25
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Human Impacts and Climate Change Influence Nestedness and Modularity in Food-Web and Mutualistic Networks

      research-article
      * ,
      PLoS ONE
      Public Library of Science

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Theoretical studies have indicated that nestedness and modularity—non-random structural patterns of ecological networks—influence the stability of ecosystems against perturbations; as such, climate change and human activity, as well as other sources of environmental perturbations, affect the nestedness and modularity of ecological networks. However, the effects of climate change and human activities on ecological networks are poorly understood. Here, we used a spatial analysis approach to examine the effects of climate change and human activities on the structural patterns of food webs and mutualistic networks, and found that ecological network structure is globally affected by climate change and human impacts, in addition to current climate. In pollination networks, for instance, nestedness increased and modularity decreased in response to increased human impacts. Modularity in seed-dispersal networks decreased with temperature change (i.e., warming), whereas food web nestedness increased and modularity declined in response to global warming. Although our findings are preliminary owing to data-analysis limitations, they enhance our understanding of the effects of environmental change on ecological communities.

          Related collections

          Most cited references23

          • Record: found
          • Abstract: found
          • Article: not found

          The architecture of mutualistic networks minimizes competition and increases biodiversity.

          The main theories of biodiversity either neglect species interactions or assume that species interact randomly with each other. However, recent empirical work has revealed that ecological networks are highly structured, and the lack of a theory that takes into account the structure of interactions precludes further assessment of the implications of such network patterns for biodiversity. Here we use a combination of analytical and empirical approaches to quantify the influence of network architecture on the number of coexisting species. As a case study we consider mutualistic networks between plants and their animal pollinators or seed dispersers. These networks have been found to be highly nested, with the more specialist species interacting only with proper subsets of the species that interact with the more generalist. We show that nestedness reduces effective interspecific competition and enhances the number of coexisting species. Furthermore, we show that a nested network will naturally emerge if new species are more likely to enter the community where they have minimal competitive load. Nested networks seem to occur in many biological and social contexts, suggesting that our results are relevant in a wide range of fields.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Resolution limit in community detection

            Detecting community structure is fundamental to clarify the link between structure and function in complex networks and is used for practical applications in many disciplines. A successful method relies on the optimization of a quantity called modularity [Newman and Girvan, Phys. Rev. E 69, 026113 (2004)], which is a quality index of a partition of a network into communities. We find that modularity optimization may fail to identify modules smaller than a scale which depends on the total number L of links of the network and on the degree of interconnectedness of the modules, even in cases where modules are unambiguously defined. The probability that a module conceals well-defined substructures is the highest if the number of links internal to the module is of the order of \sqrt{2L} or smaller. We discuss the practical consequences of this result by analyzing partitions obtained through modularity optimization in artificial and real networks.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Link communities reveal multiscale complexity in networks

              Networks have become a key approach to understanding systems of interacting objects, unifying the study of diverse phenomena including biological organisms and human society. One crucial step when studying the structure and dynamics of networks is to identify communities: groups of related nodes that correspond to functional subunits such as protein complexes or social spheres. Communities in networks often overlap such that nodes simultaneously belong to several groups. Meanwhile, many networks are known to possess hierarchical organization, where communities are recursively grouped into a hierarchical structure. However, the fact that many real networks have communities with pervasive overlap, where each and every node belongs to more than one group, has the consequence that a global hierarchy of nodes cannot capture the relationships between overlapping groups. Here we reinvent communities as groups of links rather than nodes and show that this unorthodox approach successfully reconciles the antagonistic organizing principles of overlapping communities and hierarchy. In contrast to the existing literature, which has entirely focused on grouping nodes, link communities naturally incorporate overlap while revealing hierarchical organization. We find relevant link communities in many networks, including major biological networks such as protein-protein interaction and metabolic networks, and show that a large social network contains hierarchically organized community structures spanning inner-city to regional scales while maintaining pervasive overlap. Our results imply that link communities are fundamental building blocks that reveal overlap and hierarchical organization in networks to be two aspects of the same phenomenon.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                20 June 2016
                2016
                : 11
                : 6
                : e0157929
                Affiliations
                [001]Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka Fukuoka, Japan
                Swedish University of Agricultural Sciences, SWEDEN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: KT KK. Analyzed the data: KT KK. Contributed reagents/materials/analysis tools: KT KK. Wrote the paper: KT.

                Article
                PONE-D-16-07180
                10.1371/journal.pone.0157929
                4913940
                27322185
                d4fe4a03-415a-409c-8c40-8d2b258d1a80
                © 2016 Takemoto, Kajihara

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 19 February 2016
                : 7 June 2016
                Page count
                Figures: 4, Tables: 5, Pages: 16
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001691, Japan Society for the Promotion of Science;
                Award ID: 2570030
                Award Recipient :
                This study was supported by a Grant-in-Aid for Young Scientists (A) from the Japan Society for the Promotion of Science (no. 25700030). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Ecology
                Community Ecology
                Ecology and Environmental Sciences
                Ecology
                Community Ecology
                Biology and Life Sciences
                Organisms
                Plants
                Flowering Plants
                Pollination
                Biology and Life Sciences
                Plant Science
                Plant Physiology
                Pollination
                Biology and Life Sciences
                Ecology
                Community Ecology
                Food Web Structure
                Ecology and Environmental Sciences
                Ecology
                Community Ecology
                Food Web Structure
                Biology and Life Sciences
                Ecology
                Ecosystems
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Earth Sciences
                Atmospheric Science
                Climatology
                Climate Change
                Biology and Life Sciences
                Ecology
                Global Change Ecology
                Ecology and Environmental Sciences
                Ecology
                Global Change Ecology
                Physical Sciences
                Chemistry
                Chemical Elements
                Biology and Life Sciences
                Ecology
                Theoretical Ecology
                Ecology and Environmental Sciences
                Ecology
                Theoretical Ecology
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article