Beyond long-term averages: making biological sense of a rapidly changing world

Biological responses to climate change are typically communicated in generalized terms such as poleward and altitudinal range shifts, but adaptation efforts relevant to management decisions often require forecasts that incorporate the interaction of multiple climatic and nonclimatic stressors at far smaller spatiotemporal scales. We argue that the desire for generalizations has, ironically, contributed to the frequent conflation of weather with climate, even within the scientific community. As a result, current predictions of ecological responses to climate change, and the design of experiments to understand underlying mechanisms, are too often based on broad-scale trends and averages that at a proximate level may have very little to do with the vulnerability of organisms and ecosystems. The creation of biologically relevant metrics of environmental change that incorporate the physical mechanisms by which climate trains patterns of weather, coupled with knowledge of how organisms and ecosystems respond to these changes, can offer insight into which aspects of climate change may be most important to monitor and predict. This approach also has the potential to enhance our ability to communicate impacts of climate change to nonscientists and especially to stakeholders attempting to enact climate change adaptation policies.

Projecting Changes in the Distribution and Productivity of Living Marine Resources: A Critical Review of the Suite of Modeling Approaches used in the Large European Project VECTORS

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

Projecting Changes in the Distribution and Productivity of Living Marine Resources: A Critical Review of the Suite of Modeling Approaches used in the Large European Project VECTORS

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

Is the Russell Cycle a true cycle? Multidecadal zooplankton and climate trends in the western English Channel

The Russell Cycle is one of the classical examples of climate influence on biological oceanography, represented as shifts in the marine plankton over several decades with warm and cool conditions. While the time-series data associated with the phenomenon indicate cyclical patterns, the question remains whether or not the Russell Cycle should be considered a “true cycle”. Zooplankton time-series data from 1924 to 2011 from the western English Channel were analysed with principal component (PC), correlation and spectral analyses to determine the dominant trends, and cyclic frequencies of the Russell Cycle indicators in relation to long-term hydroclimatic indices. PC1 accounted for 37.4% of the variability in the zooplankton data with the main contributions from non-clupeid fish larvae, southwestern zooplankton, and overall zooplankton biovolume. For PC2 (14.6% of data variance), the dominant groups were northern fish larvae, non-sardine eggs, and southern fish larvae. Sardine eggs were the major contributors to PC3 (representing 12.1% of data variance). No significant correlations were observed between the above three components and climate indices: Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and local seawater temperature. Significant 44- and 29-year frequencies were observed for PC3, but the physical mechanisms driving the cycles are unclear. Harmonic analysis did not reveal any significant frequencies in the physical variables or in PCs 1 and 2. To a large extent, this is due to the dominant cycles in all datasets generally being long term (>50 years or so) and not readily resolved in the examined time frame of 88 years, hence restricting the ability to draw firm conclusions on the multidecadal relationship between zooplankton community dynamics in the western English Channel and environmental indices. Thus, the zooplankton time-series often associated and represented as the Russell Cycle cannot be concluded as being truly cyclical.

Is the Russell Cycle a true cycle? Multidecadal zooplankton and climate trends in the western English Channel

The Russell Cycle is one of the classical examples of climate influence on biological oceanography, represented as shifts in the marine plankton over several decades with warm and cool conditions. While the time-series data associated with the phenomenon indicate cyclical patterns, the question remains whether or not the Russell Cycle should be considered a “true cycle”. Zooplankton time-series data from 1924 to 2011 from the western English Channel were analysed with principal component (PC), correlation and spectral analyses to determine the dominant trends, and cyclic frequencies of the Russell Cycle indicators in relation to long-term hydroclimatic indices. PC1 accounted for 37.4% of the variability in the zooplankton data with the main contributions from non-clupeid fish larvae, southwestern zooplankton, and overall zooplankton biovolume. For PC2 (14.6% of data variance), the dominant groups were northern fish larvae, non-sardine eggs, and southern fish larvae. Sardine eggs were the major contributors to PC3 (representing 12.1% of data variance). No significant correlations were observed between the above three components and climate indices: Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and local seawater temperature. Significant 44- and 29-year frequencies were observed for PC3, but the physical mechanisms driving the cycles are unclear. Harmonic analysis did not reveal any significant frequencies in the physical variables or in PCs 1 and 2. To a large extent, this is due to the dominant cycles in all datasets generally being long term (>50 years or so) and not readily resolved in the examined time frame of 88 years, hence restricting the ability to draw firm conclusions on the multidecadal relationship between zooplankton community dynamics in the western English Channel and environmental indices. Thus, the zooplankton time-series often associated and represented as the Russell Cycle cannot be concluded as being truly cyclical.

Interactions between multiple large macrofauna species and nematode communities — Mechanisms for indirect impacts of trawling disturbance

Highlights •We exposed meiofauna to 7 different large macrofauna species at high and low densities. •Macrofauna presence altered nematode community structure and reduced their abundance. •Macrofauna species had similar effects by reducing the few dominant nematode species. •Meio–macrofauna resource competition and spatial segregation are the main drivers. •Trawling effects on macrofauna affect nematode communities indirectly. Diverse assemblages of infauna in sediments provide important physical and biogeochemical services, but are under increasing pressure by anthropogenic activities, such as benthic trawling. It is known that trawling disturbance has a substantial effect on the larger benthic fauna, with reductions in density and diversity, and changes in community structure, benthic biomass, production, and bioturbation and biogeochemical processes. Largely unknown, however, are the mechanisms by which the trawling impacts on the large benthic macro- and megafauna may influence the smaller meiofauna. To investigate this, a mesocosm experiment was conducted whereby benthic nematode communities from a non-trawled area were exposed to three different densities (absent, low, normal) of 7 large (> 10 mm) naturally co-occurring, bioturbating species which are potentially vulnerable to trawling disturbance. The results showed that total abundances of nematodes were lower if these large macrofauna species were present, but no clear nematode abundance effects could be assigned to the macrofauna density differences. Nematode community structure changed in response to macrofauna presence and density, mainly as a result of the reduced abundance of a few dominant nematode species. Any detectable effects seemed similar for nearly all macrofauna species treatments, supporting the idea that there may be a general indirect, macrofauna-mediated trawling impact on nematode communities. Explanations for these results may be, firstly, competition for food resources, resulting in spatial segregation of the meio- and macrobenthic components. Secondly, different densities of large macrofauna organisms may affect the nematode community structure through different intensities of bioturbatory disturbance or resource competition. These results suggest that removal or reduced densities of larger macrofauna species as a result of trawling disturbance may lead to increased nematode abundance and hints at the validity of interference competition between large macrofauna organisms and the smaller meiofauna, and the energy equivalence hypothesis, where a trade-off is observed between groups of organisms that are dependent on a common source of energy.