**Possible Evolutionary Response to Global Change – Evolutionary Rescue?**

Lars A. Bach and Cino Pertoldi *University of Aarhus Denmark* 

## **1. Introduction**

84 International Perspectives on Global Environmental Change

Nori, M., El Mourid, M. & Nefzaoui, A. (2009). Herding in a shifting Mediterranean

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#### **1.1 Climate-induced environmental changes**

With a pace that is higher than observed in the past 10,000 years global warming is currently changing the global and local environments. On average, the global temperature has increased by 0.7 degree over the past century and future projections show an acceleration of global temperature rise (Walther et al., 2002) which produces climate-induced environmental changes (CIEC). Increasing the mean temperature furthermore corresponds to an increasing range between the minimum and the maximum temperatures due to a pure scaling effect of the variance with the mean (Pertoldi et al., 2007a). Additional factors may then add even more to the increased range of temperatures combined with increased variability in precipitation patterns. An increased temperature range is translated into a fluctuating selective regime for natural populations and amplified environmental variability (2e) which have several consequences at different levels of organization.

In order to understand what limits the ability of species to adapt to CIEC, we need to integrate (local) short-term and (local) long-term changes and to increase our knowledge on the importance of genetic and environmental components on phenotypic variability (2p) (Pertoldi et al., 2005). A notorious debate between ecologists and geneticists concerns the relative importance of genetic and ecological factors for the persistence of populations. There is a need for a deeper understanding of how genetic measures can be used to indicate causal processes, including the genetic signature of population declines or expansions due to CIEC. Evolutionary biologists and ecologists have increasingly turned to molecular genetics to study the demographic and genetic consequences of CIEC on populations. However, this approach has some serious limitations: 1) many different population processes lead to similar patterns of genetic structure and 2) population genetic models most commonly applied to these systems are based on the assumption of equilibrium conditions typically not found in nature and surely not in disturbed ecosystems.

#### **1.2 A natural experiment from the past and experimental investigations on the consequences of climate-induced changes**

Detailed knowledge on how CIEC have shaped the genetic composition and the present geographic distribution of species can help us to better comprehend the possible future consequences of climatic changes. The biotic effects of Pleistocene glaciations exemplify how climatic changes influence species distributions by alternately inducing southward range

Possible Evolutionary Response to Global Change – Evolutionary Rescue? 87

Stochastic genetic models may mimic events at individual loci, so-called finite loci or allelic models, or may be parameter based, unfolding the average genetic effects according to

Determining the biodiversity impacts of climate change is a great challenge (Schwenk et al., 2009). The major consequences of CIEC for biodiversity at various scales include: distributional range of species, phenology, community structure and species interactions (Walther et al. 2002). The demographic context of 2p has considerable significance to the process of adaptation. Not only does dispersal among patches influence the evolution of traits and their plasticity, but the changing meta-community also plays a role in determining how populations respond to change (Angilletta, 2009; Mitchell & Angilletta, 2009). Given this situation, predictions at the community level seem either pointless at present or unworthy of pursuit (Ricklefs, 2008), especially since initial conditions, instabilities, and model errors should greatly affect the impact of climate change on ecological communities. Substantial shifts in the ranges and phenologies of species from an array of groups have occurred in response to climate change (Steltzer & Post, 2009). This emphasises the importance of mitigating such shifts through e.g. corridors or by securing large coherent areas with suitable habitats for wildlife. Without such initiatives many populations may become extinct due to combined effects of environmental stress, lack of evolutionary

**1.4 Shifts in the ranges and phenologies of the species as a consequence of climate-**

Biologists no longer doubt that biological systems have already responded to the current global anthropogenic changes in climate. Many studies have demonstrated substantial shifts in the ranges and phenologies of species from a broad array of taxa, indicating a coherent fingerprint of climate change (e.g. Chen et al., 2009; Steltzer & Post, 2009; Knudsen et al., 2011). Given the substantial evidence of shifting ranges and phenologies, and of substantial range shifts in the past (Davis & Shaw, 2001), much attention has also been given to forecasting the likely effects of ongoing climate change on species distributions and ecosystems from these perspectives (e.g. Kearney et al., 2008). A large, and often contentious, literature has developed about how changes in species' ranges should be modelled and how biotic interactions mechanisms might be incorporated to generate novel

Although environmental variation is not necessarily reflected in transformed vital rates, such as growth rate, interplay between environmental variation and population dynamics has been shown in a variety of species Stenseth et al., 2002). Understanding the consequences of demographic stochasticity in populations requires information of local fluctuations in population size, extinction probability and colonisation potential as well as reproductive success, which can be gained from population dynamics analyses. DNA analyses are progressively used to estimate the extent and organization of genetic diversity in populations in order to infer the causes of spatio-temporal dynamics (Schwartz et al.,

quantitative genetics theory (Verrier et al., 1990; Wang, 1996).

**1.3 Consequences of CIEC on biodiversity** 

potential and inbreeding depression.

insights (e.g. Jeschke & Strayer 2008; Keith et al., 2008).

**2. Exploiting population variation and molecular techniques** 

**induced changes** 

contractions with northward expansions. The geographic patterns resulting from these processes differ with the varying dispersal abilities and ecological requirements of species. The geographical distribution of genetic diversity in species may be used to reconstruct historical biogeographies (Avise, 1998). CIEC do not only affect the distribution of organisms, through changing the abiotic environment, they also change the patterns of biotic interactions between species, and their morphology. More emphasis should therefore be given to morphometrical investigation, which can unravel ecological patterns that are undetectable using neutral molecular markers (Pertoldi et al., 2003). The joint application of different molecular genetic and morphometric methods may prove useful in the description of population structure and help in identifying factors that shape the observed demographical, morphometrical, geographical and genetic structure (Røgilds et al., 2005; Plejdrup et al., 2006).

In particular, studies have been conducted in the attempt to obtain more detailed knowledge on the potential of 2p in an evolutionary context. A number of investigations have shown that 2p is positively associated with the level of genetic and environmental stresses that individuals experience (Kristensen et al., 2004; Røgilds et al., 2005). Several studies have also tried to elucidate the effect of genetic variability (2g) on 2p (e.g. Pertoldi et al., 2003). These studies include analyses of differences in 2p between males and females of haplo-diploid taxa, or parthenogenetic and sexually reproducing individuals (Andersen et al., 2002). Pertoldi et al., (2006b) have suggested several methods to split-up the different components of 2p (canalization, plasticity and developmental homeostasis), developing algoritms and suggesting the use of clonal organisms to remove the effect of 2g and its interaction (GXE) with 2e by means of admixture analysis (Pertoldi et al., 2006b).

Several investigations have also been conducted in order to resolve the controversies existing about the causal relationships between molecular genetic variation and phenotypebased measures of success. Pertoldi et al. (2006a) recently suggested that greater clarity would be achieved by partitioning genetic diversity into two components: that arising from adaptive evolution and that resulting from long-term historical isolation. The former can be estimated through analysis of phenotypic variation, while the latter is readily assayed through molecular phylogeography. Both approaches have their place, but measure different components of intraspecific diversity. Pertoldi et al., (2007a) suggested that a proper comparison between genetic variability using neutral molecular markers and genetic variability detected in quantitative and fitness related traits could significantly add to the open debate among evolutionary biologists on the correlation between these two measures. Recent genetics studies are beginning to broaden in scope and impact by attempting to correlate genetic, demographic and phenotypic properties of the same populations (Plejdrup et al., 2006). Furthermore, recent progress in biostatistics and mathematics (e.g. theory of coalescence, Bayesian statistics, individual-based population dynamics, algorithms for efficient simulation and sampling of complex processes), have strengthened our potential to infer population genetic processes of neutral and non-neutral genes via the development of theoretical models (Randi et al., 2003; Pertoldi et al., 2007a).

Modelling techniques having the capacity to incorporate explicit genetic variables linked to important life history traits can also be constructive for the identification of the factors (and their interactions) which are affected by CIEC and can be used as complementary tools (Strand, 2002; Bach et al., 2007). Simulation models can also easily accommodate different global change scenarios, which may not be readily accomplished by mathematical analysis. Stochastic genetic models may mimic events at individual loci, so-called finite loci or allelic models, or may be parameter based, unfolding the average genetic effects according to quantitative genetics theory (Verrier et al., 1990; Wang, 1996).

#### **1.3 Consequences of CIEC on biodiversity**

86 International Perspectives on Global Environmental Change

contractions with northward expansions. The geographic patterns resulting from these processes differ with the varying dispersal abilities and ecological requirements of species. The geographical distribution of genetic diversity in species may be used to reconstruct historical biogeographies (Avise, 1998). CIEC do not only affect the distribution of organisms, through changing the abiotic environment, they also change the patterns of biotic interactions between species, and their morphology. More emphasis should therefore be given to morphometrical investigation, which can unravel ecological patterns that are undetectable using neutral molecular markers (Pertoldi et al., 2003). The joint application of different molecular genetic and morphometric methods may prove useful in the description of population structure and help in identifying factors that shape the observed demographical, morphometrical, geographical and genetic structure (Røgilds et al., 2005;

In particular, studies have been conducted in the attempt to obtain more detailed knowledge on the potential of 2p in an evolutionary context. A number of investigations have shown that 2p is positively associated with the level of genetic and environmental stresses that individuals experience (Kristensen et al., 2004; Røgilds et al., 2005). Several studies have also tried to elucidate the effect of genetic variability (2g) on 2p (e.g. Pertoldi et al., 2003). These studies include analyses of differences in 2p between males and females of haplo-diploid taxa, or parthenogenetic and sexually reproducing individuals (Andersen et al., 2002). Pertoldi et al., (2006b) have suggested several methods to split-up the different components of 2p (canalization, plasticity and developmental homeostasis), developing algoritms and suggesting the use of clonal organisms to remove the effect of 2g and its

interaction (GXE) with 2e by means of admixture analysis (Pertoldi et al., 2006b).

theoretical models (Randi et al., 2003; Pertoldi et al., 2007a).

Several investigations have also been conducted in order to resolve the controversies existing about the causal relationships between molecular genetic variation and phenotypebased measures of success. Pertoldi et al. (2006a) recently suggested that greater clarity would be achieved by partitioning genetic diversity into two components: that arising from adaptive evolution and that resulting from long-term historical isolation. The former can be estimated through analysis of phenotypic variation, while the latter is readily assayed through molecular phylogeography. Both approaches have their place, but measure different components of intraspecific diversity. Pertoldi et al., (2007a) suggested that a proper comparison between genetic variability using neutral molecular markers and genetic variability detected in quantitative and fitness related traits could significantly add to the open debate among evolutionary biologists on the correlation between these two measures. Recent genetics studies are beginning to broaden in scope and impact by attempting to correlate genetic, demographic and phenotypic properties of the same populations (Plejdrup et al., 2006). Furthermore, recent progress in biostatistics and mathematics (e.g. theory of coalescence, Bayesian statistics, individual-based population dynamics, algorithms for efficient simulation and sampling of complex processes), have strengthened our potential to infer population genetic processes of neutral and non-neutral genes via the development of

Modelling techniques having the capacity to incorporate explicit genetic variables linked to important life history traits can also be constructive for the identification of the factors (and their interactions) which are affected by CIEC and can be used as complementary tools (Strand, 2002; Bach et al., 2007). Simulation models can also easily accommodate different global change scenarios, which may not be readily accomplished by mathematical analysis.

Plejdrup et al., 2006).

Determining the biodiversity impacts of climate change is a great challenge (Schwenk et al., 2009). The major consequences of CIEC for biodiversity at various scales include: distributional range of species, phenology, community structure and species interactions (Walther et al. 2002). The demographic context of 2p has considerable significance to the process of adaptation. Not only does dispersal among patches influence the evolution of traits and their plasticity, but the changing meta-community also plays a role in determining how populations respond to change (Angilletta, 2009; Mitchell & Angilletta, 2009). Given this situation, predictions at the community level seem either pointless at present or unworthy of pursuit (Ricklefs, 2008), especially since initial conditions, instabilities, and model errors should greatly affect the impact of climate change on ecological communities. Substantial shifts in the ranges and phenologies of species from an array of groups have occurred in response to climate change (Steltzer & Post, 2009). This emphasises the importance of mitigating such shifts through e.g. corridors or by securing large coherent areas with suitable habitats for wildlife. Without such initiatives many populations may become extinct due to combined effects of environmental stress, lack of evolutionary potential and inbreeding depression.

#### **1.4 Shifts in the ranges and phenologies of the species as a consequence of climateinduced changes**

Biologists no longer doubt that biological systems have already responded to the current global anthropogenic changes in climate. Many studies have demonstrated substantial shifts in the ranges and phenologies of species from a broad array of taxa, indicating a coherent fingerprint of climate change (e.g. Chen et al., 2009; Steltzer & Post, 2009; Knudsen et al., 2011). Given the substantial evidence of shifting ranges and phenologies, and of substantial range shifts in the past (Davis & Shaw, 2001), much attention has also been given to forecasting the likely effects of ongoing climate change on species distributions and ecosystems from these perspectives (e.g. Kearney et al., 2008). A large, and often contentious, literature has developed about how changes in species' ranges should be modelled and how biotic interactions mechanisms might be incorporated to generate novel insights (e.g. Jeschke & Strayer 2008; Keith et al., 2008).
