Climate change affects marine biological processes from genetic to ecosystem levels [1-3]. Recent warming in the northeast Atlantic [4, 5] has caused distributional shifts in some fish species along latitudinal and depth gradients [6, 7], but such changes, as predicted by climate envelope models [8], may often be prevented because population movement requires availability of suitable habitat. We assessed the full impacts of warming on the commercially important European continental shelf fish assemblage using a data-driven Eulerian (grid-based) approach that accommodates spatial heterogeneity in ecological and environmental conditions. We analyzed local associations of species abundance and community diversity with climatic variables, assessing trends in 172 cells from records of >100 million individuals sampled over 1.2 million km(2) from 1980-2008. We demonstrate responses to warming in 72% of common species, with three times more species increasing in abundance than declining, and find these trends reflected in international commercial landings. Profound reorganization of the relative abundance of species in local communities occurred despite decadal stability in the presence-absence of species. Our analysis highlights the importance of focusing on changes in species abundance in established local communities to assess the full consequences of climate change for commercial fisheries and food security.

European continental shelf seas have experienced intense warming over the last 30 33 years 1 . In the North Sea, fishes have been comprehensively monitored throughout 34 this period and resulting data provide a unique record of changes in distribution and 35 abundance in response to climate change 2,3 . We use these data to demonstrate the 36 remarkable power of Generalised Additive Models (GAMs), trained on data earlier in 37 the time-series, to reliably predict trends in distribution and abundance in later years. 38Then, challenging process-based models that predict substantial and ongoing 39 poleward shifts of cold-water species 4,5 , we find that GAMs coupled with climate 40 projections predict future distributions of demersal (bottom-dwelling) fish species 41 over the next 50 years will be strongly constrained by availability of habitat of suitable 42depth. This will lead to pronounced changes in community structure, species 43 interactions and commercial fisheries, unless individual acclimation or population-44 level evolutionary adaptations enable fish to tolerate warmer conditions or move to 45 previously uninhabitable locations. 46 47While the temperature of the world's oceans has gradually risen through the 20 th Century, 48 the northeast Atlantic has experienced particularly intense warming, resulting in the North 49 Sea mean annual sea-surface temperature increasing by 1.3°C over the last 30 years 1 , a 50 rate four times faster than the global average 6 . Predictions for the North Sea suggest a 51 further 1.8°C rise in sea-surface temperatures during the next five decades (Hadley Centre 52 QUMP_ens_00 model, unpublished data supplied by J. Tinker) (Fig. 1). Impacts of recent 53 warming on northeast Atlantic marine ecosystems have been diverse, including 54 reorganisation of the plankton community 7 , modification to the phenology of fish spawning 8,9 , 55 and alterations of ecosystem interactions 10,11 . Due to its longstanding economic importance 56 to fisheries (reported landings in 2007 valued at $1.2 billion 1 ) and other industries, the 57 ecology of the North Sea has been intensively monitored throughout this period of recent 58 warming. 59 60 3 Analyses of North Sea fish surveys have revealed northerly range expansions of warmer-61 water species 12 , population redistributions to higher latitudes 2 and deeper water 13 , and 62 widespread changes in local abundance associated with warming, with impacts on 63 community structure 3 . This substantial modification to fish community composition in the 64 region has had an observable economic impact on fisheries, with landings of cold-adapted 65 species halved but landings of warm-adapted species increasing 2.5 times since the 1980s 3 ; 66 a pattern also identified in other marine ecosystems 14 . With a uniquely rich fish abundance 67 time-series from the period of warming, it is possible to split these data to assess how 68 predictions made using data from earlier years match observations from later years; a 69 validation approach which has been...

Summary1. Commercial fisheries risk unintentionally depleting local population components if stock management units do not reflect the population structure of the species. Atlantic cod Gadus morhua L. was over exploited in the sea areas around the British Isles in the last century and is struggling to recover. There is an urgent need to define the biological stock structure to improve management. 2. In this study, we used data recovered from temperature and depth loggers attached to 252 Atlantic cod to infer and map their movements around the British Isles. Individual cod showed a range of behaviours including migration, site fidelity and limited home ranging. We estimated home ranges and seasonal movements and test predictions based on data from population genetics. Cod from a northern offshore area in the North Sea did not mix with cod from the central and southern North Sea, which in turn did not mix with those from western areas (the Celtic and Irish Seas). 3. Cod experienced average monthly temperatures between 6 and 17°C and occupied average depths between 15 and 165 m. Cod that occupied the deeper northern offshore area lived in colder and less variable waters than elsewhere. Differences in thermal experience are likely to underpin variation in physiology and growth rate that will have implications for how the species responds to climate change. 4. This study provides evidence that cod living around the British Isles are comprised of at least one more distinct population unit that is currently recognized for stock management purposes. Failure to recognize this complexity of stock structure in past management plans is likely to have been a contributory factor to the over-exploitation of cod stocks around the British Isles. 5. Synthesis and applications. The results of this study and recent genetic research provide a new and more definitive understanding of movement patterns and population structure of cod around the British Isles. The applied implication of this is that spatially explicit adjustment of exploitation strategies, for example setting a maximum sustainable yield for each of the population units, should be considered to ensure sustainable harvesting of cod in the future.

2003. Managing Atlantic salmon in the mixed stock environment: challenges and considerations. e ICES Journal of Marine Science, 61: 1344e1358.Atlantic salmon, as a result of their population structure and behaviour, are potentially subject to a complex array of fisheries, ranging from those within rivers harvesting single stocks, to distant-water mixed stock fisheries that harvest fish from different countries, stock complexes, and continents. In addition, estuarine and in-river fisheries may catch fish from more than one stock or stock component, where these are present. One of the main challenges in managing salmon across this range of fisheries is to account for the differing status of stocks with respect to safe biological limits, noting that stocks of differing productivity may require different harvest strategies. Also, the existence of sequential harvest in different fisheries provides unique challenges, because decisions in an individual fishery cannot be made in isolation of the impacts of other fisheries on those stocks. We illustrate the uncertainties and complexities involved in managing mixed stocks of salmon, whether in homewaters or in distant-water fisheries, and examples are given to illustrate how science and management are, or should be, developing to face these challenges.

Most exploitation of Atlantic salmon (Salmo salar) is restricted to “homewater fisheries”, which operate close to or within the rivers of origin of the stocks, but two “distant-water fisheries” are permitted to operate off the west coast of Greenland and in the Norwegian Sea, and take salmon from a large number of rivers over a wide geographical area. Providing robust quantitative catch advice for these mixed-stock fisheries depends upon the ability to forecast stock abundance for about 2000 salmon river-stocks around the North Atlantic, more than 1500 of which are in Europe. A “run-reconstruction” model is presented for estimating the historic pre-fishery abundance (PFA) of salmon for countries or regions around the Northeast Atlantic, based upon catch data and estimates of non-reporting rates and exploitation rates. These estimates are then used to develop predictive models of PFA on the basis of estimates of the egg deposition, derived from the run-reconstruction model and various environmental data. Although the selected environmental indices correlated with the PFA of both southern and northern European stock complexes, the main statistical significance in the forecast models was provided by temporal trends in the PFA. Clearly, such a model is only tenable in the short term, and will be poor at predicting a major change in stock status. Alternative approaches, based upon juvenile production indices and including Bayesian techniques, are therefore being considered.

Hoare, D., Graham, N., and Schön, P-J. 2011. The Irish Sea data-enhancement project: comparison of self-sampling and national data-collection programmes—results and experiences. – ICES Journal of Marine Science, 68: 1778–1784. The Irish Sea Data Enhancement Pilot (ISDEP) was initiated by the UK and Irish fishing sectors, with the objective of improving the precision of commercial catch data (landings and discards) from vessels engaged in demersal trawling in the Irish Sea (ICES Division VIIa). The programme was supported by the Irish and UK Governments and managed by national laboratories. The experience of establishing and managing such a programme, including logistical, data-quality, and participation issues, is discussed. By contrasting with parallel national programmes, it is shown that the new data are robust and have improved precision. Experience has also shown that it is preferable to involve a few vessels in providing frequent samples, but that positive incentives are needed to maintain the participation.

The accessibility of databases of global or regional stock assessment outputs is leading to an increase in meta-analysis of the dynamics of fish stocks. In most of these analyses, each of the time-series is generally assumed to be directly comparable. However, the approach to stock assessment employed, and the associated modelling assumptions, can have an important influence on the characteristics of each time-series. We explore this idea by investigating recruitment time-series with three different recruitment parameterizations: a stock–recruitment model, a random-walk time-series model, and non-parametric “free” estimation of recruitment. We show that the recruitment time-series is sensitive to model assumptions and this can impact reference points in management, the perception of variability in recruitment and thus undermine meta-analyses. The assumption of the direct comparability of recruitment time-series in databases is therefore not consistent across or within species and stocks. Caution is therefore required as perhaps the characteristics of the time-series of stock dynamics may be determined by the model used to generate them, rather than underlying ecological phenomena. This is especially true when information about cohort abundance is noisy or lacking.

No abstract