Yoko L. Dupont

Bio: Yoko L. Dupont is an academic researcher from Aarhus University. The author has contributed to research in topics: Pollination & Pollinator. The author has an hindex of 22, co-authored 45 publications receiving 3520 citations.

The modularity of pollination networks.

Abstract: In natural communities, species and their interactions are often organized as nonrandom networks, showing distinct and repeated complex patterns. A prevalent, but poorly explored pattern is ecological modularity, with weakly interlinked subsets of species (modules), which, however, internally consist of strongly connected species. The importance of modularity has been discussed for a long time, but no consensus on its prevalence in ecological networks has yet been reached. Progress is hampered by inadequate methods and a lack of large datasets. We analyzed 51 pollination networks including almost 10,000 species and 20,000 links and tested for modularity by using a recently developed simulated annealing algorithm. All networks with >150 plant and pollinator species were modular, whereas networks with <50 species were never modular. Both module number and size increased with species number. Each module includes one or a few species groups with convergent trait sets that may be considered as coevolutionary units. Species played different roles with respect to modularity. However, only 15% of all species were structurally important to their network. They were either hubs (i.e., highly linked species within their own module), connectors linking different modules, or both. If these key species go extinct, modules and networks may break apart and initiate cascades of extinction. Thus, species serving as hubs and connectors should receive high conservation priorities.

Biodiversity, species interactions and ecological networks in a fragmented world

Abstract: Biodiversity is organised into complex ecological networks of interacting species in local ecosystems, but our knowledge about the effects of habitat fragmentation on such systems remains limited. We consider the effects of this key driver of both local and global change on both mutualistic and antagonistic systems at different levels of biological organisation and spatiotemporal scales. There is a complex interplay of patterns and processes related to the variation and influence of spatial, temporal and biotic drivers in ecological networks. Species traits (e.g. body size, dispersal ability) play an important role in determining how networks respond to fragment size and isolation, edge shape and permeability, and the quality of the surrounding landscape matrix. Furthermore, the perception of spatial scale (e.g. environmental grain) and temporal effects (time lags, extinction debts) can differ markedly among species, network modules and trophic levels, highlighting the need to develop a more integrated perspective that considers not just nodes, but the structural role and strength of species interactions (e.g. as hubs, spatial couplers and determinants of connectance, nestedness and modularity) in response to habitat fragmentation. Many challenges remain for improving our understanding: the likely importance of specialisation, functional redundancy and trait matching has been largely overlooked. The potentially critical effects of apex consumers, abundant species and super-generalists on network changes and evolutionary dynamics also need to be addressed in future research. Ultimately, spatial and ecological networks need to be combined to explore the effects of dispersal, colonisation, extinction and habitat fragmentation on network structure and coevolutionary dynamics. Finally, we need to embed network approaches more explicitly within applied ecology in general, because they offer great potential for improving on the current species-based or habitat-centric approaches to our management and conservation of biodiversity in the face of environmental change.

Missing and forbidden links in mutualistic networks

Abstract: Ecological networks are complexes of interacting species, but not all potential links among species are realized. Unobserved links are either missing or forbidden. Missing links exist, but require more sampling or alternative ways of detection to be verified. Forbidden links remain unobservable, irrespective of sampling effort. They are caused by linkage constraints. We studied one Arctic pollination network and two Mediterranean seed-dispersal networks. In the first, for example, we recorded flower-visit links for one full season, arranged data in an interaction matrix and got a connectance C of 15 per cent. Interaction accumulation curves documented our sampling of interactions through observation of visits to be robust. Then, we included data on pollen from the body surface of flower visitors as an additional link ‘currency’. This resulted in 98 new links, missing from the visitation data. Thus, the combined visit–pollen matrix got an increased C of 20 per cent. For the three networks, C ranged from 20 to 52 per cent, and thus the percentage of unobserved links (100 − C) was 48 to 80 per cent; these were assumed forbidden because of linkage constraints and not missing because of under-sampling. Phenological uncoupling (i.e. non-overlapping phenophases between interacting mutualists) is one kind of constraint, and it explained 22 to 28 per cent of all possible, but unobserved links. Increasing phenophase overlap between species increased link probability, but extensive overlaps were required to achieve a high probability. Other kinds of constraint, such as size mismatch and accessibility limitations, are briefly addressed.

Structure of a plant–flower‐visitor network in the high‐altitude sub‐alpine desert of Tenerife, Canary Islands

Abstract: Confined within a volcanic caldera at 2000 m a.s.l., the sub-alpine desert of Tenerife, Canary Islands, harbors a distinct biota. At this altitude the climate is harsh and the growing season short. Hence, plant and animal communities, constituting the sub-alpine plant-flower-visitor network, are clearly delimited, both spatially and temporally. We investigated species composition and interaction structure of this system. A total of 11 plant species (91% endemics) and 37 flower-visiting animal species (62% endemics) formed 108 interactions. Numbers of interactions among species varied ten-fold within both plant and animal communities. Generalization level of a species was positively correlated with its local abundance. Two separate network analyses revealed a significantly nested structure. In relation to a plant-flower-visitor system, nestedness implies that specialized species (animals or plants) interact with a subset of the species pool visiting (animals) or being visited (plants) by more generalized species. Therefore, specialized, locally rare plants tend to be visited by generalized, locally abundant animals, and specialized, locally rare animals tend to utilize generalized, locally abundant food plants. Such patterns could have implications for conservation of the sub-alpine network, and stress the importance of preserving not only rare species, but also the more abundant ones, which may be key food resources or pollinators in the plant-flower-visitor network.

Spatio‐temporal variation in the structure of pollination networks

Abstract: Pollination networks are representations of all interactions between co-existing plants and their flower visiting animals at a given site. Although the study of networks has become a distinct sub-discipline in pollination biology, few studies have attempted to quantify spatio-temporal variation in species composition and structure of networks. We here investigate patterns of year-to-year change in pollination networks from six different sites spanning a large latitudinal gradient. We quantified level of species persistence and interactions among years, and examined year-to-year variation of network structural parameters in relation to latitude and sampling effort. In addition, we tested for correlations between annual variation in network parameters and short and long-term climate change variables. Numbers of plant and animal species and interactions were roughly constant from one year to another at all sites. However, composition of species and interactions changed from one year to another. Turnover was particularly high for flower visitors and interactions. On the other hand, network structural parameters (connectance, nestedness, modularity and centralization) remained remarkably constant between years, regardless of network size and latitude. Inter-annual variation of network parameters was not related to short or long term variation in climate variables (mean annual temperature and annual precipitation). We thus conclude that pollination networks are highly dynamic and variable in composition of species and interactions among years. However, general patterns of network structure remain constant, indicating that species may be replaced by topologically similar species. These results suggest that pollination networks are to some extent robust against factors affecting species occurrences.

The Theory of Island Biogeography

Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The modularity of pollination networks.

Abstract: In natural communities, species and their interactions are often organized as nonrandom networks, showing distinct and repeated complex patterns. A prevalent, but poorly explored pattern is ecological modularity, with weakly interlinked subsets of species (modules), which, however, internally consist of strongly connected species. The importance of modularity has been discussed for a long time, but no consensus on its prevalence in ecological networks has yet been reached. Progress is hampered by inadequate methods and a lack of large datasets. We analyzed 51 pollination networks including almost 10,000 species and 20,000 links and tested for modularity by using a recently developed simulated annealing algorithm. All networks with >150 plant and pollinator species were modular, whereas networks with <50 species were never modular. Both module number and size increased with species number. Each module includes one or a few species groups with convergent trait sets that may be considered as coevolutionary units. Species played different roles with respect to modularity. However, only 15% of all species were structurally important to their network. They were either hubs (i.e., highly linked species within their own module), connectors linking different modules, or both. If these key species go extinct, modules and networks may break apart and initiate cascades of extinction. Thus, species serving as hubs and connectors should receive high conservation priorities.

Molecular ecological network analyses

Abstract: Background: Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data. Results: Here, we describe a novel mathematical and bioinformatics framework to construct ecological association networks named molecular ecological networks (MENs) through Random Matrix Theory (RMT)-based methods. Compared to other network construction methods, this approach is remarkable in that the network is automatically defined and robust to noise, thus providing excellent solutions to several common issues associated with highthroughput metagenomics data. We applied it to determine the network structure of microbial communities subjected to long-term experimental warming based on pyrosequencing data of 16 S rRNA genes. We showed that the constructed MENs under both warming and unwarming conditions exhibited topological features of scale free, small world and modularity, which were consistent with previously described molecular ecological networks. Eigengene analysis indicated that the eigengenes represented the module profiles relatively well. In consistency with many other studies, several major environmental traits including temperature and soil pH were found to be important in determining network interactions in the microbial communities examined. To facilitate its application by the scientific community, all these methods and statistical tools have been integrated into a comprehensive Molecular Ecological Network Analysis Pipeline (MENAP), which is open-accessible now (http://ieg2.ou.edu/MENA). Conclusions: The RMT-based molecular ecological network analysis provides powerful tools to elucidate network interactions in microbial communities and their responses to environmental changes, which are fundamentally important for research in microbial ecology and environmental microbiology.

A consistent metric for nestedness analysis in ecological systems: reconciling concept and measurement

Abstract: Nestedness has been widely reported for both metacommunities and networks of interacting species. Even though the concept of this ecological pattern has been well-defined, there are several metrics by which it can be quantified. We noted that current metrics do not correctly quantify two major properties of nestedness: (1) whether marginal totals (i.e. fills) differ among columns and/or among rows, and (2) whether the presences (1’s) in less-filled columns and rows coincide, respectively, with those found in the more-filled columns and rows. We propose a new metric directly based on these properties and compare its behavior with that of the most used metrics, using a set of model matrices ranging from highly-nested to alternative structures in which no nestedness should be detected. We also used an empirical dataset to explore possible biases generated by the metrics as well as to evaluate correlations between metrics. We found that nestedness has been quantified by metrics that inappropriately detect this pattern, even for matrices in which there is no nestedness. In addition, the most used metrics are prone to type I statistical errors while our new metric has better statistical properties and consistently rejects a nested pattern for different types of random matrices. The analysis of the empirical data showed that two nestedness metrics, matrix temperature and the discrepancy measure, tend to overestimate the degrees of nestedness in metacommunities. We emphasize and discuss some implications of these biases for the theoretical understanding of the processes shaping species interaction networks and metacommunity structure.