Sustainability 1131

aerial surveys than from ships, because the aircraft travels much faster. For some species, correction factors have been developed to correct for the proportion of animals missed from airplanes or ships. Vessel attraction or avoidance is another concern when designing shipboard marine mammal surveys. For example, harbor porpoise are known to avoid vessels, and if animals are not detected before they react, result­ing abundance estimates may be too low. The opposite problem exists for species that are attracted to vessels to “ ride the bow ” ; in these cases abundance estimates may be too high. Both of these problems can be minimized by using a larger vessel that allows viewing from a greater height and with high-power binoculars; animals can then be detected at a greater distance before they react to the vessel.

There is increasing recognition that marine mammal surveys are most effectively interpreted in the context of the habitat conditions at the time of the survey. Marine ecosystems are very dynamic, and the concurrent collection of real-time ecosystem data during surveys pro­vides an ecological context for the observed patterns in marine mam­mal distribution and abundance. Physical oceanographic measurements and indices of biological productivity can readily be obtained through shipboard sampling, aerial instrumentation, or satellite data. Biological measurements generally require shipboard sampling, such as net tows and hydroacoustic measurements. With the addition of such ecosystem data, survey results can be used to model ecological relationships and evaluate the effect of environmental variability on marine mammal spe­cies (Hedley et al ., 1999; Forney, 2000; Ferguson et al. , 2006).

See Also the Following Articles Abundance Estimation Management

References Aragones , L. V. , Jefferson , T. A., and Marsh , H. ( 1997 ). Marine mam­

mal survey techniques applicable in developing countries. Asian Mar. Biol. 14, 15– 39.

Barlow , J. ( 1995 ). The abundance of cetaceans in California waters. Ship surveys in summer and fall of 1991. Fish. Bull. 93, 1– 14.

Buckland , S. T. , Breiwick , J. M., Cattanach , K. L., and Laake , J. L. ( 1993 ). Estimated population size of the California gray whale . Mar. Mamm. Sci. 9, 235–249.

Buckland , S. T. , Anderson , D. R., Burnham , K. P. , Laake , J. L., Borchers , D. L., and Thomas , L. ( 2001 ). “Introduction to Distance Sampling: Estimating Abundance of Biological Populations . ” Oxford University Press, New York , 432 p. .

Buckland , S. T. , Anderson , D. R., Burnham , K. P. , Laake , J. L., Borchers , D. L., and Thomas , L. ( 2004 ). “Advanced Distance Sampling.” Oxford University Press, New York , 434 p. .

Ferguson , M. C., Barlow, J., Fiedler, P. , Reilly, S. B., and Gerrodette , T. ( 2006 ). Spatial models of delphinid (family Delphinidae) encoun­ter rate and group size in the eastern tropical Pacific Ocean . Ecol. Modell. 193, 645–662.

Fiedler, P. C., and Reilly, S. B. ( 1994 ). Interannual variability of dolphin habitats in the eastern tropical Pacific. I: Research vessel surveys, 1986–1990 . Fish. Bull. 92, 434–450.

Forney , K. A. ( 2000 ). Environmental models of cetacean abundance: reducing uncertainty in population trends . Conserv. Biol. 14 ( 5 ), 1271–1286.

Forney , K. A., Barlow , J., and Carretta , J. V. ( 1995 ). The abundance of cetaceans in California waters. Part II. Aerial surveys in winter and spring of 1991 and 1992. Fish. Bull. 93, 15– 22.

Garner , G. W. , Amstrup , S. C., Laake , J. L., Manly , B. F. J., McDonald , L. L., and Robertson , D. G. ( 1999 ). “Marine Mammal Survey and Assessment Methods . ” A.A. Balkema , Rotterdam.

Hedley , S. L., Buckland , S. T. , and Borchers , D. L. ( 1999 ). Spatial mode­ling from line transect data. J. Cetacean Res. Manage. 1( 3 ), 255–264.

Heide-Jørgensen , M. P. , Teilmann , J., Benke , H., and Wulf , J. ( 1993 ). Abundance and distribution of harbor porpoises Phocoena phoc­oena in selected areas of the western Baltic and the North Sea . Helg. Meeresunter. 47, 335–346.

Hiby, A. R., and Hammond, P. S. (1989). Survey techniques for estimat­ing abundance of cetaceans. Rep. Int. Whal. Commn. (Spec. Iss. 11), 47–80.

Kraus , S. D., Gilbert , J. R., and Prescott , J. H. ( 1983 ). A comparison of aerial, shipboard, and land-based survey methodology for the harbor porpoise, Phocoena phocoena. Fish. Bull. 81, 910–913.

Lowry, M. S. ( 1999 ). Counts of California sea lion (Zalophus califor­nianus) pups from aerial color photographs and from the ground: a comparison of two methods. Mar. Mamm. Sci. 15, 143–158.

Øien, N. (1991). Abundance of the northeastern Atlantic stock of minke whales based on shipboard surveys conducted in July 1989. Rep. Int. Whal. Commn. 41 , 433–437.

Rathbun , G. ( 1988 ). Fixed-wing airplane versus helicopter surveys of manatees (Trichechus manatus). Mar. Mamm. Sci. 4, 71– 74.

Vidal , O., Barlow , J., Hurtado , L. A., Torre , J., Cendon , P. , and Ojeda , Z. ( 1997 ). Distribution and abundance of the Amazon river dolphin (Inia geoffrensis) and the tucuxi (Sotalia fl uviatilis) in the upper Amazon River. Mar. Mamm. Sci. 13, 427–445.

Wade, P. R., and Gerrodette, T. (1993). Estimates of cetacean abun­dance and distribution in the eastern tropical Pacifi c. Rep. Int. Whal. Commn. 413, 477–494.

Sustainability CHARLES W. FOWLER AND MICHAEL A. ETNIER

Sustainability has been elusive in spite of its ubiquitous appear­ance in the goals for management. Human impacts need to be sustainable, whether they are the harvest of a marine mam­

mal population, the harvest of fi nfishes in the marine environment, our production of CO2, or the genetic effects we have on other spe­cies. Sustainable human interactions with other systems must be established in ways that account for the suite of factors involved in ecosystems and the complexity of the biosphere to include both our direct effects and our indirect effects on such systems. It is unlikely that historical harvests of marine mammal populations are sustain­able, partly because of their low productivity levels ( Perrin, 1999 ). Thus, defining sustainability, whether it involves our interactions with marine mammals, fisheries resources, or ecosystems, remains an important objective.

Historically, the concept of Maximum Sustainable Yield (MSY) has played a major role in the management of our utilization of natu­ral resources. This approach has yet to be assessed in its contribu- S tion to worldwide problems such as over-harvested fi sh populations (Rosenberg et al., 1993; Committee on Ecosystem Management for Sustainable Marine Fisheries, 1999). Commercial whaling and seal­ing have also involved concepts derived from the MSY approach.

The inadequacies of management based on MSY have been recognized [e.g., it is illogical ( Fowler and Smith, 2004 )]; such approaches are not sustainable. Progress in understanding such problems involve the development of other methodologies, e.g., the Catch Limit Algorithm of the International Whaling Commission ( Slooten, 1998 ) and the Potential Biological Removal approach being used by the National Marine Fisheries Service in the United

1132 Sustainability

States ( Wade, 1998 ). These alternatives, however, have not escaped the weaknesses of being applicable only to individual species and they do not account for complexity. The ecosystem effects of fi sh­ing ( Hall, 1999 ), whaling, or sealing are not adequately considered in current management strategies. The challenges currently facing management are not being met.

It is therefore extremely important to find alternatives that will work. One approach is systemic management ( Fowler, 2003 ) in which empirical examples are used to define and measure sustain-ability and set sustainable goals. Along with other species, marine mammals are sources of information about sustainability that is broadly applicable and meets the demands being made of manage­ment. Using empirical examples of sustainability, the abnormal or pathological can be avoided.

Marine mammals serve as empirical examples of sustainable roles, or niches, within marine ecosystems; they have persisted as parts of such systems to integrate the various factors contributing to their evolution. Resource consumption is an example of an ecosystem rela­tionship for which we need measures of sustainability. Both marine mammals and fisheries consume biomass from resource/prey spe­cies, making part of their interaction competitive. The rates of preda­tion by marine mammals exemplify variation in sustainable levels of consumption. The size selectivity of their feeding habits exemplifi es sustainability involving genetic impact. Importantly, there are lim­its to variation in such interspecific interactions as there are with all ecological interactions ( Fowler and Hobbs, 2002 ). The failures of con­ventional management can be overcome by replacing such manage­ment with processes that mimic empirical examples of sustainability ( Fowler, 2003 ). Such management ensures that fisheries catches or selectivity are not abnormal, in comparison to the consumption and selectivity observed among other consumer species. Thus, observed examples of sustainable consumption rates, and size selectivity can be used to regulate the catches taken by fisheries while simultaneously conserving resources and habitat for other species. As such, marine mammals, like other species, are empirical examples of sustainability that provide guiding information. Use of such information prevents the bias of human limitations in converting scientific information to objective management advice ( Fowler, 2003 ).

I. Management Questions, Empirical Answers

S

How many tons of whales, seals, fish, cephalopods, or other resources should we harvest each year? What is the appropriate or optimal rate at which to harvest biomass, and when and where should it be harvested? What is an advisable size selectivity for com­mercial fishing, to deal with one of the many aspects of the genetic effects of harvesting? Such questions can be asked with regard to a single resource species, or with respect to any area of the oceans, an ecosystem, a group of resource species, a season, or the biosphere. How do we answer all such questions so that the answer for one case will not be in conflict with the answer for another? Empirical infor­mation is key to answering such questions consistently, and marine mammals are key elements in providing such information for man­agement in marine environments (Fowler, 1999; Fowler, 2003).

Fig. 1 shows frequency distributions (empirical probability dis­tributions) for consumption rates exhibited by various marine mam­mals. Also shown, for comparison in each case, is the harvest rate for fisheries—the rate at which humans consume biomass. The top panel illustrates consumption from a population of an individual spe­cies and the bottom panel total consumption within the biosphere. Intermediate panels depict consumption from a group of resource

species, an ecosystem, and the marine environment. Thus, Fig. 1 represents information for a telescoped series of increasing com­plexity. In this case, the biosphere contains the marine environment which, in turn, includes the ecosystem (Bering Sea). Within the eco­system we find populations of resource species (the fi nfi sh) among which is the population of walleye pollock (Theragra chalcogramma, one species).

Figure 2 is a comparison of the mean size of Atlantic cod (Gadus morhua) taken by 19 species of marine mammals with that of com­mercial fisheries. This represents one measure of the abnormality of commercial fishing in regard to the size composition of catches and its related genetic effects on the resource species compared to the situation normally experienced in the ecosystem ( Etnier and Fowler, 2005 ). The intensity of this selectivity is directly related to the abnor­mally high harvest rates shown in Fig. 1.

Various requirements are placed on management (e.g., the tenets of management) ( Fowler, 2003 ). It has been made clear that man­agement should avoid abnormality in the components, processes,

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Sustainability 1133

and characteristics of systems (Christensen et al., 1996; Mangel et al., 1996) [see the review of Fowler and Hobbs (2002)]. These include the components and processes that constitute individuals, species, ecosystems, and the biosphere. Humans (through commer­cial fi shing) are, or have been, obvious outliers relative to the natural variation illustrated in Figs. 1 and 2 ( Fowler and Hobbs, 2003 ).

There are things management can not do. The other species within these distributions are largely beyond our control, but not our influence, especially the collective aggregate of species in each distribution. Individual species can undergo change opposite to our intentions if we act to influence them directly. In fact, changes we stimulate in these species may result in unwanted reactions in the rest of the system, whether we purposely manipulate them individu­ally or as a group. These changes include repercussions throughout the food web (e.g., predator/prey dynamics) and domino-effects of genetic consequences in the underlying coevolutionary web. Such reactions cannot be avoided.

Management can move forward, however, by focusing on reduc­ing consumption by humans, or harvesting smaller fish, thus avoiding the abnormal by falling within the range of the variation exhibited by other species. Nonhuman species exhibit predator–prey interac­tions that occur within the context of complexity—all the things that influence these species to result in what we observe (all the explana­tory factors) ( Fowler and Crawford, 2004 ). That is, all the things that have contributed to the observed rates of consumption such as those shown in Fig. 1, or the size selectivity shown in Fig. 2, are taken into account. These factors include all anthropogenic factors to include

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the effects of global warming, toxic chemicals, overfi shing, intro­duced species, and oceanic acidification. This complexity is inherent to the patterns we observe.

Figures 1 and 2, then, serve to guide the management of our use of fisheries resources when achieving sustainability is the ultimate goal. The empirical data exemplify what works in the face of the com­plete suite of factors that set limits on the consumption of resources. Better options are found among the more numerous examples toward the centers of the distributions compared to the lack of examples beyond the tails ( Figs. 1 and 2 ). The risks and constraints that prevent the accumulation of species in such regions are to be avoided. How, then, can we carry out sustainable management?

II. Management to Achieve Sustainability It has long been recognized that we need a form of management

that applies to ecosystems ( Christensen et al., 1996 ). To develop sustainable management strategies, humans must manage by hav­ing sustainable influence on ecosystems. This includes consuming biomass from ecosystems at rates that are sustainable. Sustainable management requires change. For example, reducing consump­tion by humans to 10% of current harvest rates of fish would place our species squarely within the range of variation shown in relevant ecosystems (third panel of Fig. 1) . Such change will require time to accomplish. Maintenance of reduced levels, once achieved, would lead to further challenges for management. These would include responding to changes within ecosystems over seasons, with shifts in climate, or in response to our management.

It has been recognized for some time, in the world of commercial fi sheries management, that the historical focus on managing harvests from the individual species point of view has been insuffi cient, partly because of the need to consider ecosystems. However, management restricted to ecosystems would be similarly insufficient because of the need to account for both the broader marine environment and the biosphere, in addition to individual species.

Management based on empirical examples is an integrated approach that simultaneously helps to define sustainable harvests at the level of individual species and the biosphere. For example, reduc­ing harvests to between 1 and 10% of recent harvest levels would be required for the species represented in the top panel of Fig. 1. We can similarly account for multi-species groups and the entire marine environment (second and fourth panels, respectively, Fig. 1). The biosphere can be involved by reducing human consumption to about 0.1% of current consumption levels (Fig. 1, panel 5). Not only would this account for food-web effects, but it would also deal with the inten­sity of any selectivity resulting in genetic effects. Selectivity per se can also be dealt with directly as a distinct management issue ( Fig. 2 ).

Figure 1 The frequency distribution of consumption rates (biomass consumed per year, in log 10 scale) for marine mammals showing opti- S mal consumption rates where most species are concentrated. The rate at which humans harvest biomass is shown for comparison. The top panel shows the natural variation in consumption of walleye Pollock ( Theragra chalcogramma ) as observed for six species of marine mam­mals in the Bering Sea in comparison to recent takes of pollock by commercial fisheries ( Livingston, 1993). The second panel shows consump­tion of fi nfish in the Bering Sea by 20 species of marine mammals compared to fisheries takes (predominantly pollock) ( Fowler and Perez, 1999). Total biomass consumption is shown for 20 species of marine mammals in the Bering Sea in the third panel, again compared to the commercial take which is predominantly pollock (Fowler and Perez, 1999). Total biomass consumption for the entire marine environment (all oceans combined) is shown in the fourth panel for 55 species of marine mammals, here compared to the take of about 110 million metric tons estimated as the harvest of biomass for human use in the late 1990s ( Committee on Ecosystem Management for Sustainable Marine Fisheries, 1999 ). Worldwide consumption of biomass by humans is compared to that of 55 species of marine mammals in the bottom panel. The last two panels are based on indirect estimates (Fowler and Perez, 1999) using population and body size data from the marine mammal series by Ridgway and Harrison (1981–1999) and equations representing ingestion rates as a function of body size in Peters (1983).

1134 Sustainability

In all cases shown in Figs. 1 and 2 , management would involve change, often measured in orders-of-magnitude, to avoid human abnormality. If the distributions themselves change in response to the reduction of harvested biomass by humans (or other management to deal with factors such as habitat modification, and the production of CO2 and toxic chemicals), then sustainable management would need to respond to the new information. This requires continuous monitor­ing through concerted scientific effort to observe such changes.

III. Accounting for Complexity In management, the list of things to be considered seems endless.

For example, we need to account for the effects of all forms of selec­tivity (evolution), endangered species, and multiple complex proc­esses such as nutrient flow within ecosystems. It is often said that management needs to be interdisciplinary, or an integrated account­ing of everything science can study. But we also need to account for the things we do not, or cannot, study or know about. This is accom­plished in two ways when we take advantage of empirical examples provided by species such as marine mammals.

First, every species reflects the effects of everything that infl u­ences it. These factors are integrated in (inherent to) the distribu­tions shown in Fig. 1 (Fowler and Crawford, 2004). For example, evolution is taken into account through its influence on the position of every species within each distribution. Each species represents a composite of balances among various opposing forces (e.g., those involved in predation, population growth, evolution, or extinction). Each species reflects the constraints of the system—constraints such as competition for the limited availability of energy in its path through the various trophic levels. The relative importance of each factor compared to every other factor is accounted for implicitly. They are integral to what we observe.

Second, we must address other management questions. Distributions similar to those of Fig. 1 can be developed for the allo­cation of biomass consumption over alternative resource species, sea­sons, and geographic space. Marine mammals can be used as empirical examples in such an endeavor and through such species we account for the unknowns that influence the position of each species in distri­butions like those of Fig. 1. For marine mammals themselves, fi nd­ing the rates at which they can be harvested sustainably would involve information regarding consumption by their predators—including other marine mammals!

IV. Consistency

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An important aspect of empirical examples is their representation of a system that is internally consistent. Advice for management at the ecosystem level (Fig. 1, panel 3) will be consistent with advice at the individual species level (panel 1) when applied simultane­ously. Collective application at the individual species level must be constrained to the limits set by application at the ecosystem level. Nutrients, energy, biomass, and species involved in this systemic con­sistency guarantee freedom of conflict because the confl icting forces of nature result in what we see in distributions derived empirically.

Marine mammals can serve as empirical sources of information about how species fi t into marine ecosystems. Through information about nonhuman species, such as marine mammals, we are pro­vided with guidance about sustainable harvest rates, size selectivity, allocation over size, allocation of harvests over time and space, allocation across resource species, and the variety of other manage­ment questions left largely unaddressed in current management practices.

See Also the Following Articles Abundance Estimation ■ Bycatch ■ Fishing Industry, Effects of ■

Management ■ Population Dynamics

References Christensen , N. L., Bartuska , A. M., Brown , J. H., Carpenter , S. R.,

D’Antonio , C., Francis , R., Franklin , J. F. , et al. ( 1996 ). The report of the Ecological Society of America Committee on the scientifi c basis for ecosystem management. Ecol. Appl. 6, 665–691.

Committee on Ecosystem Management for Sustainable Marine Fisheries ( 1999 ). “Sustaining Marine Fisheries . ” National Academy Press, Washington, D.C. .

Etnier, M. A., and Fowler, C. W. (2005). Comparison of size selectivity between marine mammals and commercial fi sheries with recommen­dations for restructuring management policies. U.S. Department of Commerce, NOAA Technical Memorandum NMFS-AFSC-159.

Fowler, C. W. (1999). Natures ’ Monte Carlo experiments in sustainabil­ity. In “ Proceedings of the Fifth NMFS Stock Assessment Workshop: Providing Scientific Advice to Implement the Precautionary Approach Under the Magnuson-Stevens Fishery Conservation and Management Act ” (V. R. Restrepo, ed.), pp. 25–32. U.S. Department of Commerce, NOAA Technical Memorandum NMFS-F/SPO-40.

Fowler , C. W. ( 2003 ). Tenets, principles, and criteria for management: the basis for systemic management. Mar. Fish. Rev. 65, 1– 55.

Fowler, C. W. , and Crawford , R. J. M. ( 2004 ). Systemic management of fisheries in space and time: tradeoffs, complexity, ecosystems, sustain-ability. Biosph. Conserv. 6, 25– 42.

Fowler, C. W. , and Hobbs , L. ( 2002 ). Limits to natural variation: implications for systemic management. Anim. Biodivers. Conserv. 25, 7– 45.

Fowler, C. W. , and Hobbs , L. ( 2003 ). Is humanity sustainable? Proc. R. Soc. Lond. B. 270, 2579–2583.

Fowler, C. W., and Perez, M. A. (1999). Constructing species frequency distributions —a step toward systemic management. U.S. Department of Commerce, NOAA Technical Memorandum NMFS-AFSC-109.

Fowler, C. W. , and Smith , T. D. ( 2004 ). Preface to the 2004 printing . In “Dynamics of Large Mammal Populations ” (C. W. Fowler , and T. D. Smith , eds ), pp. xiii–xxvi. Blackburn Press , Caldwell.

Hall , S. J. ( 1999 ). “The Effects of Fishing on Marine Ecosystems and Communities .” Blackwell Science , Oxford.

Livingston , P. A. ( 1993 ). Importance of predation by groundfi sh, marine mammals and birds on walleye pollock Theragra chalcogramma and Pacific herring Clupea pallasi in the eastern Bering Sea . Mar. Ecol. Prog. Ser. 102, 205–215.

Mangel , M., Talbot , L. M., Meffe , G. K., Agardy , M. T. , Alverson , D. L., Barlow , J., Botkin , D., et al. ( 1996 ). Principles for the conservation of wild living resources. Ecol. Appl. 6, 338–362.

Perrin , W. F. ( 1999 ). Selected examples of small cetaceans at risk . In “Conservation and Management of Marine Mammals” (J. Twiss , and R. R. Reeves , eds ), pp. 296–310. Smithsonian Press , Washington, D.C.

Peters , R. H. ( 1983 ). “The Ecological Implications of Body Size . ” Cambridge University Press, New York .

Ridgway, S. H., and Harrison , R. (eds) ( 1981–1999 ). “Handbook of Marine Mammals , ” pp. 1–6. Academic Press , New York .

Rosenberg , A. A., Fogarty , M. J., Sissenwine , M. P. , Beddington , J. R., and Shephard , J. G. ( 1993 ). Achieving sustainable use of renewable resources . Science 262, 828–829.

Slooten , E. ( 1998 ). Risk analysis at the International Whaling Commission . In “Statistics in Ecology and Environmental Monitoring 2” (D. J. Fletcher , L. Kavalieris, and B. F. J. Manly , eds ), pp. 173–180. University of Otago Press, Dunedin.

Wade , P. R. ( 1998 ). Calculating limits to the allowable human-caused mortality of cetaceans and pinnipeds. Mar. Mamm. Sci. 14, 1– 37.