Ecological networks have emerged as a powerful method to understand the dynamics of the myriad species and their interactions that comprise complex ecosystems. In particular, modeling communities as networks enables us to develop our understanding of how the species-level interactions lead to emergent patterns of interaction. The structure of interactions is in turn related to the resilience of a community to disturbance, and the ability of the system to avoid collapse. To predict the response to communities to global change, it is thus important to elucidate the mechanisms that underlie the patterns of interactions observed in communities.
Coevolution, species turnover, and mutualistic networks
With Paulo Guimaraes, we are building a large community evolution model to examine how
community variables affect the structure of interactions. We are asking:
1. How does the rate of temporal turnover of species affect network topology through time?
2. What are the characteristics of the species that are most important to network evolution/coevolution? Are they the most temporally persistent species? If so, what makes those species the most persistent? Do the characteristics of the most important species change through time?
3. How does the structure of interactions change the rate of temporal turnover of species (e.g., eco-evolutionary feedbacks)?
4. How does the rate of species turnover effect the patterns of species diversification (e.g., the shape of the community phylogeny, phylogenetic signal on the structure of interactions)?
5. How does the stability and response to perturbations depend on structural and dynamic characteristics of the network?
community variables affect the structure of interactions. We are asking:
1. How does the rate of temporal turnover of species affect network topology through time?
2. What are the characteristics of the species that are most important to network evolution/coevolution? Are they the most temporally persistent species? If so, what makes those species the most persistent? Do the characteristics of the most important species change through time?
3. How does the structure of interactions change the rate of temporal turnover of species (e.g., eco-evolutionary feedbacks)?
4. How does the rate of species turnover effect the patterns of species diversification (e.g., the shape of the community phylogeny, phylogenetic signal on the structure of interactions)?
5. How does the stability and response to perturbations depend on structural and dynamic characteristics of the network?
Network synthesis
The modeling work with Paulo will help to lay the foundation for understanding the interaction patterns favored by assembly in real-world communities that vary in their rate of temporal species turnover. Based on island biogeography theory, large islands far from sources (e.g., Hawaii) will have lower species temporal turnover than small islands near sources (e.g., habitat fragments). By using a synthesis approach to compare the assembly of true islands, natural island-like systems, and anthropogenically generated habitat islands, we will build on our understanding of how and why the interaction patterns vary between human modified and more natural landscapes.
We working to compile and augment existing collections of plant-pollinator interaction networks from true islands such as the Channel Islands, natural island-like systems like montane meadows in the Sierra Nevada, and human generated islands like habitat fragments in agricultural matrices. I will test the predictions from my theoretical work on the effect of species temporal turnover on interaction patterns. We will also use the empirical data as starting points for the large community evolution model, and examine the evolutionary trajectory of the communities through time. We can then explore how the stability and response to perturbations of the different island systems changes through time. An understanding of the the differences in network structures between islands and islands-like systems will help elucidate any differences in resilience between these systems, as well as provide targets for restoration interventions.
We working to compile and augment existing collections of plant-pollinator interaction networks from true islands such as the Channel Islands, natural island-like systems like montane meadows in the Sierra Nevada, and human generated islands like habitat fragments in agricultural matrices. I will test the predictions from my theoretical work on the effect of species temporal turnover on interaction patterns. We will also use the empirical data as starting points for the large community evolution model, and examine the evolutionary trajectory of the communities through time. We can then explore how the stability and response to perturbations of the different island systems changes through time. An understanding of the the differences in network structures between islands and islands-like systems will help elucidate any differences in resilience between these systems, as well as provide targets for restoration interventions.
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