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Molecular ecology of global change

  1. THORSTEN B. H. REUSCH1,
  2. TROY E. WOOD1,2

Article first published online: 3 AUG 2007

DOI: 10.1111/j.1365-294X.2007.03454.x

Issue

Molecular Ecology

Molecular Ecology

Volume 16, Issue 19, pages 3973–3992, October 2007

Additional Information

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

Author Information

  1. 1

    Plant Evolutionary Ecology, Institute for Evolution and Biodiversity, University of Münster, Hüfferstr.1, 48149 Münster, Germany,

  2. 2

    Department of Biology, Indiana University, Jordan Hall 142, 1001 E. Third Street, Bloomington, IN 47405, USA

* Thorsten B. H. Reusch, Fax: +492518324668; E-mail: treusch@uni-muenster.de

  • Studying evolutionary responses to climate changeTwo 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 (†; ‡). 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 (§). Moreover, the evolvability of the fundamental range limits of a species cannot be addressed ().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 (‖), through assessments of the selection differential (††) or heritability estimates of target traits (‡‡; ††).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 (§§; ¶¶). 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 (‖‖).As a special form of artificial selection, antagonistic artificial selection probes trait correlations that may slow down adaptive trait changes (†††). 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 (§§). While the former can be broken up by recombination, the latter cannot (‡‡‡).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 concentrationAn 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, §§§).¶¶¶) 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.‖‖‖) 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 (††††); 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.

Publication History

  1. Issue published online: 28 AUG 2007
  2. Article first published online: 3 AUG 2007
  3. Received 11 March 2007; revision accepted 11 June 2007

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