we model the temperature-dependent activity and development of the Colorado potato beetle, and analyse the influence of uncertainty associated with parameterization of temperature and day length response. We found that the developmental threshold has a major impact on the simulated number of generations per year. Little is known about local adaptations and individual variations, but the use of an upper and a lower developmental threshold gave an indication on the potential variation. The day length conditions triggering diapause are known only for a few populations. We used gridded observed temperature data to estimate local adaptations, hypothesizing that cold autumns can leave a footprint in the population genetics by low survival of individuals not reaching the adult stage before winter. Our study indicated that the potential selection pressure caused by climate conditions varies between European regions. Provided that there is enough genetic variation, a local adaption at the northern distribution limit would reduce the number of unsuccessful initiations and thereby increase the potential for spreading to areas currently not infested. The simulations of the impact model were highly sensitive to biases in climate model data, i.e. systematic deviations in comparison with observed weather, highlightening the need of improved performance of regional climate models. Even a moderate temperature increase could change the voltinism of Leptinotarsa decemlineata in Europe, but knowledge on agricultural practice and strategies for countermeasures is needed to evaluate changes in risk of attacks.

Questions: To what extent is species richness in semi-natural grasslands related to local environmental factors and (present/ past) surrounding landscape structure? Do responses of species richness depend on degree of habitat specialization (specialists vs generalists) and/ or scale of the study? Location: O " land, Sweden. Methods: Richness of herbaceous vascular plants (subdivided into richness of grassland specialists and generalists) was recorded within 50 9 50 cm plots and 0.1-4.8 ha grassland polygons. Generalized linearmodels and hierarchical partitioning were used to identify local factors (habitat area and heterogeneity, grazing intensity, habitat continuity) and landscape factors (proportion of surrounding grassland in 2004, 1938 and 1800, and landscape diversity in 2004) associated with the richness estimates. Results: At the polygon scale, both specialist and generalist richness was positively associated with local habitat area and heterogeneity and, independently of area and heterogeneity, with grazing intensity, habitat continuity and amount of surrounding grassland in 1800. At the plot scale, specialist species richness was positively associated with habitat heterogeneity, amount of surrounding grassland in 2004 and landscape diversity. Plot-scale generalist richness was negatively associated with surrounding grassland in 1938 and positively associated with local grazing intensity. Conclusions: Because both habitat specialization and study scale influence conclusions about relationships between species richness and local and landscape factors, the study highlights the need to consider species diversity at multiple spatial scales when making decisions about grassland management. Large-scale (polygon) species richness is influenced by immigration processes, with both specialists and generalists accumulating in old grasslands over centuries of grazing management. Habitat heterogeneity increased specialist species richness at both scales, suggesting that management policies should favour maintenance of a heterogeneous mosaic of open areas, trees and shrubs in temperate grazed grasslands. Although grassland specialists are sensitive to grassland isolation, in extensively managed landscapes with high landscape diversity input of grassland species from the landscape matrix may buffer negative effects of habitat fragmentation on grassland communities.

Question: Can satellite data be related to fine-scale species diversity and does the integrated use of field and satellite data provide information that can be used in the estimation of fine-scale species diversity in semi-natural grassland sites?Location: The Baltic Island of Oland (Sweden).Methods: Field work including the on-site description of 62 semi-natural grassland sites (represented by three 0.5 m x 0.5 m plots per site) was performed to record response variables (total species richness, mean species richness and species spatial turnover) and field-measured explanatory variables (field-layer height and distance between plots). Within each site, QuickBird satellite data were extracted from a standardized sample area by associating each field plot with a 3 x 3 pixel window (1 pixel = 2.4 m x 2.4 m). Explanatory variables (the normalized difference vegetation index and spectral heterogeneity) were generated from the satellite data. Correlation tests, univariate regressions, variance partitioning and multivariate linear regressions were used to analyse the associations between response and explanatory variables.Results: There was a significant association between the spectral heterogeneity of the near-infrared band and the field-measured spatial turnover of species. The most parsimonious explanatory model for each response variable included both field-measured and satellite-generated explanatory variables. The models explained 30-35% of the variation in species diversity (total richness 36%, mean richness 31%, species turnover 33%).Conclusions: High spatial resolution satellite data are capable of supplying fine-scale habitat information that is relevant for the monitoring and conservation management of fine-scale plant diversity in semi-natural grasslands.

QuestionCan we reliably estimate grazing intensity, indicators of grazing intensity (i.e. field-layer height and shrub-cover), and vascular plant species richness in semi-natural grasslands from high spatial resolution satellite data?LocationThe Baltic Island of Oland (Sweden).MethodsFieldwork included the on-site description of grazed and ungrazed areas and shrub-cover within 107 semi-natural grassland sites. Field-layer height and vascular plant species richness (total within-site and mean small-scale species richness) were recorded within the sites. Digital classification of QuickBird data was performed to identify grazed and ungrazed areas and shrub-cover. Vegetation indices were generated to analyze the performance of satellite data for estimating field-layer height, and the spectral heterogeneity was used to characterize the within-site environmental heterogeneity.ResultsThe proportion of digitally classified grazed area explained 45% of the variation in field-layer height and 43% of the variation in shrub-cover. Field-layer height was significantly related to vegetation indices. A linear model with three explanatory variables (spectral richness(red), spectral richness(NIR), and shrub-cover) explained 47% of the variation in total within-site species richness.ConclusionsHigh spatial resolution imagery may assist in the monitoring of the processes that follow the cessation of grazing, on the scale of individual grassland sites. Measures of spectral heterogeneity acquired by high spatial resolution imagery can be used in the assessment of total within-site vascular plant species richness in semi-natural grassland vegetation.

Summary 1. Temperate semi‐natural grasslands are characterized by high levels of species diversity and have a high conservation value. Plant species diversity in grazed semi‐natural grasslands is known to be influenced by management intensity and habitat connectivity. Both grazing pressure and between‐patch connectivity are expected to depend on the movement patterns of livestock in the landscape. 2. The present study examines associations between fine‐scale (within 0·25 m2 plots) plant species diversity in semi‐natural grasslands and present grazing intensity, present and historical habitat connectivity, and the (present and historical) distance from the nearest village. The study area was a local (4·5 × 4·5 km) agricultural landscape on the island of Öland, Sweden. 3. Fine‐scale (Shannon) diversity and species richness were unimodally associated with the distance from the nearest historical (ad 1800) village, with maximum values c. 1–1·5 km from villages. These associations suggest that the distance from historical villages behaves as an integrated descriptor of variation in long‐term management intensity (livestock movements) and reflects aspects of the functional connectivity between plant communities in semi‐natural grasslands. 4. Groups of variables characterizing village distances, grazing pressure and habitat connectivity had overlapping effects on species diversity. Grazing intensity had the largest individual impact on diversity, followed by the distance from the nearest historical village and present‐day habitat connectivity. 5. Synthesis and applications. The study indicates the importance of viewing grassland diversity in the context of local landscape history. Unimodal associations between fine‐scale plant species diversity and the distance from the nearest village in ad 1800 suggest that information on the proximity to villages in the historical landscape has a potential use in conservation planning – as an indicator of variation in long‐term grassland management intensity. Conservation programmes for grazed temperate grasslands should (1) give priority to old grasslands with an uninterrupted history of grazing management, (2) ensure a moderate grazing intensity, (3) avoid overgrazing and/or long breaks in the continuity of grazing management.

Many of Sweden’s red listed species are found in the agricultural landscape. Small biotopes (e.g. field margins and field islets) are important for the maintenance of biodiversity in agricultural landscapes, and agri-environmental support is paid to farmers who keep them open. However, a proper evaluation of the biodiversity-gains from this type of management is lacking. We examined the predicted response of vascular plant species in field margins in Scania, S. Sweden, to the removal of woody vegetation and found that more species are expected to show a positive than a negative response to this type of management. Comparison of present-day and historical (1940s) aerial photographs shows that field size and the amount of small biotopes have decreased while the cover of woody vegetation on many of the remaining small biotopes has increased. Changes are greater in the arable plains and in the mixed district than in the forest district.