clear SFG advantage to explain the dominance of M. trossulus in cold habitats. As SST continues to warm due to climate change, the energetics of these three species provide a basis for developing mechanistic models8 predicting future distribution and productivity changes in mussel populations (Fly & Hilbish 2013).
Montalto et al. (2016) used three interconnected models (climatic, biophysical and energetics) to estimate changes in growth, reproduction and mortality risk by 2050 for three commercially and ecologically important mussels (Brachidontes pharaonis, Mytilaster minimus and M. galloprovincialis) at 51 sites in the Mediterranean Sea. Helmuth et al. (2014) have cautioned that to focus solely on range limits may lead to failure to notice highly significant impacts that are both occurring now and will likely occur in the future. All three species inhabit intertidal habitats, and thus are affected by changes in both terrestrial and marine environments. They differ from one another in their thermal optima, performance breadth and lethal temperatures. Montalto et al. (2016) predicted highly variable responses (both positive and negative) in the timing of reproductive maturity and the risk of lethality among the species and sites that do not conform to simple latitudinal gradients, which would be undetectable by methods focused only on lethal limits and/or range boundaries. Also, results strongly suggest that the three species will likely experience changes in the timing of reproductive maturity, and that in intertidal zones thermal stress may cause changes to the risk of mortality. However, these consequences are highly species‐ and site‐specific in ways that do not always conform to simple latitudinal gradients, and in some cases reveal potential benefits for Mediterranean Sea ecosystems.
Challenges with managing bivalve culture may become more pronounced as the uncertainty associated with climate change makes it difficult to predict future production levels. Steeves et al. (2018) coupled a previously established high‐resolution climate model with two dynamic energy budget (DEB) models (see Chapter 6) to explore the future growth and distribution of two economically and ecologically important species, the oyster Crassostrea virginica and the mussel M. edulis, along the Atlantic coast of Canada. SST data were extracted from the climate model and used as a forcing variable in the bioenergetic models. This approach was applied across three distinct time periods: the past (1986–1990), the present (2016–2020) and the future (2046–2050), thus permitting a comparison of bivalve performance under different temporal scenarios. Results showed that growth in the future is variable both spatially and interspecifically. Modelling outcomes suggested that warming ocean temperatures will cause an increase in growth rates of both species as a result of their ectothermic nature. Since the thermal tolerance of C. virginica is higher than that of M. edulis, oysters will generally out‐perform mussels (Gosling 2015). The predicted effects of temperature on bivalve physiology also provided insight into vulnerabilities, such as mortality, under future SST scenarios. This information is useful for adapting future management strategies for both farmed and wild shellfish. Although the study focused on a geographically specific area, the approach of coupling bioenergetic and climate models is valid for species and environments across the globe.
Apart from the impact on mussel biogeographic distribution and physiological traits already discussed, there is evidence that global warming can impact on: interspecific (Petes et al. 2007) and predator–prey (Freitas et al. 2007; Broitman et al. 2009; Menge et al. 2008; Harley 2011; Kordas et al. 2011; Monaco et al. 2016; Torossian et al. 2020) interactions; reproductive timing and larval dispersal (Carson et al. 2010); the immune response (Matozzo & Marin 2011; Beaudry et al. 2016; Hernroth & Baden 2018); byssal thread strength (Newcomb et al. 2019); developmental instability (Nishizaki et al. 2015); species invasion success (US EPA 2008; Occhipinti‐Ambrogi & Galil 2010; Firth et al. 2011; Somero 2010, 2011; Thyrring et al. 2017); mussel culture (Guyondet et al. 2015; Steeves et al. 2018; Silva et al. 2017; Filgueira et al. 2016; Callaway et al. 2012); and radiation‐induced damage (Dallas et al. 2016).
Ocean Acidification
Human activities such as the burning of oil, coal and gas, as well as deforestation, are the primary cause of the increased CO2 concentrations in the atmosphere. The global average atmospheric CO2 in 2018 was 407.4 ppm, with a range of uncertainty of ±0.1 ppm. Carbon dioxide levels today are higher than at any point in at least the past 800 000 years (NOAA Global Climate Report 2019). Human‐induced rise in atmospheric CO2 concentration has been linked to changes in seawater carbonate chemistry and a decrease in ocean pH, a process known as ocean acidification (OA) (Ventura et al. 2016; see Chapter 6). When carbon dioxide diffuses into the ocean, it reacts with water to create carbonic acid (H2CO3), most of which quickly dissociates into a hydrogen ion (H+) and bicarbonate (HCO3 −), which can further dissociate into carbonate (CO3 2−) and hydrogen ions (Figure 3.18). Some of the carbonate ions already in the ocean combine with some of the hydrogen ions to form further bicarbonate, thereby reducing the availability of carbonate ions, which are necessary for marine calcifying organisms such as corals, foraminiferans, echinoderms, crustaceans and molluscs to produce their CaCO3 shells and skeletons (Fabry et al. 2008).
Since the Industrial Revolution, a time span of less than 250 years, the pH of surface oceans has dropped by 0.1 pH units, representing a ~30% increase in hydrogen ion concentration relative to the preindustrial value (Guinotte & Fabry 2008). The pH scale is logarithmic, and consequently each whole unit decrease in pH is equal to a 10‐fold increase in acidity. The pH of the oceans is projected to drop another 0.3–0.4 pH units by 2100 (Mackenzie et al. 2014). The rate of this change is cause for concern, as many marine organisms – particularly those that calcify (see earlier) – may not be able to adapt quickly enough to survive. The degree of change will depend on whether we adopt a concerted rapid CO2 mitigation effort or a ‘business‐as‐usual’ attitude (Mora et al.2013). The lowest surface ocean pH is found in the equatorial regions from 20 °N to 20 °S, especially in the eastern Pacific (Jiang et al. 2019). The Arctic Ocean shows the largest spatial variability, followed by the Southern Ocean, which surrounds Antarctica. The globally and annually averaged surface ocean pHs in the Atlantic, Pacific and Indian Oceans (60 °N to 60 °S) are very similar at 8.07 ± 0.02, 8.06 ± 0.03 and 8.07 ± 0.02, respectively, with a global average of 8.07 ± 0.02 between 60 °N to 60 °S. The most rapid acidification is presently occurring in the Arctic Ocean (see Qi et al. 2017).
Figure 3.18 Schematic diagram of ocean acidification (OA). The reaction between dissolved carbon dioxide (CO2) and water results in an increase in the concentration of hydrogen ions (H+); additional changes include an increase in bicarbonate ions (HCO3–) and a great decrease in carbonate ions (CO32−). These ions will modify the carbonate saturation state, leading to acidification.
Source: From Birchenough et al. (2017). Open Government Licence v3.0.
Dupont & Pörtner (2013) reviewed a selection of papers covering a range of experimental approaches used to investigate the impact of OA on marine species and ecosystems. They found that while the vast majority of studies (>90%) on the potential effects of OA were laboratory‐based, there were a few field studies using natural gradients or CO2‐rich
