Evolution of geographic variation in thermal performance curves in the face of climate change and implications for biotic interactions
Introduction
Understanding how performance changes with temperature is crucial to assess the potential of populations to deal with current and future thermal regimes [1]. The relationship between a performance trait and temperature is known as the thermal performance curve (TPC). TPCs of insects typically have a rising part until the temperature where the best performance is reached (i.e. thermal optimum, or Topt). Above this temperature, performance steeply decreases until reaching the critical thermal maximum (CTmax), where performance becomes zero (Figure 1).
Populations across geographic gradients may experience strongly different thermal regimes. This holds both at the macrogeographic scale, for example along latitudinal and altitudinal gradients, and at the microgeographic scale, for example along urbanization gradients [2]. As a result, TPCs can strongly depend on the populations’ geographic origin [3]. Studying the evolution of TPCs across geographic gradients is getting renewed interest to predict responses to climate change [1,3]. Using a space-for-time approach [4], the current TPC at a warmer site can indeed be used as a proxy to predict the TPC at a colder site under a given warming scenario.
Although it is increasingly accepted that the fate of populations to persist locally depends not only the ability to deal with warming per se, but also on the ability to deal with biotic interactions under warming [5], this has been much less studied. Very few studies indeed directly addressed how biotic interactions change along temperature-associated geographic gradients (e.g. [6,7]). Importantly, the outcome of biotic interactions such as consumer–resource interactions [8, 9, 10] and interspecific competition [11,12] at a given temperature can be predicted based on the TPCs of the interacting species. For example, comparing the TPCs for swimming speed of a predator and its prey, the predator attack speed was found to be lower than the prey escape speed below a certain temperature, which was suggested to be the reason of the mostly unsuccessful predator attacks below that temperature [10]. Therefore, geographic patterns of TPCs of interacting species may inform on geographic patterns of their interaction, and using a space-for-time approach also on the evolution of biotic interactions under future warming.
We here review recent work on TPCs across geographic gradients in insects and describe emerging patterns. Based on this review we then generate hypothetical scenarios of evolutionary changes in TPCs of two interacting species to infer possible patterns in the outcomes of their interactions in the face of future warming. We particularly highlight how evolution of the TPCs, often ignored in such studies, may affect the predictions of the outcome of the interaction between species in the face of climate change.
Section snippets
General geographic patterns in TPCs
Shifts in ectotherm TPCs along geographic gradients can show three, not mutually exclusive, patterns [13] that are visualized in Figure 1:
- (i)
A `horizontal shift’ occurs when warm/cold-adapted populations perform better at higher/lower temperatures. This pattern is often associated with local thermal adaptation, where the maximum performance is achieved at the temperature the population is adapted to (Topt), and is driven by a trade-off between performance at higher and lower temperatures [14].
- (ii)
A
Geographic patterns in insect TPCs
To identify geographic patterns in insect TPCs, we selected recent intraspecific studies with at least two geographically separated conspecific populations, that assessed performance at ≥3 constant temperatures (the minimum requirement for constructing TPCs). We follow the definition of performance traits as biological rate processes with a time-dependent component [25]. We specifically focused on performance traits directly relevant for the outcome of biotic interactions in the short term
Predicting interaction outcomes under future warming based on evolving TPCs
Differences in TPCs between two interacting species have been successfully used to predict the outcome of their pairwise interaction in the short term (e.g. [10]). Based on this, we hypothesize that patterns in TPCs along geographic gradients can be useful tools to predict how species interactions will change along these gradients. Moreover, we can use the TPC of a given species at the warmer site of a gradient to infer how the TPC at the colder site will evolve under future warming (i.e.
Current studies using TPCs to predict biotic interactions under future warming
Empirical studies that incorporated spatial patterns in (and associated evolution of) TPCs of interacting species to predict the outcome of their interaction under warming are extremely rare (but see [11] for a study with tunicates and bryozoans). Instead, fragmentary pieces of information exist. The many studies on geographic variation in TPCs (Figure 1) did not explicitly consider biotic interactions. Further, it has been widely documented that trophic interactions can show strong spatial
Conclusions and future directions
Our review on recent insect studies identified that in many cases TPCs do not show geographic differentiation along strong thermal gradients, suggesting TPCs of these species will not evolve in situ under warming. Yet, in many other cases, a geographic signal was detected, mainly taking the forms of CnGV, and to a lesser extent CoGV and horizontal shifts. Hypothetical scenarios showed that in such cases taking evolution of the TPC into account may have a very strong impact on the predicted
Conflict of interest statement
Nothing declared.
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as
• of special interest
•• of outstanding interest
Acknowledgements
This work was supported by Belspo project Speedy, the KU Leuven Centre of Excellence program PF/2010/07, FWO research grant G.0524.17 and FWO scientific network EVE-net. Comments by Adam Rosenblatt and an anonymous reviewer greatly improved this paper.
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