Search

Agricultural intensification, afforestation and land abandonment are major drivers of biodiversity loss in semi-natural grasslands across Europe. Reversing these losses requires the reinstatement of plant–animal interactions such as pollination. Here we assessed the differences in species composition and patterns of plant-pollinator interactions in ancient and restored grasslands and how these patterns are influenced by landscape connectivity, across three European regions (Belgium, Germany and Sweden). We evaluated the differences in pollinator community assemblage, abundance and interaction network structure between 24 ancient and restored grasslands. We then assessed the effect of surrounding landscape functional connectivity (i.e. green infrastructure, GI) on these variables and tested possible consequences on the reproduction of two model plants, Lotus corniculatus and Salvia pratensis. Neither pollinator richness nor species composition differed between ancient and restored grasslands. A high turnover of interactions across grasslands was detected but was mainly due to replacement of pollinator and plant species. The impact of grassland restoration was consistent across various pollinator functional groups, whereas the surrounding GI had differential effects. Notably, bees, butterflies, beetles, and dipterans (excluding hoverflies) exhibited the most significant responses to GI variations. Interestingly, networks in restored grasslands were more specialised (i.e. less functionally redundant) than in ancient ones and also showed a higher number of insect visits to habitat-generalist plant species. Landscape connectivity had a similar effect, with habitat-specialist plant species receiving fewer visits at higher GI values. Fruit set in S. pratensis and L. corniculatus was unaffected by grassland type or GI. However, the fruit set in the specialist S. pratensis increased with the number of pollinator visits, indicating a positive correlation between pollinator ac

Ancient semi-natural grasslands in Europe are important for ecosystem service (ES) provision. Often, the surrounding matrix contains ‘Grassland Green Infrastructure’ (GGI) that contain grassland species which have the potential to supplement grassland ES provision across the landscape. Here we investigate the potential for GGI to deliver a set of complementary ES, driven by plant composition.We surveyed 36 landscapes across three European countries comprising core grasslands and their surrounding GGI. We calculated community-level values of plant species characteristics to provide indicators for four ES: nature conservation value, pollination, carbon storage and aesthetic appeal.Inferred ES delivery for GGI was substantially lower than in core grasslands for conservation, pollination and aesthetic appeal indicators, but not for carbon storage. These differences were driven by the GGI having 17% fewer plant species, and compositional differences, with 61% of species unique to the core grasslands. In addition, connectivity to the core, the amount of GGI and inferred seed dispersal distances by livestock, were strongly positively correlated with conservation value, pollination and aesthetic indicators. All ES indicators showed similar responses to the GGI spatial structure and distance to the core, suggesting robust effects of these drivers on ES. We projected that improved landscape-wide delivery of nature conservation value and pollination could be achieved through targeted GGI management. Reductions in the distances seeds would need to disperse, more GGI, along with a diversification of the GGI elements, were predicted to enhance service credits.We conclude that for vegetation-related ES, species surveys can be employed to assess potential ES delivery. Creating and enhancing GGI is a useful landscape management strategy to supplement the ES delivered by ancient grasslands.

Species may benefit from green infrastructure, i.e. the network of natural and anthropogenic habitat remnants in human-dominated landscapes, if it helps isolated populations in remaining habitat patches to be functionally connected. The importance of green infrastructure is therefore increasingly emphasized in conservation policy to counter biodiversity loss. However, there is limited evidence, particularly in plants, that green infrastructure promotes functional connectivity, i.e. supports the colonization of habitat patches across a landscape. We applied landscape genetics to test whether the green infrastructure supports structural and functional connectivity in the grassland perennial Galium verum, in 35 landscapes in Belgium, Germany and Sweden. We used multivariate genetic clustering techniques, nestedness analyses and conditional inference trees to examine landscape-scale patterns in genetic diversity and structure of plant populations in the green infrastructure surrounding semi-natural grasslands. Inferred functional connectivity explained genetic variation better than structural connectivity, yielding positive effects on genetic variation. The road verge network, a major structural component of the green infrastructure and its functional connectivity, most effectively explained genetic diversity and composition in G. verum. Galium verum ramets occupying the surrounding landscape proved to be genetic subsets of focal grassland populations, shaping a nested landscape population genetic structure with focal grasslands, particularly ancient ones, harbouring unique genetic diversity. This nested pattern weakened as road network density increased, suggesting road verge networks enable high landscape occupancy by increased habitat availability and facilitates gene flow into the surrounding landscape. Our study proposes that green infrastructure can promote functional connectivity, providing that a plant species can survive outside of core habitat patches. As this

Many ecosystem services (ES) models exist to support sustainable development decisions. However, most ES studies use only a single modelling framework and, because of a lack of validation data, rarely assess model accuracy for the study area. In line with other research themes which have high model uncertainty, such as climate change, ensembles of ES models may better serve decision-makers by providing more robust and accurate estimates, as well as provide indications of uncertainty when validation data are not available. To illustrate the benefits of an ensemble approach, we highlight the variation between alternative models, demonstrating that there are large geographic regions where decisions based on individual models are not robust. We test if ensembles are more accurate by comparing the ensemble accuracy of multiple models for six ES against validation data across sub-Saharan Africa with the accuracy of individual models. We find that ensembles are better predictors of ES, being 5.0-6.1% more accurate than individual models. We also find that the uncertainty (i.e. variation among constituent models) of the model ensemble is negatively correlated with accuracy and so can be used as a proxy for accuracy when validation is not possible (e.g. in data-deficient areas or when developing scenarios). Since ensembles are more robust, accurate and convey uncertainty, we recommend that ensemble modelling should be more widely implemented within ES science to better support policy choices and implementation.

Habitat destruction and degradation represent serious threats to biodiversity, and quantification of land-use change over time is important for understanding the consequences of these changes to organisms and ecosystem service provision. Comparing land use between maps from different time periods allows estimation of the magnitude of habitat change in an area. However, digitizing historical maps manually is time-consuming and analyses of change are usually carried out at small spatial extents or at low resolutions. HistMapR contains a number of functions that can be used to semi-automatically digitize historical land use according to a map's colours, as defined by the RGB bands of the raster image. We test the method on different historical land-use map series and compare results to manual digitizations. Digitization is fast, and agreement with manually digitized maps of around 80-90% meets common targets for image classification. We hope that the ability to quickly classify large areas of historical land use will promote the inclusion of land-use change into analyses of biodiversity, species distributions and ecosystem services.

1. Dispersal is essential for species to survive the threats of habitat destruction and climate change. Combining descriptions of dispersal ability with those of landscape structure, the concept of functional connectivity has been popular for understanding and predicting species' spatial responses to environmental change. 2. Following recent advances, the functional connectivity concept is now able to move beyond landscape structure to consider more explicitly how other external factors such as climate and resources affect species movement. We argue that these factors, in addition to a consideration of the complete dispersal process, are critical for an accurate understanding of functional connectivity for plant species in response to environmental change. 3. We use recent advances in dispersal, landscape and molecular ecology to describe how a range of external factors can influence effective dispersal in plant species, and how the resulting functional connectivity can be assessed. 4. Synthesis. We define plant functional connectivity as the effective dispersal of propagules or pollen among habitat patches in a landscape. Plant functional connectivity is determined by a combination of landscape structure, interactions between plant, environment and dispersal vectors, and the successful establishment of individuals. We hope that this consolidation of recent research will help focus future connectivity research and conservation.