Quantitative Prediction of Interactions in Bipartite Networks Based on Traits, Abundances, and Phylogeny.

AbstractEcological interactions link species in networks. Loss of species from or introduction of new species into an existing network may have substantial effects for interaction patterns. Predicting changes in interaction frequency while allowing for rewiring of existing interactions-and hence estimating the consequences of community compositional changes-is thus a central challenge for network ecology. Interactions between species groups, such as pollinators and flowers or parasitoids and hosts, are moderated by matching morphological traits or sensory clues, most of which are unknown to us. If these traits are phylogenetically conserved, however, we can use phylogenetic distances to construct latent, surrogate traits and try to match those across groups, in addition to observed traits. Understanding how important traits and trait matching are, relative to abundances and chance, is crucial to estimating the fundamental predictability of network interactions. Here, we present a statistically sound approach ("tapnet") to fitting abundances, traits, and phylogeny to observed network data to predict interaction frequencies. We thereby expand existing approaches to quantitative bipartite networks, which so far have failed to correctly represent the nonindependence of network interactions. Furthermore, we use simulations and cross validation on independent data to evaluate the predictive power of the fit. Our results show that tapnet is on a par with abundance-only, matching centrality, and machine learning approaches. This approach also allows us to evaluate how well current concepts of trait matching work. On the basis of our results, we expect that interactions in well-sampled networks can be well predicted if traits and abundances are the main driver of interaction frequency.

Seeing through the static: the temporal dimension of plant-animal mutualistic interactions.

Most studies of plant-animal mutualistic networks have come from a temporally static perspective. This approach has revealed general patterns in network structure, but limits our ability to understand the ecological and evolutionary processes that shape these networks and to predict the consequences of natural and human-driven disturbance on species interactions. We review the growing literature on temporal dynamics of plant-animal mutualistic networks including pollination, seed dispersal and ant defence mutualisms. We then discuss potential mechanisms underlying such variation in interactions, ranging from behavioural and physiological processes at the finest temporal scales to ecological and evolutionary processes at the broadest. We find that at the finest temporal scales (days, weeks, months) mutualistic interactions are highly dynamic, with considerable variation in network structure. At intermediate scales (years, decades), networks still exhibit high levels of temporal variation, but such variation appears to influence network properties only weakly. At the broadest temporal scales (many decades, centuries and beyond), continued shifts in interactions appear to reshape network structure, leading to dramatic community changes, including loss of species and function. Our review highlights the importance of considering the temporal dimension for understanding the ecology and evolution of complex webs of mutualistic interactions.

Increasing connectivity enhances habitat specialists but simplifies plant-insect food webs.

Strong declines of grassland species diversity in small and isolated grassland patches have been observed at local and landscape scales. Here, we study how plant-herbivore interaction webs and habitat specialisation of leafhopper communities change with the size of calcareous grassland fragments and landscape connectivity. We surveyed leafhoppers and plants on 14 small (0.1-0.6 ha) and 14 large (1.2-8.8 ha) semi-natural calcareous grassland fragments in Central Germany, differing in isolation from other calcareous grasslands and in the percentage of arable land in the surrounding landscape (from simple to complex landscapes). We quantified weighted trophic links between plants and their phytophagous leafhoppers for each grassland fragment. We found that large and well-connected grassland fragments harboured a high portion of specialist leafhopper species, which in turn yielded low interaction diversity and simple plant-leafhopper food webs. In contrast, small and well-connected fragments exhibited high levels of generalism, leading to higher interaction diversity. In conclusion, food web complexity appeared to be a poor indicator for the management of insect diversity, as it is driven by specialist species, which require high connectivity of large fragments in complex landscapes. We conclude that habitat specialists should be prioritized since generalist species associated with small fragments are also widespread in the surrounding landscape matrix.

Within-day dynamics of plant-pollinator networks are dominated by early flower closure: an experimental test of network plasticity.

Temporal variability of plant-pollinator interactions is important for fully understanding the structure, function, and stability of plant-pollinator networks, but most network studies so far have ignored within-day dynamics. Strong diel dynamics (e.g., a regular daily cycle) were found for networks with Cichorieae, which typically close their flowers around noon. Here, we experimentally prevented early flower closure to test whether these dynamics are driven by the temporally limited availability of Cichorieae, or by timing of pollinator activity. We further tested if the dynamics involving Cichorieae and their pollinators also affect the dynamics on other plants in the network. Finally, we explored the structure of such manipulated networks (with Cichorieae available in the morning and afternoon) compared to unmanipulated controls (Cichorieae available only in the morning). We found that flower closure of Cichorieae is indeed an important driver of diel network dynamics, while other drivers of pollinator timing appeared less important. If Cichorieae flowers were available in the afternoon, they were visited by generalist and specialist pollinators, which overall decreased link turnover between morning and afternoon. Effects of afternoon availability of Cichorieae on other plants in the network were inconclusive: pollinator switching to and from Cichorieae tended to increase. On the level of the aggregated (full-day) network, the treatment resulted in increased dominance of Cichorieae, reducing modularity and increasing plant generality. These results highlight that network dynamics can be predicted by knowledge of diel or seasonal phenology, and that fixed species timing assumptions will misrepresent the expected dynamics.

Crop pests and predators exhibit inconsistent responses to surrounding landscape composition.

The idea that noncrop habitat enhances pest control and represents a win-win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win-win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.

Co-occurrence patterns and the large-scale spatial structure of benthic communities in seagrass meadows and bare sand.

BACKGROUND: Species distribution models are commonly used tools to describe diversity patterns and support conservation measures. There is a wide range of approaches to developing SDMs, each highlighting different characteristics of both the data and the ecology of the species or assemblages represented by the data. Yet, signals of species co-occurrences in community data are usually ignored, due to the assumption that such structuring roles of species co-occurrences are limited to small spatial scales and require experimental studies to be detected. Here, our aim is to explore associations among marine sandy-bottom sediment inhabitants and test for the structuring effect of seagrass on co-occurrences among these species across a New Zealand intertidal sandflat, using a joint species distribution model (JSDM). RESULTS: We ran a JSDM on a total of 27 macrobenthic species co-occurring in 300,000 m2 of sandflat. These species represented all major taxonomic groups, i.e. polychaetes, bivalves and crustaceans, collected in 400 sampling locations. A number of significant co-occurrences due to shared habitat preferences were present in vegetated areas, where negative and positive correlations were approximately equally common. A few species, among them the gastropods Cominella glandiformis and Notoacmea scapha, co-occurred randomly with other seagrass benthic inhabitants. Residual correlations were less apparent and mostly positive. In bare sand flats shared habitat preferences resulted in many significant co-occurrences of benthic species. Moreover, many negative and positive residual patterns between benthic species remained after accounting for habitat preferences. Some species occurring in both habitats showed similarities in their correlations, such as the polychaete Aglaophamus macroura, which shared habitat preferences with many other benthic species in both habitats, yet no residual correlations remained in either habitat. CONCLUSIONS: Firstly, analyses based on a latent variable approach to joint distributions stressed the structuring role of species co-occurrences beyond experimental scales. Secondly, results showed context dependent interactions, highlighted by species having more interconnected networks in New Zealand bare sediment sandflats than in seagrass meadows. These findings stress the critical importance of natural history to modelling, as well as incorporating ecological reality in SDMs.

Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using multiple taxa.

BACKGROUND: Spatial conservation prioritisation (SCP) is a set of computational tools designed to support the efficient spatial allocation of priority areas for conservation actions, but it is subject to many sources of uncertainty which should be accounted for during the prioritisation process. We quantified the sensitivity of an SCP application (using software Zonation) to possible sources of uncertainty in data-poor situations, including the use of different surrogate options; correction for sampling bias; how to integrate connectivity; the choice of species distribution modelling (SDM) algorithm; how cells are removed from the landscape; and two methods of assigning weights to species (red-list status or prediction uncertainty). Further, we evaluated the effectiveness of the Egyptian protected areas for conservation, and spatially allocated the top priority sites for further on-the-ground evaluation as potential areas for protected areas expansion. RESULTS: Focal taxon (butterflies, reptiles, and mammals), sampling bias, connectivity and the choice of SDM algorithm were the most sensitive parameters; collectively these reflect data quality issues. In contrast, cell removal rule and species weights contributed much less to overall variability. Using currently available species data, we found the current effectiveness of Egypt's protected areas for conserving fauna was low. CONCLUSIONS: For SCP to be useful, there is a lower limit on data quality, requiring data-poor countries to improve sampling strategies and data quality to obtain unbiased data for as many taxa as possible. Since our sensitivity analysis may not generalise, conservation planners should use sensitivity analyses more routinely, particularly relying on more than one combination of SDM algorithm and surrogate group, consider correction for sampling bias, and compare the spatial patterns of predicted priority sites using a variety of settings. The sensitivity of SCP to connectivity parameters means that the responses of each species to habitat loss are important knowledge gaps.

Adaptation of wild boar (Sus scrofa) activity in a human-dominated landscape.

BACKGROUND: Wild boars (Sus scrofa L.) are globally widely distributed, and their populations have increased in Europe during recent decades. Encounters between humans and wild boars are rare because of the predominantly nocturnal lifestyle of the latter, and wild boar management by hunting is a challenging task. Animal activity patterns are important for understanding the behaviour of a species. However, knowledge of detailed temporal patterns and an understanding of the drivers of wild boar activity at a fine temporal scale are lacking. Of special relevance for human-wild boar interactions (e.g., encounters, conflicts, and management) is the question of whether nocturnal activity depends on anthropogenic factors and, particularly, how local hunting regimes may affect activity patterns. We used GPS telemetry and acceleration measurements to shed light on this part of wild boar behaviour, observing 34 animals in Central Europe. Animals were tracked along a gradient of hunting pressure from hunting-free areas to areas with low or high hunting pressure. Fitted generalised additive models allowed predicting the probability of active behaviour under differing disturbance regimes precisely to day of year and time of day. RESULTS: The wild boars were predominantly nocturnal, with peak activity at approximately midnight. However, the data showed increased activity during daylight for wild boars that used no-hunting zones or reduced-hunting zones. Large areas with low disturbance levels promoted activity during daylight more than smaller areas with an intermediate disturbance regime. High air temperatures and locations within forests reduced the probability of active behaviour, whereas proximity to tracks used for forestry or agriculture was accompanied by a higher probability of activity. CONCLUSIONS: We conclude that wild boars flexibly adjust their activity to their local environmental conditions, considering disturbances at the scale of long-term home ranges as well as actual small-scale landscape quality. Entire wild boar home ranges should be covered in the delineation of reserves intending to stimulate activity during daylight.

Plant species richness increases with light availability, but not variability, in temperate forests understorey.

BACKGROUND: Temperate forest understorey vegetation poses an excellent study system to investigate whether increases in resource availability lead to an increase in plant species richness. Most sunlight is absorbed by the species-poor tree canopy, making the much more species-rich understorey species inhabit a severely resource-limited habitat. Additionally, the heterogeneity of light availability, resulting from management-moderated tree composition and age structure, may contribute to species coexistence. One would therefore expect that the diversity in the herb layer correlates positively with either the overall light availability, or the light heterogeneity, depending on whether resource availability or heterogeneity are more important drivers of diversity. To test this idea, we assessed variability of light conditions in 75 forest plots across three ecoregions with four different methods. RESULTS: We correlated these data with vegetation relevés and found light availability to be strongly positively correlated with understorey plant species richness, as well as with understorey cover. Light variability (assessed with two approaches) within plots was positively correlated with transmittance, but did not improve the relationship further, suggesting that the main driver of species richness in this system is the overall resource availability. Two of the three beech-dominated regions exhibited near-identical effects of light transmittance, while the third, featuring pine alongside beech and thus with the longest gradient of transmittance and lowest species richness, displayed a weaker light response. CONCLUSIONS: While site conditions are certainly responsible for the trees selected by foresters, for the resulting forest structure, and for the differences in plant species pools, our results suggest that light transmittance is a strong mediating factor of understorey plant species richness.

Exploration of Concerns about the Evidence-Based Guideline Approach in Conservation Management: Hints from Medical Practice.

The importance of using evidence in decision-making is frequently highlighted in policy reports and scientific papers. However, subjective judgments of the reliability of environmental evidence vary widely, and large-scale systematic searches for evidence are only common for climate-related topics. In the medical field, evidence-based guidelines are routinely used to guide treatments. In the management of multiple-use landscapes similar guidelines could substantially narrow the science-practice gap but are largely absent. The challenges potential guidelines face are therefore unknown. For the case of forest conservation, we conducted 14 semistructured interviews with mainly forest practitioners and presented them an example medical guideline together with evidence-based statements on forest conservation (hereinafter: statement paper). We identified 28 concerns related to potential evidence-based guidelines in forest conservation. The interviews yielded approximately three major findings. First, recommendations on forest conservation are better accepted if they include clear instructions and are formulated for a specific context. Fragmentary conservation evidence complicates the formulation of specific recommendations. Second, the level of evidence framework, which indicates the strength of the available evidence, is perceived as too complex. Third, neglecting forest multifunctionality in a potential guideline hampers its application but, if addressed, potentially weakens its ecological relevance. We show that major concerns about potential evidence-based conservation guidelines are similar to the challenges experienced by medical guidelines. We also identify concerns unique to forestry.

The interplay of landscape composition and configuration: new pathways to manage functional biodiversity and agroecosystem services across Europe.

Managing agricultural landscapes to support biodiversity and ecosystem services is a key aim of a sustainable agriculture. However, how the spatial arrangement of crop fields and other habitats in landscapes impacts arthropods and their functions is poorly known. Synthesising data from 49 studies (1515 landscapes) across Europe, we examined effects of landscape composition (% habitats) and configuration (edge density) on arthropods in fields and their margins, pest control, pollination and yields. Configuration effects interacted with the proportions of crop and non-crop habitats, and species' dietary, dispersal and overwintering traits led to contrasting responses to landscape variables. Overall, however, in landscapes with high edge density, 70% of pollinator and 44% of natural enemy species reached highest abundances and pollination and pest control improved 1.7- and 1.4-fold respectively. Arable-dominated landscapes with high edge densities achieved high yields. This suggests that enhancing edge density in European agroecosystems can promote functional biodiversity and yield-enhancing ecosystem services.

No consistent effect of plant species richness on resistance to simulated climate change for above- or below-ground processes in managed grasslands.

BACKGROUND: Species richness affects processes and functions in many ecosystems. Since management of temperate grasslands is directly affecting species composition and richness, it can indirectly govern how systems respond to fluctuations in environmental conditions. Our aim in this study was to investigate whether species richness in managed grasslands can buffer the effects of drought and warming manipulations and hence increase the resistance to climate change. We established 45 plots in three regions across Germany, each with three different management regimes (pasture, meadow and mown pasture). We manipulated spring warming using open-top chambers and summer drought using rain-out shelters for 4 weeks. RESULTS: Measurements of species richness, above- and below-ground biomass and soil carbon and nitrogen concentrations showed significant but inconsistent differences among regions, managements and manipulations. We detected a three-way interaction between species richness, management and region, indicating that our study design was sensitive enough to detect even intricate effects. CONCLUSIONS: We could not detect a pervasive effect of species richness on biomass differences between treatments and controls, indicating that a combination of spring warming and summer drought effects on grassland systems are not consistently moderated by species richness. We attribute this to the relatively high number of species even at low richness levels, which already provides the complementarity required for positive biodiversity-ecosystem functioning relationships. A review of the literature also indicates that climate manipulations largely fail to show richness-buffering, while natural experiments do, suggesting that such manipulations are milder than reality or incur treatment artefacts.

Interannual variation in land-use intensity enhances grassland multidiversity.

Although temporal heterogeneity is a well-accepted driver of biodiversity, effects of interannual variation in land-use intensity (LUI) have not been addressed yet. Additionally, responses to land use can differ greatly among different organisms; therefore, overall effects of land-use on total local biodiversity are hardly known. To test for effects of LUI (quantified as the combined intensity of fertilization, grazing, and mowing) and interannual variation in LUI (SD in LUI across time), we introduce a unique measure of whole-ecosystem biodiversity, multidiversity. This synthesizes individual diversity measures across up to 49 taxonomic groups of plants, animals, fungi, and bacteria from 150 grasslands. Multidiversity declined with increasing LUI among grasslands, particularly for rarer species and aboveground organisms, whereas common species and belowground groups were less sensitive. However, a high level of interannual variation in LUI increased overall multidiversity at low LUI and was even more beneficial for rarer species because it slowed the rate at which the multidiversity of rare species declined with increasing LUI. In more intensively managed grasslands, the diversity of rarer species was, on average, 18% of the maximum diversity across all grasslands when LUI was static over time but increased to 31% of the maximum when LUI changed maximally over time. In addition to decreasing overall LUI, we suggest varying LUI across years as a complementary strategy to promote biodiversity conservation.

The influence of floral traits on specialization and modularity of plant-pollinator networks in a biodiversity hotspot in the Peruvian Andes.

BACKGROUND AND AIMS: Modularity is a ubiquitous and important structural property of ecological networks which describes the relative strengths of sets of interacting species and gives insights into the dynamics of ecological communities. However, this has rarely been studied in species-rich, tropical plant-pollinator networks. Working in a biodiversity hotspot in the Peruvian Andes we assessed the structure of quantitative plant-pollinator networks in nine valleys, quantifying modularity among networks, defining the topological roles of species and the influence of floral traits on specialization. METHODS: A total of 90 transects were surveyed for plants and pollinators at different altitudes and across different life zones. Quantitative modularity (QuanBiMo) was used to detect modularity and six indices were used to quantify specialization. KEY RESULTS: All networks were highly structured, moderately specialized and significantly modular regardless of size. The strongest hubs were Baccharis plants, Apis mellifera, Bombus funebris and Diptera spp., which were the most ubiquitous and abundant species with the longest phenologies. Species strength showed a strong association with the modular structure of plant-pollinator networks. Hubs and connectors were the most centralized participants in the networks and were ranked highest (high generalization) when quantifying specialization with most indices. However, complementary specialization d' quantified hubs and connectors as moderately specialized. Specialization and topological roles of species were remarkably constant across some sites, but highly variable in others. Networks were dominated by ecologically and functionally generalist plant species with open access flowers which are closely related taxonomically with similar morphology and rewards. Plants associated with hummingbirds had the highest level of complementary specialization and exclusivity in modules (functional specialists) and the longest corollas. CONCLUSIONS: We have demonstrated that the topology of networks in this tropical montane environment was non-random and highly organized. Our findings underline that specialization indices convey different concepts of specialization and hence quantify different aspects, and that measuring specialization requires careful consideration of what defines a specialist.

An evidence assessment tool for ecosystem services and conservation studies.

Reliability of scientific findings is important, especially if they directly impact decision making, such as in environmental management. In the 1990s, assessments of reliability in the medical field resulted in the development of evidence-based practice. Ten years later, evidence-based practice was translated into conservation, but so far no guidelines exist on how to assess the evidence of individual studies. Assessing the evidence of individual studies is essential to appropriately identify and synthesize the confidence in research findings. We develop a tool to assess the strength of evidence of ecosystem services and conservation studies. This tool consists of (1) a hierarchy of evidence, based on the experimental design of studies and (2) a critical-appraisal checklist that identifies the quality of research implementation. The application is illustrated with 13 examples and we suggest further steps to move towards more evidence-based environmental management.

Ecological, historical and evolutionary determinants of modularity in weighted seed-dispersal networks.

Modularity is a recurrent and important property of bipartite ecological networks. Although well-resolved ecological networks describe interaction frequencies between species pairs, modularity of bipartite networks has been analysed only on the basis of binary presence-absence data. We employ a new algorithm to detect modularity in weighted bipartite networks in a global analysis of avian seed-dispersal networks. We define roles of species, such as connector values, for weighted and binary networks and associate them with avian species traits and phylogeny. The weighted, but not binary, analysis identified a positive relationship between climatic seasonality and modularity, whereas past climate stability and phylogenetic signal were only weakly related to modularity. Connector values were associated with foraging behaviour and were phylogenetically conserved. The weighted modularity analysis demonstrates the dominating impact of ecological factors on the structure of seed-dispersal networks, but also underscores the relevance of evolutionary history in shaping species roles in ecological communities.

The potential for indirect effects between co-flowering plants via shared pollinators depends on resource abundance, accessibility and relatedness.

Co-flowering plant species commonly share flower visitors, and thus have the potential to influence each other's pollination. In this study we analysed 750 quantitative plant-pollinator networks from 28 studies representing diverse biomes worldwide. We show that the potential for one plant species to influence another indirectly via shared pollinators was greater for plants whose resources were more abundant (higher floral unit number and nectar sugar content) and more accessible. The potential indirect influence was also stronger between phylogenetically closer plant species and was independent of plant geographic origin (native vs. non-native). The positive effect of nectar sugar content and phylogenetic proximity was much more accentuated for bees than for other groups. Consequently, the impact of these factors depends on the pollination mode of plants, e.g. bee or fly pollinated. Our findings may help predict which plant species have the greatest importance in the functioning of plant-pollination networks.

Identifying potential provenances for climate-change adaptation using spatially variable coefficient models.

BACKGROUND: Selection of climate-change adapted ecotypes of commercially valuable species to date relies on DNA-assisted screening followed by growth trials. For trees, such trials can take decades, hence any approach that supports focussing on a likely set of candidates may save time and money. We use a non-stationary statistical analysis with spatially varying coefficients to identify ecotypes that indicate first regions of similarly adapted varieties of Douglas-fir (Pseudotsuga menziesii (Mirbel) Franco) in North America. For over 70,000 plot-level presence-absences, spatial differences in the survival response to climatic conditions are identified. RESULTS: The spatially-variable coefficient model fits the data substantially better than a stationary, i.e. constant-effect analysis (as measured by AIC to account for differences in model complexity). Also, clustering the model terms identifies several potential ecotypes that could not be derived from clustering climatic conditions itself. Comparing these six identified ecotypes to known genetically diverging regions shows some congruence, as well as some mismatches. However, comparing ecotypes among each other, we find clear differences in their climate niches. CONCLUSION: While our approach is data-demanding and computationally expensive, with the increasing availability of data on species distributions this may be a useful first screening step during the search for climate-change adapted varieties. With our unsupervised learning approach being explorative, finely resolved genotypic data would be helpful to improve its quantitative validation.

Predicting plant-pollinator interactions: concepts, methods, and challenges.

Plant-pollinator interactions are ecologically and economically important, and, as a result, their prediction is a crucial theoretical and applied goal for ecologists. Although various analytical methods are available, we still have a limited ability to predict plant-pollinator interactions. The predictive ability of different plant-pollinator interaction models depends on the specific definitions used to conceptualize and quantify species attributes (e.g., morphological traits), sampling effects (e.g., detection probabilities), and data resolution and availability. Progress in the study of plant-pollinator interactions requires conceptual and methodological advances concerning the mechanisms and species attributes governing interactions as well as improved modeling approaches to predict interactions. Current methods to predict plant-pollinator interactions present ample opportunities for improvement and spark new horizons for basic and applied research.