Mechanisms underpinning community stability along a latitudinal gradient: Insights from a niche-based approach.

At large scales, the mechanisms underpinning stability in natural communities may vary in importance due to changes in species composition, mean abundance, and species richness. Here we link species characteristics (niche positions) and community characteristics (richness and abundance) to evaluate the importance of stability mechanisms in 156 butterfly communities monitored across three European countries and spanning five bioclimatic regions. We construct niche-based hierarchical structural Bayesian models to explain first differences in abundance, population stability, and species richness between the countries, and then explore how these factors impact community stability both directly and indirectly (via synchrony and population stability). Species richness was partially explained by the position of a site relative to the niches of the species pool, and species near the centre of their niche had higher average population stability. The differences in mean abundance, population stability, and species richness then influenced how much variation in community stability they explained across the countries. We found, using variance partitioning, that community stability in Finnish communities was most influenced by community abundance, whereas this aspect was unimportant in Spain with species synchrony explaining most variation; the UK was somewhat intermediate with both factors explaining variation. Across all countries, the diversity-stability relationship was indirect with species richness reducing synchrony which increased community stability, with no direct effects of species richness. Our results suggest that in natural communities, biogeographical variation observed in key drivers of stability, such as population abundance and species richness, leads to community stability being limited by different factors and that this can partially be explained due to the niche characteristics of the European butterfly assemblage.

Local adaptation to climate anomalies relates to species phylogeny.

Climatic anomalies are increasing in intensity and frequency due to rapid rates of global change, leading to increased extinction risk for many species. The impacts of anomalies are likely to vary between species due to different degrees of sensitivity and extents of local adaptation. Here, we used long-term butterfly monitoring data of 143 species across six European bioclimatic regions to show how species' population dynamics have responded to local or globally-calculated climatic anomalies, and how species attributes mediate these responses. Contrary to expectations, degree of apparent local adaptation, estimated from the relative population sensitivity to local versus global anomalies, showed no associations with species mobility or reproductive rate but did contain a strong phylogenetic signal. The existence of phylogenetically-patterned local adaptation to climate has important implications for forecasting species responses to current and future climatic conditions and for developing appropriate conservation practices.

Inferring species interactions from ecological survey data: A mechanistic approach to predict quantitative food webs of seed feeding by carabid beetles.

Ecological networks are valuable for ecosystem analysis but their use is often limited by a lack of data because many types of ecological interaction, for example, predation, are short-lived and difficult to observe or detect. While there are different methods for inferring the presence of interactions, they have rarely been used to predict the interaction strengths that are required to construct weighted, or quantitative, ecological networks.Here, we develop a trait-based approach suitable for inferring weighted networks, that is, with varying interaction strengths. We developed the method for seed-feeding carabid ground beetles (Coleoptera: Carabidae) although the principles can be applied to other species and types of interaction.Using existing literature data from experimental seed-feeding trials, we predicted a per-individual interaction cost index based on carabid and seed size. This was scaled up to the population level to create inferred weighted networks using the abundance of carabids and seeds from empirical samples and energetic intake rates of carabids from the literature. From these weighted networks, we also derived a novel measure of expected predation pressure per seed type per network.This method was applied to existing ecological survey data from 255 arable fields with carabid data from pitfall traps and plant seeds from seed rain traps. Analysis of these inferred networks led to testable hypotheses about how network structure and predation pressure varied among fields.Inferred networks are valuable because (a) they provide null models for the structuring of food webs to test against empirical species interaction data, for example, DNA analysis of carabid gut regurgitates and (b) they allow weighted networks to be constructed whenever we can estimate interactions between species and have ecological census data available. This permits ecological network analysis even at times and in places when interactions were not directly assessed.

Combining range and phenology shifts offers a winning strategy for boreal Lepidoptera.

Species can adapt to climate change by adjusting in situ or by dispersing to new areas, and these strategies may complement or enhance each other. Here, we investigate temporal shifts in phenology and spatial shifts in northern range boundaries for 289 Lepidoptera species by using long-term data sampled over two decades. While 40% of the species neither advanced phenology nor moved northward, nearly half (45%) used one of the two strategies. The strongest positive population trends were observed for the minority of species (15%) that both advanced flight phenology and shifted their northern range boundaries northward. We show that, for boreal Lepidoptera, a combination of phenology and range shifts is the most viable strategy under a changing climate. Effectively, this may divide species into winners and losers based on their propensity to capitalize on this combination, with potentially large consequences on future community composition.

Enriching the Shared Socioeconomic Pathways to co-create consistent multi-sector scenarios for the UK.

As the pressure to take action against global warming is growing in urgency, scenarios that incorporate multiple social, economic and environmental drivers become increasingly critical to support governments and other stakeholders in planning climate change mitigation or adaptation actions. This has led to the recent explosion of future scenario analyses at multiple scales, further accelerated since the development of the Intergovernmental Panel on Climate Change (IPCC) research community Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). While RCPs have been widely applied to climate models to produce climate scenarios at multiple scales for investigating climate change impacts, adaptation and vulnerabilities (CCIAV), SSPs are only recently being scaled for different geographical and sectoral applications. This is seen in the UK where significant investment has produced the RCP-based UK Climate Projections (UKCP18), but no equivalent UK version of the SSPs exists. We address this need by developing a set of multi-driver qualitative and quantitative UK-SSPs, following a state-of-the-art scenario methodology that integrates national stakeholder knowledge on locally-relevant drivers and indicators with higher level information from European and global SSPs. This was achieved through an intensive participatory process that facilitated the combination of bottom-up and top-down approaches to develop a set of UK-specific SSPs that are locally comprehensive, yet consistent with the global and European SSPs. The resulting scenarios balance the importance of consistency and legitimacy, demonstrating that divergence is not necessarily the result of inconsistency, nor comes as a choice to contextualise narratives at the appropriate scale.

A new comprehensive trait database of European and Maghreb butterflies, Papilionoidea.

Trait-based analyses explaining the different responses of species and communities to environmental changes are increasing in frequency. European butterflies are an indicator group that responds rapidly to environmental changes with extensive citizen science contributions to documenting changes of abundance and distribution. Species traits have been used to explain long- and short-term responses to climate, land-use and vegetation changes. Studies are often characterised by limited trait sets being used, with risks that the relative roles of different traits are not fully explored. Butterfly trait information is dispersed amongst various sources and descriptions sometimes differ between sources. We have therefore drawn together multiple information sets to provide a comprehensive trait database covering 542 taxa and 25 traits described by 217 variables and sub-states of the butterflies of Europe and Maghreb (northwest Africa) which should serve for improved trait-based ecological, conservation-related, phylogeographic and evolutionary studies of this group of insects. We provide this data in two forms; the basic data and as processed continuous and multinomial data, to enhance its potential usage.

Ecology and Genetic Structure of the Parasitoid Phobocampe confusa (Hymenoptera: Ichneumonidae) in Relation to Its Hosts, Aglais Species (Lepidoptera: Nymphalidae).

The biology of parasitoids in natural ecosystems remains very poorly studied, though they are key species for their functioning. Here we focused on Phobocampe confusa, a Nymphalini specialist, responsible for high mortality rates in charismatic butterfly species in Europe (genus Aglais). We studied its ecology and genetic structure in connection with those of its host butterflies in Sweden. To this aim, we gathered data from 428 P. confusa individuals reared from 6094 butterfly larvae (of A. urticae, A. io, and in two occasions of Araschnia levana) collected over two years (2017 and 2018) and across 19 sites distributed along a 500 km latitudinal gradient. We found that P. confusa is widely distributed along the latitudinal gradient. Its distribution seems constrained over time by the phenology of its hosts. The large variation in climatic conditions between sampling years explains the decrease in phenological overlap between P. confusa and its hosts in 2018 and the 33.5% decrease in the number of butterfly larvae infected. At least in this study, P. confusa seems to favour A. urticae as host. While it parasitized nests of A. urticae and A. io equally, the proportion of larvae parasitized is significantly higher for A. urticae. At the landscape scale, P. confusa is almost exclusively found in vegetated open land and near deciduous forests, whereas artificial habitats are negatively correlated with the likelihood of a nest to be parasitized. The genetic analyses on 89 adult P. confusa and 87 adult A. urticae using CO1 and AFLP markers reveal a low genetic diversity in P. confusa and a lack of genetic structure in both species, at the scale of our sampling. Further genetic studies using high-resolution genomics tools will be required to better understand the population genetic structure of P. confusa, its biotic interactions with its hosts, and ultimately the stability and the functioning of natural ecosystems.

Data Integration for Large-Scale Models of Species Distributions.

With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species' potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in ways that retain the strengths of each. We describe a flexible approach to data integration using point process models, which provide a convenient way to translate across ecological currencies. We highlight recent examples of large-scale ecological models based on data integration and outline the conceptual and technical challenges and opportunities that arise.

The importance of landscape characteristics for the delivery of cultural ecosystem services.

The importance of Cultural Ecosystem Services (CES) to human wellbeing is widely recognised. However, quantifying these non-material benefits is challenging and consequently they are often not assessed. Mapping approaches are increasingly being used to understand the spatial distribution of different CES and how this relates to landscape characteristics. This study uses an online Public Participation Geographic Information System (PPGIS) to elicit information on outdoor locations important to respondents in Wiltshire, a dynamic lowland landscape in southern England. We analysed these locations in a GIS with spatial datasets representing potential influential factors, including protected areas, land use, landform, and accessibility. We assess these characteristics at different spatial and visual scales for different types of cultural engagement. We find that areas that are accessible, near to urban centres, with larger views, and a high diversity of protected habitats, are important for the delivery of CES. Other characteristics including a larger area of woodland and the presence of sites of historic interest in the surrounding landscape were also influential. These findings have implications for land-use planning and the management of ecosystems, by demonstrating the benefits of high quality ecological sites near to towns. The importance of maintaining and restoring landscape features, such as woodlands, to enhance the delivery of CES were also highlighted.

Pollination and reproduction of a self-incompatible forest herb in hedgerow corridors and forest patches.

Habitat-corridors are assumed to counteract the negative impacts of habitat loss and fragmentation, but their efficiency in doing so depends on the maintenance of ecological processes in corridor conditions. For plants dispersing in linear habitats, one of these critical processes is the maintenance of adequate pollen transfer to insure seed production within the corridor. This study focuses on a common, self-incompatible forest herb, Trillium grandiflorum, to assess plant-pollinator interactions and the influence of spatial processes on plant reproduction in hedgerow corridors compared to forests. First, using pollen supplementation experiments over 2 years, we quantified the extent of pollen limitation in both habitats, testing the prediction of greater limitation in small hedgerow populations than in forests. While pollen limitation of fruit and seed set was common, its magnitude did not differ between habitats. Variations among sites, however, suggested an influence of landscape context on pollination services. Second, we examined the effect of isolation on plant reproduction by monitoring fruit and seed production, as well as pollinator activity and assemblage, in small flower arrays transplanted in hedgerows at increasing distances from forest and from each other. We detected no difference in the proportion of flowers setting fruit or in pollinator activity with isolation, but we observed some differences in pollinator assemblages. Seed set, on the other hand, declined significantly with increasing isolation in the second year of the study, but not in the first year, suggesting altered pollen transfer with distance. Overall, plants in hedgerow corridors and forests benefited from similar pollination services. In this system, plant-pollinator interactions and reproduction seem to be influenced more by variations in resource distribution over years and landscapes than by local habitat conditions.

Spatial and temporal dynamics of hedgerows in three agricultural landscapes of southern Quebec, Canada.

Noncrop areas such as hedgerows in agricultural landscapes can perform several ecological and agronomic functions (e.g., habitat, movement corridors, windbreak, etc.), but their dynamics and drivers of changes are often poorly known. We conducted a study in three agricultural landscapes of southern Quebec, Canada, to assess and compare the spatial and temporal (1958-1997) dynamics of three hedgerow networks in relation to geomorphic conditions (marine, glacial, and mixed deposit) and land-use changes. Hedgerow networks were mapped and described in terms of their structure (density, degree of connectivity, and presence of trees or shrubs) and their relationship to other components of the landscape (connection to woodland). Relationships were assessed in time and space using nonparametric correlation, Mantel test, and principal components analysis (PCA). Results show significant differences between hedgerow structure for the three landscapes and distinct temporal and spatial dynamics that can be related to changes in management practices and agricultural policies. On marine deposits, increases in hedgerow density did not always correspond to an increase in their degree of connectivity, suggesting a possible reduction in network quality. On glacial deposits, hedgerow density declined following abandonment of agricultural land, but rather than disappearing, these linear structures were integrated into adjacent brush or forested areas. Our analysis reveals the complex spatial and temporal dynamics of the hedgerow networks and highlights the need to take into account spatial attributes such as connectivity and connection to woodland to evaluate more accurately overall network quality.