Studying evolutionary responses to climate change
Molecular ecology of global change
Article first published online: 3 AUG 2007
Volume 16, Issue 19, pages 3973–3992, October 2007
How to Cite
REUSCH, T. B. H. and WOOD, T. E. (2007), Molecular ecology of global change. Molecular Ecology, 16: 3973–3992. doi: 10.1111/j.1365-294X.2007.03454.x
Two approaches are available for documenting past evolution. In spatial studies, locations with contrasting abiotic conditions, for example across latitudes or altitudes, are surrogates for expected temporal changes (Davis & Shaw 2001; Davis et al. 2005). With the appropriate caution, inferences on future evolutionary potential of populations and species are possible. Shortcomings are that evolutionary rates cannot be directly estimated, but divergence-time estimates from molecular markers can be used as proxies (Kinnison & Hendry 2001). Moreover, the evolvability of the fundamental range limits of a species cannot be addressed (Kirkpatrick & Barton 1997).
Retrospective temporal studies follow trait distributions in local populations through time, providing direct evidence that evolution has happened and monitor potential environmental variables that may be causal. However, because temporal and spatial studies identify correlations, deciding whether or not the observed environmental variation caused shifts in trait distribution is not trivial. Inferences can be supported by measuring fitness of local and nonlocal genotypes across contrasting habitat types (Bradshaw et al. 2004), through assessments of the selection differential (Etterson & Shaw 2001) or heritability estimates of target traits (Bradshaw & Holzapfel 2001; Etterson & Shaw 2001).
Selection experiments can overcome these problems because they are manipulative. In artificial selection experiments, mating is determined by the experimenter, a procedure similar to animal or plant breeding. Controlled natural selection instead allows populations under experimentally controlled conditions to freely evolve by fertility- and mortality selection (Fuller et al. 2005; Chippindale 2006). The most appropriate test for evolutionary responses at the end of natural selection experiments is a reciprocal assessment of control and evolved lines under both conditions. Responses to selection are detectable as ‘selection–environment’ interactions, analogous to the detection of local adaptation in the field.
Controlled natural selection is the only method that provides a simulation of the future trajectory of populations, projecting rates of sustained evolutionary change as a function of a defined selection regime, but inferences on genetic architecture of traits are not possible. In artificial selection, information on the genetic architecture of the chosen trait such as heritability and correlations with other traits can be obtained. As a major disadvantage, it remains unclear whether the chosen traits contribute to fitness in the wild (Coyne & Lande 1985).
As a special form of artificial selection, antagonistic artificial selection probes trait correlations that may slow down adaptive trait changes (Beldade et al. 2002b). The experimenter tries to select for trait divergence among correlated traits in order to decide whether or not genetic correlations are due to linkage disequilibrium or due to pleiotropy (Fuller et al. 2005). While the former can be broken up by recombination, the latter cannot (Conner 2002).
Because the population is the basic unit of observation, it should also be the unit of replication. All selection experiments need untreated populations to control for changes induced by the experimental procedure (reviewed in Conner 2003; Fuller et al. 2005). A few intermittent generations without imposing selection will prevent carry-over (e.g. maternal) effects.
Predicting evolutionary effects of increased CO2 concentration
An increase of atmospheric CO2 concentration may be immediately advantageous for plant growth as it alleviates the CO2 limitation of photosynthesis, in particular for plant species without carbon concentrating mechanisms (C3-carbon fixation, Ward & Kelly 2004).
Ward et al. (2000) studied the evolutionary response of Arabidopsis thaliana towards lower and higher CO2 concentration compared to present values in a five-generation-selection experiment. Starting from an outcrossed and genetically diverse base population, seed production increased lines selected at 700 p.p.m. under these novel conditions compared to random control individuals, while growth and survival remained unchanged.
Wieneke et al. (2004) found elevated vegetative growth in Sanguisorba minor, a common herb of European grasslands, as a response to selection by increased CO2-concentration. After six years of elevated CO2 under field conditions, corresponding to presumably 1–6 generations, control and treated plants were compared in the greenhouse under both conditions. The results demonstrate enhanced litter production and carbon sequestration as a response to the selection regime.
Because of the low efficiency of Rubisco, carbon concentration mechanisms (CCM), such as CAM (crassulacean acid metababolism) or C4-carbon fixation have evolved to enrich the CO2 at the point of Rubisco fixation. In accordance with evolutionary theory, one would predict that such energetically costly carbon concentration mechanisms are no longer selected for under elevated CO2. This was indeed found after 1000 generations of experimental selection in the green unicellular algae Chlamydomonas reinhardtii. Strains under increased CO2 concentration were less efficient in carbon fixation after 1000 generations of artificial selection when tested under present-day CO2 conditions (Collins & Bell 2004); a finding which was attributed to conditional detrimental mutations compromising costly carbon-concentrating mechanisms that use bicarbonate (HCO3−) in addition to dissolved CO2 as inorganic carbon source.
- Issue published online: 28 AUG 2007
- Article first published online: 3 AUG 2007
- Received 11 March 2007; revision accepted 11 June 2007
- genetic architecture;
- genome scan;
- global change;
- range shift;
- selection experiment;
- stress tolerance;
- transcription profiling
Global environmental change is altering the selection regime for all biota. The key selective factors are altered mean, variance and seasonality of climatic variables and increase in CO2 concentration itself. We review recent studies that document rapid evolution to global climate change at the phenotypic and genetic level, as a response to shifts in these factors. Among the traits that have changed are photoperiod responses, stress tolerance and traits associated with enhanced dispersal. The genetic basis of two traits with a critical role under climate change, stress tolerance and photoperiod behaviour, is beginning to be understood for model organisms, providing a starting point for candidate gene approaches in targeted nonmodel species. Most studies that have documented evolutionary change are correlative, while selection experiments that manipulate relevant variables are rare. The latter are particularly valuable for prediction because they provide insight into heritable change to simulated future conditions. An important gap is that experimental selection regimes have mostly been testing one variable at a time, while synergistic interactions are likely under global change. The expanding toolbox available to molecular ecologists holds great promise for identifying the genetic basis of many more traits relevant to fitness under global change. Such knowledge, in turn, will significantly advance predictions on global change effects because presence and polymorphism of critical genes can be directly assessed. Moreover, knowledge of the genetic architecture of trait correlations will provide the necessary framework for understanding limits to phenotypic evolution; in particular as lack of critical gene polymorphism or entire pathways, metabolic costs of tolerance and linkage or pleiotropy causing negative trait correlations. Synergism among stressor impacts on organismal function may be causally related to conflict among transcriptomic syndromes specific to stressor types. Because adaptation to changing environment is always contingent upon the spatial distribution of genetic variation, high-resolution estimates of gene flow and hybridization should be used to inform predictions of evolutionary rates.