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Wade , P. R. ( 2002 ). A Bayesian stock assessment of the eastern pacifi c gray whale using abundance and harvest data from 1967–1996 .J. Cetacean Res. Manage. 4 , 85 – 98 .

York , A. E. ( 1994 ). Population dynamics of northern sea lions 1975–1985 .Mar. Mamm. Sci. 10 , 38 – 51 .

York , A. E. , and Hartley , J. R. ( 1981 ). Pup production following harvest of female northern fur seals . Can. J. Fish. Aquat. Sci. 38 , 84 – 90 .

Stock Identity JOHN Y. WANG

I. Importance of Stock Identity

Determining how a species is divided into stocks (the term “ stocks ” is used here to refer to biological stocks rather than management stocks; see later) is fundamental to the con-

servation of marine mammals. Because evolutionary processes act at the intraspecifi c level, genetic differences and locally adaptive char-acters will accumulate in stocks over time. This reservoir of genetic and phenotypic diversity increases a species ’ ability to persist through environmental changes. Thus, one of the main goals in conservation is to preserve the evolutionary potential of species by maintaining the diversity found in stocks. Another important goal is to maintain spe-cies as functioning elements in their ecosystem by preventing regional overexploitation and depletion. Consequently, knowledge of stock structure of species is integral for developing effective management programs to achieve these goals.

The greatest threats to the survival of marine mammals are human activities. Marine mammals experience various levels and kinds of anthropogenic threats in different regions, and all exhibit life history characteristics (i.e., long-lived, low fecundity, late age of maturity) that make them susceptible to these threats. In order to assess the impact of human activities on marine mammals, it is crucial to identify stocks accurately, establish where the stock boundaries exist, and determine the permeability of the boundaries to genetic exchange with other stocks. This information will infl uence how the biological data needed for assessments are collected and interpreted and how management plans are designed. Inaccurate stock designations can lead to either unnecessary regulation(s) of fi sheries or fallacious management that may result in the depletion of a stock and its accompanying genetic material. For example, if stock structure goes unrecognized and two distinct stocks are incorrectly managed as one, one may inadvertently become depleted.

Understanding stock structure can also help in streamlining the design of other studies, providing insights into evolution and moni-toring illegal activities [e.g., DNA analysis of cetacean meat prod-ucts from Japanese markets found stocks that were prohibited from sale (Baker et al ., 2000)]. Therefore, much effort has been directed toward identifying stocks of marine mammals. However, the task remains problematic, with two major diffi culties: (1) semantic uncer-tainty and disagreement in the defi nition of “ stock ” and (2) studying stock identity with incomplete biological knowledge.

II. Defi nition of Stock The term “ stock ” has been used to refer to both biological and

management entities (although in many cases, they are combined or inseparable). A management stock is a group of conspecifi c indi-viduals that are managed separately. The delineation of these stocks is very much dependent on the goals of managers and may not be based on biological discontinuities (e.g., International Whaling Commission management stock designations for baleen whales). With the exception of the defi nition by Moritz (1994) , who described a “ management unit ” (MU) (which he synonymized with “ stock ” and appears to be equivalent to management stock) as having signifi cant differences in allele frequencies at nuclear or mitochondrial DNA loci, the criteria for determining management stocks may have lit-tle or no biological rationale or consistency and may be infl uenced greatly by political interests. Nevertheless, management stocks have been used widely due to the paucity of biological information and will likely continue to play an important role in conservation. Developments in management strategies for situations with incom-plete biological information should improve the success of conser-vation programs ( Taylor, 1997 ). Although management stocks offer more fl exibility in the sense that they can still be the focus of man-agement programs without evidence of biological distinctiveness, conservation goals (e.g., maintaining genetic diversity) are more likely to be achieved if stocks are based on biological data. Therefore, this article focuses mainly on biological stocks.

Biological stocks are characterized by no or low levels of genetic exchange (which means that members of a biological stock tend to interbreed with each other more often than with other individu-als). An entity with this property has also been called a population, subpopulation, evolutionary signifi cant unit (ESU), deme, and sub-species (the only intraspecifi c taxon recognized by the International Commission on Zoological Nomenclature). When gene fl ow between two groups is absent, there is usually no disagreement that they rep-resent separate biological stocks. However, it is more typical that some level of genetic exchange exists. Even low levels of genetic exchange can obscure stock boundaries and complicate the task of discriminating biological stocks. Although there is no consensus on the threshold level of gene fl ow above which stock status is no longer recognized, several approaches have been developed to make the identifi cation of biological stocks more objective and explicit.

III. Stock Identifi cation Approaches Defi ning stocks is linked inextricably with defi ning species. There

are many concepts that propose species defi nitions, but those advo-cated most commonly today include biological, evolutionary, and phylogenetic species concepts [for a detailed overview of these and other concepts, see Sites and Crandall (1997) and King (1993) ]. However, because these concepts all have major limitations, agree-ment on the best species defi nition still eludes biologists. Like the species concepts, each approach to stock identifi cation has limita-tions and weaknesses. In addition, defi ning stocks can be infl uenced, and therefore complicated further, by the goals of conservation and legislation. For example, one of the goals of the U.S. Endangered Species Act (ESA) is to decrease the loss of genetic variation. Thus, for this purpose, defi ning stocks using genetic criteria [e.g., the ESU of Moritz (1994) ] is a reasonable proposal [however, see Pennockand Dimmick (1997) and Dimmick et al. (1999) ]. Unlike the ESA, the US Marine Mammal Protection Act (MMPA) endeavors to keep biological stocks at or beyond their optimum sustainable levels and functioning in their ecological roles. To accomplish the intent of this

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legislation, defi ning conservation units also requires demographic information.

There are several operational approaches to stock identifi ca-tion. Whereas some approaches are clear extensions of certain spe-cies concepts, the theoretical basis of others may be less explicit or embedded within the methodology. Brief descriptions of the approaches used most commonly are presented here.

Morphological characters have been the main evidence for delin-eating species. Because differences between stocks are generally less obvious than between species, examination of a large series of speci-mens is recommended for the identifi cation of stocks using morphol-ogy. However, for most marine mammal species, it is diffi cult, if not impossible, to obtain a large number of specimens for analysis.

The “ phylogeographic ” approach proposed by Dizon et al. (1992) determines the likelihood that a group of organisms is an ESU. The determination is based on distribution, population response (includ-ing demography, behavior, vocalizations), and phenotypic and gen-otypic information, all of which serve as proxies for reproductive isolation (the essence of the biological species concept). Groups most likely to be ESUs have clear geographic and genetic separation and are assigned to “ category I. ” “ Category II ” units are characterized by clear genetic separation but little to no geographic partitioning. Units with little genetic differentiation but isolated geographically from other conspecifi cs defi ne “ category III. ” “ Category IV ” units are least likely to be ESUs because they are separated neither geo-graphically nor genetically from other units. This approach has been described as being unwieldy, but it is explicit, transparent, and has performed well. It also seems to provide the most fl exibility in stock delineation, because several kinds of evidence are used and it offers more than a simple dichotomy for the mosaic of variation present. In addition, by considering information on distribution and population responses, it is much better than the other approaches at detecting recently diverged stocks.

Moritz (1994) proposed defi nitions for ESU and MU that differ from those of the phylogeographic approach. His defi nition of an ESU requires these entities to exhibit reciprocal monophyly (i.e., to have diagnostic differences) in the mitochondrial DNA (mtDNA) and signifi cant divergence in nuclear DNA allele frequencies, whereas MUs are defi ned by signifi cant divergence in either mtDNA or nuclear DNA allele frequencies (irrespective of the distinctiveness of the alleles). Because these defi nitions are based solely on DNA patterns, they cannot be realized with nonmolecular characters and therefore have limited application. Although DNA information may be more direct for determining whether genetic differences exist (some phenotypic characters can be plastic and infl uenced by envi-ronmental factors), it is not always available, and differences in phe-notypic characters may be established more rapidly after divergence (e.g., demographic response).

The “ phylogenetic ” approach for defi ning ESU was advocated by Vogler and DeSalle (1994) . Their procedure for recognizing ESUs is similar to how species are delimited under the phylogenetic species concept. Only heritable genetic, morphological, ecological, or behav-ioral characters are analyzed. An entity is deemed an ESU if it differs from all other entities in having a unique character or a diagnostic combination of characters. However, it is unclear how the defi ni-tions of ESU and species differ with this approach, and the process of determining useful characters may require expert knowledge and can be operationally complex.

The “ character concordance ” approach ( Avise and Ball, 1990 ; Grady and Quattro, 1999 ) suggests that a group of individuals sharing a common evolutionary history should share characters that are unique

to the group, and the level of concordance among independent, shared characters should increase with increasing divergence time. Thus, high concordance would be strong support for distinctiveness. When con-cordance is incomplete, the weight of the evidence governs the deci-sion on stock status. Because there are no clear procedural guidelines for interpreting discordant evidence, decisions may be complicated and subjective. Furthermore, many independent characters evolve at different rates, so a lack of concordance may be expected for groups that diverged recently. Therefore this approach may not be effective in identifying recently separated stocks.

A recent workshop on cetacean taxonomy recommended a defi ni-tion for what should be recognized as a subspecies, the highest cat-egory of what could be considered a stock ( Reeves et al. , 2004 ): a group of organisms that appear to have been on an independent evo-lutionary trajectory (with minor continuing fl ow with other groups) as demonstrated by morphological evidence or at least one line of genetic evidence, with the notes that geographical or behavioral dif-ferences can complement morphological and genetic evidence and that subspecies could be geographical forms, incipient species, or even actual species for which data are currently too poor to sup-port elevation to the species level. However, quantitative criteria for determining adequate levels of difference were not specifi ed; it was felt that individual researchers should have the responsibility of con-vincing their peers of the force of distinctions drawn.

Regardless of the approach one decides to use, it is important that clear hypotheses are stated so that interpretation of the results can be objective and divorced from philosophical or conceptual issues. It is also important that the interpretation of data is within the limitations of the hypotheses being tested. For example, if the results of a study do not support distinct units, then the statistical ability (or power) of the study to detect separate units should be examined. With inad-equate power, the appropriate conclusion would be that differences in the characters examined were not detected rather than differences do not exist between the units being studied. Without suffi cient power, conclusions regarding stock structure would be premature and should not be made. Finally, it may be tempting to combine units when evi-dence for separating the units is not found; however, this is neither correct nor does such grouping keep to the precautionary principle.

In situations where essentially no biological stock information exists, the participants of a workshop on the genetics of marine mammals recommended that the smallest area where exploitation occurs be recognized as a stock (management stock). However, they also cautioned that in certain circumstances (e.g., migratory stocks that experience exploitation in several fi sheries in different areas or seasons), this strategy may not be precautionary ( Dizon et al., 1997 ). Therefore, the suitability of this approach should be assessed for each case and used only temporarily while immediate attention is directed at studying biological stock structure.

IV. Analytical Techniques Several types of information have contributed to our understanding

of marine mammal stocks. Which analytical techniques are adopted depends on which stock defi nition and identifi cation approach are fol-lowed. The types of information that have been used in understanding marine mammal stock structure include phenotypic, genetic, distribu-tional, demographic, and ecological information.

Analyses of phenotypic characters have dominated this task. Comparisons of osteology, morphology, and pigmentation have con-tributed the most to stock identifi cation because these characters provide tangible evidence of distinctness. Also, increased computing

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capabilities have made multivariate analyses of large data sets simple and quick. However, there are few species (and even fewer stocks) for which data from a large series of specimens can be examined, because specimens are diffi cult and expensive to obtain, prepare, and store and some characters can be affected greatly by the condi-tion of the specimen (e.g., decomposition and external morphology; postmortem changes in pigmentation).

Increasingly, attention has been shifting toward molecular char-acters. Protein analyses were important for stock identifi cation but have become obsolete with the development of more effi cient DNA technology. Presently, most conclusions regarding stock status are not accepted fully until DNA has been analyzed as well.

Because the properties of mammalian mtDNA are fairly well understood, analyses of mtDNA have dominated molecular studies of marine mammal stocks. For many marine mammal conservation goals, mtDNA evidence is suffi cient for designating management stocks [for more details, see Dizon et al. (1997) ]. For biological stocks, evidence from characters that are heritable from both par-ents would provide more details about contemporary gene fl ow and be more convincing. This is because the majority of criteria for inter-preting mtDNA data assume that mutation, drift and migration have reached an equilibrium, which can take a long time (particularly in species with long life spans and generation times) so this assumption may not be always valid. Direct analyses of nuclear DNA, especially microsatellites and SNPs (single nucleotide polymorphisms), which is inherited from both parents, are becoming more common.

Most marine mammal species do not have uniform distributions. Areas of high density are usually separated by areas with low or no concentration. Thus, distribution can provide a fi rst approximation of where stock boundaries may exist. Based on heterogeneous distribu-tions, seasonality of occurrence, oceanographic features (e.g., barri-ers, water currents, temperature), and geographic distance between areas of high abundance, provisional stocks can be proposed for fur-ther studies to test. However, distributional data should always be interpreted in conjunction with additional biological knowledge (e.g., daily and seasonal movement patterns, philopatric behavior).

Most distinct stocks are separated geographically or tempo-rally. Therefore, each stock experiences unique ambient conditions (e.g., differential environmental stresses, food quality or availability, exploitation). Adaptations to different conditions may be expressed demographically or ecologically. Different demographic profi les in two groups would be strong evidence of non-interbreeding stocks. Also, demographic differences can reveal recently isolated stocks that have yet to develop genetic or phenotypic distinctiveness. However, to obtain accurate demographic information, a large data set must be analyzed. Because other techniques can address stock identity more directly and effi ciently, few studies employ demographic analysis for delineating stocks. If available, demographic information should also be analyzed, especially if stock status, based on molecular and phe-notypic evidence, is uncertain.

Many studies have proposed stocks using analyses of ecological differences. Prey preference, parasitology, pollutant loads, stable isotope ratios, and fatty acid signatures are some of the ecological information used most commonly. Although ecological studies pro-vide another line of evidence for understanding stocks, they act only as proxies for genetic and demographic separation.

V. Study Design and Sampling Often the people performing analyses of stock structure and

identifi cation are distant from the sample collection and may lack

knowledge of the local situation. As a result, they are dependent on those collecting the specimens for information, which sometimes may be incomplete. Thus, it is important for studies (and hypothe-ses) to be designed with a requirement for a set of standard, a prioriinformation (e.g., sex, morphology, demography, ecology, oceanogra-phy, etc.).

Selection of samples to be analyzed is a critical part of study design, but researchers are commonly handcuffed by the limited availability of samples. As a result, it is common to include samples with limited or no information about their origin, so assumptions are made, often implicitly (e.g., stranded individuals are commonly assumed to be from a local or nearby “ population ” or designated as being from a certain body of water or area). Inclusion of such specimens and assumptions can unknowingly further complicate or obscure our understanding of stock structure and identity or lead to erroneous conclusions. In addi-tion, political borders can often affect the scope of sampling. Because man-made boundaries are often unconnected with biology, they should not be used for grouping specimens in analyses.

In general, samples of coastal species (e.g., harbor porpoise, fran-ciscana, etc.) are easier to obtain than for offshore species. However, some coastal species have small populations (e.g., Sousa , Orcaella , etc.) so specimens may be extremely rare. Also, industrial offshore fi sheries may result in the capture of large numbers of oceanic species (e.g., the infamous eastern tropical Pacifi c tuna purse-seine fi shery). For coastal species, assuming that stranded specimens are from local or nearby waters is often fairly reasonable, especially if other infor-mation exists such as local fauna composition, freshness of carcass, evidence of entanglement in local fi sheries, etc.). However, the same assumption is highly questionable for offshore species, which may be less tied to land masses or fi xed geographic locations but more related to highly dynamic water masses with boundaries that can vary greatly seasonally or annually. Dead or dying oceanic animals may also be car-ried by water currents for long distances before stranding. Therefore, great caution must be exercised when attempting to understand stock structure of oceanic species with analyses that include stranded speci-mens. It is also often assumed implicitly that stranded animals (which are often all that may be available) are representative of a population or stock rather than a specifi c part of the group.

More and more studies are employing in situ sampling (e.g., biopsy darting). Even with such direct sampling methods, it is crucial that extensive information accompany each sample. Standard data such as date, time and geographic location, while vital, are insuffi cient for species that may be relating to fl uid boundaries. Sampling from the same geographical position may result in the sampling of different stocks at different times when water masses shift ( Fig. 1 ). Recording data that can help to characterize water masses from which samples were collected (e.g., water temperature, salinity, turbidity, etc.) will help greatly in understanding stock structure. Photographs of animals sampled may also allow recognition of slight differences in morphol-ogy (e.g., pigmentation, etc.) that may help to set a priori groupings for tests. Although some analyses do not require a priori grouping (e.g., cluster analyses, STRUCTURE for nuclear genetic data), taking a more holistic approach and incorporating ecological, oceanographic and other information into study design and interpretation of results will produce more powerful and convincing conclusions.

V. Other Complications Even if there were agreement on a single stock defi nition and

multiple techniques were used, defi ning stocks would still not be a trivial task. Many situations can obscure and complicate our attempts

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to delineate stocks, including taxonomic uncertainty; various lev-els of genetic exchange between stocks; clinal variation; differences between sexes in dispersal and philopatric behavior; diversity in mat-ing strategies; habitat shifts (e.g., occasional environmental fl uctua-tions may bring stocks that are usually separated geographically into contact and allow interbreeding); fragmentation and genetic bottle-necks resulting from exploitation; mixed stocks; social structure; and short-term and seasonal movements, sometimes across international boundaries. Without knowledge of, and consideration for these (and other) attributes, conclusions about stock structure can be com-promised. With so many complications, it is not surprising that the biological stock structure of most marine mammal species (even those that were exploited heavily by commercial harvesting) remains uncertain. However, multidisciplinary techniques, technological advancements, and continued attention should allow us to make rapid progress in identifying biological stocks of marine mammals and to design more effective management programs in the absence of essential biological information.

See Also the Following Articles Conservation Biology ■ Genetics for Management ■ MolecularEcology ■ Species

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cordance in species concepts and biological taxonomy . Oxf. Surv. Evol. Biol. 7 , 45 – 67 .

Baker , C. S. , and Palumbi , S. R. ( 1994 ). Which whales are hunted? A molecular genetic approach to monitoring whaling . Science 265 , 1538 – 1539 .

Dimmick , W. W. , Ghedotti , M. J. , Grose , M. J. , Maglia , A. M. , Meinhardt , D. J. , and Pennock , D. S. ( 1999 ). The importance of sys-tematic biology in defi ning units of conservation . Conserv. Biol. 13 , 653 – 660 .

Dizon , A. E. , Lockyer , C. , Perrin , W. F. , DeMaster , D. P. , and Sisson , J. ( 1992 ). Rethinking the stock concept: a phylogeographic approach .Conserv. Biol. 6 , 24 – 36 .

Dizon, A. E. et al. (18 authors). (1997). Report of the Workshop . In “ Molecular Genetics of Marine Mammals ” (A. E. Dizon, S. J. Chivers, and W. F. Perrin, eds.), Special Publication 3, 3–48. The Society for Marine Mammalogy, Lawrence, KS.

Grady , J. M. , and Quattro , J. M. ( 1999 ). Using character concord-ance to defi ne taxonomic and conservation units . Conserv. Biol. 13 , 1004 – 1007 .

King , M. ( 1993 ). “ Species Evolution: The Role of Chromosome Change . ” Cambridge University Press , Cambridge .

Moritz , C. ( 1994 ). Defi ning “ evolutionary signifi cant units ” for conserva-tion . Trends Evol. Ecol. 9 , 373 – 375 .

Pennock , D. S. , and Dimmick , W. W. ( 1997 ). Critique of the evolution-ary signifi cant unit as a defi nition for “ distinct population segments ”under the US Endangered Species Act . Conserv. Biol. 11 , 611 – 619 .

Reeves, R. R., Perrin, W. F., Taylor, B. L., Baker, C. S., and Mesnick, S. L. (2004). Report of the Workshop on Shortcomings of Cetacean Taxonomy in Relation to Needs of Conservation and Management, April 30–May 2, 2004 La Jolla, California. NOAA Tech. Mem. NMFS NOAA-TM-NMFS-SWFSC-363 , 94 pp.

Sites , J. W. , Jr. , and Crandall , K. A. ( 1997 ). Testing species boundaries in biodiversity studies . Conserv. Biol. 11 , 1289 – 1297 .

Taylor , B. L. ( 1997 ). Defi ning “ population ” to meet management objectives for marine mammals . In “ Molecular Genetics of Marine Mammals ” ( A. E. Dizon , S. J. Chivers , and W. F. Perrin , eds ) , pp. 49 – 65 . The Society for Marine Mammalogy , Lawrence, KS , Special Publication 3 .

Vogler , A. P. , and DeSalle , B. ( 1994 ). Diagnosing units of conservation management . Conserv. Biol. 8 , 354 – 363 .

Stranding WILLIAM F. PERRIN AND JOSEPH R. GERACI

Stranded whales have fascinated us through history ( Fig. 1 ). Why do marine mammals strand, what can we learn from their misfortune, and what can we do about it?

I. Why Do Marine Mammals Strand? Animals that die or become enfeebled at sea of course may be

brought passively to shore by wind and wave action. More intriguing are those cases where marine mammals in distress purposely come ashore. A stranded animal when returned to the water may delib-erately strand again. This is very frustrating to those who are try-ing to “ rescue ” it. It must be understood that an animal may have stranded because it has decided that it cannot keep itself afl oat and survive at sea. Thus, deliberate stranding may represent an effort to keep breathing, whatever the ultimate cost. While this may not be adaptive behavior in evolutionary terms, because nearly all stranded animals die if unassisted, given the alternative of equally certain but earlier death the consideration may be moot. A will to survive is adaptive in general, even if not effective in this circumstance.

Figure 1 Different possible scenarios of shifts in water masses (dark and light blue and green) past a nearby land mass (brown) and through the sampling area (crossed circle) are shown. The sizes of the arrows represent the strength of the currents.