Juha Merilä and Ary A. Hoffmann
Changing climatic conditions have both direct and indirect influences on abiotic and biotic processes and represent a potent source of novel selection pressures for adaptive evolution. In addition, climate change can impact evolution by altering patterns of hybridization, changing population size, and altering patterns of gene flow in landscapes. Given that scientific evidence for rapid evolutionary adaptation to spatial variation in abiotic and biotic environmental conditions—analogous to that seen in changes brought by climate change—is ubiquitous, ongoing climate change is expected to have large and widespread evolutionary impacts on wild populations. However, phenotypic plasticity, migration, and various kinds of genetic and ecological constraints can preclude organisms from evolving much in response to climate change, and generalizations about the rate and magnitude of expected responses are difficult to make for a number of reasons.
First, the study of microevolutionary responses to climate change is a young field of investigation. While interest in evolutionary impacts of climate change goes back to early macroevolutionary (paleontological) studies focused on prehistoric climate changes, microevolutionary studies started only in the late 1980s. The discipline gained real momentum in the 2000s after the concept of climate change became of interest to the general public and funding organizations. As such, no general conclusions have yet emerged. Second, the complexity of biotic changes triggered by novel climatic conditions renders predictions about patterns and strength of natural selection difficult. Third, predictions are complicated also because the expression of genetic variability in traits of ecological importance varies with environmental conditions, affecting expected responses to climate-mediated selection.
There are now several examples where organisms have evolved in response to selection pressures associated with climate change, including changes in the timing of life history events and in the ability to tolerate abiotic and biotic stresses arising from climate change. However, there are also many examples where expected selection responses have not been detected. This may be partly explainable by methodological difficulties involved with detecting genetic changes, but also by various processes constraining evolution.
There are concerns that the rates of environmental changes are too fast to allow many, especially large and long-lived, organisms to maintain adaptedness. Theoretical studies suggest that maximal sustainable rates of evolutionary change are on the order of 0.1 haldanes (i.e., phenotypic standard deviations per generation) or less, whereas the rates expected under current climate change projections will often require faster adaptation. Hence, widespread maladaptation and extinctions are expected. These concerns are compounded by the expectation that the amount of genetic variation harbored by populations and available for selection will be reduced by habitat destruction and fragmentation caused by human activities, although in some cases this may be countered by hybridization. Rates of adaptation will also depend on patterns of gene flow and the steepness of climatic gradients. Theoretical studies also suggest that phenotypic plasticity (i.e., nongenetic phenotypic changes) can affect evolutionary genetic changes, but relevant empirical evidence is still scarce. While all of these factors point to a high level of uncertainty around evolutionary changes, it is nevertheless important to consider evolutionary resilience in enhancing the ability of organisms to adapt to climate change.
Fisheries science emerged in the mid-19th century, when scientists volunteered to conduct conservation-related investigations of commercially important aquatic species for the governments of North Atlantic nations. Scientists also promoted oyster culture and fish hatcheries to sustain the aquatic harvests. Fisheries science fully professionalized with specialized graduate training in the 1920s.
The earliest stage, involving inventory science, trawling surveys, and natural history studies continued to dominate into the 1930s within the European colonial diaspora. Meanwhile, scientists in Scandinavian countries, Britain, Germany, the United States, and Japan began developing quantitative fisheries science after 1900, incorporating hydrography, age-determination studies, and population dynamics. Norwegian biologist Johan Hjort’s 1914 finding, that the size of a large “year class” of juvenile fish is unrelated to the size of the spawning population, created the central foundation and conundrum of later fisheries science. By the 1920s, fisheries scientists in Europe and America were striving to develop a theory of fishing. They attempted to develop predictive models that incorporated statistical and quantitative analysis of past fishing success, as well as quantitative values reflecting a species’ population demographics, as a basis for predicting future catches and managing fisheries for sustainability. This research was supported by international scientific organizations such as the International Council for the Exploration of the Sea (ICES), the International Pacific Halibut Commission (IPHC), and the United Nations’ Food and Agriculture Organization (FAO).
Both nationally and internationally, political entanglement was an inevitable feature of fisheries science. Beyond substituting their science for fishers’ traditional and practical knowledge, many postwar fisheries scientists also brought progressive ideals into fisheries management, advocating fishing for a maximum sustainable yield. This in turn made it possible for governments, economists, and even scientists, to use this nebulous target to project preferred social, political, and economic outcomes, while altogether discarding any practical conservation measures to rein in globalized postwar industrialized fishing. These ideals were also exported to nascent postwar fisheries science programs in developing Pacific and Indian Ocean nations and in Eastern Europe and Turkey.
The vision of mid-century triumphalist science, that industrial fisheries could be scientifically managed like any other industrial enterprise, was thwarted by commercial fish stock collapses, beginning slowly in the 1950s and accelerating after 1970, including the massive northern cod crisis of the early 1990s. In the 1980s scientists, aided by more powerful computers, attempted multi-species models to understand the different impacts of a fishery on various species. Daniel Pauly led the way with multi-species models for tropical fisheries, where the need for such was most urgent, and pioneered the global database FishBase, using fishing data collected by the FAO and national bodies. In Canada the cod crisis inspired Ransom Myers to use large databases for fisheries analysis to show the role of overfishing in causing that crisis. After 1980 population ecologists also demonstrated the importance of life history data for understanding fish species’ responses to fishery-induced population and environmental change.
With fishing continuing to shrink many global commercial stocks, scientists have demonstrated how different measures can manage fisheries for species with different life-history profiles. Aside from the need for effective scientific monitoring, the biggest ongoing challenges remain having politicians, governments, fisheries industry members, and other stakeholders commit to scientifically recommended long-term conservation measures.
Maria Cristina Fossi and Cristina Panti
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Environmental Science. Please check back later for the full article.
In the past, the use of large marine vertebrates in marine ecosystem monitoring and assessment has been criticized. The fact that these species are pelagic and highly mobile has led some to suggest that they are not useful indicator species. However, in recent years a contrary view has emerged suggesting that when we gain sufficient understanding of differences in species distribution and behavior, at different times of the year, they can be extremely valuable sentinels of environmental quality. Among large vertebrates, top predators play a crucial role in maintaining the structure and function of pelagic marine ecosystems. Among top predator species, 90% have been lost from the world’s oceans. Pelagic ecosystems may undergo collapse when large marine vertebrates are lost. It is crucial to know the status of large vertebrate populations and to establish mitigation measures for their conservation. For example, it is well known that the various cetacean species exhibit different home ranges and occupy different habitats. This knowledge can be exploited in hot-spot areas, such as the Mediterranean basin, where different species could serve as sentinels of marine environmental quality at different times during the annual cycle. In this contest, the bottlenose dolphin, a coastal species, could be an indicator of various anthropogenic pressures on the coastal environment. Similarly, the striped dolphin, the most abundant odontocete in the Mediterranean region, is distributed in deeper offshore waters and could be a sentinel of the pelagic environment. Finally, due to its broad-ranging seasonal movements across the whole basin, the fin whale could represent an integrated indicator of the whole Mediterranean area.
In this case, it seems that there is usually a particular large marine vertebrate species that provides the best opportunity for detecting and monitoring specific types of pollutants in particular marine areas at different times of the year. For example, swordfish and tuna are valuable for monitoring mercury concentrations and organochlorines, while turtles are especially useful for monitoring the occurrence of plastics, and mysticete cetaceans for looking at microplastics. It also emerged that large pelagic fish may be especially useful for monitoring short- to medium-term changes in pelagic ecosystems, while marine mammals such as whales provided a more integrated view over the long-term.