Eco-evolutionary consequences of habitat warming and fragmentation in communities

Abstract

Eco-evolutionary dynamics can mediate species and community responses to habitat warming and fragmentation, two of the largest threats to biodiversity and ecosystems. The eco-evolutionary consequences of warming and fragmentation are typically studied independently, hindering our understanding of their simultaneous impacts. Here, we provide a new perspective rooted in trade-offs among traits for understanding their eco-evolutionary consequences. On the one hand, temperature influences traits related to metabolism, such as resource acquisition and activity levels. Such traits are also likely to have trade-offs with other energetically costly traits, like antipredator defences or dispersal. On the other hand, fragmentation can influence a variety of traits (e.g. dispersal) through its effects on the spatial environment experienced by individuals, as well as properties of populations, such as genetic structure. The combined effects of warming and fragmentation on communities should thus reflect their collective impact on traits of individuals and populations, as well as trade-offs at multiple trophic levels, leading to unexpected dynamics when effects are not additive and when evolutionary responses modulate them. Here, we provide a road map to navigate this complexity. First, we review single-species responses to warming and fragmentation. Second, we focus on consumer-resource interactions, considering how eco-evolutionary dynamics can arise in response to warming, fragmentation, and their interaction. Third, we illustrate our perspective with several example scenarios in which trait trade-offs could result in significant eco-evolutionary dynamics. Specifically, we consider the possible eco-evolutionary consequences of (i) evolution in thermal performance of a species involved in a consumer-resource interaction, (ii) ecological or evolutionary changes to encounter and attack rates of consumers, and (iii) changes to top consumer body size in tri-trophic food chains. In these scenarios, we present a number of novel, sometimes counter-intuitive, potential outcomes. Some of these expectations contrast with those solely based on ecological dynamics, for example, evolutionary responses in unexpected directions for resource species or unanticipated population declines in top consumers. Finally, we identify several unanswered questions about the conditions most likely to yield strong eco-evolutionary dynamics, how better to incorporate the role of trade-offs among traits, and the role of eco-evolutionary dynamics in governing responses to warming in fragmented communities.

Keywords: climate change; consumer-resource dynamics; eco-evolutionary dynamics; environmental warming; food webs; habitat fragmentation; metacommunities.

Fig. 1

Conceptual diagram showing eco-evolutionary dynamics, where changes in the ecology of populations or communities that result in evolutionary changes (A), or vice versa (B), can occur when ecology and evolution occur at contemporary timescales. Such dynamics are considered eco-evolutionary feedbacks when the secondary evolutionary (as in A) or ecological (as in B) response then results in an additional reciprocal ecological (A) or evolutionary (B) response. As our focus is on environmental change, we assume that the dynamics are initiated in response to a change in the environment of a population.

Fig. 2

Likelihood of eco-evolutionary dynamics in response to warming and fragmentation as a function of species’ traits, habitat connectivity, and community complexity. For simplicity, two potential eco-evolutionary scenarios are presented and separated by the dotted grey line, corresponding to weak and strong eco-evolutionary potential. Grey-scale shading indicates the relative level from low to high of each of the factors: ‘warming phenotype matching’, ‘habitat connectivity/population size/genetic diversity’, and ‘community complexity’. Warming phenotype matching refers to the degree to which an organism’s thermal phenotype matches the thermal environment in which it is found. We consider habitat connectivity, population size, and genetic diversity as a single factor in our figure because they are frequently positively correlated. Community complexity refers to the number of organisms and trophic levels, and consequently interspecific interactions, present in the community. We evaluate the role of each factor for weak (factor bars 1−3) and strong (factor bars 4−6) eco-evolutionary dynamics. Colours on the bars show the expected range of each factor for a given eco-evolutionary outcome (A−D). When an outcome is predicted for the entire range of a factor, for example, as in outcomes A and B that we predict across the full range of community complexity (3), the coloured bar spans the vertical range of the grey-scale factor bar. We identified four potential outcomes. Under weak eco-evolutionary potential, local extinctions without evolutionary responses (A) are predicted with high warming phenotype matching (1), low habitat connectivity/ population size/genetic diversity (2), and across a range of community complexity (3). Plastic responses and migration (B) are predicted under weak eco-evolutionary potential with high warming phenotype matching (1), high habitat connectivity/population size/genetic diversity (2), and across a range of community complexity (3). For responses with strong eco-evolutionary potential, we predict that cryptic eco-evolutionary dynamics (C) will be likely to occur with high warming phenotype matching (4), intermediate habitat connectivity/population size/genetic diversity (5), and a range of community complexity (6). The final outcome with strong eco-evolutionary potential, dramatic eco-evolutionary dynamics (D), is predicted to occur with low warming phenotype matching (4), intermediate habitat connectivity/population size/genetic diversity (5), and, high community complexity (6).

Fig. 3

(A) Conceptual diagram of an ecological trade-off with two fitness components (conceptualized as a linear relationship for simplicity). (B) Evolution that improves performance in one fitness component results in a concomitant reduction in performance in a second fitness component. Here a starting population (pink fish) evolves increased performance in Fitness component 1 (x-axis trait), at the expense of performance in Fitness component 2 (y-axis trait), resulting in an overall shift along the trade-off curve (red arrow) for the evolved population (blue fish).

Fig. 4

Conceptual diagram (top panels) illustrating a hypothetical scenario for an eco-evolutionary feedback (evoàeco àevo) between a consumer species and its resource with evolutionary trade-offs visualized below each conceptual panel. Fragmentation in a habitat experiencing a thermal gradient results in patches that differ in thermal environment (colour of background, with blue as cold and pink as warm). In the conceptual panels, for each species the colour of the illustration represents different genotypes (or phenotypes) within each population, while the size of the illustration represents the relative contribution of each phenotype to the population make-up. In the trade-off diagrams, the curve for the trade-off relationship is indicated with a grey dashed line, while evolutionary movement along the trade-off curve is indicated with a solid red arrow. Dashed black arrows show the positive (+) or negative (−) direction of the movement for each fitness attribute. (A) The presence of habitat patches differing in their thermal environment results in evolution of the resource (alga) for increased heat-shock tolerance leading to an increase in its abundance in warm patches due to lower mortality under heat shock. (B) Increased abundance of the resource results in increased attack by the consumer (daphnid) as an ecological (dashed red line departing from the trade-off curve) or evolutionary response, a trait whose performance is not necessarily tied to thermal environment. (C) Decreased dispersal of the resource occurs as a result of higher predation pressure, increasing the opportunity for local adaptation to increase defence against the predator.

Fig. 5

Conceptual diagram (top panels) illustrating a hypothetical scenario for an eco-evolutionary feedback (eco→evo→eco) for a tri-trophic food chain with evolutionary trade-offs visualized below each conceptual panel. See legend to Fig. 4 for further explanation. For the fish, size of the illustration corresponds to body mass rather than the relative contribution of a phenotype to the population make-up. (A) The presence of habitat patches differing in their thermal environment results in a plastic reduction of top consumer (fish) body size (dashed red line on the trade-off curve). (B) Decreased predation pressure linked to reduced fish body mass then allows the intermediate consumer (daphnid) to evolve increased resource acquisition. (C) The resource (alga) evolves increased defence in response to higher predation pressure from the intermediate consumer.