Measures of microsatellite and morphological variability
We examined presumptive neutral genetic variation using microsatellite DNA and presumptive adaptive variation in external morphology and internal anatomy in a geographically widespread species. Molecular variation in rainbow trout results from the impacts of: (i) isolation and postglacial dispersal from two main glacial refugia (a ‘coastal’ refuge and an ‘interior’ refuge), and (ii) contemporary restrictions in gene flow imposed, at least in part, by extrinsic landscape features such as distance, presence of waterfall migration barriers, isolated lake habitats, and underlying geomorphology (McCusker et al. 2000; Tamkee et al. 2010). Consequently, while not of obvious intrinsic value in-and-of-itself, neutral molecular variation represents a proxy measure of the history or ‘bioheritage’ of a taxon as well as reflecting aspects of its contemporary biology (e.g., demographic bottlenecks in population size) and future evolutionary potential – the three temporal scales of conservation (Bowen 1999).
By contrast, we have described patterns of morphological and anatomical variation among rainbow trout populations that appear, at least in part, to represent evolved differences of functional significance to persistence of specific populations in contrasting environments, that is, adaptive variation (Keeley et al. 2005, 2007). To a large degree, most of the variation occurred along an axis that differentiated stream-dwelling from lake-dwelling fish, and piscivorous populations from those with more generalist diets. These findings are consistent with the generally accepted importance of hydrodynamic and trophic environmental features in promoting adaptive variation in fishes (e.g., McGuigan et al. 2003; Kocher 2004; Langerhans 2008). Consequently, the morphological variation we have described might be important for population persistence in particular contemporary environments as well as providing a reservoir of evolutionary potential for adaptation to future changing environments. Langerhans (2009), for instance, demonstrated the importance of post-Pleistocene divergence in morphology to survival of Bahamas mosquitofish (Gambusia hubbsi) in environments that varied in predation pressure.
One challenge to using morphological variation in a diversity of taxa is in selecting which traits should be assayed. The value of using morphological variation in the present context lies in the evidence for its genetic basis and functional significance – the variation in the traits assayed reflect, in part, genetic variation that contributes to performance differences within specific environments which has promoted evolutionary divergence in these traits across populations (Keeley et al. 2005, 2007). More generally, when selecting morphological traits it will be critical to have a basic understanding of the genetics of variation and the possible role of plasticity in phenotypic expression (e.g., Pakkasmaa and Piironen 2000; Keeley et al. 2007). In addition, while some morphological traits may have relatively simple and common genetic architecture across populations (e.g., Colosimo et al. 2004), cases of multifarious morphological distinction that we have described will almost surely be considerably more complex in the number, identity, and action of genes that control such variation. Understanding the genetic architecture of such traits is challenging (Mackay 2003), but should not be necessary to detail as long as the basic requirement that aspects of phenotype are genetically controlled in a way that can respond to selection and lead to evolutionary change is met. Thus, it is also important to have some a priori basis for the functional significance of such variation in natural environments such that the traits examined reflect an assessment of the ecological exchangeability of populations (sensuCrandall et al. 2000). This will require background breeding studies, studies of phenotype-environment associations or experimental functional studies of the significance of morphological variation. Natural variation in traits as diverse as shell shape in mollusks (Conde-Padín et al. 2009) and pigmentation patterns in mice (Mullen and Hoekstra 2008) indicate that morphological variants across a diversity of taxa are amenable to experimental studies to assess their adaptive potential for use as a measure of ecological legacy as a component of conservation prioritization. Even in the absence of knowledge of the genetic control or architecture of specific traits, variation in morphology could still be used in conservation ranking schemes. For instance, extensive phenotypic plasticity may be important for population persistence in variable environments. In this case, phenotypic variants can signal important components of the habitat that are of high conservation value because they drive the expression of divergent phenotypes (e.g., Pakkasmaa and Piironen 2000; Holopainen et al. 2005).
The two measures of variation that we have examined in this study are also related biologically. For example, a strong degree of divergence at neutral microsatellite DNA loci between two adjacent populations implies either that there is restricted dispersal between these populations (and hence restricted potential gene flow) or that while interpopulation dispersal may be significant, these loci are linked to regions under divergent selection such that realized gene flow between localities is low. Under either scenario, the microsatellite divergence between localities suggests the potential (from isolation) or actual importance of natural selection promoting adaptive divergence between populations. The high PST values that we observed between many populations is consistent with environmental differences in their habitats (lakes vs streams, large rivers vs streams, etc.) and with the potential for the effects of genetic drift and divergent selection to promote morphological diversity in rainbow trout. Leinonen et al. (2006) came to a similar conclusion in a study of stream, lake, and anadromous populations of threespine stickleback (Gasterosteus aculeatus). We did, however, observe a positive correlation between FST and PST in our study and, overall, average FST and PST values were very similar (0.37 vs 0.39, respectively) which suggests a potential role of drift in driving some of the morphological diversity we have documented. Notwithstanding this general trend, there were clearly instances when comparing the same two populations showed that pairwise PST was either considerably less than FST (suggesting stabilizing selection) or considerably higher (suggesting divergent selection). For instance, several comparisons (e.g., Blanchet vs Skinny, Canyon Creek vs Clearwater River) had very high FST (0.34–0.49) in the face of very low PST (<0.1). By contrast, other comparisons (Skinny vs Horseshoe lakes; Nimpkish River vs Blackwater River) exhibited low FST (0.03–0.12), but relatively high PST (0.25 and 0.56, respectively). In summary, we suggest that our measures of microsatellite and morphological/anatomical variation within and between populations are of direct relevance to biodiversity conservation for the reasons discussed above. Our analysis of these data has attempted to consider both simultaneously in a population prioritization context. There are, however, other kinds of data that could be used in similar contexts. In fact, salmonid fishes in general show extensive variability in other aspects of phenotype, such as behaviour and life history, that may have more obvious adaptive significance than morphology (e.g., migratory behaviour, age and size at maturity –Taylor 1991; Garcia de Leaniz et al. 2007) and similar quantification and ranking procedures could be developed for these other traits in combination with assays of neutral variation.
Valuation of biodiversity
Avise (2005) listed three major contexts within which humanity rationalizes the conservation of biodiversity: aesthetic value, provision of ecosystem services, and ethics – a recognition of an intrinsic value to life. An additional consideration, in particular for species such as rainbow trout, is economic value – the recognition that biodiversity represents direct or indirect economic value to humans. Given these rationalizations for the value of biodiversity, jurisdictions responsible for the protection and or management of biodiversity are commonly faced with the difficult task of prioritizing effort, expenditures, regulatory initiatives, and opportunity costs towards various units of biodiversity whether they represent individuals, populations, or ecosystems (Brooks et al. 2006). One of the parameters that is considered in such prioritization exercises are the relative, actual, or perceived ‘values’ of the units being considered.
The valuation of biodiversity is a growing research area and has economic, cultural, and biological components which are not necessarily mutually exclusive. For instance, Rudd (2009) presented an analysis of nonmarket values for six species of vertebrates at risk in Canada that essentially ranked each of the species in terms of the amount of money that a sample (n = 2761) of people were willing to pay for conservation programs. By contrast, Redding and Mooers (2006) provided a ranking of 9546 species of birds based on threat status and a measure of the ‘genetic value’ of each taxon. The genetic value was based, essentially, on a measure of the evolutionary isolation of each species relative to all others and, hence, its biological value in terms of representing unique genetic variation. The former example is one in which the prioritization is based largely on the perceived societal values of the unit of biodiversity while the latter is an example of a more strictly biological/scientific prioritization (see also Meuser et al. 2009). Our analysis is more aligned with the latter approach, but is one that combines molecular and morphological aspects of diversity rather than relying on a single measure of distinctiveness (e.g., Bush and Adams 2007) which is akin to the idea of using character concordance to identify conservation units (e.g., Grady and Quattro 1999). Essentially, our analysis resulted in measures (MDS, GDS, CT, CDr,) of how divergent or ‘atypical’ each population was from the average rainbow trout both in terms of microsatellite and morphological characterization. In addition, for the genetic data we examined the relative levels of variation within each population (CS, CSr). Although we observed a positive correlation between FST and PST (see above) which are pairwise comparisons, we observed negative correlations between GDS, CTr, CT (and their components) and MDS. This implies that when evaluating population distinctiveness, use of single character types is problematic because distinctiveness in one character type is not necessarily accompanied by distinctiveness in another. We applied one solution to this possible outcome by taking the average rank of genetic diversity, allelic richness, and MDS to provide an overall rank of population distinctiveness. This procedure resulted in six of the 27 populations having the five highest average rankings with two of those populations tied with the highest average ranking.
In any system designed to rank populations based on biological attributes relevant to conservation ties will occur. One possible solution to this dilemma would be to weight the input variables differentially. Although this is easily achieved in a practical sense, the biological rationale for weighting morphological variation over neutral molecular variation (or vice versa), or within population variation over among population variation (or vice versa) is not obvious and a consensus would likely be difficult to reach (e.g., Petit et al. 1998). In the case of ties, it may be informative to include further ecological or habitat characteristics. For instance, the two creek populations (Canyon and Fry creeks) tied for the highest ranking are both classified ecologically as ‘headwater’. Given that these populations are similar in terms of their average morphological and genetic distinctiveness, one could further prioritize amongst them based on their ecology or fish communities. For instance, Canyon Creek fish are the only ones to co-exist with bull trout (Salvelinus confluentus) and coastal cutthroat trout (O. clarkii) whereas Fry Creek contains only rainbow trout, a similar ecological condition as Murray Creek (ranked 3rd). In this case, ranking Canyon Creek higher than Fry Creek could be justified because another headwater, rainbow trout-only population also occurs within the top five (Murray Creek). Allendorf et al. (1997) suggested that the ‘native assemblage’ of which a population is part of could be used to evaluate the ecological legacy of that population for conservation prioritization. Another possible ‘tie-breaker’ could be geographic representation. For instance, animal distributions can be mapped onto physical biogeoclimatic zones, ecozones, biogeographic zones, or in the case of aquatic organisms, major drainage systems (e.g., COSEWIC 2009). Ties in quantitative rankings could be broken by assigning the higher priority to that population which resides in a drainage system that is not yet represented.
Allendorf et al. (1997) used a points system in which populations were given either 1 or 0 ‘points’ for satisfying (or not) specific questions regarding their evolutionary and/or ecological character whereas our system provides a quantitative assessment of the degree to which populations differ from one another and are ranked thereafter. Perhaps a combination of such approaches would be fruitful. First, populations could be ranked based on quantitative measures of how much they differ from one another in molecular and morphological (or other quantifiable adaptive differences) traits. Second, any ties could be addressed by pairwise evaluation of populations of the same rank based on qualitative criteria such as community composition, habitat type, drainage basin occupancy, or ecological role or function. In this manner, a combination our system and others such as that of Allendorf et al. (1997) could objectively rank populations using a variety of criteria that are difficult to combine on the same quantitative scale. Another possible use of ranking systems is to utilize them in an iterative fashion. Initially, populations are quantitatively ranked based on molecular and morphological distinctiveness and selected for conservation priority based on these ranks subject to the limitation that there must be at least one population from each ecotype (six in the case of rainbow trout) or major drainage system (eight in the case of BC – see Taylor 2004). Then, the procedure is repeated to add a second population to each ecotype group or drainage system based on the quantitative rankings. Pressey and Nicholls (1989) proposed this kind of iterative process for selecting representative areas for conservation reserves based on different scoring criteria.
The scenarios discussed above are subject to the limitation that we sampled only 27 of what are likely 100s of populations of rainbow trout in BC. Consequently, the relative rankings of the populations that we have included in the current analysis could change with the addition of new populations, a limitation that is common to all prioritization schemes. Although the ranking of populations could easily be updated with new data, it would be preferable to sample as widely as possible such that all geographic areas, ecotypes, and putative genetic groups (perhaps inferred from geography) are represented in the initial study to minimize shifting ranking among populations (cf. Crandall et al. 2000).
In addition, these biological attributes can also be used in conjunction with additional criteria. For species-level prioritization, Avise (2005) suggested a multifaceted procedure where taxa are ranked by the sums of the weighted ranks of five criteria: rarity, distribution, ecological importance, ‘charisma’, and phylogeny. The criteria of rarity and distribution are also strongly tied to threat status of the unit of biodiversity being considered while the latter three are more related to inherent biological value. The use of the information that we have collected on each population is best viewed as a method of conservation priority in the absence of factors related to actual threat status, that is, they relate more closely to assessments of the genetic, evolutionary, and ecological legacy of the species (sensuAllendorf et al. 1997). For instance, our examples and protocol might be best applied in situations when conservation priority is a proactive exercise, that is, when attempting to set protective measures and rank populations that are healthy and exist under relatively pristine conditions (as most of ours do) or when evaluating the potential consequences of loss of such populations in response to proposed environmental changes. Further, a higher order analysis that factors in socio-economic real and opportunity costs to make proactive decisions on priorities for conservation planning, or reactively when challenges to specific populations arise, can augment prioritization schemes initiated with biological data (Avise 2005; Rudd 2009). For instance, Fish Lake (110 hectares) is located in the Chilcotin Region of southcentral BC and a gold-copper mine has been proposed for the area. There have been extensive environmental assessment and fish compensation studies related to this project (see http://www.ceaa.gc.ca/050/details-eng.cfm?cear_id=44811) which would, in the end, involve the loss of Fish Lake and its rainbow trout in their current state via the construction of a dam and conversion of Fish Lake into a tailings pond. Our analysis of Fish Lake compared to the other 26 populations in our study indicates that it ranked 5th overall with its distinctiveness driven largely by the measures of neutral genetic variation rather than by morphological distinctiveness (Table 3). The lake, however, supports a vigorous and popular recreational fishery for rainbow trout and the development has many other cultural, historical, and societal impacts all of which must be factored into a final decision on the whether or not the project proceeds and what kinds and levels of compensation are appropriate. Finally, when attempting to rank populations in terms of conservation and if those population are already compromised and/or susceptible to existing or future threats, then clearly other factors (e.g., rate of decline, population viability analyses, number and degree of threats) need to be considered in addition to measures of ecological and evolutionary legacy (cf. Allendorf et al. 1997).