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ch06 2/9/06 12:45 PM Page 113 189686 / Island Press / Falk Chapter 6 Evolutionary Restoration Ecology Craig A. Stockwell, Michael T. Kinnison, and Andrew P. Hendry Restoration Ecology and Evolutionary Process Restoration activities have increased dramatically in recent years, creating evolutionary chal- lenges and opportunities. Though restoration has favored a strong focus on the role of habi- tat, concerns surrounding the evolutionary ecology of populations are increasing. In this con- text, previous researchers have considered the importance of preserving extant diversity and maintaining future evolutionary potential (Montalvo et al. 1997; Lesica and Allendorf 1999), but they have usually ignored the prospect of ongoing evolution in real time. However, such contemporary evolution (changes occurring over one to a few hundred generations) appears to be relatively common in nature (Stockwell and Weeks 1999; Bone and Farres 2001; Kin- nison and Hendry 2001; Reznick and Ghalambor 2001; Ashley et al. 2003; Stockwell et al. 2003). Moreover, it is often associated with situations that may prevail in restoration projects, namely the presence of introduced populations and other anthropogenic disturbances (Stockwell and Weeks 1999; Bone and Farres 2001; Reznick and Ghalambor 2001) (Table 6.1). Any restoration program may thus entail consideration of evolution in the past, present, and future. Restoration efforts often involve dramatic and rapid shifts in habitat that may even lead to different ecological states (such as altered fire regimes) (Suding et al. 2003). Genetic variants that evolved within historically different evolutionary contexts (the past) may thus be pitted against novel and mismatched current conditions (the present). The degree of this mismatch should then determine the pattern and strength of selection acting on trait variation in such populations (Box 6.1; Figure 6.1). If trait variation is heritable and selection is sufficiently strong, contemporary evolution is likely to occur and may have dramatic impacts on the adaptive dynamics of restoration scenarios. Adaptation to current conditions (the present) may in turn influence the ability of such populations to subsequently persist and evolve over short or long periods (the future). Thus, the success (or failure) of a restoration effort may of- ten be as much an evolutionary issue as an ecological one. It is also useful to recognize that contemporary evolution may alter the interactions of species with their environments and each other. Restoration ecologists may thus be faced with a changed cast of players, even if many of the same nominal species are restored. Efforts that assume species and populations are evolutionarily stagnant may face frustrating and 113 ch06 2/9/06 12:45 PM Page 114 189686 / Island Press / Falk 1 eeks and u ick et al. 1997;eh 2004 w 1970; W w 1966; Antono-iling 1995 References ison et al. 2001; arres 2001 1999 arres 2001 2001; KinnQuinn et al. 2001 O’Steen et al. 2002Stearns 1983; Stockwell and Wlyer et al., 2005vics and BradshaKruckeberg 1985; Macnair 1987;Bone and Fand Snaydon 1976; Bone andFard et al. 2000 Bell et al. 2004Hendry et al. 2000; Hendry et al.Koskinen et al. 2002Endler 1980; ReznStockwell and Mulvey 1998; Col-Rasner et al. 2004; YWilliams and Moore 1989Hargeby et al. 2004Jain and BradshaSnaydon and Davies 1972; DaviesDavison and ReWLevinton et al. 2003 ine , thermal ancy ils (e.g., m t il pH a ium imals in nature. al const inated so Evolutionary agentigratory rigor)w ity) am m ing environment (temperature,,ity/flo concentration w al cont 2 eshwater habitfloater temperatureenvironmentand aridwaste piles)rtilizer, altered so r Sexual selection e Removal of cadm F Breed W Predator regimesEnvironmentSalinEcoregional variation (temperaturePredationMetFHigh ozone concentrationCO , able 6.1 ail) t wth, morphology, offspring size, ance raits ing, ovarian invest- T , fat storage als (e.g., copper) ination, yolk-sac vol- ium resist wth rate, survival ation reproductive timmentume, groantipredator behaviornase); body shapewth rate Examples of contemporary evolution in plants and anDevelopment and groge and size at maturityize at maturityigmentolerance to met Lateral plate armor Length at termPgdh (Phosphogluconate dehydroge-Morphology (amount of white in tMorphologyTpH toleranceGroSeed productionLoss of cadm )S ) ing spp.) ) )A xanthum Lupinus hus )P , Gasterosteus hymallus Cyprinodon T ies, includAntho unco hyemalis , shianus J uaticus Oncorhync Gambusia affinis ) Agrostis tenuis Limnodrilus hoff- ) oecilia reticulata) , Lotus per ) P Oryctolagus cuniculusAsellus aq, uitofish ( isturbance xanthum odoratum izationaculeatusfic salmon (thymallustularosadMimulus guttatusodoratumbicolormeisteri ci Threespine stickleback (PaEuropean Grayling (Guppies (MosqWhite Sands pupfish (Dark-eyed juncos (Rabbits (Isopod (Numerous plant specAnthoPlantago majorArabidopsis thalianaOligochaete ( Context/ExampleColon In situ ch06 2/9/06 12:45 PM Page 115 189686 / Island Press / Falk ik 1994 ad 2001 abashn w and Holzapfel 2001 lendorf et al. 2001; Grant andGrant 2002 Mallet 1989; TCarroll et al. 2001BradshaHairston et al. 1999Grant and Grant 2002Réale et al. 2003Haugen and VøllestOlsen et al. 2004Coltman et al. 2003Rhymer and Simberloff 1996; Al- , wing ies ality ality or sterilitying ies -related mort ization among wild spec Bt lobal warmeutrophicationtures)gear (e.g., mesh size of nets)and between wild and domestic(sub)spec Selective mortIntroduced host fruit sizeGCyanobacteria increase folloDrought effects on food resourcesGlobal change (increased tempera-Selectivity of harvest methods andHarvest of large cod Selective harvest of large males Hybrid ance to iet apause response ance (e.g., resisti ic d ide resist)ance to poor/toxic ding season esticBt P Beak lengthPhotoperiodResistBody size, beak shapeBreedAge and size at maturitySize, age at maturityMale body and horn sizeMorphology (other aspects likely) ) ) - ) w yeomyia ) ) W leata ids, sunflo ies Diamonda hymallus uitoes (Geospiza fortisT adera Plutella xylostellaJ)amiasciurus Gadus morhuaOvis canadensis T) ) Daphnia g ids, salmon ) uirrels ( back moths (haematolomasmithiiater flea (hudsonicusthymallusers, etc. Numerous insect specSoapberry bugs (Pitcher plant mosqWGalapágos finches (Red sqEuropean Grayling (Northern cod (Bighorn sheep (Ducks, can Selective harvestIntrogression ch06 2/9/06 12:45 PM Page 116 189686 / Island Press / Falk 1 116 ecological theory and the restoration of populations and communities Box 6.1 Evolutionary Change in Quantitative Traits For a quantitative trait (influenced by multiple genes, often of small effect), a simple equa- tion can be used to predict how adaptation should proceed, at least under a number of sim- plifying assumptions (Lande and Arnold 1983). Specifically, ∆z = Gß, where ∆z is the change in mean trait value from one generation to the next, G is the additive genetic vari- ance for the trait and ß is the selection gradient acting on the trait (slope of the relationship between the trait and fitness). When considering a single trait, this equation is analogous to the traditional “breeder’s equation” (evolutionary response = heritability * selection; R = h2S) because G/P= h2and S/P= ß, where Pis the phenotypic variance and S is the selection differential (difference between the mean trait value before and after selection). When con- sidering multiple traits, ∆z becomes a vector of changes in mean trait values, G becomes a matrix of additive genetic variances/covariances, and ß becomes a vector of selection gradi- ents. That is, ∆z = Gß (Lande and Arnold 1983; Schluter 2000; Arnold et al. 2001). In the case of two traits, the multivariate equation expands to Dz G G b c 1d = c 11 12dc 1d, Dz G G b 2 21 22 2 where ∆z is the evolutionary response for trait i, G and G are the additive genetic vari- i 11 22 ances for the two traits, G and G are identical and are the additive genetic covariance be- 12 21 tween the two traits, and ß is the selection gradient acting on the trait. Selection gradients are i commonly estimated as partial regression coefficients from a multiple regression of both traits on fitness. In this case, selection gradients represent the effect of each trait on fitness af- ter controlling for the effect of the other trait (i.e., “direct” selection). This equation shows how the evolutionary response for each trait will be a function of selection acting directly on that trait, the additive genetic variance for that trait, selection acting on the other trait, and the additive genetic covariance between the traits. That is, ∆z = G ß + G ß and ∆z = 1 11 1 12 2 2 G ß + G ß . This formulation illustrates how apparently paradoxical evolutionary changes 22 2 21 1 can be observed in some situations. For example, the first trait can evolve to be smaller even if it is under selection to be larger (e.g., Grant and Grant 1995). This can occur when G ß 12 2 < 0 and |G ß | > G ß ; that is, when the negative indirect effect of selection on the first trait 12 2 11 1 is stronger than the positive direct effect of selection. These negative indirect effects should increase as selection on the second trait becomes stronger and as the genetic covariance be- comes stronger, with one of these quantities necessarily being negative. Phenotypes in an undisturbed population should be centered around an optimal value (i.e., the population is well adapted). In a restoration context, however, a disturbance to the environment may shift the phenotypic optimum away from the current phenotypes (Figure 6.1). This shift leads to a mismatch between current phenotypes and optimal phenotypes, leaving the population maladapted and subject to directional selection. Under a number of assumptions, the strength of this selection can be represented as: b = 1z q2 2 w + P where z is the mean trait value, q is the optimal trait value, P is the phenotypic variance, and 2 2 w is the strength of stabilizing selection around the optimum (for simplicity, we assume w is
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