Relationships between North Atlantic salmon, plankton and hydroclimatic change in the Northeast Atlantic

The abundance of wild salmon (Salmo salar) in the North Atlantic has declined markedly since the late 1980s as a result of increased marine mortality that coincided with a marked rise in sea temperature in oceanic foraging areas. There is substantial evidence to show that temperature governs the growth, survival, and maturation of salmon during their marine migrations through either direct or indirect effects. In an earlier study (2003), long-term changes in three trophic levels (salmon, zooplankton, and phytoplankton) were shown to be correlated significantly with sea surface temperature (SST) and northern hemisphere temperature (NHT). A sequence of trophic changes ending with a stepwise decline in the total nominal catch of North Atlantic salmon (regime shift in ∼1986/1987) was superimposed on a trend to a warmer dynamic regime. Here, the earlier study is updated with catch and abundance data to 2010, confirming earlier results and detecting a new abrupt shift in ∼1996/1997. Although correlations between changes in salmon, plankton, and temperature are reinforced, the significance of the correlations is reduced because the temporal autocorrelation of time-series substantially increased due to a monotonic trend in the time-series, probably related to global warming. This effect may complicate future detection of effects of climate change on natural systems.

ICES status report on climate change in the North Atlantic

Although the physical and chemical principles that explain the warming of the Earth’s system resulting from emissions of CO2 and other greenhouse gases were understood at the end of the 19th century (Tyndall, 1861; Arrhenius, 1896) and at the beginning of the 20th century (Callendar, 1938), it was almost 100 years later, in the mid‐1980s, before it was realized that these processes were contributing to a rapid change in climate. The potential consequences of this global warming have still to be revealed and are difficult to anticipate.

Temporal change in UK marine communities: trends or regime shifts?

A regime shift is a large, sudden, and long-lasting change in the dynamics of an ecosystem, affecting multiple trophic levels. There are a growing number of papers that report regime shifts in marine ecosystems. However, the evidence for regime shifts is equivocal, because the methods used to detect them are not yet well developed. We have collated over 300 biological time series from seven marine regions around the UK, covering the ecosystem from phytoplankton to marine mammals. Each time series consists of annual measures of abundance for a single group of organisms over several decades. We summarised the data for each region using the first principal component, weighting either each time series or each biological component (e.g. plankton, fish, benthos) equally. We then searched for regime shifts using Rodionov’s regime shift detection (RSD) method, which found regime shifts in the first principal component for all seven marine regions. However, there are consistent temporal trends in the data for six of the seven regions. Such trends violate the assumptions of RSD. Thus, the regime shifts detected by RSD in six of the seven regions are likely to be artefacts caused by temporal trends. We are therefore developing more appropriate time series models for both single populations and whole communities that will explicitly model temporal trends and should increase our ability to detect true regime shift events.

Black-legged kittiwakes as indicators of environmental change in the North Sea; evidence from long-term studies

Top predators, particularly seabirds, have repeatedly been suggested as indicators of marine ecosystem status. One region currently under pressure from human fisheries and climate change is the North Sea. Standardized seabird monitoring data have been collected on the Isle of May, an important seabird colony in the northwestern North Sea, over the last 10–20 years. Over this period oceanographic conditions have varied markedly, and between 1990 and 1999 a major industrial fishery for sandlance (Ammodytes marinus), the main prey of most seabird species, was prosecuted nearby. Sandlance fishing grounds close to seabird colonies down the east coast of the UK were closed in 2000 in an attempt to improve foraging opportunities for breeding seabirds, particularly black-legged kittiwakes (Rissa tridactyla). Initially this closure seemed to be beneficial for kittiwakes with breeding success recovering to pre-fishery levels. However, despite the ban continuing, kittiwakes and many other seabird species in the North Sea suffered severe breeding failures in 2004. In this paper, we test the predictive power of four previously established correlations between kittiwake breeding success and climatic/trophic variables to explain the observed breeding success at the Isle of May in 2004. During the breeding season, kittiwakes at this colony switch from feeding on 1+ group to 0 group sandlance, and results up until 2003 indicated that availability of both age classes had a positive effect on kittiwake breeding success. The low breeding success of kittiwakes in 2004 was consistent with the late appearance and small body size of 0 group sandlance, but at odds with the two variables likely to operate via 1 group availability (lagged winter sea surface temperature and larval sandlance cohort strength in 2003). The reason for the discrepancy is currently unknown, but analysis of 1 group sandlance body composition indicated that lipid content in 2004 was extremely low, and thus fish eaten by kittiwakes during pre-breeding and early incubation were likely to be of poor quality. Monitoring of reproductive success of kittiwakes, although useful, was clearly not sufficient to tease apart the complex causation underlying the 2004 event. Monitoring programs such as this, therefore, need to be complemented by detailed research to identify the mechanisms involved, and to attribute and predict the effects of natural and human-induced environmental change.

Defining scenarios of future vectors of change in marine life and associated economic sectors

Addressing the multitude of challenges in marine policy requires an integrated approach that considers the multitude of drivers, pressures, and interests, from several disciplinary angles. Scenarios are needed to harmonise the analyses of different components of the marine system, and to deal with the uncertainty and complexity of the societal and biogeophysical dynamics in the system. This study considers a set of socio-economic scenarios to (1) explore possible futures in relation to marine invasive species, outbreak forming species, and gradual changes in species distribution and productivity; and (2) harmonise the projection modelling performed within associated studies. The exercise demonstrates that developing interdisciplinary scenarios as developed in this study is particularly complicated due to (1) the wide variety in endogeneity or exogeneity of variables in the different analyses involved; (2) the dual role of policy decisions as variables in a scenario or decisions to be evaluated and compared to other decisions; and (3) the substantial difference in time scale between societal and physical drivers.

Analyses of sublittoral macrobenthic community change in a marine nature reserve using similarity profiles (SIMPROF).

Sublittoral macrobenthic communities in the Skomer Marine Nature Reserve (SMNR), Pembrokeshire, Wales, were sampled at 10 stations in 1993, 1996, 1998, 2003, 2007 and 2009 using a Day grab and a 0.5 mm mesh. The time series is analysed using Similarities Profiles (SIMPROF) tests and associated methods. Q-mode analysis using clustering with Type 1 SIMPROF addresses multivariate structure among samples, showing that there is clear structure associated with differences among years. Inverse (r-mode) analysis using Type 2 SIMPROF decisively rejects a hypothesis that species are not associated with each other. Clustering of the variables (species) with Type 3 SIMPROF identifies groups of species which covary coherently through the time-series. The time-series is characterised by a dramatic decline in abundances and diversity between the 1993 and 1996 surveys. By 1998 there had been a shift in community composition from the 1993 situation, with different species dominating. Communities had recovered in terms of abundance and species richness, but different species dominated the community. No single factor could be identified which unequivocally explained the dramatic changes observed in the SMNR. Possible causes were the effects of dispersed oil and dispersants from the Sea Empress oil spill in February 1996 and the cessation of dredge-spoil disposal off St Anne’s Head in 1995, but the most likely cause was severe weather. With many species, and a demonstrable recovery from an impact, communities within the SMNR appear to be diverse and resilient. If attributable to natural storms, the changes observed here indicate that natural variability may be much more important than is generally taken into account in the design of monitoring programmes.

The Industrial Context of Occupational Mobility: Change in Structure

The neglect of a consideration of history has been a feature of mobility research. ‘History’ affects the results of analyses of social mobility by altering the occupational/industrial structure and by encouraging exchange mobility. Changes in industrial structure are rooted more directly in historical causes and can be seen as more fundamental than changes in occupational structure. Following a substantial review of the secondary literature on changes in industrial and occupational structure in Northern Ireland, loglinear analyses of intra- and intergenerational mobility tables for sociologically-derived cohort generations that incorporate occupational and industrial categories are presented. Structural and inheritance effects for industry are as significant as those for occupation. Given the well-established finding of ‘constant social fludity’ in mobility tables once structural effects are controlled, the inclusion of categorization by industry is necessary in order to reach an accurate understanding of occupational mobility and the role of historical change in mobility.