Impacts of climate change on marine ecosystem production in societies dependent on fisheries

Growing human populations and changing dietary preferences are increasing global demands for fish, adding pressure to concerns over fisheries sustainability. Here we develop and link models of physical, biological and human responses to climate change in 67 marine national exclusive economic zones, which yield approximately 60% of global fish catches, to project climate change yield impacts in countries with different dependencies on marine fisheries. Predicted changes in fish production indicate increased productivity at high latitudes and decreased productivity at low/mid latitudes, with considerable regional variations. With few exceptions, increases and decreases in fish production potential by 2050 are estimated to be <10% (mean C3.4%) from present yields. Among the nations showing a high dependency on fisheries, climate change is predicted to increase productive potential in West Africa and decrease it in South and Southeast Asia. Despite projected human population increases and assuming that per capita fish consumption rates will be maintained1, ongoing technological development in the aquaculture industry suggests that projected global fish demands in 2050 could be met, thus challenging existing predictions of inevitable shortfalls in fish supply by the mid-twenty-first century. This conclusion, however, is contingent on successful implementation of strategies for sustainable harvesting and effective distribution of wild fish products from nations and regions with a surplus to those with a deficit. Changes in management effectiveness2 and trade practices5 will remain the main influence on realized gains or losses in global fish production.

Scale-dependent response diversity of seabirds to prey in the North Sea

Functional response diversity is defined as the diversity of responses to environmental change among species that contribute to the same ecosystem function. Because different ecological processes dominate on different spatial and temporal scales, response diversity is likely to be scale dependent. Using three extensive data sets on seabirds, pelagic fish, and zooplankton, we investigate the strength and diversity in the response of seabirds to prey in the North Sea over three scales of ecological organization. Two-stage analyses were used to partition the variance in the abundance of predators and prey among the different scales of investigation: variation from year to year, variation among habitats, and variation on the local patch scale. On the year-to-year scale, we found a strong and synchronous response of seabirds to the abundance of prey, resulting in low response diversity. Conversely, as different seabird species were found in habitats dominated by different prey species, we found a high diversity in the response of seabirds to prey on the habitat scale. Finally, on the local patch scale, seabirds were organized in multispecies patches. These patches were weakly associated with patches of prey, resulting in a weak response strength and a low response diversity. We suggest that ecological similarities among seabird species resulted in low response diversity on the year-to-year scale. On the habitat scale, we suggest that high response diversity was due to interspecific competition and niche segregation among seabird species. On the local patch scale, we suggest that facilitation with respect to the detection and accessibility of prey patches resulted in overlapping distribution of seabirds but weak associations with prey. The observed scale dependencies in response strength and diversity have implications for how the seabird community will respond to different environmental disturbances.

Transfer Across the Air-Sea Interface

The efficiency of transfer of gases and particles across the air-sea interface is controlled by several physical, biological and chemical processes in the atmosphere and water which are described here (including waves, large- and small-scale turbulence, bubbles, sea spray, rain and surface films). For a deeper understanding of relevant transport mechanisms, several models have been developed, ranging from conceptual models to numerical models. Most frequently the transfer is described by various functional dependencies of the wind speed, but more detailed descriptions need additional information. The study of gas transfer mechanisms uses a variety of experimental methods ranging from laboratory studies to carbon budgets, mass balance methods, micrometeorological techniques and thermographic techniques. Different methods resolve the transfer at different scales of time and space; this is important to take into account when comparing different results. Air-sea transfer is relevant in a wide range of applications, for example, local and regional fluxes, global models, remote sensing and computations of global inventories. The sensitivity of global models to the description of transfer velocity is limited; it is however likely that the formulations are more important when the resolution increases and other processes in models are improved. For global flux estimates using inventories or remote sensing products the accuracy of the transfer formulation as well as the accuracy of the wind field is crucial.

Recovery or decline of the Northwestern Black Sea: A societal choice revealed by socio-ecological modelling

During recent decades anthropogenic activities have dramatically impacted the Black Sea ecosystem. High levels of riverine nutrient input during the 1970s and 1980s caused eutrophic conditions including intense algal blooms resulting in hypoxia and the subsequent collapse of benthic habitats on the northwestern shelf. Intense fishing pressure also depleted stocks of many apex predators, contributing to an increase in planktivorous fish that are now the focus of fishing efforts. Additionally, the Black Sea's ecosystem changed even further with the introduction of exotic species. Economic collapse of the surrounding socialist republics in the early 1990s resulted in decreased nutrient loading which has allowed the Black Sea ecosystem to start to recover, but under rapidly changing economic and political conditions, future recovery is uncertain. In this study we use a multidisciplinary approach to integrate information from socio-economic and ecological systems to model the effects of future development scenarios on the marine environment of the northwestern Black Sea shelf. The Driver–Pressure–State-Impact-Response framework was used to construct conceptual models, explicitly mapping impacts of socio-economic Drivers on the marine ecosystem. Bayesian belief networks (BBNs), a stochastic modelling technique, were used to quantify these causal relationships, operationalise models and assess the effects of alternative development paths on the Black Sea ecosystem. BBNs use probabilistic dependencies as a common metric, allowing the integration of quantitative and qualitative information. Under the Baseline Scenario, recovery of the Black Sea appears tenuous as the exploitation of environmental resources (agriculture, fishing and shipping) increases with continued economic development of post-Soviet countries. This results in the loss of wetlands through drainage and reclamation. Water transparency decreases as phytoplankton bloom and this deterioration in water quality leads to the degradation of coastal plant communities (Cystoseira, seagrass) and also Phyllophora habitat on the shelf. Decomposition of benthic plants results in hypoxia killing flora and fauna associated with these habitats. Ecological pressure from these factors along with constant levels of fishing activity results in target stocks remaining depleted. Of the four Alternative Scenarios, two show improvements on the Baseline ecosystem condition, with improved waste water treatment and reduced fishing pressure, while the other two show a worsening, due to increased natural resource exploitation leading to rapid reversal of any recent ecosystem recovery. From this we conclude that variations in economic policy have significant consequences for the health of the Black Sea, and ecosystem recovery is directly linked to social–economic choices.

Microbial spatial variability: An example from the Celtic Sea

In July 2004, dominant populations of microbial ultraplankton (<5 μm), in the surface of the Celtic Sea (between UK and Eire), were repeatedly mapped using flow cytometry, at 1.5 km resolution over a region of diameter 100 km. The numerically dominant representatives of all basic functional types were enumerated including one group of phototrophic bacteria (Syn), two groups of phytoplankton (PP, NP), three groups of heterotrophic bacterioplankton (HB) and the regionally dominant group of heterotrophic protists (HP). The distributions of all organisms showed strong spatial variability with little relation to variability in physical fields such as salinity and temperature. Furthermore, there was little agreement between distributions of different organisms. The only linear correlation consistently explaining more than 50% of the variance between any pairing of the organism groups enumerated is between two different groups of HB. Specifically, no linear, or non-linear, relationship is found between any pairings of SYB, PP or HB groups with their protist predators HP. Looking for multiple dependencies, factor analysis reveals three groupings: Syn, PP and low nucleic acid content HB (LNA); high nucleic acid content HB (HNA); HP and NP. Even the manner in which the spatial variability of Syn, PP and HB abundance varies as a function of lengthscale (represented by a semivariogram) differs significantly from that for HP. In summary, although all microbial planktonic groups enumerated are present and numerically dominant throughout the region studied, at face value the relationships between them seem weak. Nevertheless, the behaviour of a simple, illustrative ecological model, with strongly interacting phototrophs and heterotrophs, with stochastic forcing, is shown to be consistent with the observed poor correlations and differences in how spatial variability varies with lengthscale. Thus, our study suggests that a comparison of microbial abundances alone may not discern strong underlying trophic interactions. Specific knowledge of these processes, in particular grazing, will be required to explain the causes of the observed microbial spatial variability and its resulting consequences for the functioning of the ecosystem.