Dataset Information

Phylogenetic trait-based analyses of ecological networks.

ABSTRACT: Ecological networks of two interacting guilds of species, such as flowering plants and pollinators, are common in nature, and studying their structure can yield insights into their resilience to environmental disturbances. Here we develop analytical methods for exploring the strengths of interactions within bipartite networks consisting of two guilds of phylogenetically related species. We then apply these methods to investigate the resilience of a plant-pollinator community to anticipated climate change. The methods allow the statistical assessment of, for example, whether closely related pollinators are more likely to visit plants with similar relative frequencies, and whether closely related pollinators tend to visit closely related plants. The methods can also incorporate trait information, allowing us to identify which plant traits are likely responsible for attracting different pollinators. These questions are important for our study of 14 prairie plants and their 22 insect pollinators. Over the last 70 years, six of the plants have advanced their flowering, while eight have not. When we experimentally forced earlier flowering times, five of the six advanced-flowering species experienced higher pollinator visitation rates, whereas only one of the eight other species had more visits; this network thus appears resilient to climate change, because those species with advanced flowering have ample pollinators earlier in the season. Using the methods developed here, we show that advanced-flowering plants did not have a distinct pollinator community from the other eight species. Furthermore, pollinator phylogeny did not explain pollinator community composition; closely related pollinators were not more likely to visit the same plant species. However, differences among pollinator communities visiting different plants were explained by plant height, floral color, and symmetry. As a result, closely related plants attracted similar numbers of pollinators. By parsing out characteristics that explain why plants share pollinators, we can identify plant species that likely share a common fate in a changing climate.

SUBMITTER: Rafferty NE

PROVIDER: S-EPMC3874136 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Phylogenetic trait-based analyses of ecological networks.

Rafferty Nicole E NE Ives Anthony R AR

Ecology 20131001 10

Ecological networks of two interacting guilds of species, such as flowering plants and pollinators, are common in nature, and studying their structure can yield insights into their resilience to environmental disturbances. Here we develop analytical methods for exploring the strengths of interactions within bipartite networks consisting of two guilds of phylogenetically related species. We then apply these methods to investigate the resilience of a plant-pollinator community to anticipated clima ...[more]

PMID: 24358717

Similar Datasets

Project description:Understanding the influences of dispersal limitation and environmental filtering on the structure of ecological communities is a major challenge in ecology. Insight may be gained by combining phylogenetic, functional and taxonomic data to characterize spatial turnover in community structure (?-diversity). We develop a framework that allows rigorous inference of the strengths of dispersal limitation and environmental filtering by combining these three types of ?-diversity. Our framework provides model-generated expectations for patterns of taxonomic, phylogenetic and functional ?-diversity across biologically relevant combinations of dispersal limitation and environmental filtering. After developing the framework we compared the model-generated expectations to the commonly used "intuitive" expectation that the variance explained by the environment or by space will, respectively, increase monotonically with the strength of environmental filtering or dispersal limitation. The model-generated expectations strongly departed from these intuitive expectations: the variance explained by the environment or by space was often a unimodal function of the strength of environmental filtering or dispersal limitation, respectively. Therefore, although it is commonly done in the literature, one cannot assume that the strength of an underlying process is a monotonic function of explained variance. To infer the strength of underlying processes, one must instead compare explained variances to model-generated expectations. Our framework provides these expectations. We show that by combining the three types of ?-diversity with model-generated expectations our framework is able to provide rigorous inferences of the relative and absolute strengths of dispersal limitation and environmental filtering. Phylogenetic, functional and taxonomic ?-diversity can therefore be used simultaneously to infer processes by comparing their empirical patterns to the expectations generated by frameworks similar to the one developed here.

Project description:A global ecological restoration agenda has led to ambitious programs in environmental policy to mitigate declines in biodiversity and ecosystem services. Current restoration programs can incompletely return desired ecosystem service levels, while resilience of restored ecosystems to future threats is unknown. It is therefore essential to advance understanding and better utilize knowledge from ecological literature in restoration approaches. We identified an incomplete linkage between global change ecology, ecosystem function research, and restoration ecology. This gap impedes a full understanding of the interactive effects of changing environmental factors on the long-term provision of ecosystem functions and a quantification of trade-offs and synergies among multiple services. Approaches that account for the effects of multiple changing factors on the composition of plant traits and their direct and indirect impact on the provision of ecosystem functions and services can close this gap. However, studies on this multilayered relationship are currently missing. We therefore propose an integrated restoration agenda complementing trait-based empirical studies with simulation modeling. We introduce an ongoing case study to demonstrate how this framework could allow systematic assessment of the impacts of interacting environmental factors on long-term service provisioning. Our proposed agenda will benefit restoration programs by suggesting plant species compositions with specific traits that maximize the supply of multiple ecosystem services in the long term. Once the suggested compositions have been implemented in actual restoration projects, these assemblages should be monitored to assess whether they are resilient as well as to improve model parameterization. Additionally, the integration of empirical and simulation modeling research can improve global outcomes by raising the awareness of which restoration goals can be achieved, due to the quantification of trade-offs and synergies among ecosystem services under a wide range of environmental conditions.

Dataset Information

Phylogenetic trait-based analyses of ecological networks.

Publications

Phylogenetic trait-based analyses of ecological networks.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets