Climate Change and Marine Communities John F. Bruno 1 , Christopher D. G. Harley 2 , and Michael T. Burrows 3 1 Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3300 USA 2 Department of Zoology and Biodiversity Research Centre, University of British Columbia, 6270 University Blvd, Vancouver, British Columbia, V6T1Z4, Canada 3 Department of Ecology, Scottish Association for Marine Science, Scottish Marine Institute, Oban, Argyll, PA37 1QA, Scotland, UK Note to reviewers: We could use feedback on; whether to add a glossary, the figures (what to add, cut, etc.), and if we should add a section on future warming, acidification, etc, i.e., projections. The dilemma is that the new IPCC projections (in ARV) will not be out until the summertime and we’d rather not use the existing projections (from ARIV), which were developed in 2005 and are somewhat outdated. We may also add a box on “how to detect climate change effects” discussing the role of theory, lab experiments, and time series data. Abstract The main effects of greenhouse gas emissions are on and in the oceans. Most of the additional heat being absorbed by the earth due to increased radiative forcing is being realized as ocean warming. Additionally, rapidly increasing atmospheric carbon dioxide is reducing the pH of seawater. Other changes include increased wind, and wave size, reduced oxygen concentration, both enhanced and reduced coastal upwelling, sea ice loss, and sea level rise. Ocean warming and acidification are probably the two impacts of greenhouse gas emissions that will most profoundly alter marine ecosystems. Both affect many processes, from enzyme kinetics, to cell signaling, to individual fitness and population Page 1 of 45 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37
Transcript
Climate Change and Marine Communities
John F. Bruno1, Christopher D. G. Harley2, and Michael T. Burrows3
1Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3300 USA
2Department of Zoology and Biodiversity Research Centre, University of British Columbia, 6270 University Blvd, Vancouver, British Columbia, V6T1Z4, Canada
3Department of Ecology, Scottish Association for Marine Science, Scottish Marine Institute, Oban, Argyll, PA37 1QA, Scotland, UK
Note to reviewers: We could use feedback on; whether to add a glossary, the figures (what to add, cut, etc.), and if we should add a section on future warming, acidification, etc, i.e., projections. The dilemma is that the new IPCC projections (in ARV) will not be out until the summertime and we’d rather not use the existing projections (from ARIV), which were developed in 2005 and are somewhat outdated. We may also add a box on “how to detect climate change effects” discussing the role of theory, lab experiments, and time series data.
Abstract The main effects of greenhouse gas emissions are on and in the oceans. Most of the additional heat being absorbed by the earth due to increased radiative forcing is being realized as ocean warming. Additionally, rapidly increasing atmospheric carbon dioxide is reducing the pH of seawater. Other changes include increased wind, and wave size, reduced oxygen concentration, both enhanced and reduced coastal upwelling, sea ice loss, and sea level rise. Ocean warming and acidification are probably the two impacts of greenhouse gas emissions that will most profoundly alter marine ecosystems. Both affect many processes, from enzyme kinetics, to cell signaling, to individual fitness and population growth rates all the way up to food web dynamics and ecosystem processes. In response to climate change, species are shifting temporally and geographically to maintain a constant thermal environment, resulting in earlier phenological timing and ranges moving towards higher latitudes. To survive, species that do not range shift must either acclimatize or adapt. Climate change will increase the rapid loss of ecosystem services from the oceans, causing socio-economic stress to coastal societies. In many systems over-harvesting, pollution, and habitat loss are currently probably more important in terms of driving population declines and ecosystem transformation, but not for long. Climate change will dominate marine ecology for the next several decades and probably for the rest of the century. Despite great progress in the budding field of marine climate change ecology, there are large knowledge gaps and ample opportunity (and challenge) for new generations of ocean scientists.
Page 1 of 30
123456789
1011121314151617181920212223
24252627282930313233343536373839404142
PrefaceOne of the big shifts in the field of marine ecology since the publication of Marine Community Ecology (Bertness et al., 2001) is a fuller appreciation of the extent to which greenhouse gas emissions will affect ocean ecosystems. Few chapters of the initial volume even mentioned ocean warming or acidification and there was no chapter on climate change.
For this chapter, we tried to provide a broad, high-altitude overview of anthropogenic climate change on ocean ecosystems. We begin with a description of the physical and chemical changes to the oceans being caused by greenhouse gas emissions. We then review the effects this is having on individuals, populations, and communities. We cover responses of populations and species to changing environmental conditions including range shifts toward higher latitudes, acclimatization, and adaptation. We end with a discussion of ocean-based solutions to climate change – some promising, others not – of the impacts of climate change on marine ecosystem services, and with some areas for future research.
What is climate change?The greenhouse effect is caused by gases that heat the atmosphere by trapping infrared radiation that would otherwise escape into space. Roughly half of the solar radiation that reaches the atmosphere is reflected back to space or absorbed, by clouds, gases, and particles like soot pollution. The other half reaches the earth’s surface and is used in photosynthesis, melts ice and evaporates water, and warms the land and lower atmosphere. This heating emits infrared radiation that is absorbed by greenhouse gas molecules, which in turn reemit that energy as heat. This further warms the land and atmosphere and the cycle continues.
Although the greenhouse effect is essential to life on earth (without it the surface temperature would be roughly -18º C), human activities are exacerbating this natural process by increasing the concentration of greenhouse gases in the atmosphere. The two primary gases causing anthropogenic climate change are carbon dioxide and methane. Other natural and anthropogenic greenhouse gases include water vapor, nitrous oxide, ozone, and chlorofluoracarbons (CFCs).
Carbon dioxide is a less potent greenhouse gas than methane (on a per molecule basis), but the concentration of the former is more than 200 times greater (as of December 2012, the concentration of carbon dioxide was 392 ppm, compared to 1.8 ppm for methane). Because increased carbon dioxide concentration accounts for nearly two thirds of anthropogenic warming, it is considered the most important greenhouse gas in terms of emissions mitigation (and catastrophe avoidance). Most activities of people in modern industrial societies lead to global warming. Nearly everything we do causes the conversion of organic carbon stored in fossil fuels and the biosphere into carbon dioxide that is released to the atmosphere, however, primary drivers include transportation, electricity generation, and deforestation.
Atmospheric carbon dioxide concentration increased by 1.9 ppm per year between 2000 and 2008 (Le Quéré et al., 2012). This rate increased in each of the last four decades, e.g., up from 1.5 ppm per year during the 1990s. The more recent increased emissions rate is primarily due to economic growth in China and other developing nations and a shift towards coal for power generation. Carbon dioxide concentration is expected to double relative to the preindustrial baseline of 278 ppm during the latter half of the 21st century and possibly as soon as 2050 (IPCC 2007). The resulting global average land surface warming (called the equilibrium climate
sensitivity) is “likely to be in the range of 2 to 4.5°C with a best estimate of about 3°C” (quote from IPCC AR4, also see Hansen and Sato 2012, Knutti and Hegerl, 2008). The uncertainty around climate sensitivity is due to potential feedbacks, some of which are not well understood. For example, warming can lead to changes in the color of the earth’s surface or albedo, e.g., a change from ice to soil or water, reducing the reflectance of solar energy, and thereby increasing warming.
Physical effects of climate change on the oceans
Ocean warming
Sunlight naturally warms the upper layers of the ocean. When the earth’s energy budget is in equilibrium, this heat is eventually returned to the atmosphere though thermal convection (because the atmosphere is generally cooler than the ocean surface, termed the cool skin layer). But an energy imbalance leads to the oceans either gaining or loosing heat. Because it is in contact with the atmosphere, the cool skin layer is also warmed by the supercharged greenhouse effect. This reduces the thermal gradient between the cool skin layer and layers just beneath it, which in turn reduces the dissipation of heat from the ocean to the atmosphere. Over time, this causes the oceans to warm. In fact, approximately 84% of the excess heat being retained via climate change is going into the oceans (Levitus, 2005), which makes you wonder why it isn’t called ocean change.
Ocean warming is occurring at all depths (Fig. 2) and has been since at least the 1980s (Purkey and Johnson, 2010)(Levitus et al., 2012). Heat gained in surface layers is transferred to the deep ocean by vertical circulation (ref). The global average warming rate (since 1960) for the upper 700 m of the oceans is estimated to be 0.1º C / decade (Casey and Cornillon 2001, Burrows et al. 2011, IPCC 2007), while the deep ocean (700-2000 m) is warming more slowly (Purkey and
Page 3 of 30
Figure 1. Some important abiotic changes to the oceans caused by greenhouse gas emissions. Redrawn from Harley et al. 2006.
89909192939495
9697
98
99
100101102103104105106107108109110111112113114115
Johnson, 2010). However, such global averages obscure enormous variability among regions and years. For example, the warming in the arctic has been much greater while some small regions such as the upwelling region off the west coast of the United States has cooled somewhat (Fig. 2). The same patchiness in temperature change has been observed in the deep sea. For instance, the deep southern ocean appears to be warming relatively quickly, at about 0.03 / decade (Purkey and Johnson, 2010).
Spatiotemporal variability in the long-term trend is a fundamental characteristic of how greenhouse gas emissions are altering the physical and chemical properties of the ocean. This patchiness is apparent even at relative small (by oceanography standards) spatial scales (Fig. 3). For example, the high temperature anomalies that cause coral bleaching are typically relatively small – the average anomaly size being only ~ 50 km2 (Selig et al., 2010). This can lead to striking variability among neighboring reefs in terms of historical temperature patterns, the frequency and severity of anomalies and the biological responses to them (Berkelmans, 2002). Furthermore, these fine-grained hot spots do not appear to be stationary as once assumed. Instead they move around in space to the extent that anomalies could be negatively spatially autocorrelated, i.e., less likely to reoccur in the same place. If true, this would pose a huge challenge for coral reef management, much of which is premised on idea that warming extent is spatially constant and predictable.
Page 4 of 30
Figure 2. (left) Changes in the heat content of the land and sea as a result of greenhouse gas emissions. From Nuccitelli et al. 2012. (right) Trends in ocean (Hadley Centre data set Had1SST 1.1) temperatures for 1980–2011.
116117118119120121
122
123124125126127128129130131132133134
135
Page 5 of 30
Figure 3. Cumulative number of weeks with sea surface temperature anomalies >1º C (1985–2005) in the Indo-Pacific. From Selig et al. 2010.
136
Ocean acidification
Warming is not the only consequence of anthropogenic greenhouse gas emissions. Much of the carbon dioxide emitted into the atmosphere by human activities is subsequently absorbed by the oceans – approximately 25% of the CO2 emitted since the industrial revolution is now dissolved in seawater. This has had a major effect on the carbonate chemistry of the oceans.
Inorganic carbon in the oceans occurs in three main forms: bicarbonate ions (HCO3-1) and
carbonate ions (CO3-2), and aqueous carbon dioxide (CO2). At preindustrial atmospheric CO2
concentrations, these three forms represented approximately 88%, 11%, and 0.5%, respectively (Fabry et al. 2008). However, when additional atmospheric CO2 dissolves in the ocean, it combines with water to form carbonic acid (H2CO3), which then dissociates to become bicarbonate (HCO3
-1) and hydrogen ions (H+). Some of the liberated hydrogen ions further interact with carbonate (CO3
-2) to create more bicarbonate (Fig. 4). The remainder of the hydrogen ions remain in solution, resulting in a reduction in pH (Orr et al., 2005).
It is this reduction in pH that has led to the term “ocean acidification” to describe this phenomenon. Although the oceans are not expected to become an acid (which is defined as pH < 7), they are becoming more acidic than they were prior to the industrial revolution. In fact, the average pH of the surface ocean has fall from 8.2 in 1750 to 8.1 in 2000 (Doney et al., 2009b). Although this sounds like a small change, because pH scale is logarithmic, a 0.1 unit change in pH represents a 30% increase in acidity.
Figure 4. Ocean acidification. (left) Time series data of atmospheric CO2, ocean surface pCO2 and seawater pH (from Doney et al., 2009a). (right) The chemical process of ocean acidification.
Box 1. Other physical changes to the oceans caused by anthropogenic emissions
Increased UVB: In addition to warming and acidification, emissions are causing a variety of other physical changes to the oceans. For example, past emissions of chlorofluorocarbon compounds (CFCs) depleted the atmospheric ozone, increasing ultraviolet B radiation at the sea surface, especially in the southern hemisphere. Small increases in UVB exposure can greatly decrease the survival and marine and invertebrate larvae (Llabrés et al., 2013).
Reduced oxygen concentration: Due to temperature-dependent solubility, warmer seawater holds less oxygen. Reduced dissolved oxygen in seawater would have obvious negative consequences for many animals. Recent evidence suggests oxygen concentration has decreased in many locations and in some causes low enough to cause stress (Stramma et al., 2010). Low oxygen concentrations can also result from intensified upwelling.
Changes in coastal upwelling: The intensity and timing of coastal upwelling could be affected by climate change in a number of ways, including changes in coastal wind patterns (Bakun, 1990; Bakun et al., 2010). For example, coastal Oregon has experienced substantially stronger upwelling since 2005 (Chan et al., 2008) that has led to anoxic conditions along the continental shelf with consequences for coastal fisheries resulting from large scale crab and fish die-offs. In contrast, upwelling off Peru is predicted to weaken (Bakun et al., 2010), reducing coastal productivity and having negative effects on the globally important anchoveta fishery.
Rising sea level: Greenhouse gas emissions are causing sea level to rise via “thermal expansion” (warming water above 4C increases its volume) and by melting glaciers. Until human activities increased the concentration of greenhouse gases in the earth’s atmosphere, global sea level had been relatively stable for several thousand years (Gehrels et al., 2006). Furthermore, the rate of sea level rise appears to be accelerating, i.e., non-linear (Church et al., 2008). Just like for temperature, upwelling intensity and every other abiotic change being caused by carbon emissions, sea level rise is highly variable in space and time due both to underlying geological dynamics and ocean surface wind patterns (Nicholls and Cazenave, 2010). Sea level rise will challenge coastal ecosystems including coral reefs, salt marshes, and mangrove forests as they cope with other threats while simultaneously needing to accrete at higher rates (Nicholls and Cazenave, 2010).
Salinity: Even sea surface salinity is changing due an intensification of the global water cycle, caused by atmospheric warming (Durack et al., 2012). In the open ocean, relatively fresh areas that are dominated by precipitation are expected to become fresher, and the converse is true of relatively salty, evaporation-dominated regions. Estuarine salinity may change dramatically due to changes in precipitation and snowmelt in the watershed.
More wind, waves, and storms: Both satellite altimeter measurements (Young et al., 2011) and local tide gage data (Bromirski et al., 2003) indicate ocean surface wind and waves are increasing. Such greater storminess at higher latitudes will likely be matched by more frequent and more intense tropical cyclonic storms, driven by warming surface waters (Emanuel, 2005).
Individual-level effects of ocean warming: ecophysiology
For marine ecotherms like invertebrates and most fishes, warming means higher metabolism and growth, increased energetic demands, and a variety of other life history changes (Fig. 5). The biological influence of temperature is based on its affect on biochemical reactions. Temperature determines diffusion rates and enzyme kinematics, and thereby controls the reaction rates for enzyme-driven biological activity. Typically, warming increases the rates at which enzymes encounter and bind with substrate molecules, thereby increasing the rate of enzyme-catalyzed reactions. However, when temperatures become too high, the enzymes themselves become damaged, and reaction rates drop. The resulting thermal response curve for enzyme activity is therefore hump-shaped, with an accelerating rise from low temperatures up to some thermal optimum, and then an increasingly steep drop-off once the optimum temperature has been exceeded (Fig. 6).
Due to these fundamental biochemical constraints, maximum metabolic rate assumes a similar relationship with temperature. Resting metabolic rate – the cost of being alive – also increases with temperature, albeit more slowly. The difference between these two curves, known as the scope for work (where work can be activity, growth, and reproduction), is maximized at some intermediate temperature.
The temperature dependence of fundamental biological processes like metabolism, photosynthesis, activity, and life span are formally unified under the Metabolic Theory of Ecology (MTE, Brown et al., 2004). MTE is based on biophysical principles and has been remarkably accurate in predicting how body mass and temperature scale with biological activity. MTE can also be used to predict and understand the primary and secondary effects of natural spatial and temporal variation in temperature as well as those of anthropogenic global warming.
Page 8 of 30
Figure 5. Ecological effects of climate change. The life cycle of a generic marine species is shown in green. Warming and other abiotic changes have direct impacts (yellow boxes) on dispersal and recruitment, and on individual performance at various stages in the life cycle. Additional effects are seen at the community level (in blue). From Harley et al. (2006).
210
211
212213214215216217218219220221222223
224225226227228229230231232233234235236237
Population-level effects of ocean warming
Temperature also has less-intuitive yet generally predictable effects on several population-level processes. For example, population growth rate often follows the same unimodal response to temperature as enzyme activity and individual growth (Fig. 6). Likewise, the underlying temperature-dependence of enzyme activity strongly influences the developmental rate of marine invertebrate larvae (O’Connor et al., 2007). This in turn largely determines the Pelagic Larval Duration (known as “PLD”), which influences larval dispersal distance (all things being equal), survival and even population connectivity (Shanks, 2009). Thus, in warmer water, marine larvae tend to develop more quickly, experience a reduced PLD, and have much shorter dispersal than congeners in colder water (O’Connor et al., 2007).
Individual- and population-level effects of ocean acidification
Declining ocean pH can also affect biochemical reactions (ref), however, most biological research on acidification is focused on its affect on calcification. The reduction in carbonate availability affects organisms that use calcium carbonate to build their shell or skeleton. In numerous laboratory experiments, carbonate ion concentration has been shown to affect rates of calcification and/or skeletal growth in taxa including single-celled coccolithophores, crustose coralline algae, crustaceans, corals, molluscs, and echinoderms (Doney et al., 2009b; Hendriks et al., 2010; Kroeker et al., 2010). A common feature of this science is how remarkably variable responses to reduced pH are among species, higher order taxonomic groupings, and even among individuals. Ries et al. (2009) quantified a variety of functional responses to experimental acidification, e.g., positive, negative, linear, hump-shaped, etc., based presumably on how well different organisms are able to protect their shells and regulate local pH at the calcification surface (Ries et al., 2009). Recent meta-analyses (an analysis of a number of different analyses) have confirmed the same variable outcomes across experimental setups and with much larger pools of experimental species (Hendriks et al. 2010, Kroeker et al. 2010). Unfortunately, such variation extends to the
Page 9 of 30
Figure. 6. Relationship between temperature and various biological rates. Redrawn from Kordas et al (2011). (a) the Antarctic Mackerel Icefish Champsocephalus gunnari, (b) sockeye salmon Oncorhynchus nerka, (c) Cortez oyster Crassostrea corteziensis, (d) the marine diatom Phaeodactylum tricornutum.
238
239240241242243244245246247248
249
250
251252253254255256257258259260261262263264265266
findings and interpretation of different meta-analyses of acidification experiments, further obscuring the search for generality. Kroeker et al. (2010) analyzed the results of acidification experiments with calcified and non-calcified algae, echinoderms, corals, molluscs, and crustaceans. Although their analysis indicated that the effect sizes of experimental acidification on photosynthesis, growth, reproduction, survival, and calcification were negligible for most taxa, they nevertheless concluded; “biological effects of ocean acidification are generally large and negative, but the variation in sensitivity amongst organisms has important implications for ecosystem responses.” In contrast, Hendriks et al. (2010) performed a similar meta-analysis of the responses of 44 species (also see Hendriks and Duarte, 2010) to acidification and came to a somewhat different conclusion; “Active biological processes and small-scale temporal and spatial variability in ocean pH may render marine biota far more resistant to ocean acidification than hitherto believed.” More recently, Chan and Connelly (2013) performed a meta-analysis of the response of scleractinian corals to experimental acidification and concluded that “under business as usual conditions, declines in coral calcification by end-of-century will be ~22%... These values are near the low end of published projections, but support the emerging view that variability due to local environmental conditions and species composition is likely to be substantial.” Interestingly, the average end-of-century impact on calcification for corals calculated by Chan and Connelly (2013), is similar to the value of 25% calculated by Hendriks et al. (2010) for all taxa.
Regarding the overall state of the field, a crucial caveat is that very few acidification experiments measure affects on reproduction, susceptibility to other stressors, interactions with other stressors (i.e., in multi-factorial designs) or otherwise attempt to put the results into an ecologically meaningful context – thus we could very well be underestimating the potential impacts of ocean acidification. In fact, we know next to nothing about how or whether the documented effects of acidification scale up to population dynamics. In other words, at this point, we have no idea what the population-level significance of a 25% reduction in calcification would be (Hendriks and Duarte, 2010).
Changes in geographic ranges and phenology in response to warming
A common response of populations and species to ocean warming is to change their geographic distribution to remain within their optimal thermal environment. Despite the complexity of influences of temperature on individual organisms, it is generally true that species cannot live outside a thermal range set by their physiological tolerance to low and high temperatures. Climate change therefore puts a proportion of the global population of a species outside these tolerance limits, and brings new areas into the range of places where the species can live – essentially a change in the geographic location of the fundamental niche.
The match between the geographical ranges of organisms and their physiological tolerance limits is good in the widest sense (ref). Latitudinal variation in thermal tolerance limits reflects, but far exceeds, the seasonal range of temperatures at each latitude (Sunday et al., 2011). Very few marine species have pan-global distributions (with the possible exception of some deep sea organisms). Species found in the tropics are generally absent from the poles and vice versa. The notable exceptions are those animals that control their internal body temperatures, mostly marine mammals and birds. Some of these are capable of extreme feats of thermal tolerance during very long distance seasonal migrations. Arctic terns (Sterna paradisaea) migrate annually to, and
return from, the Antarctic from the Arctic (24,000km in 40d (Egevang et al., 2010)), while Northern and Southern right whales (Eubalaena glacialis and Eubalaena australis) move from polar feeding grounds in the summer to wintering areas near the tropics.
Figure 7. (left) Seasonal temperature ranges at different latitudes (Pacific Ocean, dark, Atlantic/Indian Oceans, light) are reflected in the thermal tolerance limits (right) of marine organisms that live at those latitudes. From Sunday et al. (2011).
Predicted changes in range and phenology
Changed species distributions have been predicted for more than a decade using “climate envelope” models (CEMs), usually derived from the statistical relationship between the abundance of a species and underlying climate variables, typically annual mean temperature. Such models make no assumptions about the processes driving the relationship between climate and distributions (Hijmans and Graham, 2006). This is both a strength and a weakness in predicting change. On the positive side, the relationships that form CEMs can represent the physiological tolerance and performance effects of temperature combined with the positive and negative interactions with other species whose distributions may also be influenced by temperature (Kiers et al., 2010) and so may provide a summary of all those additional influence. Weaknesses of CEMs include the lack of consideration of ecological processes that underpin distributions, such as dispersal from one population (acting as a source) to another (acting as a sink), and these weaknesses limit accuracy of this approach (Davis et al., 1998).
The primary use for CEMs is for making predictions for past and future change: did past change in distributions match climate change (or shorter term fluctuations), and what change might be expected in the future? They can also offer a useful check on whether present-day or past distributions ‘fit’ with the underlying climate, and, in failing to predict distributions, can highlight biogeographical barriers to spread. At best therefore, CEMs can act as null models against which observed shifts can be compared. Such models may even show up ‘faster-than-climate’ shifts that apparently defy expectations but probably have some other cause like rare long-distance dispersal events, such as the appearance of mussels in Svalbard after 500 years absence (Berge et al., 2005).
Consequences for changing patterns of biodiversity under future climate scenarios can be inferred by combining many climate envelope models at a global scale. Using such an approach for the IPCC A1B climate scenario (650ppm CO2 by 2100) Pereira et al. (2010) estimated the poleward shifts of pelagic fish as >60km/decade for much of the ocean, and typically 40km/decade for demersal (bottom-living) fish.
Better predictions for future shifts in distributions can be made by including ecological processes, primarily dispersal and colonization, alongside the basic links between abundance and climate. With the advent of global inventories of biodiversity information such as OBIS (Ocean Biodiversity Information System, http://www.iobis.org/) and ecological information about species, such as FishBase (www.fishbase.org/), more realistic models can be developed for 100s of species. For example, Cheung et al. (2009) took this approach to project range shifts for commercially exploited fishes. This approach includes assumptions about processes controlling spread and the rate of population growth. In their model the global ocean was divided into 0.5 degree grid cells (about 175000 cells). Population dynamics at single locations in the model are controlled by the intrinsic population growth rate in a cell and the immigration of fish (as larvae or adults) from surrounding areas, while the carrying capacity of the cell is determined by the suitability of the habitat – derived from the statistical association between abundance and the climate variable. In equations this is represented by the equation for change in abundance in a single cell (denoted by the i subscript)
d A i
dt=Gi+∑
j=1
N
M ji
where Gi is the population growth rate of the species in that cell, and Mij is the number of inward migrants from neighboring cells (denoted j). The growth rate depends on the species’ intrinsic growth rate r, the abundance in that cell Ai and the carrying capacity Ki set by the suitability of the cell itself.
Gi=r ∙ A i ∙(1−Ai
K i)
Other models include a more explicit consideration of physiology (Hijmans and Graham, 2006), or even models that fully implement a simulated version of the internal energetics of whole organisms linked to ecosystem models, that effectively predict the offshore shift and deepening of juvenile plaice in the southern North Sea from the 1980s to the 2010s (Teal et al., 2012). These approaches can help in making the right management decisions in the face of climate change, but generally come at a cost of loss of general applicability.
The simplest approach to predicting shifts in distribution comes from considering the shifting patterns of the climate variables themselves. All predictions of changes in distributions are driven by observed or projected changes in climate, so much can be learned from simply examining these shifts in climate in biologically relevant ways. One such measure is the velocity of climate change (Loarie et al., 2009). At any location on the globe, this is given by the ratio of the long-term trend in the climate variable to the local spatial gradient in that climate variable, with the direction also given by the direction of the local gradient. For temperature, the velocity of climate change represents the speed and direction of movement of isotherms (lines of equal temperature). Velocity of climate change is highly variable across the ocean (Fig. 8) with areas of rapid shifts (e.g. >100km/decade as in the North Sea) in areas of either or both rapid temperature change or shallow spatial gradients in temperature. Slower shifts occur where warming is slower or spatial gradients are very steep, such as at the boundaries between major ocean currents, such as the Gulf Stream and the cold Labrador current (Fig. 8). Negative shifts (i.e. towards warmer areas) happen when the long term trend in temperature is a cooling one, as in the Southern Ocean between 1960 and 2009, probably as the result of increased wind-driven mixing of the water mass. The median velocity of climate change for the ocean surface for 1960 to 2009 was 21.7km/decade, but this value does not give an appreciation of the full spread of values across the globe. Velocities were much higher than this near the Equator (>100km/decade between 5°N and 5°S), but lower in the Southern Hemisphere below 30°S.
Changing seasonal patterns of temperature will affect the timing of seasonal events, known as phenology, with warming spring temperatures arriving earlier and cooling fall temperatures coming later in the year. A similar approach as for velocity of climate gives the rate of shift in seasonal temperatures, termed seasonal climate shift, using the ratio of the long term trend in temperature for a particular month or season to the seasonal rate of change in temperature (Fig 7D).
Page 13 of 30
Figure. 8. Temperature trends (A) divided by spatial gradients (B) give the velocity of climate change for temperature (C). From Burrows et al. 2011.
Since the 1990s there have been a large number of reported changes in geographical ranges of marine organisms that have mostly been attributed to climate. A recent review by Sorte et al. (2010) calculated a mean rate of shift of 190km/decade, much higher than the median value for velocity of climate (21.7 km/decade). One reason for this difference is that the mean value is strongly influenced by a few very high values, such as the rapid poleward expansion of the snake pipefish Entelurus aequoreus (Harris et al., 2007) in the northern North Sea and Norwegian Sea at a rate equivalent to 1650km/decade, and the 1650km poleward shift of the Humboldt squid Dosidicus gigas, normally found only in Central America but present along the coast of California in 2004 at a rate equivalent to 2000 km/decade. A faster-than-expected average rate of distribution shift may also be the tendency for only positive or notable shifts to be reported in the scientific literature – so called publication bias. Species that have not shifted are not ‘news’ in the scientific sense and such lack of movement may have gone unreported.
Nonetheless, much of this variation may be associated with the ecological characteristics of the species themselves. A meta-analysis of the reported shifts in distributions by Poloczanska et al. (2013) found significant differences among taxonomic groups in the rate of range shifts (Fig. 8). Zooplankton and phytoplankton show the most rapid shifts, at 100 and 400 km/decade on average respectively. These are typically widely dispersed on ocean currents and have very short life cycles and, as such, their distributions may be expected to respond especially rapidly to climatic change.
One of the best examples of a dramatic and rapid shift in zooplankton distributions is that of calanoid copepods in the northeastern North Atlantic (Beaugrand et al., 2009). Whole groups of species shifted 1100km poleward at 280 km/decade between 1960 and 2000. For phytoplankton an even more alarming shift has been seen since 2000: the arrival of a North Pacific diatom Neodenticula seminae (Reid et al., 2007) in the North Atlantic as a likely consequence of the loss of Arctic sea ice. This may be the start of many more trans-Arctic migrants, and, though dissimilar to the many other poleward shifts, it represents a degree of connection among northern temperate waters not seen since before the last series of ice ages 2.5Mya (Vermeij, 1991; Vermeij and Roopnarine, 2008).
Figure. 9. Rates of change in (A) phenology (days dec-1) during spring (red) and summer (yellow); and (B) distribution (km dec-1) for marine taxonomic groups at the leading edges (red) and trailing edges (yellow). Average distribution shifts calculated using all data, regardless of range location, are in black. Distribution rates have been square-root transformed; standard errors may be asymmetric as a result. Negative phenological changes are consistent with warming (generally earlier) and positive distribution changes are consistent with warming (generally poleward into previously cooler waters). Means ± standard error are shown, with number of observations and significance (*, p<0.1; **, p<0.05; ***, p<0.01; binomial test). Sample sizes (n) above each taxon refer to all rates of change. From Poloczanska et al in review.
Climate-related changes in phenology in the ocean are much less well reported, mostly because of the intensity of sampling effort required to determine the timing of events, let alone the difficulty in sustaining this effort over a long enough period to detect a climate-related effect. Plankton have received such attention, however, through programs like the Continuous Plankton Recorder survey. This regular, automated sampling system has been deployed on ships of opportunity in the Northeast Atlantic since the 1930s. From 1960 to 2000 the peak abundance of many planktonic groups has shifted earlier in the year (Edwards and Richardson, 2004). Meroplankton (the temporary planktonic stages of bottom-living species), for example, have shifted earlier in spring with echinoderm larvae 47d earlier in 2002 than in 1958, or approximately 10 earlier days per decade. Dinoflagellates also showed a similar shift earlier in summer: the peak abundance of Ceratium species being 27d earlier over the same period. Shifts were less clear cut for other planktonic groups. Seabirds have also been extensively studied with timing of reproduction and migration getting much attention. For this group changes are not
Page 15 of 30
437
438439440441442443444445446
447448449450451452453454455456457458459
consistently in the direction expected, with as many showing delays in breeding as advances in areas of significant warming (Fig. 9).
Comparing predictions and empirical observations
On land, latitudinal shifts in species distributions correspond well with latitudinal shifts in average temperatures over the same period (Chen et al., 2011), even if expected shifts in elevation towards cooler temperatures were less than expected. In the ocean, the match between rates of shifting distributions and shifting climatic conditions is not as good (Poloczanska et al., 2013)(Fig. 10), although, more rapid range shifting has in fact occurred in areas where the velocity of climate is greater. Rates of geographical range shifts have been faster than expected for zooplankton and phytoplankton, suggesting that other explanations may be needed for reported range changes in these species, such as long-range dispersal events or release from some other external control on population size. The majority (68%) of shifts lagged behind the rates expected from shifting climate. Limited dispersal, failure to colonize new suitable environments, biogeographical barriers to movement, a lack of suitable habitats in the new climatic space and a failure to match the observed shifts with the most relevant aspect of climate for each taxa all contribute to this mismatch. Finally species may adapt to the new thermal regime in their existing geographical range. The lack of a shift when one may be expected can be seen as a ‘climate debt’, expressed as a distance between the expected shift and that observed (evidence from butterflies and birds in Europe (Devictor et al., 2012), and seen as an accumulated delay in species response to climate that must be repaid in the future.
Figure. 10. (A) Observed rates of shift in geographical distributions compared with rates of shifts in isotherms (from Poloczanska et al. (2013): dotted line: equality, solid line: regression. (B)
Population and species-level effects: adaptation and acclimatization
Populations and species that do not change their ranges to maintain a constant thermal envelope must acclimatize, adapt or go extinct. Measuring the potential for physiological acclimatization and adaptation via natural selection has been a major theme in marine climate change ecology over the last decade. We know that tolerances to abiotic change vary enormously among and within species (refs). The latter is often interpreted as evidence of genetic potential for population persistence despite changing environmental conditions via physiological plasticity or
genetic variation that can enable natural selection.
One of the few examples of actual selection for resistance to climate change comes from the phytoplankton Emiliania huxleyi (Lohbeck et al., 2012). Over the course of a year long experiment, populations exposed to elevated CO2 conditions grew and calcified faster than control populations. Yet those twelve months represented 500 generations for this species. It would have been surprising if it hadn’t adapted. For longer-lived species – for which 500 generations would take many centuries to many millennia – the implications are less clear. Additionally, these are the species whose life history has already made them more vulnerable to other human activities like over-harvesting and pollution.
Corals, for example clearly display among-clone and among-population variation for thermal sensitivity (refs) and are also apparently able to physiologically acclimatize to natural and experimental warming (refs). These findings, suggest some potential resistance to ocean warming, however, there are also clearly limits to this response, and it appears to be well below projected warming, even over the next several decades. Furthermore, the generation time for many coral species is on the order of decades, meaning many centuries would be required for existing genetic variation for thermal tolerance to enable meaningful natural selection to occur (Hoegh-Guldberg, 2009). Even if it occurred, such adaptive evolution would greatly compromise the ecological function of corals on reefs as populations would be dominated by very young and very small colonies, a very different population size structure from today (or more accurately yesterday). Since the stresses would continue to amplify (in the absence of emissions reductions), strong selection pressure would remain, effectively resulting in adaptively resistance coral populations and communities in a constant state of recovery from disturbance.
Despite plentiful evidence for at least the potential for adaptation and acclimatization in many groups including invertebrates, seaweeds, fishes, and phytoplankton, the key question remains: which (if any) taxa will adapt/acclimatize fast enough to keep up with abiotic conditions?
The question is unfortunately largely intractable for three reasons. First, most measures of tolerances to environmental change come from unnatural lab settings in which the stress is imposed immediately or quickly, relative to what the organism would experience in nature over months, years or decades. Experimental animals are often stressed due to collection, movement, and lab conditions and are thus more sensitive to experimental treatments. On the other hand, unlike real climate change, experimental climate change usually only consists of a single factor, such as temperature or acidity, rather than multiple factors that are changing simultaneously, which is the reality for most species (Wernberg et al., 2012).
Second, it is often hard or impossible to put individual measurements from such experiments into a population-level context. Even if a careful lab experiment demonstrates large potential for acclimatization to lowered pH, e.g., enabling an individual to minimize negative effects on calcification, what does that mean for the growth or extinction potential for a natural population? Does such acclimation have fitness costs that affect reproductive output, thermal tolerance, disease resistance or some other unmeasured parameter?
Third, even if the potential for biological change were perfectly known, the rate of warming,
acidification and other abiotic changes is not. Not due to scientific uncertainty, but instead mainly because we do not know how quickly emissions will decline (or increase). That isn’t to say there isn’t any scientific uncertainty regarding radiative forcing, but that it is dwarfed by social, political, economic and technological uncertainty.
Population and species-level effects: extinction
Countless populations and some species will fail to adapt, acclimatize or move, and will simply go extinct. How many depends largely on how quickly and by how much the oceans warm and acidify. Surprisingly few studies have attempted to model when, where, and which marine populations and species will go extinct in response to climate change. One exception is a study by Wernberg et al. (2011) based on an extensive herbarium collection of macroalgae that inhabit the coasts of western and eastern Australia. First, > 20,000 species occurrence records were used to estimate the rate of range shifts (generally southward) since the 1940s. Then, known geographic distributions, median range shifts rates, and projected warming were combined to predict the number of species that would literally disappear from the continent as their thermal envelope moved southward, and away from appropriate coastal habitat (Fig. 11).
Another potential source of information is the paleontological record on how past regional and global climate shifts affected extinction rates and which taxa were most susceptible (Vermeij, 2001). For example, a recent review of extinction in the oceans (Harnik et al., 2012) found that four of five mass extinctions of reef building corals coincided with natural (as opposed to anthropogenic) ocean warming and acidification. The fossil record can also be used to estimate the sensitivity of foundation species, and thus whole communities, to climate shifts of different magnitudes. For instance, based on a coring study of eastern Pacific reefs, Toth et al. (2012) concluded that a relatively modest natural climatic shift halted reef growth in the eastern Pacific for 2,500 years beginning nearly 4,000 years ago.
More detailed paleontological analyses are being used to estimate coral species sensitivity to ocean warming. van Woesik et al. (2012) found that extinction-prone coral species of the present are related to susceptible species from past geological eras. This finding suggests that life
Page 18 of 30
Figure 11. Predicted number of seaweed species that will be displaced beyond the Australian continent given different degrees of warming. The black line indicates the projected relative total species loss (out of 1,454 species). The shaded boxes indicate the range of current temperature projections for 2030 and 2070. From Wernberg et al. 2011.
536537538539
540
541542543544545546547548549550551
552553554555556557558559560561562563564565566
history traits such as colony morphology, calcification rate, and mode of reproduction can be used to predict extinction sensitivity (Darling et al., 2012; Harnik et al., 2012; van Woesik et al., 2012). Such trait-based approaches to extinction vulnerability assessment are being used more frequently, but are rarely validated by the fossil record. Based on their analysis, van Woesik et al. (2012) found that Pacific coral taxa Pocillopora, Stylophora and foliose Pavona (which were once common in the Caribbean but are now extinct there) are highly vulnerable to extinction, despite their broad distribution. In other words, current abundance and distribution can be poor predictors of vulnerability to climate shifts, an important counter-intuitive lesson ecologists need to consider when assessing the sensitivity of species and communities.
Community-level effects of climate change
Climate change will have innumerable effects on marine communities, food webs, and ecosystems (Kordas et al., 2011). Because the effects of changing abiotic conditions vary among species, harming some but benefitting others, climate change will mean greatly altered relative abundances. For instance, on Tatoosh Island (Washington, USA), reduced pH related to intensified upwelling, caused calcified species like mussels and coralline algae to be gradually replaced by non-calcified, fleshy seaweeds (Wootton et al. 2008).
Species range shifts will also change community composition and diversity. In many cases, at high latitudes biodiversity will increase (Vermeij, 1991), at least initially as new immigrants join existing assemblages (extinctions due to increased competition or predation could eventually mitigate gains in species richness). The redistribution of species among latitudes will result in wholesale reorganization of marine (and terrestrial) ecosystems over the next century and beyond. While similar changes may have happened in the geologically past (Vermeij and Roopnarine, 2008) our current understanding of the way oceanic ecosystems work is mostly built on our knowledge of the functioning of present-day communities of co-evolved species. For example, prey will soon be introduced to new predators against which they have no evolved defenses, such as king crabs that are invading benthic communities around Antarctica (Aronson et al., 2007; Smith et al., 2012). Climate-change-assisted predator introductions will have similar impacts as the introduction of exotic consumers like rats, cats, snakes, and fishes by other means.
Ocean warming will not only lead to new consumers, but also to hungrier ones. By increasing metabolism, warming will increase the activity and metabolic demands of predators, thereby intensifying many predator-prey interactions (Sanford, 1999; Kordas et al., 2011). In some cases, this will lead to greater prey consumption and reduced prey populations. Furthermore, metabolic rate (and therefore consumption) in animals increases more with warming than photosynthetic rate and thus primary production (O’Connor et al., 2011). So assuming temperatures do not become stressful, warming should increase per capita herbivory rates relative to primary production, leading to reduced standing stock of plant biomass (O’Connor et al., 2009). How these changes will influence production and standing biomass of higher trophic levels is unclear, especially given other simultaneous effects of warming on food webs, e.g., selection for smaller phytoplankton in pelagic systems (Moran et al. 2010).
The virulence of many pathogens is also temperature-dependent, and there are a growing number of documented examples where water temperature and disease severity are positively related (Harvell et al., 2002, 2009; Bruno et al., 2007). Acidification could also alter the playing field
for prey if it weakens their shells and makes predation less energetically costly. For example, mussels are heavily calcified and grow more slowly in acidified conditions (ref). In the northeast Pacific, mussels are preyed upon by the sea star Pisaster ochraceus, which responds positively to acidification (Gooding et al. 2009). Thus, the already negative effect of acidification on mussels will be exacerbated by the indirect effect of increased sea star predation. Conversely, kelp forests are inhabited by calcified consumers (sea urchins and gastropods), while their uncalcified prey (kelps and other seaweeds) appear to have mixed or even positive responses to experimental acidification (Harley et al. 2012). In this case, kelp forests might be expected to expand in an acidified ocean, however, recent work suggests that increased storms and warming (Byrnes et al., 2011) will likely overwhelm any benefits of reduced consumer pressure.
By producing new winners and losers, climate change will also alter the competitive landscape. For example, competitively dominant but thermally sensitive species should become more rare enabling competitively inferior but warm-tolerant species to thrive. On coral reefs, competitively dominant plating Acroporid corals are very sensitive to warming, storms, predators, and pathogens and are being replaced across the western Pacific by slower growing massive species such as Porities xxx. The classical marine example of competition in the intertidal is that between the warm-water barnacle Chthamalus montagui and the cold-water barnacle Semibalanus balanoides. In the mid shore in areas of high larval settlement in Scotland, Semibalanus is able to exclude Chthamalus (Connell, 1961), leaving the poorer competitor in a narrow band at the top of the shore that experiences drying and temperatures that the superior competitor cannot withstand. Yet Chthamalus can persist in patches of warmer rock lower on the shore, where it is released from competition with the warmth-intolerant Semibalanus (Wethey, 1984). At warmer, lower latitude shores, Chthamalus montagui is released from competition with its cold-water competitor and can extend throughout the intertidal. A cooler climate episode reversed this effect in the 1960s and 1970s with an associated increase in Semibalanus, but Chthamalus dominated in the warmer climate of the last decade. The balance between these northern and southern species has therefore followed changes in temperature in southwest England from the 1930s (Southward et al., 1995) to the present day (Mieszkowska et al., 2012).
Climate change will also alter the role of mutulisms and other forms of facilitation (Kiers et al., 2010), particularly via impacts on habitat forming species. Some entire communities will cease to exist if their foundation species fail to adapt or change their ranges. Others will (and indeed already are) be degraded by climate change as foundation species become more and more sparse. Current examples include kelp forests, intertidal mussel beds, and oyster, and coral reefs.
The degree to which foundation species modify the environment, ameliorate environmental stress, and facilitate other species is strongly dependent on individual and population characteristics like size and density (Bruno and Bertness, 2001). For example, the cover of living hard corals is positively related to the richness of fish and invertebrate inhabitants of reefs. Less live coral usually means a less heterogeneous environment and fewer places to hide from enemies. Therefore, as ocean warming and acidification thin coral populations, the negative consequences for other species that may not be as sensitive to warming as corals is still immediate (Jones et al., 2004). For example Jones et al (Fig. 11) found that in Papua New Guinea, a decline in coral cover, due large part to ocean warming led to a striking decrease in
fish population abundances and overall richness and even local extinction of some coral specialists.
Figure 12. from Jones et al. 2004. “Over 75% of reef fish species declined in abundance… 50% declined to less than half of their original numbers [and] several rare coral-specialists became locally extinct.”
Ocean solutions to climate changeIt is becoming clear that we need to reduce our emissions – immediately and radically – and develop policies and technologies to remove already-emitted greenhouse gases. One new approach is to sequester atmospheric CO2 by conserving and restoring mangroves, salt marshes, and seagrasses (Hoegh-Guldberg, 2009). Such coastal vegetation, dubbed “blue carbon” (AKA “coastal carbon”) covers a relatively small proportion of the earth but has a disproportionately large effect on the global carbon cycle (Duarte et al., 2005) because it sequesters carbon at a far greater rate (~ 50-100x) and more permanently than terrestrial forests(Laffoley and Grimsditch, 2009).
Organic carbon is stored in peat below coastal vegetation habitats as they accrete vertically. Because the sediment beneath these habitats is typically anoxic, a lower fraction of the organic carbon is broken down and released by microbes, compared to a terrestrial forest. Coastal vegetation also continues to sequester carbon for thousands of years in contrast to forest, where soils can become carbon-saturated relatively quickly. Additionally, unlike freshwater wetlands and bogs, marine wetlands release very little methane (ref).
Table 1. A comparison of carbon sequestration by coastal vegetation and terrestrial forests.
Recent loss rate and trend ~1-5% yr-1, increasing2,3,7,8 ~0.8% yr-1, stable or decreasing9
Self-expansion potential10 High / rapid11,12 LowNotes and References: 1values are averages, sequestration is defined as the burial and storage of carbon in the soil/sediment, 2Laffoley and Grimsditch 2009, 3Nellemann et al 2007 and references therein, 4Chmura et al 2003, 5Duarte et al 2005 but note more recent studies indicate average rates of 160 to 186 gC m-2 yr-1 (Duarte et al. in review), 6IPCC 2007, 7Waycott et al 2009, 8Polidoro et al 2010, 9FAO Global Forest Resources Assessment 2005, 10i.e., via unassisted clonal expansion, 11Liu et al 2007, 12Duarte unpublished
Additionally, coastal vegetation can spread rapidly via clonal propagation. This greatly magnifies the value of a conservation investment in blue carbon over time. For example, small plots of the marsh grass Spartina alterniflora introduced to the Jiangsu Province of China in 1982 expanded 1875x by 2004 and sequestered an estimated 83 million kg of organic carbon (Liu et al., 2007). Likewise, Duarte (ref) calculated that a 1m2 plot of restored seagrass could expand to 30,000 m2 and sequester at least 300 tons of carbon over 50 years.
The rate of loss of all three primary blue carbon habitats is breathtaking: salt marshes have been buried for development for centuries and in just the last several decades, we have easily lost half of the world’s mangrove forests (for charcoal and for shrimp farming and other agricultural purposes). When blue carbon habitats are destroyed we lose their sequestration function and conversely when we restore these habitats, we restore this function.
However, the far greater concern is the release of enormous quantities of carbon due to some forms of “conversion ”, i.e., from a natural state to a shrimp farm or a parking lot. For example, when the surface vegetation is removed from mangrove forests or salt marshes for development, the carbon rich soil can be aerated. This can lead to the release of carbon that has been locked up for centuries or millennia. Pendleton et al. (2012) estimated that this leads to up to one billion tons of carbon annual emissions or roughly 20% of carbon emissions from deforestation. Enhanced erosion caused by rising sea level could have a similar effect.
A less practical solution for our greenhouse gas problem is artificially boosting the biological pump. The oceans naturally remove carbon dioxide from the atmosphere via diffusion (as long as the concentration of CO2 is higher in the atmosphere) and when plankton and larger organisms die and sink to the deep sea floor (Fig. x). Combined these processes currently remove roughly a fourth of anthropogenic greenhouse gas emissions from the atmosphere (another quarter is removed by forests and other terrestrial “sinks” and nearly a half remains in the atmosphere).
Entrepreneurs and some misinformed environmentalists want to enhance the “biological pump”
by fertilizing the surface of the ocean with iron filings to spur plankton blooms. Phytoplankton populations can indeed be iron limited and experimental work indicates that iron addition can enable sharp increases in phytoplankton density. However, there are a number of problems with this approach to carbon sequestration. First, only a small fraction of phytoplankton sink and are not consumed by heterotrophs. Thus the approach is very inefficient. Aumont et al. (2006) calculated that continuous seeding of the entire oceans surface for a century would only reduced atmospheric concentration by roughly 30 ppm. Second, there would also be a variety of deleterious consequences including the production of toxic algal blooms, the damage of massive amounts of filings on deep sea benthic communities, and the costs of mining, transporting, and adding the iron.
Several other climate change “solutions” limit warming by reducing solar radiation, but do nothing to mitigate ocean acidification. The strategy is to deflect a small fraction of incoming short wave radiation by adding sulfur aerosols, salt spray or other compounds to the troposphere. There are many reasons why such untested “geoengineering” approaches are dangerous – but the biggest in our mind is that they focus only on warming and ignore the equally dangerous problem (for both the oceans and humanity) of ocean acidification since they do nothing about carbon emissions. In fact, it seems reasonable to expect they will accelerate acidification by reducing the urgency to reduce atmospheric carbon dioxide.
Climate change and services from ocean ecosystemsIt seems to us that the imminent loss of species and entire ecosystems is reason enough to reduce
Page 23 of 30
What is next?
We do have some solid examples of clear effects of ocean warming and acidification on marine
species. Yet we know little if anything about their generality and context. The field needs much
more work – many years of work – with different species in different settings to begin to sort
this out.
We know next to nothing about synergisms (and antagonisms) with other stressors.
We need far better and finer grained forecast models that are ecologically relevant. And we
really need to know what the safe concentration of CO2 for various ocean properties and
processes.
Finally, to even detect effects of climate change on populations, communities, and ecosystem
processes we need stable funding for long-term monitoring studies. We also need to do a much
global greenhouse gas emissions. Yet these changes will also lead to immense financial and social costs, as ecosystem services crucial to humanity are lost. One obvious cost is the loss of income from tourism when visitors stop coming to see a now extinct species or habitat such as a coral reef after it is degraded by bleaching and acidification (Brander et al., 2007). Losing the reef adjacent to a coastal community also means reduced buffering from waves and increased shoreline erosion (Pryzant and Bruno, 2012). Accelerating sea level rise and the destruction of coastal vegetation will further accentuate this problem.
Climate change will also directly and indirectly affect fisheries production and thus jobs, food security, fisheries related income, etc. Indirectly, climate change-related habitat loss will continue to damage fisheries. Directly, range-shifts by commercially important species will change regional and global patterns of productivity, increasing catch in some places and decreasing it in others. Based on bioclimate envelope models, catch potential could increase by 30-70% in high-latitude fisheries and decrease by as much as 40% in the tropics (Cheung et al., 2009). However, this is clearly a rough approximation. In reality, changes in fisheries productivity will be related to many biotic and abiotic trends, such as changes in surface currents, primary productivity, oxygen, and even new and unpredictable species interactions. And of course climate impacts on fish stocks and fisheries will come on top of many other pressures such as overfishing and pollution (Brander, 2010).
Conclusions We have really only scratched the surface here of all that has been discovered about the impacts of climate change on the oceans over the last decade. Twenty years ago, hardly anyone did such work and now few marine ecology labs do not in some way consider how ocean warming or acidification are affecting their study system or organism. The omnipresence of climate change has in part driven the work of many marine ecologists from basic science to a more applied realm. When we were students, few mainstream ecology labs did conservation. Now it seems preposterous to try to avoid it. That is because everything in the oceans is changing, and not only due to climate change.
The coral species that dominated the Caribbean, Acropora palmata and A. cervicornis, for thousands of years up until the early 1980s, are gone from most reefs (Aronson and Precht, 2001). Large predators and other herbivores, e.g., sharks, manatees and dugongs, sea turtles and seals, that also were also common on coral reefs – in some locations only a few decades ago – are now extinct or so depleted that they are rarely if ever seen (Jackson, 1997). Thousands of invasive species have come to dominate temperate estuaries during the same time frame (Byrnes et al., 2007). Finally, Semibalanus balanoides, a barnacle made famous (among marine ecologist) by pioneering work by Alan Southward and Joe Connell, is becoming rare in southwest England due to warming (Poloczanska et al., 2008). These and other changes will only accelerate providing both opportunity and an enormous challenge to future generations of marine ecologists. Only a decade or two from now a new volume on Marine Ecology will have to be written, describing all the changes, probably many unforeseen, that occurred since the publication of this second edition.
Literature CitedAronson, R.B., and Precht, W.F. (2001). White-band disease and the changing face of Caribbean coral reefs. Hydrobiologia 460, 25–38.
Aronson, R.B., Thatje, S., Clarke, A., Peck, L.S., Blake, D.B., Wilga, C.D., and Seibel, B.A. (2007). Climate change and invasibility of the antarctic benthos. Annual Review of Ecology, Evolution, and Systematics 38, 129–154.
Bakun, A. (1990). Global climate change and intensification of coastal ocean upwelling. Science 247, 198–201.
Bakun, A., Field, D.B., Redondo-Rodriguez, A., and Weeks, S.J. (2010). Greenhouse gas, upwelling-favorable winds, and the future of coastal ocean upwelling ecosystems. Global Change Biology 16, 1213–1228.
Beaugrand, G., Luczak, Christophe, and Edwards, Martin (2009). Rapid biogeographical plankton shifts in the North Atlantic Ocean. Global Change Biology 15, 1790–1803.
Berge, J., Johnsen, G., Nilsen, F., Gulliksen, B., and Slagstad, D. (2005). Ocean temperature oscillations enable reappearance of blue mussels Mytilus edulis in Svalbard after a 1000 year absence. Marine Ecology-Progress Series 303, 167–175.
Berkelmans, R. (2002). Time-integrated thermal bleaching thresholds of reefs and their variation on the Great Barrier Reef. Marine Ecology Progress Series 229, 73–82.
Bertness, M.D., Gaines, S.D., and Hay, M.E. (2001). Marine Community Ecology (Sinauer Associates).
Brander, K. (2010). Impacts of climate change on fisheries. Journal of Marine Systems 79, 389–402.
Brander, L.M., Van Beukering, P., and Cesar, H.S.J. (2007). The recreational value of coral reefs: A meta-analysis. Ecological Economics 63, 209–218.
Bromirski, P.D., Flick, R.E., and Cayan, D.R. (2003). Storminess variability along the California coast: 1858-2000. Journal of Climate 16, 982–993.
Brown, J.H., Gillooly, J.F., Allen, A.P., Savage, V.M., and West, G.B. (2004). Toward a metabolic theory of ecology. Ecology 85, 1771–1789.
Bruno, J.F., and Bertness, M.D. (2001). Habitat modification and facilitation in benthic marine communities. In Marine Community Ecology, (Sunderland, MA: Sinauer), pp. 201–218.
Bruno, J.F., Selig, E.R., Casey, K.S., Page, C.A., Willis, B.L., Harvell, C.D., Sweatman, H., and Melendy, A.M. (2007). Thermal stress and coral cover as drivers of coral disease outbreaks. PLoS Biology 5, e124.
Byrnes, J.E., Reed, D.C., Cardinle, B.J., Cavanaugh, K.C., Holbrook, S.J., and Schmitt, R.J. (2011). Climate-driven increases in storm frequency simplify kelp forest food webs. Global Change Biology 17, 2513–2524.
Byrnes, J.E., Reynolds, P.L., and Stachowicz, J.J. (2007). Invasions and extinctions reshape coastal marine food webs. PLoS ONE 2, e295.
Page 25 of 30
787788789
790791792
793794
795796797
798799
800801802
803804
805
806
807808
809810
811812
813814
815816817
818819820
821822
Chan, F., Barth, J.A., Lubchenco, J., Kirincich, A., Weeks, H., Peterson, W.T., and Menge, B.A. (2008). Emergence of Anoxia in the California Current Large Marine Ecosystem. Science 319, 920–920.
Chen, I.-C., Hill, J.K., Ohlemüller, R., Roy, D.B., and Thomas, C.D. (2011). Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024 –1026.
Cheung, W.W.L., Lam, V.W.Y., Sarmiento, J.L., Kearney, K., Watson, R., Zeller, D., and Pauly, D. (2009). Large-scale redistribution of maximum fisheries catch potential in the global ocean under climate change. Global Change Biology 16, 24 – 35.
Church, J.A., White, N.J., Aarup, T., Wilson, W.S., Woodworth, P.L., Domingues, C.M., Hunter, J.R., and Lambeck, K. (2008). Understanding global sea levels: past, present and future. Sustainability Science 3, 9–22.
Connell, J.H. (1961). The influence of interspecific competition and other factors on the distribution of the barnacle Chthamalus stellatus. Ecology 42, 710–723.
Darling, E.S., Alvarez-Filip, L., Oliver, T.A., McClanahan, T.R., and Côté, I.M. (2012). Evaluating life-history strategies of reef corals from species traits. Ecology Letters.
Davis, A.J., Jenkinson, L.S., Lawton, J.H., Shorrocks, B., and Wood, S. (1998). Making mistakes when predicting shifts in species range in response to global warming. Nature 391, 783–786.
Devictor, V., Van Swaay, C., Brereton, T., Chamberlain, D., Heliölä, J., Herrando, S., Julliard, R., Kuussaari, M., Lindström, \AA, Roy, D.B., et al. (2012). Differences in the climatic debts of birds and butterflies at a continental scale. Nature Climate Change 2, 121–124.
Doney, S.C., Balch, W.M., Fabry, V.J., and Feely, R.A. (2009a). Ocean acidification: a critical emerging problem for the ocean sciences.
Doney, S.C., Fabry, V.J., Feely, R.A., and Kleypas, J.A. (2009b). Ocean Acidification: The Other CO2 Problem. Annual Review of Marine Science 1, 169–192.
Duarte, C.M., Middelburg, J.J., and Caraco, N. (2005). Major role of marine vegetation on the oceanic carbon cycle. Biogeosciences 2, 1–8.
Durack, P.J., Wijffels, S.E., and Matear, R.J. (2012). Ocean Salinities Reveal Strong Global Water Cycle Intensification During 1950 to 2000. Science 336, 455–458.
Edwards, M., and Richardson, A.J. (2004). Impact of climate change on marine pelagic phenology and trophic mismatch. Nature 430, 881–884.
Egevang, C., Stenhouse, I.J., Phillips, R.A., Petersen, A., Fox, J.W., and Silk, J.R.D. (2010). Tracking of Arctic terns Sterna paradisaea reveals longest animal migration. Proceedings of the National Academy of Sciences 107, 2078–2081.
Emanuel, K. (2005). Increasing destructiveness of tropical cyclones over the past 30 years. Nature 436, 686–688.
Page 26 of 30
823824
825826
827828829
830831832
833834
835836
837838
839840841
842843
844845
846847
848849
850851
852853854
855856
Gehrels, W.R., Marshall, W.A., Gehrels, M.J., Larsen, G., Kirby, J.R., Eiriksson, J., Heinemeier, J., and Shimmield, T. (2006). Rapid sea-level rise in the North Atlantic Ocean since the first half of the nineteenth century. The Holocene 16, 949–965.
Hansen, J., and Sato, M. Paleoclimate implications for human-made climate change. In Climate Change: Inferences from Paleoclimate and Regional Aspects, (Springer), pp. 21–48.
Harnik, P.G., Lotze, H.K., Anderson, S.C., Finkel, Z.V., Finnegan, S., Lindberg, D.R., Liow, L.H., Lockwood, R., McClain, C.R., and McGuire, J.L. (2012). Extinctions in ancient and modern seas. Trends in Ecology & Evolution.
Harris, M., Beare, D., Toresen, R., Nøttestad, L., Kloppmann, M., Dörner, H., Peach, K., Rushton, D., Foster-Smith, J., and Wanless, S. (2007). A major increase in snake pipefish ( Entelurus aequoreus ) in northern European seas since 2003: potential implications for seabird breeding success. Marine Biology 151, 973–983.
Harvell, C.D., Altizer, S., Cattadori, I.M., Harrington, L., and Weil, E. (2009). Climate change and wildlife diseases: when does the host matter the most? Ecology 90, 912–920.
Harvell, C.D., Mitchell, C.E., Ward, J.R., Altizer, S., Dobson, A.P., Ostfeld, R.S., and Samuel, M.D. (2002). Climate warming and disease risks for terrestrial and marine biota. Science 296, 2158–2162.
Hendriks, I.E., and Duarte, C.M. (2010). Ocean acidification: Separating evidence from judgment–A reply to Dupont et al. Estuarine, Coastal and Shelf Science 89, 186–190.
Hendriks, I.E., Duarte, C.M., and Álvarez, M. (2010). Vulnerability of marine biodiversity to ocean acidification: A meta-analysis. Estuarine, Coastal and Shelf Science 86, 157–164.
Hijmans, R.J., and Graham, C.H. (2006). The ability of climate envelope models to predict the effect of climate change on species distributions. Global Change Biology 12, 2272–2281.
Hoegh-Guldberg, O. (2009). Climate change and coral reefs: Trojan horse or false prophecy? Coral Reefs 28, 569–575.
Jackson, J.B.C. (1997). Reefs since Columbus. Coral Reefs 16, S23–S32.
Jones, G.P., McCormick, M.I., Srinivasan, M., and Eagle, J.V. (2004). Coral decline threatens fish biodiversity in marine reserves. Proc Natl Acad Sci USA 101, 8251–8253.
Kiers, E.T., Palmer, T.M., Ives, A.R., Bruno, J.F., and Bronstein, J.L. (2010). Mutualisms in a changing world: an evolutionary perspective. Ecology Letters 13, 1459–1474.
Knutti, R., and Hegerl, G.C. (2008). The equilibrium sensitivity of the Earth’s temperature to radiation changes. Nature Geoscience 1, 735–743.
Kordas, R.L., Harley, C.D.G., and O’Connor, M.I. (2011). Community ecology in a warming world: The influence of temperature on interspecific interactions in marine systems. Journal of Experimental Marine Biology and Ecology 400, 218–226.
Kroeker, K.J., Kordas, R.L., Crim, R.N., and Singh, G.G. (2010). Meta-analysis reveals negative yet variable effects of ocean acidification on marine organisms. Ecology Letters 13, 1419–1434.
Page 27 of 30
857858859
860861
862863864
865866867868
869870
871872
873874
875876
877878
879880
881
882883
884885
886887
888889890
891892
Laffoley, D., and Grimsditch, G.E. (2009). Management of natural coastal carbon sinksID - 3156.
Levitus, S. (2005). Warming of the world ocean, 1955–2003. Geophysical Research Letters 32,.
Levitus, S., Antonov, J.I., Boyer, T.P., Baranova, O.K., Garcia, H.E., Locarnini, R.A., Mishonov, A.V., Reagan, J.R., Seidov, D., Yarosh, E.S., et al. (2012). World ocean heat content and thermosteric sea level change (0–2000 m), 1955–2010. Geophysical Research Letters 39,.
Liu, J., Zhou, H., Qin, P., and Zhou, J. (2007). Effects of Spartina alterniflora salt marshes on organic carbon acquisition in intertidal zones of Jiangsu Province, China. Ecological Engineering 30, 240–249.
Loarie, S.R., Duffy, P.B., Hamilton, H., Asner, G.P., Field, C.B., and Ackerly, D.D. (2009). The velocity of climate change. Nature 462, 1052–1055.
Lohbeck, K.T., Riebesell, U., and Reusch, T.B.H. (2012). Adaptive evolution of a key phytoplankton species to ocean acidification. Nature Geoscience 5, 346–351.
Mieszkowska, N., Burrows, M.T., Pannacciulli, F.G., and Hawkins, S.J. (2012). Multidecadal signals within co-occuring intertidal barnacles Semibalanus balanoides and Chthamalus spp. linked to the Atlantic Multidecadal Oscillation. Journal of Marine Systems.
Nicholls, R.J., and Cazenave, A. (2010). Sea-level rise and its impact on coastal zones. Science 328, 1517–1520.
O’Connor, M.I., Bruno, J.F., Gaines, S.D., Halpern, B.S., Lester, S.E., Kinlan, B.P., and Weiss, J.W. (2007). Temperature control of larval dispersal and its implications for marine ecology, evolution, and conservation. Proceedings of the National Academy of Sciences of the United States of America 104, 1266–1271.
O’Connor, M.I., Piehler, M.F., Leech, D.M., Anton, A., and Bruno, J.F. (2009). Warming and resource availability shift food web structure and metabolism. PLoS Biology 7, e1000178.
Orr, J.C., Fabry, V.J., Aumont, O., Bopp, L., Doney, S.C., Feely, R.A., Gnanadesikan, A., Gruber, N., Ishida, A., and Joos, F. (2005). Anthropogenic ocean acidification over the twenty-first century and its impact on calcifying organisms. Nature 437, 681–686.
Pereira, H.M., Leadley, P.W., Proença, V., Alkemade, R., Scharlemann, J.P.W., Fernandez-Manjarrés, J.F., Araújo, M.B., Balvanera, P., Biggs, R., Cheung, W.W.L., et al. (2010). Scenarios for global biodiversity in the 21st century. Science 330, 1496 –1501.
Poloczanska, E.S., Brown, C.J., Sydeman, W.J., Kiessling, W., Schoeman, D.S., Moore, P.J., Brander, K., Bruno, J.F., Buckley, L.B., Burrows, M.T., et al. (2013). Global imprint of climate change on marine life. Nature Climate Change in review,.
Pryzant, L.K., and Bruno, J.F. (2012). What to Do When the Oceans Rise. PLoS Biology 10, e1001387.
Purkey, S.G., and Johnson, G.C. (2010). Warming of Global Abyssal and Deep Southern Ocean Waters between the 1990s and 2000s: Contributions to Global Heat and Sea Level Rise Budgets*. Journal of Climate 23, 6336–6351.
Page 28 of 30
893
894
895896897
898899
900901
902903
904905906
907908
909910911912
913914
915916917
918919920
921922923
924
925926927
Le Quéré, C., Andres, R.J., Boden, T., Conway, T., Houghton, R.A., House, J.I., Marland, G., Peters, G.P., Van der Werf, G., Ahlström, A., et al. (2012). The global carbon budget 1959–2011. Earth System Science Data Discussions 5, 1107–1157.
Reid, P.C., Johns, D.G., Edwards, M., Starr, M., Poulin, M., and Snoeijs, P. (2007). A biological consequence of reducing Arctic ice cover: arrival of the Pacific diatom Neodenticula seminae in the North Atlantic for the first time in 800 000 years. Global Change Biology 13, 1910–1921.
Ries, J.B., Cohen, A.L., and McCorkle, D.C. (2009). Marine calcifiers exhibit mixed responses to CO2-induced ocean acidification. Geology 37, 1131–1134.
Sanford, E. (1999). Regulation of keystone predation by small changes in ocean temperature. Science 283, 2095–2097.
Selig, E.R., Casey, K.S., and Bruno, J.F. (2010). New insights into global patterns of ocean temperature anomalies: implications for coral reef health and management. Global Ecology and Biogeography 19, 397–411.
Shanks, A.L. (2009). Pelagic larval duration and dispersal distance revisited. The Biological Bulletin 216, 373–385.
Smith, C.R., Grange, L.J., Honig, D.L., Naudts, L., Huber, B., Guidi, L., and Domack, E. (2012). A large population of king crabs in Palmer Deep on the west Antarctic Peninsula shelf and potential invasive impacts. Proceedings of the Royal Society B: Biological Sciences 279, 1017–1026.
Sorte, C.J.B., Williams, S.L., and Carlton, J.T. (2010). Marine range shifts and species introductions: comparative spread rates and community impacts. Global Ecology and Biogeography 19, 303–316.
Southward, A.J., Hawkins, S.J., and Burrows, M.T. (1995). 70 years observations of changes in distribution and abundance of zooplankton and intertidal organisms in the western English Channel in relation to rising sea temperature. Journal of Thermal Biology 20, 127–155.
Stramma, L., Schmidtko, S., Levin, L.A., and Johnson, G.C. (2010). Ocean oxygen minima expansions and their biological impacts. Deep Sea Research Part I: Oceanographic Research Papers 57, 587–595.
Sunday, J.M., Bates, A.E., and Dulvy, N.K. (2011). Global analysis of thermal tolerance and latitude in ectotherms. Proc. R. Soc. B 278, 1823–1830.
Teal, L.R., Hal, R., Kooten, T., Ruardij, P., and Rijnsdorp, A.D. (2012). Bio-energetics underpins the spatial response of North Sea plaice (Pleuronectes platessa L.) and sole (Solea solea L.) to climate change. Global Change Biology.
Toth, L.T., Aronson, R.B., Vollmer, S.V., Hobbs, J.W., Urrego, D.H., Cheng, H., Enochs, I.C., Combosch, D.J., Van Woesik, R., and Macintyre, I.G. (2012). ENSO Drove 2500-Year Collapse of Eastern Pacific Coral Reefs. Science 337, 81–84.
Vermeij, G.J. (2001). Community Assembly in the Sea: Geologic History of the Living Shore Biota (Sunderland, Ma.: Sinauer Assoc., Inc.).
Page 29 of 30
928929930
931932933
934935
936937
938939940
941942
943944945
946947
948949950
951952
953954
955956957
958959960
961
962963
Vermeij, G.J., and Roopnarine, P.D. (2008). The coming Arctic invasion. Science 321, 780–781.
Wernberg, T., Russell, B.D., Thomsen, M.S., Gurgel, C.F.D., Bradshaw, C.J.A., Poloczanska, E.S., and Connell, S.D. (2011). Seaweed communities in retreat from ocean warming. Current Biology.
Wernberg, T., Smale, D.A., and Thomsen, M.S. (2012). A decade of climate change experiments on marine organisms: procedures, patterns and problems. Global Change Biology.
Wethey, D.S. (1984). Sun and shade mediate competition in the barnacles Chthamalus and Semibalanus: a field experiment. Biol Bull 167, 176–185.
Van Woesik, R., Franklin, E.C., O’Leary, J., McClanahan, T.R., Klaus, J.S., and Budd, A.F. (2012). Hosts of the Plio-Pleistocene past reflect modern-day coral vulnerability. Proceedings of the Royal Society B: Biological Sciences 279, 2448–2456.
Young, I.R., Zieger, S., and Babanin, A.V. (2011). Global Trends in Wind Speed and Wave Height. Science 332, 451–455.
