Climate forcing on marine ecosystems
Climate forcing on marine ecosystems
Abstract and Keywords
This chapter discusses the role of climate variability and change and their effects on the marine environment. As the frequency of physical forcing increases, the biological changes progress from local effects on individuals at synoptic weather scales, towards regional effects on population dynamics at monthly to decadal scales, and over and across basins on systems ecology at multidecadal timescales and longer. The nature of the impact is size‐ and age‐dependent with generally greater and more rapid impacts on the smaller and younger individuals. The use of large‐scale climate indices to link climate forcing with ecological responses is highlighted as are the insights gained through comparative studies between ecosystems or between fish populations that inhabit different hydrographic regimes.
One of the main aims of the Global Ocean Ecosystem Dynamics (GLOBEC) programme was to increase understanding of how the structure and functioning of the global ocean ecosystem and its major subsystems respond to physical forcing. Long before GLOBEC began in the 1990s, it was well understood that physical forcing strongly affects marine ecological processes. The American fisheries biologist, Spencer Fullerton Baird, recognized the importance of the environment in generating fluctuations in fish stocks as early as the 1870s (Lehodey et al. 2006). The expected links between the environment and fish stocks played a significant role in the strong emphasis on hydrographic data collection by the International Council for the Exploration of the Seas (ICES) from its inception at the beginning of the twentieth century. Around this same time a systematic search began for relations between physical conditions and different aspects of fish stocks (Helland-Hansen and Nansen 1909). A significant warming period in the North Atlantic during the 1920s and 1930s had demonstrated effects on the distribution and production of several important commercial fish species, as well as on other components of the marine ecosystem ( Jensen 1939; ICES 1949; Cushing and Dickson 1976; Cushing 1982). By the mid-1900s, the mechanisms through which the physical environment affects primary production had been elegantly elaborated by Sverdrup (1953). New sampling methods began to reveal the extent of the ocean's variability in the 1960s and 1970s, and it became increasingly clear that physical variability and its influence on marine ecology occurred over a multitude of spatial and temporal scales. In spite of this progress, by the 1990s when GLOBEC was established, understanding of the role of physical forcing on marine ecology still remained incomplete and in particular the mechanisms linking the environment with ecological responses were often not well understood. Thus, GLOBEC began to tackle these issues in order to provide better advice on marine resource management issues (e.g. see Barange et al., Chapter 9, this volume), and as a way to increase our capability to improve projections of what future marine ecosystems may look like, especially under human-induced global change (see Ito et al., Chapter 10, this volume).
In the present chapter, we focus on the roles of climate variability and climate change on the ecological components of marine ecosystems, especially at large spatial scales, that is, regional and larger. We begin by defining climate, climate variability, and climate change. This is followed by descriptions of some of the large-scale climate indices and their connection to regional climate variability as well as a discussion of teleconnections across large spatial scales. After introducing the role of the oceans in the climate system, we describe the patterns and effects of climate forcing on marine ecosystems. We then provide several examples of the responses of marine ecosystems to climate variability and climate change from GLOBEC-generated studies. Further descriptions of the processes linking physical forcing to ecological responses are discussed by deYoung et al. (Chapter 5, this volume) and Moloney et al. (Chapter 7, this volume).
2.2 Climate forcing, climate variability, and climate change
Climate is defined by the American Meteorological Society (Glossary of meteorology, http://amsglossary. (p.12) allenpress.com/glossary/) as the slowly varying aspects of the atmosphere-hydrosphere-land system and is characterized statistically in terms of long-term averages and variability of climate elements such as temperature, precipitation, winds, etc. The period over which the ‘average’ is determined is typically 30 years, as recommended by the World Meteorological Organization (WMO). Climate variability is the temporal variation around this average state and is associated with time scales of months to millennia and beyond, that is, longer than those associated with synoptic weather events. Natural climate variability refers to climate variations due to such factors as changes in solar radiation, volcanic eruptions, or internal dynamics within the climate system, and pertains to any influence that is not attributable to, or influenced by, activities related to humans. Human effects on climate, such as those due to greenhouse gas emissions or land use, are termed anthropogenic influences. Climate change, on the other hand, is any systematic change in the long-term statistics of climate elements from one state to another and where the new state is sustained over several decades or longer (AMS Glossary of Meteorology). The new state might be due to changes in the mean level, the characteristic variability, or both. Climate change arises from both natural and anthropogenic causes. The United Nations Framework Convention on Climate Change (UNFCCC) has restricted its definition of climate change to causes arising directly or indirectly from human activity only, while it regards climate variability as changes attributable to natural causes. In recent years this definition has been often adopted by the media, in policy documents, and in some scientific literature. Climate change in this sense has also been used interchangeably with global warming. Finally, the term regime shift has also been used in the oceanographic literature in relation to changes in climate and marine ecology. While several different definitions have been proposed (see discussion by Overland et al. 2008), from the climate perspective it typically refers to a rapid shift from one climatic state, or ‘regime’, to another. Regime shifts, as defined, cover climate change as well as situations when the duration of the climatic state following the shift is too short (typically decadal to quasi-decadal) to be designated as a climate change. Ecosystem regime shifts, also called abrupt ecosystem shifts (Beaugrand et al. 2008), usually refer to large time and space shifts in abundances of major components of marine biological communities (Bakun 2005; Moloney et al., Chapter 7, this volume).
Examples of climate change include shifts between Ice Ages and the warmer interglacial periods. In historic times, it includes multicentenial changes in the northern Hemisphere from warm periods such as during the ‘Medieval Warm Period’ (890–1170 AD) to colder periods such as the ‘Little Ice Age’ (1580–1850 AD) (Osborn and Briffa 2006). On multidecadal scales, the shift in the North Atlantic from the generally warm period of the 1930s to the 1960s to the colder period in the 1970s and 1980s and a return to warm conditions in the 1990s has been labelled the Atlantic Multidecadal Oscillation or AMO (Kerr 2000). The AMO fits within the definition of climate change as it is multidecadal but perhaps fits better as an example of longer-term climate variability. Other examples of climate variability include the strong decadal fluctuations associated with changes in the atmospheric pressure systems such as the North Atlantic Oscillation (NAO; see Box 2.1) and the 2 to 3-year variability of El Niño-Southern Oscillation (ENSO) events in the equatorial Pacific. Examples of regime shifts include the changes in both climate and ecology in the North Pacific that occurred in the late 1970s (Francis et al. 1998; Hare and Mantua 2000) and in the north-east Atlantic, especially the North Sea, in the late 1980s (Reid et al. 2001a,b).
2.3 Large-scale climate variability patterns
By the early 1990s, at the onset of GLOBEC, researchers studying the responses of marine ecology to physical environmental forcing began to consider the large-scale climate variability (Forchhammer and Post 2004), typically expressed in terms of changes in climate indices related to atmospheric pressure patterns, such as the ENSO, NAO, or the North Pacific Index (NPI). The NPI is the area-weighted sea-level pressure over the region 30°N–65°N, 160°E–140°W. Other climate indices, such as the Pacific Decadal Oscillation (PDO) or the (p.13) AMO, were developed based on the intensity of sea temperature patterns. Further descriptions of several of these indices are provided in Box 2.1. While the observed climate-induced changes in marine ecosystems are indeed responses to local conditions, large-scale indices often account for significant portions of this local or regional variability. This is because the local climate changes are often a response to the large-scale processes, and also because large-scale indices are related to several physical elements (e.g. air and ocean temperatures, sea ice, winds, etc.) and as such they can be more representative of the climate forcing than any single local variable (Stenseth et al. 2003). Also, local indices can vary significantly while large-scale indices are smoother, with less noise. Thus, in some cases large-scale indices can account for as much, or at times more, of the variance of ecosystem elements than local indices (e.g. Drinkwater et al. 2003). Using large-scale climate indices potentially allows linking climate-induced ecological dynamics over a range of trophic levels, species, and geographic locations. Some examples of the ecological impacts of the variability in these indices are provided in Section 2.7.
Linkages between climate indices, weather events, or climate patterns at far distant locations are called teleconnections. Such teleconnections can be within ocean basins or between oceans. For example, Müller et al. (2008) found that at decadal to 20-year time scales, the NAO in the North Atlantic tends to be out of phase with ENSO in the equatorial Pacific and with the PDO in the North Pacific. Better known, through ENSO forcing, are the associations between heavy rains along the west coast of South America and droughts in Indonesia (McPhaden et al. 2006), or, in the Atlantic Ocean, between years of reduced ice in the Barents Sea and heavy ice off Labrador due to NAO variability (Deser et al. 2000). Because the ecological literature often puts emphasis on climate and ecosystem (p.14) (p.15) (p.16) teleconnections, we will discuss this in greater detail with a focus on northern Hemisphere atmospheric teleconnections.
2.3.1 Atmospheric teleconnections
The concept of atmospheric teleconnections and their influences on marine ecosystems has been explored by a number of authors inside the GLOBEC programme (e.g. Bakun 1996; Alheit and Bakun 2010; Overland et al. 2010; Schwing et al. 2010. Overland et al. 2010 noted that stationary atmospheric waves are formed in winter in the northern Hemisphere due to continent-ocean heating contrasts and the influences of large mountain ranges such as the Rockies and Himalayas. These waves generate regions of atmospheric low and high pressure which are linked, often with opposite conditions, over large spatial scales. The most prominent (p.17) teleconnections over the northern Hemisphere are the NAO and the Pacific-North America (PNA) pattern (Barnston and Livezey 1987; also see Box 2.1). Analyses of northern Hemisphere pressure patterns indicate that the NAO, PNA, and similar large-scale climate patterns represent about one-half of the climate variability signal in the northern Hemisphere, the remainder being ‘climate noise’ (Overland et al. 2010). Although atmospheric teleconnections between ocean basins have been investigated (e.g. Honda et al. 2005), no consistent covariability between ocean basins is apparent when the full records for the twentieth century are considered (Overland et al. 2010). Evidence for atmospheric teleconnections within ocean basins is more convincing, in particular for marine populations across the North and South Pacific Ocean (e.g. Alheit and Bakun 2010; Schwing et al. 2010).
2.4 The role of ocean forcing on climate variability
The oceans play a key role in regulating the climate due in large part to their immense capacity to store heat compared to the atmosphere. Not only is the heat stored in the ocean, it is redistributed through transport by ocean currents and by heat exchanges with the atmosphere. The amount of heat in the upper ocean influences evaporation and precipitation patterns. How these are distributed geographically affects the distribution of atmospheric pressure systems, storm tracks and the development of severe weather such as hurricanes and cyclones, and can alter the timing and intensity of monsoons, droughts, and floods. The tropical oceans and their complex ocean-atmosphere interactions play a significant role in the global climate system. Variations in both the NAO (Liu and Alexander 2007) and the PDO (Lau 1997) have been linked to sea surface temperature (SST) variability in the tropical oceans. The oceans contribute to the formation, distribution, and melting of sea ice in polar and subpolar regions, and are subsequently affected by the climatic conditions they help to create.
The oceans are also an important storage medium for greenhouse gases such as CO2. At the surface of the ocean these gases are in equilibrium with the atmosphere. Some of this CO2 is transformed into dissolved carbon and transferred to the deep ocean through vertical mixing and circulation processes. Marine phytoplankton, which account for approximately half of the world's photosynthesis, also contribute to the removal of CO2 because a proportion of the production is transferred to the deep ocean, whether by sinking detritus or faecal pellets, or via food webs. This is called the ‘biological pump’. In this respect the oceans play a vital role in slowing down the build-up of CO2 in the atmosphere, and hence the rate of anthropogenic-induced climate change (Fasham 2003).
2.5 Patterns of climate forcing on marine ecosystems
Individual organisms, populations, and communities in marine ecosystems fluctuate in response to a multitude of physical processes, variations in the dynamics internal to the population, and interactions with predator, prey, and competitive species (Harris et al., Chapter 6; Moloney et al., Chapter 7, both this volume). This multitude of forcing and pathways can often make it difficult to establish unequivocal connections between climate and ecological responses. It is thus important to understand the main patterns in how physics affects the biology, but in particular we need to know more about the actual mechanisms and processes involved.
A population may react immediately to a climate signal or it may have a delayed (lagged) response. The atmosphere tends to have a ‘short memory’ of external forcing, although because it responds quickly, the effects also dissipate quickly. The ocean tends to have a ‘long memory’ of external forcing, because it responds slowly but the effects persist. Ecosystem responses to atmospheric and ocean forcing tend to have features of both short and long memory: forcing effects are short at lower trophic levels which reproduce and turnover quickly, whereas they persist longer at higher trophic levels with slower turnover rates (Ottersen et al. 2010). The longer memory of higher trophic levels to climate forcing make them more predictable for management purposes when the climate signal can also be predicted (e.g. Perry et al. 2010).
Ottersen et al. (2010) identify four major classes of the effect of climate processes on marine ecosystems: (p.18) direct effects, indirect effects, integrated effects, and translations. Direct effects involve a direct ecological response to climate forcing with no or little time lag. The effect of climate on metabolic rates via temperature (e.g. Pörtner and Knust 2007) is one example. Indirect effects involve several physical or biological intermediate steps between climate forcing and the ecological trait. An example is the alternation in the abundance of two copepod species Calanus finmarchicus and Calanus helgolandicus in the North Sea due to changes in SST and phytoplankton production caused by variations of the NAO (Fromentin and Planque 1996). Indirect climate-induced effects can also occur through changes in bottom-up food web forcing from primary or secondary production or through top-down effects caused by changes in upper trophic levels and cascading food-web effects. Intensive fishing can also produce top-down effects (e.g. Frank et al. 2005, 2006).
Integrated effects of climate involve ecological responses that occur during and after an extreme climate event (Ottersen et al. 2010). Examples are provided by the gradual replacement of water masses in an area, and by the effects of climate warming causing spatial relocation of species distributions (e.g. Perry et al. 2005; Mueter and Litzow 2008). In contrast, translations involve movements of organisms from one place to another as for example, the advection of C. finmarchicus from the continental slope onto the continental shelf (e.g. Heath et al. 1999a).
Ecological responses to climate forcing may be linear or non-linear (Ottersen et al. 2004). The former occurs when the variability in the climate is reflected in the flora or fauna being investigated, either positively or negatively, and can be with or without time delays between the environment change and the response. Non-linear responses include dome-shaped relationships where the impact is at a maximum at some intermediate value. The dome-shaped relationship between pelagic fish recruitment and upwelling intensity (Cury and Roy 1989) or between Atlantic cod (Gadus morhua) growth and temperature (Björnsson et al. 2001) are two examples. Non-linear responses include regime shifts where climate events trigger major changes in ecological states (e.g. Francis et al. 1998; Reid et al. 2001a,b). Beaugrand et al. (2008) showed that marine ecosystems are not equally sensitive to climate change and revealed a critical thermal boundary where a small increase in temperature triggers abrupt ecosystem shifts seen across multiple trophic levels ranging from phytoplankton to zooplankton to fish. Another case of non-linear responses is when an ecological threshold is passed, for example, the temperature at which the symbiotic algae in corals will leave, resulting in coral ‘bleaching’ and ultimately coral death (Hoegh-Guldberg 1999). Coral destruction can lead to declines in reef community biodiversity as well as the abundance of a significant number of the individual species (Jones et al. 2004). Because physical forcing is often not the only factor acting on marine ecosystems, the strength of environment-ecological associations may vary over time, that is, they are non-stationary (e.g. Ottersen et al. 2006).
The response of a particular species to climate variability and change depends in part upon their life history strategies. For example, small pelagic fishes such as sardine (Sardinops spp.), anchovy (Engraulis spp.), and herring (Clupea spp.), among others, can respond dramatically and quickly to changes in ocean climate (Alheit and Niquen 2004). Most have short, plankton-based food chains, they tend to be short-lived (3–7 years), highly fecund, and some spawn all year round. These life history characteristics make them highly sensitive to environmental forcing and extremely variable in their abundance (Barange et al. 2009). Several orders of magnitude changes in abundance over a few decades are characteristic for small pelagics, especially in the upwelling regions, such as sardines in the California Current, off Japan and in the Benguela Current and anchovies in the Humboldt Current (see Section 2.6.2). Although not in upwelling regions, the abundance of herring in European waters also undergoes such variability (Alheit and Hagen 1997; Toresen and Østveldt 2000). In contrast, demersal (living close to the sea bed) species such as cod (Gadus spp.), haddock (Melanogrammus spp.) and redfish (Sebastes spp.), etc. tend to be relatively long-lived (up to 15 to 20 years and beyond) and feed mainly on forage fish or other fish or invertebrate species. Before abundance changes can be perceived for demersal and other long-lived fish species, their populations usually need to be repeatedly affected by physical forcing (biological inertia) or similar environmental conditions need to persist over many years (physical (p.19) inertia) (Ottersen et al. 2004). In instances where fishing has reduced the mean size and age of a fish stock through removals of many of the older age groups, such stocks become more responsive to climate variability (Pauly 2003; Ottersen et al. 2006; Section 2.8).
The nature of the ecological response is also dependent on the frequency of physical forcing (Sundby and Nakken 2008). On very short time scales of hours to days (weather, not climate), the forcing tends to be on small geographic scales and acts on individuals or groups of individuals. Examples include changes in the feeding rates of fish due to variable turbulence levels (Rothschild and Osborn 1988; Lough and Mountain 1996) or through temperature-dependent swimming speeds (Pörtner 2002a; Peck et al. 2006). Under rare circumstances mortality can occur if the temperature or oxygen levels that fish are exposed to rapidly cross a potentially lethal threshold (Marsh et al. 1999; Hoag 2003; Lilly 2003). At interannual time scales, physical forcing operates on wider (regional) geographic scales and tends to be linked to processes in population ecology. These include phenomena such as individual growth rates (e.g. Brander 1994, 1995), recruitment (e.g. Baumann et al. 2006), transport of eggs and larvae (e.g. Lough et al. 1994; Hermann et al. 1996a; Vikebø et al. 2005), and spatial distributions of plankton and fish (e.g. Ottersen et al. 1998; Platt et al. 2003). On the decadal to multidecadal timescale, the physical forcing can be multi-regional and even basin- or global-scale and, as such, responses tend to be related to systems ecology. These responses include large changes in abundance (Lluch-Belda et al. 1997; Alheit and Hagen 2001), selection of spawning areas (Sundby and Nakken 2008), changes in spawning or feeding migrations (Vilhjálmsson 1997b), or large-scale distributional shifts (Drinkwater 2006). These can also lead to changes in the life history of fish stocks, species interactions, trophic transfer, and evolutionary ecosystem processes. Thus, shifts from individuals to populations to systems generally tend to occur with decreasing frequency of physical forcing.
2.6 Effects of climate on marine ecosystem processes
Drinkwater et al. (2010a) provide examples of ecosystem impacts in response to climate variability and the possible mechanisms by which the response is generated. It must be remembered, however, that each of these individual processes usually act in concert with several others to produce the observed response on marine ecosystems.
2.6.1 Sea temperature
Sea temperature is the variable that has received the most attention from researchers in terms of its effect upon marine ecosystems and its dependency on climate. While this may simply be because it is easily measured and often available, it can also be argued that temperature is the climate-influenced variable that is most dominant in terms of its influence on marine ecosystem processes. The following are some of the temperature-dependent responses.
Successful individual growth often occurs within a limited thermal range that can differ between developmental stages and even populations of the same species (Pörtner et al. 2001, 2005). One of the hypotheses explaining the out-of-phase stock oscillations at multidecadal time scales for anchovy and sardine species in the California, Humboldt, Kuroshio and Benguela Current systems (Lluch-Belda et al. 1989; Chavez et al. 2003) is based on differential thermal ranges for the two species (Moloney et al., Chapter 7, this volume). The physiological background of these patterns requires answering why animals specialize on and perform in limited thermal ranges. Laboratory studies have focused on thermal adaptation and limitation at genetic, molecular, and stress levels, but have largely neglected organism performance. However, the concept of oxygen- and capacity-limited thermal tolerance as a unifying principle has been proposed as an integrative physiological concept linking climate to ecosystem characteristics and to ecosystem change under the influence of climate variability (Pörtner 2001, 2002b).
For widely distributed species, those inhabiting colder waters tend to exhibit slower individual growth than those in warmer waters. This conforms to the latitudinal compensation hypothesis that predicts local evolution should maximize metabolic efficiency and thus favour maximum growth under (p.20) local thermal conditions (Levinton 1983). Faster growth results in reduced susceptibility to predation due to shorter durations during early development stages. Growth variations can lead to a greater than a 100-fold difference in survival probabilities during larval stages (Houde 1987). As such, even slight changes in temperature can induce growth variations that have the potential to result in dramatic fluctuations in recruitment success through cumulative effects of changes in stage durations and predation pressure.
184.108.40.206 Swimming speed and activity rates
Another impact of temperature is on performance through swimming speed and activity rate (Fuiman et al. 2005, 2006) and subject to modification through temperature-dependent evolution (Pörtner 2002a,b). Swimming speed affects both feeding success and anti-predator behaviour through changes in encounter rates with prey and predators, respectively. Temperature has two primary effects on swimming speed. First, it influences the viscosity of the water with increased viscosity at lower temperatures, which in turn increases the drag on the organism. Thus, higher energy expenditure is generally required to move through colder water with the overall effect of slowing the individual's swimming speed. This effect is principally on small organisms such as fish larvae and zooplankton (e.g. Müller et al. 2000, 2008). A second effect of temperature, primarily on adult fish, is related to the delivery of oxygen. Oxygen consumption rate and the organism's scope for activity tend to have temperature-dependent optima that are not only species specific but can vary between stocks of the same species (Lee et al. 2003).
Reproduction of marine organisms is also affected by temperature. Egg production rate has been found to be temperature-dependent for several zooplankton species in both the Pacific and Atlantic (Runge 1984, 1985a; Hirche et al. 1997) principally due to effects on the spawning interval of the zooplankton (Hirche et al. 1997). Temperature affects gonadal development of several fish species resulting in spawning times generally occurring earlier under warmer-than-normal conditions (Hutchings and Myers 1994). The age-of-maturity in different stocks of Atlantic cod varies with temperature (Drinkwater 2000), and is believed to be caused by faster growth rates for those cod stocks inhabiting warmer waters. Egg size of Atlantic cod, Gadus morhua (Miller et al. 1995), and Atlantic mackerel, Scomber scombrus (Ware 1977), have been found to vary with temperature. It has been hypothesized that this is to match the size of the larvae to their prey at the time of hatching, the latter also being temperature-dependent (Ware 1977). Rapid changes in temperature also have been observed in the field to trigger spawning in some invertebrate species, such as the scallop, Placopecten magellanicus (Bonardelli et al. 1996).
Temperature and light are the most important physical factors affecting phenology in the marine environment, with the responses being species-dependent. For example, recent observed temperature increases have resulted in earlier phytoplankton blooms in the Oyashio region (Chiba et al. 2008). In the North Sea, dinoflagellates have advanced their seasonal peak by nearly 1 month under increasing temperatures, while diatoms have shown no consistent pattern of change (Edwards and Richardson 2004). The latter is because their reproduction is triggered principally by light intensity that has not changed. Copepod responses in the North Sea have been more variable, but some species have had their seasonal maximum earlier in the year (Edwards and Richardson 2004). In the north-east Pacific, recent warming has caused the life cycle timing of the zooplankton species Neocalanus plumchrus to be earlier by several weeks (Mackas et al. 2007).
Earlier seasonal warming also leads to earlier migratory movements, for example, for Atlantic mackerel, Scomber scombrus (Sette 1950), and American shad, Alosa sapidissima (Leggett and Whitney 1972), off the east coast of North America; squid, Loligo forbesi (Sims et al. 2001), and flounder, Platichthys flesus (Sims et al. 2004), in the English Channel; and pink salmon, Oncorhynchus gorbuscha, in Alaska (Taylor 2008). In principle, such shifts in timing of migration may be understood as an earlier/later entry of ambient temperature into species-specific thermal ranges.
(p.21) 220.127.116.11 Distribution
The most convincing evidence of the effects of climate change on marine ecosystems comes from distributional shifts of marine organisms. They generally are most evident near the northern or southern boundaries of the species' geographic range with warming usually causing poleward movement and cooling an equatorward movement. Examples abound of northward distributional shifts in response to increasing temperatures, for example, C. finmarchicus and C. helgolandicus in the north-east Atlantic (Beaugrand et al. 2002c; Box 2.2); several zooplankton species in the north-east Pacific (Mackas et al. 2007); Atlantic cod off West Greenland, (p.22) Iceland, and in the Barents Sea (Drinkwater 2006); capelin off the east coast of Canada (Frank et al. 1996), Iceland (Sæmundsson 1934), and the Barents Sea (Vilhjálmsson 1997b); and numerous fish species during recent warming in the North Sea (Perry et al. 2005), along the continental shelf from the Iberian Peninsula to west of Scotland (Brander et al. 2003a) and in the Bering Sea (Mueter and Litzow 2008). The spawning location of Atlantic cod off Norway has been found to vary in concert with the long-term temperature changes such that the cod tend to favour more northern spawning during warm conditions and more southern spawning under cold conditions (Sundby and Nakken 2008). The spawning areas of squid (Todarodes pacificus) off Japan expand in the Sea of Japan and East China Sea during warm periods and retract to the East China Sea during cold years (Sakurai et al. 2000; Box 2.3). Temperature changes can have a strong, especially negative, effect on species whose distribution is tied to specific geographic features (Pershing et al. 2004) such as fish species that spawn on a few fixed submarine banks (Mann and Lazier 1996), seals whose breeding grounds are geographically limited, and the nesting grounds of marine birds (Graybill and Hodder 1985).
The reasons fish change their distribution is often unclear. Adult fish may actively move to seek their preferred thermal range, to follow their prey or to avoid their predators. Larval survival may improve in more northern areas with atmospherically induced temperature increases, but temperature (p.23) (p.24) changes may also be associated with modification in circulation patterns, which in turn may carry larvae into areas that they previously had not occupied.
One of the consequences of distributional shifts of individual species is the possibility of changes in the composition of ecosystem assemblages, as observed in the fish community around Britain (Attrill and Power 2002; Genner et al. 2004) and in the intertidal regions off California (Helmuth et al. 2006). These changes can occur due to differential rates of movement of various species in response to ocean climate conditions (Mueter and Litzow 2008), through invasion of new species (Stachowicz et al. 2002), or when some species disappear either due to the new temperatures exceeding the species thermal tolerance, a reduction of their prey, or an increase in their predators or competitors. These changes in community structure can also result in changes in ecosystem function, that is, who is feeding on whom.
Recruitment levels of several species of fish vary with temperature during their first years of life (Drinkwater and Myers 1987; Ellertsen et al. 1989; Ottersen and Stenseth 2001; Pörtner et al. 2001; Sirabella et al. 2001). The response to temperature can vary between stocks of the same species. For example, Atlantic cod that inhabit the coldest water within this species' temperature range tend to show increasing recruitment with increasing temperatures, whereas those inhabiting the warmest waters show decreasing recruitment with increasing temperatures (Ottersen 1996; Planque and Frédou 1999; Pörtner et al. 2001; Sirabella et al. 2001). However, (p.25) temperature is often a necessary but not sufficient condition for good recruitment due to the influence of other factors.
Temperature has an indirect effect on mortality, for example through its influence on growth rate and larval stage duration (Houde 1987; Cury and Pauly 2000; also see Section 2.1.1). However, on rare occasions, rapid temperature increases or decreases can cause direct mortality. Colton (1959) observed mortality of large numbers of cod larvae off Georges Bank due to thermal shock caused by transport of the larvae off the bank into much warmer offshore waters. Marsh et al. (1999) reported on the tilefish kill of 1882 along the continental slope off Georges Bank when millions of fish were found dead, floating on the surface, but showed no signs of long-term stress or disease. Their conclusion was that a rapid decrease in temperature led to the mass mortality of this bottom dwelling species. In Smith Sound in Newfoundland, Canada, adult Atlantic cod died in large numbers following the advection of extremely cold (−1.7°C) water into this overwintering region (Lilly 2003). Approximately 5% of the estimated cod at that time in Smith Sound died. Examination of the fish that survived showed they were supercooled (i.e. their tissues were at a temperature below their freezing point), while those that died were frozen, likely due to contact with ice crystals (Lilly 2003).
Coral reefs provide habitat for a highly diverse ecosystem and short-term extreme water temperature can cause the symbiotic algae in corals to leave, resulting in coral ‘bleaching’ that may result in coral death (Hoegh-Guldberg 1999). For example, the elevation of temperature by 1–2°C above the climatological maximum for a period of weeks may trigger bleaching. When bleached corals do not recover, algae may grow over the corals, resulting in a shift to an algal-dominated ecosystem.
2.6.2 Vertical stratification and mixed-layer depth
The intensity of the vertical density stratification and the depth of the mixed layer have important implications for the marine ecosystem, especially primary production. Primary production depends on the amount of solar radiation and the availability of nutrients, both of which can vary with the intensity of upper layer stratification and the mixed-layer depth. Strong stratification tends to favour a pelagic-dominated system, where energy is recycled within the upper layers, while weaker stratification favours (p.26) a more demersal or benthic-dominated system, especially on the continental shelves (Frank et al. 1990). Arguably, the most dramatic ecosystem effects of changes in stratification and mixed-layer depth occurs during El Niño events. These events result in a deepening of the thermocline and an intensification of the stratification between the surface and subsurface layers, as well as rapid warming of the waters off western South America. As a consequence of the increase in stratification, there is much less upwelling of nutrients. The directly driven biological responses include a decrease in the local primary production, collapses of a variety of small planktonic herbivore and low-trophic-level carnivore populations, and dramatic declines of the normally dominant Peruvian anchoveta population (Overland et al. 2010). Once an El Niño event has subsided, conditions begin to return to normal, although sequences of transient responses of varying duration can carry effects forward into ensuing years (Overland et al. 2010). Such a process of transient responses to frequent El Niño events may represent a continuous ‘resetting’ of the Peru system by recurring El Niño episodes before internal non-linear feedback responses can arise, possibly switching the system into a different state (Overland et al. 2010). On the opposite side of the tropical Pacific during an El Niño, the thermocline shallows resulting in a vertical extension of the mid-depth temperature habitats of yellowfin and bigeye tuna, changes that are favourable for the tuna fisheries (Lehodey 2004; see Box 2.4). During La Niña (opposite phase to an El Niño), the reverse patterns prevail on both sides of the Pacific. These ENSO patterns also seriously impact the ecosystem in the northern portion of the North Pacific subtropical gyre. There, a La Niña tends to result in an increase in vertical stratification during winter leading to a drop in nutrients and subsequently plankton productivity (Polovina et al. 2008; Ottersen et al. 2010).
(p.28) 2.6.3 Sea ice
In polar regions, changes in air and ocean temperatures produce variability in the seasonal abundance of sea ice, which in turn impacts their ecosystems. The timing of the ice retreat and its associated melt water affects the timing intensity, speciation, and fate of the spring bloom (Hunt et al. 2002; also see detailed discussion in Section 2.7.1). For example, sea-ice algae can produce intense blooms before zooplankton have developed, resulting in much of the production sinking out of the pelagic zone onto the ocean floor for use by the benthos (Carroll and Carroll 2003; Grebmeier et al. 2004). Along the Antarctic Peninsula, cold years tend to result in a krill-dominated ecosystem, benefiting from overwintering under the abundant sea ice. In contrast, warm years with limited sea ice result in fewer krill and a salp-dominated ecosystem (Atkinson et al. 2004). Sea ice also provides necessary habitat for many species of marine mammals, including several species of seals for breeding and protection of their young, walrus for resting areas, and polar bears for hunting and resting. Significant reductions in sea ice-coverage can pose hardships on these animals (Loeng et al. 2005).
Turbulence increases the contact rate between plankton predators and prey (Rothschild and Osborn 1988), which in turn can increase their feeding rates (MacKenzie and Leggett 1991; Sundby et al. 1994; Saiz and Kiørboe 1995). At the same time, small-scale turbulence can change the behaviour of copepods between ‘slow’ and ‘fast’ swimming speeds (Costello et al. 1990; Margalef 1997). A parabolic relationship between feeding efficiency and turbulence exists with the shape and threshold limits dependent upon the species, their stage, and also the region (Cury and Roy 1989). Higher turbulence levels can also cause an increase in total metabolism (Alcaraz et al. 1994) and wind-induced turbulence and high temperatures during winter can reinforce the energetic imbalance of copepods and potentially decrease fecundity.
Dispersion of fish eggs and larvae from their spawning ground is considered a key aspect of recruitment success in several fish stocks as currents may carry them into or away from favourable nursery areas. Numerical models are well suited for the study of transport of fish larvae, for example, for gadoids on Georges Bank (Werner et al. 1993), in the North Sea (Gallego et al. 1999), in the Baltic (Voss et al. 1999; Hinrichsen et al. 2003), and in the Barents Sea (Vikebø et al. 2005) and for flatfish in the Bering Sea (Wilderbuer et al. 2002). These studies indicate that recruitment success has a (p.29) strong dependency on wind-dependent drift. Advection through entrainment by Gulf Stream rings also has been shown statistically to lead to reduced recruitment levels of several groundfish stocks off the eastern United States and Canada (Myers and Drinkwater 1989). This is believed to be due to increased mortality of the larvae in the offshore waters through insufficient food quantity or quality or increased predation pressures (Drinkwater et al. 2000).
Zooplankton are also advected, leading to important ecological consequences. On the Faroe Plateau the transport of adequate numbers of C. finmarchicus onto the Faroese Shelf regions is required to ensure high recruitment of Atlantic cod (Hansen et al. 1994; Steingrund and Gaard 2005). The zooplankton overwinter in the deep waters of the Norwegian Sea Basin, rise in the spring and are then carried by the flows through the Faroes-Shetland Channel and the Faroe Bank Channel before reaching the vicinity of the Faroe Plateau (Gaard 1996). Similarly, advection of C. finmarchicus from the Norwegian Sea into the Barents Sea by the Atlantic water inflow impacts ecological production of phytoplankton and fish in that region (Skjoldal et al. 1987; Sakshaug 1997; Sundby 2000; Ottersen and Stenseth 2001). The strength of the Atlantic inflow is related to both local and the large-scale wind patterns.
Modification in circulation patterns can produce significant shifts in water mass distributions, which in turn can influence ecosystem dynamics. For example, the abundance of C. finmarchicus off northern Iceland has been linked to interchanges in the distribution of polar, Arctic, and Atlantic water masses. Higher C. finmarchicus abundance is generally associated with increased presence of higher nutrient Atlantic waters. The connection may be either through increased levels of associated primary production brought about from the increase in nutrient concentrations, direct transport of C. finmarchicus with the Atlantic water mass, or a combination of these (Ástthórsson and Gislason 1995).
Benthos also has been observed to undergo distributional changes in response to water mass shifts. Increased Atlantic water flow during the warm period of the 1920s to the 1960s resulted in the northward extension of its associated benthic fauna and flora by 500 km along western Spitzbergen (Blacker 1957) and eastward into the Barents Sea (Nesis 1960; Cushing 1982).
2.7 Comparative studies of climate forcing on marine ecosystems
Previous sections have demonstrated the diverse and multiple impacts of climate on marine ecosystem processes. In this section we provide further examples, with an emphasis on insights gained using the comparative approach applied by GLOBEC.
2.7.1 Subarctic ecosystems
The subarctic ecosystems of the Bering (Alaska) and Barents (Norway) Seas are strongly impacted by climate, but there are significant differences in how they respond to climate forcing (Mueter et al. 2009), including different responses to sea-ice variability and possibly to differences in food web structures (e.g. Ciannelli et al. 2004).
Sea ice is a crucial aspect of the physical environment of the continental shelves in both the Bering and Barents Seas. The Bering Sea is typically ice-free from June through to the autumn when cold arctic winds cool the water and ice begins to form, first in the north and western shelves and later in the east (Pavlov and Pavlov 1996). Throughout winter, prevailing winds advect the ice southward into warmer water where it melts, cooling and freshening the seawater (Pease 1980; Niebauer et al. 1999). The date of the retreat of the sea ice, as well as the timing of the last major winter storms, determine the timing of spring primary production (Sambroto et al. 1986; Stabeno et al. 1998, 2001; Eslinger and Iverson 2001) and the ambient water temperatures in which grazers of the bloom must forage. In a typical light-ice year, the ice retreat occurs prior to mid-March, at which time there is insufficient light within the water column to support net primary production (Fig. 2.1; Hunt et al. 2002). The spring bloom is delayed until May or June, after winter winds have ceased and thermal stratification stabilizes the water column (Stabeno et al. 1998, 2001; Eslinger and Iverson 2001). In a heavy-ice year, melting is usually delayed until April or May and the ice-associated bloom occurs immediately after ice melt and hence earlier than in light-ice years. Although wind (p.30)
The late bloom under warm conditions leads to increased abundance of small neritic zooplankton (copepod) species while the early ice-associated bloom favours the larger shelf copepod species, Calanus marshallae (Baier and Napp 2003). The timing and ice-association of the bloom also influences the fate of carbon between the pelagic and benthic components (Walsh and McRoy 1986; Alexander et al. 1996; Mueter et al. 2007). Under an early bloom, there is less zooplankton to crop the phytoplankton production and thus a significant portion of this production falls to the bottom of the ocean resulting in more food for the benthos (Fig. 2.1). On the other hand, if the bloom is late the primary production is mainly consumed by the zooplankton community and less makes it to the bottom. This hypothesis is supported by the inverse relationship between survival anomalies of walleye pollock (Theragra chalcogramma) whose young feed on zooplankton, and of yellowfin sole (Limanda aspera) that feed on the benthos (Mueter et al. 2007). In light-ice years with late blooms, more production remains in the upper layers, the populations of small copepod species increase and early stages of pollock thrive, while in heavy-ice years with earlier blooms, more of the production makes its way to the benthos and there are more yellowfin sole. However, in the very warm years with little ice, the large copepod, C. marshallae, (p.31) has reduced recruitment, as is apparently also true for the shelf euphausiid, Thysanoessa raschii (Coyle et al. 2008; Hunt et al. 2008; Moss et al. 2009). Under these circumstances, in summer middle shelf populations of pollock of all ages lack zooplankton prey, and cannibalism of smaller pollock is increased. Thus an initial bottom-up limitation results in a subsequent top-down limitation of pollock recruitment. Survival of age-0 pollock is further limited in warm years because they invest more energy in growth than in storage, and therefore enter winter with very low energy supplies, leading to overwinter mortality (Moss et al. 2009).
In the Barents Sea, which lies approximately 15° of latitude farther north than the Bering Sea, approximately 40% is ice covered on an annual basis but with extensive seasonal variability (Loeng 1979; Vinje and Kvambekk 1991). Minimum ice coverage occurs in August/September but by the end of October new ice begins to form, eventually leading to peak coverage in March or April, although in some years not until early June. Approximately 60% of the sea is covered at the time of maximum extent, mainly in the northern and eastern regions. The interannual variability of ice coverage in the Barents Sea generally reflects local temperature conditions. In contrast to the Bering Sea, phytoplankton blooms in the northern Barents Sea tend to coincide with the disappearance of the ice, resulting in a northward progressing spring bloom, typically during June and July (Rey and Loeng 1985; Wassmann et al. 1999). The differences between ecosystems will likely depend on the relative timings of the increase in solar radiation, decline in wind strength (i.e. the number and intensity of the storms), and melting of sea ice. However, similar to the Bering Sea in cold years, a significant portion of the phytoplankton bloom in the seasonally ice-covered Arctic waters settles to the seabed (Sakshaug and Skjodal 1989; Sakshaug 1997). During extremely cold winters in the Barents Sea there is often a more southern distribution of ice than usual. If it extends far enough south to reach the warm Atlantic waters, it will melt and the resultant stratification will tend to initiate an earlier-than-usual phytoplankton bloom in these areas (Rey et al. 1987). As in the Bering, early blooms usually result in lower secondary production.
Another difference between the two seas is that in eastern shelf of the Bering Sea, most zooplankton are recruited from local populations, whereas in the Barents Sea advection plays an important role in the abundance of zooplankton. In the northern Barents Sea, the dominant copepods are Arctic species, which are advected in Arctic water masses, whereas in the southern Barents Sea, the advection of zooplankton, mainly C. finmarchicus, in Atlantic water plays an important role in their productivity, and ultimately the abundance of higher trophic levels (Skjoldal et al. 1992; Sundby 2000; Wassmann et al. 2006).
The Barents Sea ecosystem also differs from that of the eastern Bering Sea in that the upper trophic levels in the former appear to be strongly influenced by downward cascading trophic effects, that is, as defined by alternating patterns of abundance across more than one trophic level. Herring and cod prey upon capelin (Hjermann et al. 2004), and capelin heavily impact their zooplankton prey (Hassel et al. 1991). Since the mid-1960s, there have been alternations between periods when herring abundance was high and capelin abundance was low and vice versa. When capelin stocks were low, large zooplankton such as krill and amphipods increased to up to 10 times their former abundance owing to a release of predation pressure (Skjoldal and Rey 1989; Dalpadado and Skjoldal 1996; Mueter et al. 2009).
2.7.2 Upwelling regions
Small pelagic fishes (sardine and anchovy) in many of the large-scale upwelling regions of the world are one of the most remarkable examples of marine populations showing low frequency environmentally-driven multidecadal biomass variations. Kawasaki (1983) first noticed that catch time series of the world's largest populations of sardine, Sardinops sagax, from the Pacific (north-east, south-east, and north-west) Ocean showed large synchronous fluctuations. The Scientific Committee on Oceanic Research (SCOR) Working Group (WG) 98 investigating ‘Worldwide Large-Scale Fluctuations of Sardine and Anchovy Populations’ adopted the term ‘Regime Problem’ to describe an alternative to the hypotheses that the variability in fish stocks was (p.32) caused either by the fisheries or by recruitment-induced variability. WG98 documented that some small pelagic fish populations grow for a period of 20 to 30 years and then collapse for similar periods until practically disappearing. Further, low sardine abundance regimes have often been marked by dramatic increases in anchovy populations (Fig. 2.2), and similar but opposite phase fluctuations were apparent in the Benguela system in the Atlantic Ocean (high anchovy abundance during sardine periods in the Pacific, and vice versa), suggesting a worldwide, rather than a basin-scale phenomena (Lluch-Belda et al. 1989, 1992).
A permanent concern in fisheries science is the use of catch as a stand-in for biomass, and no catch-independent biomass reconstructions exist for all upwelling systems over the same periods. Some independent evidence suggests that large multidecadal fluctuations, and the alternation between
The underlying mechanisms of these alternating large-scale fluctuations remain a mystery, but several hypotheses have been proposed including ecological mechanisms, direct physical forcing, and recently some integrative frameworks. Ecological mechanisms include both top-down (predatory outbreaks) and bottom-up (primary productivity) trophic controls, sudden reductions in predation pressure resulting from environmental shifts that allow rapid increases of small pelagics (environmental ‘loopholes’; Bakun and Broad 2003), competition between species (Matsuda et al. 1992), and the ‘school-mix feedback’ hypothesis to explain alternation between species and cycling though the schooling behaviour (Bakun 2001; see Moloney et al., Chapter 7, this volume). While some of these mechanisms might be operating, they are extremely hard to test, and accounting for longer than interannual variability and synchrony between regions is problematic.
The first physical variable to be related to the observed fluctuations in small pelagics was temperature (Lluch-Belda et al. 1989), and detailed thermal habitat analyses were carried out for some of the systems and periods (e.g. Lluch-Belda et al. (p.33) 1991; Hardman-Mountford et al. 2003). Takasuka et al. (2007) proposed that the dominant mechanism of fish regime shifts may be through direct temperature impacts on survival during early life stages. They documented that in the western North Pacific the temperature optimum range for sardine is colder and wider than that of anchovy, the opposite to what happens in the eastern North Pacific (Lluch-Belda et al. 1991).
Habitat expansion and contraction have been related to abundance fluctuations. For many years it was thought that when the Japanese sardine population increase, they expand offshore, whereas when they decrease, they are confined to a more coastal distribution (Kawasaki 1983; Watanabe et al. 1996). In contrast, in California and the other eastern boundary systems, sardine population growth coincides with latitudinal expansion poleward, and declines with area contraction equatorwards (Lluch-Belda et al. 1992). This notion was re-examined by Logerwell and Smith (2001) who postulated two principal spawning habitats in the California Current: inshore and offshore, the former resulting in continuing moderate sized cohorts, and the latter associated with oceanic eddies and fronts, allowing sporadic occurrence of large size cohorts. Recently, Barange et al. (2009) demonstrated that anchovy and sardine in the Benguela, California, Humbodt, and Kuroshio regions have a positive relationship between stock abundance and distributional area, but suggested that habitat availability may not be a prerequisite for sardine growth in some areas, while anchovy may require habitat to become available for its population to grow.
Ocean dynamics and large-scale circulation patterns have also been suggested as influencing the sardine populations. Lluch-Cota et al. (1997) proposed a hypothetical mechanism where shifts in large-scale ocean circulation and global average temperature conditions would drive low-frequency small pelagic regimes, with strong ENSO events as the possible trigger to shift from one regime to another. Support for this idea was provided by Parrish et al. (2000) who found relationships between the mid-latitude wind stresses and the major climate variations in the North Pacific and to the decadal variations in several fisheries, including sardines and anchovies.
Optimistically, we should see significant progress in the next few years in understanding the low-frequency fluctuations in sardine and anchovy populations and their synchronous behaviour based on available databases, modelling capabilities, and several interdisciplinary analysis and integration efforts presently underway.
2.7.3 Atlantic cod
The above examples have compared ecosystem responses to climate variability between similar types of ecosystems. However, important insights have also been gained within GLOBEC by comparing the response of a particular species within different oceanographic conditions. One of the primary species that has been studied is Atlantic cod (Gadus morhua), which inhabits the continental shelves of the North Atlantic, including those off the north-eastern United States, Canada, West Greenland, Iceland, in the Barents Sea and south to the North Sea, the Irish Sea, and the Celtic Sea. One of the best studied of all of the world's fish species, evidence abounds that climate strongly influences cod abundance.
Fish recruitment is the number of young that survive through to the fishery and is typically measured for cod at age 1 to 3. The recruitment response as a function of temperature shows that some cod stocks exhibit increasing recruitment while others show decreasing recruitment or no relationship. By comparing the different cod stocks it was found that the temperature-recruitment relationship depended upon the mean bottom temperature the cod occupied. Increasing recruitment with increasing temperatures occurred for cold water stocks (mean annual bottom temperatures of approximately 0–5°C), decreasing recruitment for warm-water stocks (>8°C), and no relationship at intermediate temperatures (Ottersen 1996; Planque and Fredou 1999; Drinkwater 2005).
At multidecadal time scales, as expressed by the Atlantic Meridional Circulation (AMO; see Box 2.1), temperature has clear influences on the distribution, abundance and growth of Atlantic cod. For example, as temperatures warmed during the 1920s and 1930s, cod along West Greenland extended their distribution approximately 1,200 km northwards and (p.34)
During the warm phase of the AMO (1930s–1960s) recruitment in the northern range of the cod's distribution (Barents Sea, Icelandic waters, and off West Greenland) was the highest on record (Drinkwater 2006). Also, since the growth of cod is temperature-dependent (Fig. 2.3), growth rates of individual cod increased throughout these northern regions during the warm period. For example, the weight of spawning cod off Norway increased, on average, by over 50% between the early 1900s and the 1950s (Drinkwater 2006). The successful recruitment and improved growth were linked not only to the warm temperatures but also to accompanying increases in phytoplankton and zooplankton production (Drinkwater 2006).
At decadal time scales, several cod stocks respond to the variability in the NAO. Ottersen and Stenseth (2001) demonstrated a positive association between the NAO and Barents Sea cod recruitment that accounted for 53% of the recruitment variability. The mechanistic link was thought to be through effects on regional sea temperatures and food availability. With a higher NAO index there is increased Atlantic inflow, which transports warmer waters and more C. finmarchicus into the Barents Sea and hence more food for cod. On the other hand, the year-class strength of cod in the much warmer North and Irish Seas is negatively related to the NAO index, which is believed to result from a limitation in energy resources necessary to achieve higher metabolic rates during NAO-induced warm years (Planque and Fox 1998). Brander and Mohn (2004) found that the NAO has a significant positive effect on cod recruitment in the North, Baltic, and Irish Seas, and a negative effect at Iceland. Later, Brander (2005) showed that the effects on these four stocks plus the Baltic and west of Scotland stocks were significant only when the stock biomass is low. Growth rates also vary with the NAO. For example, the variability in the growth rate of northern cod off Labrador and Newfoundland is negatively associated with the NAO (Drinkwater 2002). The NAO accounted for 66% of the variance in the weight gain between ages 3 to 5 of the northern cod over the years 1980 to 1995 and is believed to be related through NAO influences on temperature and food, similar to the case in the Barents Sea.
2.7.4 Pacific salmon
Pacific salmon have also received attention from GLOBEC, with comparisons made between the dynamics of different salmon species and their response to climate forcing. Salmon spawn in freshwater, where they stay for up to 3 years, before moving into the marine environment. They remain in the ocean for 1 to 5 years depending on the species, during which time they mature sexually. They then return to their natal river to spawn and all Pacific species die immediately after spawning. Catches of salmon species in Alaskan waters (principally pink, Onchorhynchus gorbuscha, and sockeye, O. nerka) vary synchronously but inversely with stocks along the west coast of the United States, most notably chinook, O. tshawytscha, and coho, O. kisutch (Mantua et al. 1997). Salmon production is linked to variability in the PDO, with higher production in Alaska during the positive phase of the PDO (Mantua et al. 1997), when SSTs along the periphery of the north-east Pacific are relatively warm. Greater salmon production along the west coast of the United States coincides with the (p.35)
Gargett (1997) suggested the fishery responses in the late 1970s climate regime shift were due to bottom-up forcing by changes in nutrient availability that led to increased biological productivity at multiple trophic levels. Adjustments between the atmosphere and upper ocean due to heat exchange and wind-driven ocean currents contributed to the anomalously warm SSTs extending from the Bering Sea and Gulf of Alaska along the North American coast (Parrish et al. 2000). While basin-scale climate (p.36) variations set the conditions for the decadal regime shifts, the ecosystem responded to local and regional perturbations in the environment. Adjustments in ocean mixing and basin circulation resulted in a 20–30% shallower mixed layer in the subarctic North Pacific after the 1970s, contributing to greater water column stability. This enhanced primary production and doubled the zooplankton biomass in the Gulf of Alaska (Brodeur and Ware 1992). The coincident deepening and strengthening of the thermocline and nutricline in the California Current (Palacios et al. 2004), reduced the availability of nutrients to the euphotic zone and led to a sharp decline in local zooplankton biomass (Roemmich and McGowan 1995). This contributed to the decline in salmon along the west coast of the United States. Peterson and Schwing (2003) suggested that this west coast salmon production shifted back to higher levels after 1997, coincident with a return to the negative PDO phase and higher ecosystem productivity in the California Current. This lasted up until 2002, after which conditions in the California Current have undergone year-to-year variability with no consistent periods of good or bad years for west coast salmon.
2.8 Influence of fishing on the responses of exploited ecosystems to climate forcing
Recently, investigators have recognized that we must understand and take account of the interactions between climate and fishing, rather than try to disentangle their effects and address each separately. Planque et al. (2010) and Perry et al. (2010a) reviewed how exploitation can modify the ability of marine populations, communities, and ecosystems to respond to climate forcing. They noted that fishing removes individuals with specific characteristics from the gene pool, and leads to a loss of older age classes, spatial contraction, loss of subunits, and changes in life history traits in populations. All of these make marine populations more sensitive to climate variability at interannual to interdecadal scales. Fishing also reduces the mean size of individuals and mean trophic level of fish communities, which decreases their turnover time leading them to track environmental variability more closely. They noted that marine ecosystems under intense exploitation also evolve towards stronger bottom-up control and greater sensitivity to climate forcing. Overall, they concluded that a less-heavily fished marine system, and one which shifts the focus from individual species to functional groups and fish communities, would be likely to provide more stable catches with climate variability and change than would a heavily fished system.
The examples presented in this chapter demonstrate that marine ecology responds to climate variability and climate change over a myriad of time and space scales. It is important to note that these examples represent only a small fraction of the work done by GLOBEC on climate forcing on marine ecosystems and that further examples are provided in later chapters (see deYoung et al., Chapter 5; Harris et al., Chapter 6; Hofmann et al., Chapter 11, this volume). GLOBEC science has also helped to show that, as the frequency of the physical forcing increases, there is a tendency for the nature of ecological changes to progress from local effects on individuals at synoptic weather scales, towards regional effects on population dynamics at monthly to decadal scales, and over basins and even across basins on systems ecology at multidecadal time scales and longer. The responses can be direct and immediate, or through predator-prey relationships and include delays between the physical forcing and the observed response. The nature of the impact is, in part, size- and age-dependent with generally greater and more rapid impacts on the smaller and younger individuals. The ecological effects can be on all trophic levels and include changes in production, recruitment, growth, abundance, distribution, catchability, and occasionally even mortality.
When GLOBEC began, the use of large-scale climate indices to link climate forcing with ecological responses was just beginning in earnest and GLOBEC researchers made major advances in documenting such relationships and improving our understanding of geographic extent of their impacts. In the North Pacific they identified the decadal scale climate variability and established the PDO index. They also championed the notion of regime shifts (p.37) (p.38) applied to both climate and ecology. This concept was useful in helping to understand the large changes in the abundance of small pelagics in upwelling systems as well as the ecological changes in the North Pacific, especially during the late 1970s (Moloney et al., Chapter 7, this volume). It was later applied to physically induced ecological changes in the North Atlantic. GLOBEC science also improved our insights into the teleconnections between climate indices through studies of the low-frequency abundance changes of sardine and anchovy populations in upwelling regions located on both sides of the Pacific, and between those in the Pacific and those in the Atlantic off Africa. More details on the timing and nature of the shifts between anchovy and sardines in these same upwelling regions and their possible mechanisms have also been gathered within GLOBEC (see Checkley et al. 2009). The role of the NAO in forcing both physical and biological variability in the North Atlantic has been led to a large degree by GLOBEC scientists. NAO variability results in spatially dependent changes in the temperature, circulation, convection, and sea ice which in turn leads to changes in zooplankton production, as well as growth and recruitment of several commercial important fish species. Studies on Georges Bank in the Gulf of Maine have shown the importance of large-scale processes operating through the NAO on the Bank's ecology. Hence, to understand the biological variability requires a broad geographic perspective. In more recent years, there has been increasing realization of the importance of the AMO in producing significant broad-scale and long-reaching ecological consequences in the North Atlantic. On shorter time scales, GLOBEC researchers have demonstrated the importance of ENSO in the equatorial regions of the Pacific on tuna abundance, distribution, and catchability by the fishing fleets.
Other important research on climate effects has been carried out by GLOBEC researchers. In the Antarctic, they have documented ecological changes in response to recent warming, including those on krill and penguins (Box 2.5). They have also revealed the importance of the physical environment on the productivity and its variability in the Antarctic waters. In the subarctic regions, the role of sea ice and its variability on the timing and subsequent fate of plankton production in driving either pelagic or benthic food webs have been elucidated. Here (p.39) too the ecological responses to recent warming have been well documented. The role of climate variability on cod dynamics has been one of the major foci within GLOBEC in the North Atlantic. In addition to the links with climate through the NAO mentioned above, this science has shown how the physical environment that cod stocks inhabit can help explain differences in growth rates, recruitment, and overall productivity.
The initial work linking the climate and ecological responses was largely done through retrospective analyses using correlation and regression methods, and while these still represent a substantial effort, new non-linear statistical approaches have been developed and used, and modelling has played an ever increasing role through the GLOBEC years (see deYoung et al., Chapter 5, this volume). It is also important to note the importance of long-term datasets in establishing linkages between the physical forcing and the biology described in this chapter. To continue to document and understand the process linking the biology to the physical forcing, it is imperative that in the future such data series be maintained and, in several regions, expanded.
While this chapter has mainly focused on the climate influences on marine ecology, it is important to recognize that there are other forces acting along with climate. These include the internal dynamics of the biological components of the ecosystem due to internally generated trophic interactions and competition. Also, humans are a major contributor to changes in the marine ecosystems, primarily through fishing but also through their influence on pollution levels, the introduction of invasive species, effects on the acidification of the oceans, UV, etc. (e.g. Brander et al., Chapter 3, this volume). It is often difficult to assign observed changes in any ecosystem to a particular cause because of the multiple forcing.
In the following chapters, further examples of the impacts of climate on the marine ecology of the world's oceans will be given, the multiple processes through which climate acts discussed, and the effects of and on humans explored. (p.40)