Thu, Aug 18, 2022: 1:30 PM-1:45 PM
520D
Background/Question/MethodsEcological networks have been used as powerful tools to study the stability of species-rich communities. However, the understanding and methods such body of research has produced can be leveraged to answer other important ecological questions beyond community stability. Here, we use them to evaluate how structural and dynamical properties of plant-pollinator networks affect ecosystem services provided by pollinators (i.e., pollen deposition and consequent seed production). We evaluated the effects of network structure, pollinator richness, and adaptive foraging (AF, behavioral responses to resource availability). We generated thousands of varying network structures and simulated their dynamics using Valdovinos et al’s (2013) model, which calculates the population dynamics of plant and pollinator species, pollinators’ foraging efforts, quantity and quality of visits, and the dynamics of floral rewards. We tested three hypotheses: 1) increased network connectance decreases pollen deposition because higher connectance increases conspecific pollen dilution, 2) increased nestedness decreases pollen deposition in networks without adaptive foraging by increasing niche overlap among plant species for pollination services of shared pollinator species, 3) adaptive foraging increases pollen deposition by allowing niche partitioning among plant and pollinator species, which will reduce conspecific pollen dilution.
Results/ConclusionsOur results confirmed our first and third hypotheses, but contradicted the second. We found that networks with moderate connectance and high nestedness (as observed in empirical networks) and with adaptive foraging, exhibit the highest pollen deposition rate. Interestingly, we found that AF reverses the positive relationship between pollen deposition and pollinator richness visiting plant species. In networks without AF, generalist plants experience higher pollen deposition rates than specialists because due to receiving more visits. In networks with AF, this relation reverses to specialists exhibiting higher pollen deposition than generalists due to receiving higher quality of visits. We used our empirical data to test our model results. We evaluated the relationship between pollinator richness visiting each plant species, the quantity and quality of visits the plants receive, and their seed production. We found support for some of the mechanisms explaining our model results but not the clear tendencies shown by the model. This discrepancy between model and empirical results can be explained by the fixed number of ovules contained in each flower, which causes nonlinear relationship (e.g., saturating) between pollen deposition and seed production. We conclude that contrasting models and data promote the discovery of mechanisms that otherwise would be unnoticed.
Results/ConclusionsOur results confirmed our first and third hypotheses, but contradicted the second. We found that networks with moderate connectance and high nestedness (as observed in empirical networks) and with adaptive foraging, exhibit the highest pollen deposition rate. Interestingly, we found that AF reverses the positive relationship between pollen deposition and pollinator richness visiting plant species. In networks without AF, generalist plants experience higher pollen deposition rates than specialists because due to receiving more visits. In networks with AF, this relation reverses to specialists exhibiting higher pollen deposition than generalists due to receiving higher quality of visits. We used our empirical data to test our model results. We evaluated the relationship between pollinator richness visiting each plant species, the quantity and quality of visits the plants receive, and their seed production. We found support for some of the mechanisms explaining our model results but not the clear tendencies shown by the model. This discrepancy between model and empirical results can be explained by the fixed number of ovules contained in each flower, which causes nonlinear relationship (e.g., saturating) between pollen deposition and seed production. We conclude that contrasting models and data promote the discovery of mechanisms that otherwise would be unnoticed.