• Energy Research

Climate change is driving changes in the physical and chemical properties of the ocean that have consequences for marine ecosystems. Here, we review evidence for the responses of marine life to recent climate change across ocean regions, from tropical seas to polar oceans. We consider observed changes in calcification rates, demography, abundance, distribution and phenology of marine species. We draw on a database of observed climate change impacts on marine species, supplemented with evidence in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. We discuss factors that limit or facilitate species’ responses, such as fishing pressure, the availability of prey, habitat, light and other resources, and dispersal by ocean currents. We find that general trends in species responses are consistent with expectations from climate change, including poleward and deeper distributional shifts, advances in spring phenology, declines in calcification and increases in the abundance of warm-water species. The volume and type of evidence of species responses to climate change is variable across ocean regions and taxonomic groups, with much evidence derived from the heavily-studied north Atlantic Ocean. Most investigations of marine biological impacts of climate change are of the impacts of changing temperature, with few observations of effects of changing oxygen, wave climate, precipitation (coastal waters) or ocean acidification. Observations of species responses that have been linked to anthropogenic climate change are widespread, but are still lacking for some taxonomic groups (e.g., phytoplankton, benthic invertebrates, marine mammals).

AbstractGlobal ecosystem models are essential tools for predicting climate change impacts on marine systems. Modeled biogenic carbon fluxes in the ocean often match measured data poorly and part of this could be because small copepods (<2 mm) are modeled as unicellular feeders grazing on phytoplankton and microzooplankton. The most abundant copepods from a seasonal upwelling region of the Eastern North Atlantic were sorted, and a molecular method was applied to copepod gut contents to evaluate the extent of metazoan predation under two oceanographic conditions, a trophic pathway not accounted for in global models. Scaling up the results obtained herein, based on published field and laboratory estimates, suggests that small copepods could ingest 1.79–27.20 gigatons C/year globally. This ignored metazoan‐copepod link could increase current estimates of biogeochemical fluxes (remineralization, respiration, and the biological pump) and export to higher trophic levels by 15.6%–24.4%. It could also account for global discrepancies between measured daily ingestion and copepod metabolic demand/growth. The inclusion of metazoan predation into global models could provide a more realistic role of the copepods in the ocean and if these preliminary data hold true at larger sample sizes and scales, the implications would be substantial at the global scale.

Movements of wide-ranging top predators can now be studied effectively using satellite and archival telemetry. However, the motivations underlying movements remain difficult to determine because trajectories are seldom related to key biological gradients, such as changing prey distributions. Here, we use a dynamic prey landscape of zooplankton biomass in the north-east Atlantic Ocean to examine active habitat selection in the plankton-feeding basking sharkCetorhinus maximus. The relative success of shark searches across this landscape was examined by comparing prey biomass encountered by sharks with encounters by random-walk simulations of ‘model’ sharks. Movements of transmitter-tagged sharks monitored for 964 days (16 754 km estimated minimum distance) were concentrated on the European continental shelf in areas characterized by high seasonal productivity and complex prey distributions. We show movements by adult and sub-adult sharks yielded consistently higher prey encounter rates than 90% of random-walk simulations. Behavioural patterns were consistent with basking sharks using search tactics structured across multiple scales to exploit the richest prey areas available in preferred habitats. Simple behavioural rules based on learned responses to previously encountered prey distributions may explain the high performances. This study highlights how dynamic prey landscapes enable active habitat selection in large predators to be investigated from a trophic perspective, an approach that may inform conservation by identifying critical habitat of vulnerable species.

AbstractClimate change is shifting species’ distribution and phenology. Ecological traits, such as mobility or reproductive mode, explain variation in observed rates of shift for some taxa. However, estimates of relationships between traits and climate responses could be influenced by how responses are measured. We compiled a global data set of 651 published marine species’ responses to climate change, from 47 papers on distribution shifts and 32 papers on phenology change. We assessed the relative importance of two classes of predictors of the rate of change, ecological traits of the responding taxa and methodological approaches for quantifying biological responses. Methodological differences explained 22% of the variation in range shifts, more than the 7.8% of the variation explained by ecological traits. For phenology change, methodological approaches accounted for 4% of the variation in measurements, whereas 8% of the variation was explained by ecological traits. Our ability to predict responses from traits was hindered by poor representation of species from the tropics, where temperature isotherms are moving most rapidly. Thus, the mean rate of distribution change may be underestimated by this and other global syntheses. Our analyses indicate that methodological approaches should be explicitly considered when designing, analysing and comparing results among studies. To improve climate impact studies, we recommend that (1) reanalyses of existing time series state how the existing data sets may limit the inferences about possible climate responses; (2) qualitative comparisons of species’ responses across different studies be limited to studies with similar methodological approaches; (3) meta‐analyses of climate responses include methodological attributes as covariates; and (4) that new time series be designed to include the detection of early warnings of change or ecologically relevant change. Greater consideration of methodological attributes will improve the accuracy of analyses that seek to quantify the role of climate change in species’ distribution and phenology changes.

To estimate primary production in the marine environment, knowledge of the vertical distribution of phytoplankton is needed. The measurement of ocean colour by satellite remote sensing makes it possible to map the near-surface phytoplankton distribution, although the subsurface vertical structure cannot be measured. In this study, we investigated the shape of vertical chlorophyll profiles from the Benguela upwelling system seasonally and with respect to environmental variables such as surface temperature and chlorophyll, and mixed layer and water column depth. We used an artificial neural network technique called a self-organizing map to identify characteristic classes of vertical chlorophyll profiles, and then classify existing profiles into these representative classes. The self-organizing map identified a continuum of patterns, ranging from those with small deep peaks (1 mg m(-3), 45 m) to those with large near-surface peaks (9 mg m(-3), 7 m). Although profile shape varied seasonally, profiles were very variable within each season, making chlorophyll profiles averaged seasonally meaningless. A canonical succession in profile shape following upwelling of cold water in spring and summer could be identified, with large surface peaks in cool water and small deep peaks in warm water. The approach presented here can be used in a semi-quantitative manner to predict the subsurface chlorophyll field from known (water column depth) or easily measured variables from satellites (surface temperature or surface chlorophyll), as the relative frequency of each characteristic profile under different environmental conditions is presented. This approach enables prediction of profile shapes in the dynamic coastal domain and thus superior regional estimates of primary production.

Manta rays Manta alfredi are present all year round at Lady Elliot Island (LEI) in the southern Great Barrier Reef, Australia, with peaks in abundance during autumn and winter. Drivers influencing these fluctuations in abundance of M. alfredi at the site remain uncertain. Based on daily count, behavioural, weather and oceanographic data collected over a three-year period, this study examined the link between the relative number of sightings of manta rays at LEI, the biophysical environment, and the habitat use of individuals around the LEI reef using generalised additive models. The response variable in each of the three generalised additive models was number of sightings (per trip at sea) of cruising, cleaning or foraging M. alfredi. We used a set of eleven temporal, meteorological, biological, oceanographic and lunar predictor variables. Results for cruising, cleaning and foraging M. alfredi explained 27.5%, 32.8% and 36.3% of the deviance observed in the respective models and highlighted five predictors (year, day of year, wind speed, chlorophyll-a concentration and fraction of moon illuminated) as common influences to the three models. There were more manta rays at LEI in autumn and winter, slower wind speeds, higher productivity, and around the new and full moon. The winter peak in sightings of foraging M. alfredi was found to precede peaks in cleaning and cruising activity around the LEI reef, which suggests that enhanced food availability may be a principal driver for this seasonal aggregation. A spatial analysis of behavioural observations highlighted several sites around the LEI reef as 'multi-purpose' areas where cleaning and foraging activities commonly occur, while the southern end of the reef is primarily a foraging area. The use of extensive citizen science datasets, such as those collected by dive operators in this study, is encouraged as they can provide valuable insights into a species' ecology.

The continental shelf in the southwestern Atlantic Ocean is among the six richest marine regions for biodiversity in the Southern Hemisphere, and its subtropical region is one of the fastest-warming hotspots. Thus, climate change could profoundly affect future species distributions. We investigated future climate-induced changes in fish larvae and harvested fish taxa in the subtropical southwestern Atlantic Ocean using a community-based modelling technique (gradient forest). This approach integrates information on multiple species rather than treating each species individually, as is typical in many species distribution approaches. We addressed two primary questions: how might climate change affect fish larval communities, and will communities of harvested fish (juveniles and adults) taxa respond similarly. Using two climate change scenarios (moderate RCP 4.5 and ‘business as usual’ 8.5), we found that fish larvae and harvested taxa are influenced differently by environmental variables, with differences in both the level and shape of the response to environmental drivers. Chlorophyll a and sea surface temperature were the most important predictors for fish larvae communities, while depth and sea surface salinity best predicted the harvested community. However, both communities are expected to move southwards in response to climate change, with greater changes in community composition predicted in the southern portion of the study area for both fish larvae and harvested taxa. To our knowledge, this is the first study to investigate the effect of future climate change on a suite of taxa of fish larvae and adults. We also suggest that modelling the integrated response of a suite of species to environmental predictors using community-modelling approaches such as gradient forest could provide robust projections and novel insights into community changes.