Interactive effects of multiple climate change variables on trophic interactions: a meta-analysis

Adam E Rosenblatt,Oswald J Schmitz

doi:10.1186/s40665-014-0008-y

Abstract

Climate change is expected to simultaneously alter many of the abiotic qualities of ecosystems as well as biotic interactions, especially trophic interactions. However, research to date has mostly focused on elucidating the effects of single climate change variables on individual species. Here, we use established meta-analysis techniques to synthesize the existing literature on the interactive effects of multiple climate change variables on trophic interactions. Most of the studies included in our meta-analysis examined plant-insect herbivore interactions. We found that the majority of trophic interaction response variables (55%) displayed multiplicative reactions to interacting climate change variables while 36% and 9% displayed antagonistic and synergistic reactions, respectively. We also found that only one of six climate change variable pairings had consistent positive or negative effects on trophic relationships, largely because interaction type and magnitude were both highly context dependent across the pairings. Most notably, males and females frequently responded differently to interacting climate change variables, and the response strength frequently varied with the underlying nutrient load of the system. Our results suggest that trophic interactions commonly respond antagonistically to interacting climate change variables whereas synergistic and simple additive/multiplicative reactions are less common than previously thought. In addition, response type and magnitude are highly context dependent. These findings further suggest that in many cases, future ecosystem responses to climate change, whether positive or negative, may be dampened relative to predictions based on experiments that investigate the effects of single climate change variables on single species. However, there is a paucity of work that has focused on the effects of interacting climate change variables on dynamic biotic relationships, likely because such research requires complex experimentation. Increasing the complexity of climate change research is necessary for accurately predicting ecosystem responses.

Highlights

Climate change is expected to simultaneously alter many of the abiotic qualities of ecosystems as well as biotic interactions, especially trophic interactions
Most studies have tended to examine climate effects on biotic components by focusing on single species while treating the larger community as background variation [7] and by typically focusing on a single climate change variable at a time [8,9,10]. Whether or not such approaches adequately capture how systems will respond to climate change remains uncertain. We address this uncertainty by comparing the responses of interacting species subjected to the manipulation of a single climate change variable with their responses to simultaneous manipulations of multiple climate change variables
2.2% (n = 47) of the studies examined the effects of multiple interacting climate change variables, with 1.9% (n = 41) using two interacting climate change variables and 0.3% (n = 6) using three interacting climate change variables. Of these 47 studies, 6 did not report all the necessary mean and variance data from the 4 required treatment groups and 7 did not report data for any response variables directly related to feeding interactions

Summary

Introduction

Climate change is expected to simultaneously alter many of the abiotic qualities of ecosystems as well as biotic interactions, especially trophic interactions. In addition to changing the fundamental abiotic qualities of ecosystems (e.g., temperature, water availability, CO2 concentration), climate change is expected to alter the behavior and life history characteristics of organisms which could lead to dramatic changes in inter and intraspecific competition, predation, mutualisms, species distributions, biodiversity patterns, and the provisioning of. We address this uncertainty by comparing the responses of interacting species subjected to the manipulation of a single climate change variable with their responses to simultaneous manipulations of multiple climate change variables. Meta-analysis is useful in research on climate change as individual studies often produce conflicting results [13]

Methods

Results

Discussion

Conclusion