2017 ESA Annual Meeting (August 6 -- 11)

COS 151-9 - Linking phenological synchrony to species interactions

Thursday, August 10, 2017: 4:20 PM
D129-130, Oregon Convention Center
Shannon K. Carter1, Daniel Saenz2 and Volker H. W. Rudolf1, (1)BioSciences, Rice University, Houston, TX, (2)Southern Research Station, US Forest Service, Nacogdoches, TX
Background/Question/Methods

Changes in the timing of species life cycle events (phenological shifts) can disrupt ecosystems by altering the timing and duration of species interactions. Most phenology research identifies phenological shifts by changes in the onset or mean of a phenological event, but these metrics ignore individual variation in timing (i.e., phenological synchrony), and therefore may be uninformative for predicting ecological effects of phenological shifts. Phenological synchrony should be ecologically important because it influences a population’s density through time, size structure, and temporal-numerical overlap with interacting populations. However, we currently know very little about phenological synchrony, how it changes across time and space, or how it contributes to population dynamics and species interactions. Therefore, we asked 1) does interannual variation a species’ phenological synchrony significantly alter numerical overlap with co-occurring species? and 2) how does phenological synchrony in a predator population affect predator-prey dynamics? We answered question 1 by analyzing high temporal resolution anuran calling data representing 12 species, 15 years, and 8 sites. We answered question 2 with an agent based model that manipulated phenological synchrony and mean of a predator population in relation to its prey and measured outcomes on predator and prey survival and fitness.

Results/Conclusions

Results from question 1 show that species’ phenological synchrony can vary dramatically across years and sites and fundamentally shapes numerical overlap of co-occurring species. Relative timing of single metrics (first, mean) between 2 species predicted shifts in their numerical overlap for only 9% (4/42) of species pairs considered. However, when we considered phenological synchrony, we were able to detect changes in numerical overlap for 26% (11/42) species pairs. Including synchrony gave more power to detect phenological shifts on a shorter time scale, and furthermore, more directly informed changes in numerical overlap, a proxy for species interactions. Therefore, it is critical to consider synchrony when measuring phenological shifts and predicting ecological outcomes. Addressing question 2, we found that predator phenological synchrony can influence predator-prey dynamics. High synchrony predator populations exhibited pulsed, high predation pressure, while low synchrony populations exerted a lighter predation pressure for a longer period of time. Therefore, synchrony changed both predator numerical and per capita effects on prey. With climate change rapidly altering species phenologies, it is increasingly important to be able to accurately track phenological shifts and predict the net effects. We demonstrate that this requires considering shifts in phenological synchrony.