Trophic amplification of climate warming

Ecosystems can alternate suddenly between contrasting persistent states due to internal processes or external drivers. It is important to understand the mechanisms by which these shifts occur, especially in exploited ecosystems. There have been several abrupt marine ecosystem shifts attributed either to fishing, recent climate change or a combination of these two drivers. We show that temperature has been an important driver of the trophodynamics of the North Sea, a heavily fished marine ecosystem, for nearly 50 years and that a recent pronounced change in temperature established a new ecosystem dynamic regime through a series of internal mechanisms. Using an end-to-end ecosystem approach that included primary producers, primary, secondary and tertiary consumers, and detritivores, we found that temperature modified the relationships among species through nonlinearities in the ecosystem involving ecological thresholds and trophic amplifications. Trophic amplification provides an alternative mechanism to positive feedback to drive an ecosystem towards a new dynamic regime, which in this case favours jellyfish in the plankton and decapods and detritivores in the benthos. Although overfishing is often held responsible for marine ecosystem degeneration, temperature can clearly bring about similar effects. Our results are relevant to ecosystem-based fisheries management (EBFM), seen as the way forward to manage exploited marine ecosystems.

Warm-water decapods and the trophic amplification of climate in the North Sea

A long-term time series of plankton and benthic records in the North Sea indicates an increase in decapods and a decline in their prey species that include bivalves and flatfish recruits. Here, we show that in the southern North Sea the proportion of decapods to bivalves doubled following a temperature-driven, abrupt ecosystem shift during the 1980s. Analysis of decapod larvae in the plankton reveals a greater presence and spatial extent of warm-water species where the increase in decapods is greatest. These changes paralleled the arrival of new species such as the warm-water swimming crab Polybius henslowii now found in the southern North Sea. We suggest that climate-induced changes among North Sea decapods have played an important role in the trophic amplification of a climate signal and in the development of the new North Sea dynamic regime.

Biomass changes and trophic amplification of plankton in a warmer ocean

Ocean warming can modify the ecophysiology and distribution of marine organisms, and relationships between species, with nonlinear interactions between ecosystem components potentially resulting in trophic amplification. Trophic amplification (or attenuation) describe the propagation of a hydroclimatic signal up the food web, causing magnification (or depression) of biomass values along one or more trophic pathways. We have employed 3-D coupled physical-biogeochemical models to explore ecosystem responses to climate change with a focus on trophic amplification. The response of phytoplankton and zooplankton to global climate-change projections, carried out with the IPSL Earth System Model by the end of the century, is analysed at global and regional basis, including European seas (NE Atlantic, Barents Sea, Baltic Sea, Black Sea, Bay of Biscay, Adriatic Sea, Aegean Sea) and the Eastern Boundary Upwelling System (Benguela). Results indicate that globally and in Atlantic Margin and North Sea, increased ocean stratification causes primary production and zooplankton biomass to decrease in response to a warming climate, whilst in the Barents, Baltic and Black Seas, primary production and zooplankton biomass increase. Projected warming characterized by an increase in sea surface temperature of 2.29 ± 0.05 °C leads to a reduction in zooplankton and phytoplankton biomasses of 11% and 6%, respectively. This suggests negative amplification of climate driven modifications of trophic level biomass through bottom-up control, leading to a reduced capacity of oceans to regulate climate through the biological carbon pump. Simulations suggest negative amplification is the dominant response across 47% of the ocean surface and prevails in the tropical oceans; whilst positive trophic amplification prevails in the Arctic and Antarctic oceans. Trophic attenuation is projected in temperate seas. Uncertainties in ocean plankton projections, associated to the use of single global and regional models, imply the need for caution when extending these considerations into higher trophic levels.

Clustering in non-parametric multivariate analyses.

Non-parametric multivariate analyses of complex ecological datasets are widely used. Following appropriate pre-treatment of the data inter-sample resemblances are calculated using appropriate measures. Ordination and clustering derived from these resemblances are used to visualise relationships among samples (or variables). Hierarchical agglomerative clustering with group-average (UPGMA) linkage is often the clustering method chosen. Using an example dataset of zooplankton densities from the Bristol Channel and Severn Estuary, UK, a range of existing and new clustering methods are applied and the results compared. Although the examples focus on analysis of samples, the methods may also be applied to species analysis. Dendrograms derived by hierarchical clustering are compared using cophenetic correlations, which are also used to determine optimum  in flexible beta clustering. A plot of cophenetic correlation against original dissimilarities reveals that a tree may be a poor representation of the full multivariate information. UNCTREE is an unconstrained binary divisive clustering algorithm in which values of the ANOSIM R statistic are used to determine (binary) splits in the data, to form a dendrogram. A form of flat clustering, k-R clustering, uses a combination of ANOSIM R and Similarity Profiles (SIMPROF) analyses to determine the optimum value of k, the number of groups into which samples should be clustered, and the sample membership of the groups. Robust outcomes from the application of such a range of differing techniques to the same resemblance matrix, as here, result in greater confidence in the validity of a clustering approach.

Clustering in non-parametric multivariate analyses.

Non-parametric multivariate analyses of complex ecological datasets are widely used. Following appropriate pre-treatment of the data inter-sample resemblances are calculated using appropriate measures. Ordination and clustering derived from these resemblances are used to visualise relationships among samples (or variables). Hierarchical agglomerative clustering with group-average (UPGMA) linkage is often the clustering method chosen. Using an example dataset of zooplankton densities from the Bristol Channel and Severn Estuary, UK, a range of existing and new clustering methods are applied and the results compared. Although the examples focus on analysis of samples, the methods may also be applied to species analysis. Dendrograms derived by hierarchical clustering are compared using cophenetic correlations, which are also used to determine optimum  in flexible beta clustering. A plot of cophenetic correlation against original dissimilarities reveals that a tree may be a poor representation of the full multivariate information. UNCTREE is an unconstrained binary divisive clustering algorithm in which values of the ANOSIM R statistic are used to determine (binary) splits in the data, to form a dendrogram. A form of flat clustering, k-R clustering, uses a combination of ANOSIM R and Similarity Profiles (SIMPROF) analyses to determine the optimum value of k, the number of groups into which samples should be clustered, and the sample membership of the groups. Robust outcomes from the application of such a range of differing techniques to the same resemblance matrix, as here, result in greater confidence in the validity of a clustering approach.