1000 resultados para Climate.


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1.Commercial fishing is an important socio-economic activity in coastal regions of the UK and Ireland. Ocean–atmospheric changes caused by greenhouse gas emissions are likely to affect future fish and shellfish production, and lead to increasing challenges in ensuring long-term sustainable fisheries management. 2.The paper reviews existing knowledge and understanding of the exposure of marine ecosystems to ocean-atmospheric changes, the consequences of these changes for marine fisheries in the UK and Ireland, and the adaptability of the UK and Irish fisheries sector. 3.Ocean warming is resulting in shifts in the distribution of exploited species and is affecting the productivity of fish stocks and underlying marine ecosystems. In addition, some studies suggest that ocean acidification may have large potential impacts on fisheries resources, in particular shell-forming invertebrates. 4.These changes may lead to loss of productivity, but also the opening of new fishing opportunities, depending on the interactions between climate impacts, fishing grounds and fleet types. They will also affect fishing regulations, the price of fish products and operating costs, which in turn will affect the economic performance of the UK and Irish fleets. 5.Key knowledge gaps exist in our understanding of the implications of climate and ocean chemistry changes for marine fisheries in the UK and Ireland, particularly on the social and economic responses of the fishing sectors to climate change. However, these gaps should not delay climate change mitigation and adaptation policy actions, particularly those measures that clearly have other ‘co-benefits’.

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Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment.

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Antarctic krill is a cold water species, an increasingly important fishery resource and a major prey item for many fish, birds and mammals in the Southern Ocean. The fishery and the summer foraging sites of many of these predators are concentrated between 0 degrees and 90 degrees W. Parts of this quadrant have experienced recent localised sea surface warming of up to 0.2 degrees C per decade, and projections suggest that further widespread warming of 0.27 degrees to 1.08 degrees C will occur by the late 21st century. We assessed the potential influence of this projected warming on Antarctic krill habitat with a statistical model that links growth to temperature and chlorophyll concentration. The results divide the quadrant into two zones: a band around the Antarctic Circumpolar Current in which habitat quality is particularly vulnerable to warming, and a southern area which is relatively insensitive. Our analysis suggests that the direct effects of warming could reduce the area of growth habitat by up to 20%. The reduction in growth habitat within the range of predators, such as Antarctic fur seals, that forage from breeding sites on South Georgia could be up to 55%, and the habitat's ability to support Antarctic krill biomass production within this range could be reduced by up to 68%. Sensitivity analysis suggests that the effects of a 50% change in summer chlorophyll concentration could be more significant than the direct effects of warming. A reduction in primary production could lead to further habitat degradation but, even if chlorophyll increased by 50%, projected warming would still cause some degradation of the habitat accessible to predators. While there is considerable uncertainty in these projections, they suggest that future climate change could have a significant negative effect on Antarctic krill growth habitat and, consequently, on Southern Ocean biodiversity and ecosystem services.

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Observations of Earth from space have been made for over 40 years and have contributed to advances in many aspects of climate science. However, attempts to exploit this wealth of data are often hampered by a lack of homogeneity and continuity and by insufficient understanding of the products and their uncertainties. There is, therefore, a need to reassess and reprocess satellite datasets to maximize their usefulness for climate science. The European Space Agency has responded to this need by establishing the Climate Change Initiative (CCI). The CCI will create new climate data records for (currently) 13 essential climate variables (ECVs) and make these open and easily accessible to all. Each ECV project works closely with users to produce time series from the available satellite observations relevant to users' needs. A climate modeling users' group provides a climate system perspective and a forum to bring the data and modeling communities together. This paper presents the CCI program. It outlines its benefit and presents approaches and challenges for each ECV project, covering clouds, aerosols, ozone, greenhouse gases, sea surface temperature, ocean color, sea level, sea ice, land cover, fire, glaciers, soil moisture, and ice sheets. It also discusses how the CCI approach may contribute to defining and shaping future developments in Earth observation for climate science.

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This paper reviews current literature on the projected effects of climate change on marine fish and shellfish, their fisheries, and fishery-dependent communities throughout the northern hemisphere. The review addresses the following issues: (i) expected impacts on ecosystem productivity and habitat quantity and quality; (ii) impacts of changes in production and habitat on marine fish and shellfish species including effects on the community species composition, spatial distributions, interactions, and vital rates of fish and shellfish; (iii) impacts on fisheries and their associatedcommunities; (iv) implications for food security and associated changes; and (v) uncertainty andmodelling skill assessment. Climate change will impact fish and shellfish, their fisheries, and fishery-dependent communities through a complex suite of linked processes. Integrated interdisciplinary research teams are forming in many regions to project these complex responses. National and international marine research organizations serve a key role in the coordination and integration of research to accelerate the production of projections of the effects of climate change on marine ecosystems and to move towards a future where relative impacts by region could be compared on a hemispheric or global level. Eight research foci were identified that will improve the projections of climate impacts on fish, fisheries, and fishery-dependent communities.

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We applied coincident Earth observation data collected during 2008 and 2009 from multiple sensors (RA2, AATSR and MERIS, mounted on the European Space Agency satellite Envisat) to characterise environmental conditions and integrated sea-air fluxes of CO2 in three Arctic seas (Greenland, Barents, Kara). We assessed net CO2 sink sensitivity due to changes in temperature, salinity and sea ice duration arising from future climate scenarios. During the study period the Greenland and Barents seas were net sinks for atmospheric CO2, with integrated sea-air fluxes of -36 +/- 14 and -11 +/- 5 Tg C yr(-1), respectively, and the Kara Sea was a weak net CO2 source with an integrated sea-air flux of +2.2 +/- 1.4 TgC yr(-1). The combined integrated CO2 sea-air flux from all three was -45 +/- 18 TgC yr(-1). In a sensitivity analysis we varied temperature, salinity and sea ice duration. Variations in temperature and salinity led to modification of the transfer velocity, solubility and partial pressure of CO2 taking into account the resultant variations in alkalinity and dissolved organic carbon (DOC). Our results showed that warming had a strong positive effect on the annual integrated sea-air flux of CO2 (i.e. reducing the sink), freshening had a strong negative effect and reduced sea ice duration had a small but measurable positive effect. In the climate change scenario examined, the effects of warming in just over a decade of climate change up to 2020 outweighed the combined effects of freshening and reduced sea ice duration. Collectively these effects gave an integrated sea-air flux change of +4.0 TgC in the Greenland Sea, +6.0 Tg C in the Barents Sea and +1.7 Tg C in the Kara Sea, reducing the Greenland and Barents sinks by 11% and 53 %, respectively, and increasing the weak Kara Sea source by 81 %. Overall, the regional integrated flux changed by +11.7 Tg C, which is a 26% reduction in the regional sink. In terms of CO2 sink strength, we conclude that the Barents Sea is the most susceptible of the three regions to the climate changes examined. Our results imply that the region will cease to be a net CO2 sink in the 2050s.

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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.

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Modeling of global climate change is moving from global circulation model (GCM)-type projections with coupled biogeochemical models to projections of ecological responses, including food web and upper trophic levels. Marine and coastal ecosystems are highly susceptible to the impacts of global climate change and also produce significant ecosystem services. The effects of global climate change on coastal and marine ecosystems involve a much wider array of effects than the usual temperature, sea level rise, and precipitation. This paper is an overview for a collection of 12 papers that examined various aspects of global climate change on marine ecosystems and comprise this special issue. We summarized the major features of the models and analyses in the papers to determine general patterns. A wide range of ecosystems were simulated using a diverse set of modeling approaches. Models were either 3-dimensional or used a few spatial boxes, and responses to global climate change were mostly expressed as changes from a baseline condition. Three issues were identified from the across-model comparison: (a) lack of standardization of climate change scenarios, (b) the prevalence of site-specific and even unique models for upper trophic levels, and (c) emphasis on hypothesis evaluation versus forecasting. We discuss why these issues are important as global climate change assessment continues to progress up the food chain, and, when possible, offer some initial steps for going forward.

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Inter-annual variability in the timing of phytoplankton spring bloom and phytoplankton community structure in the central North Atlantic Ocean was quantified using ocean color data and continuous plankton recorder (CPR) data. This variability was related to the North Atlantic Oscillation using correlation analysis and multivariate auto-regression models. The initiation of the spring bloom derived from CPR phytoplankton color index data is similar to that derived from satellite chlorophyll, and exhibits a nominal correlation with the sea surface temperature (SST) and the North Atlantic Oscillation (NAO). The extrapolated spring bloom timing suggested later initiation of blooms in the mid-1980s and earlier initiation of blooms in the 1990s. The climatological phytoplankton community structure in the central North Atlantic is dominated by diatoms, except for a shift in community composition favoring dinoflagellates in August. The ratio of diatoms to total phytoplankton abundance and the ratio of dinoflagellates to total phytoplankton abundance are both closely correlated with the NAO and SST. The extended time series of phytoplankton community structure between 1985 and 2009, deduced from the time series of SST and NAO over the same interval, showed a decadal shift away from diatoms towards dinoflagellates. The linkages between the NAO, and changes in stratification and phytoplankton processes occur over a larger scale than previously observed.

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Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

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Following the publication of our paper (Attrill et al. 2007), we became quickly aware of a couple of errors. We have subsequently been collaborating with Dr. Chris Lynam (Lynam et al. 2004, 2005) to bring together our two datasets, explore the common patterns within our data, and attempt to provide a consensus on how climate is affecting gelatinous plankton in the North Sea. During this reanalysis, two errors within the data were discovered, one involving a transcription error of a column of residuals during de-trended analysis, the other a major data entry error deep in the Continuous Plankton Recorder (CPR) database for sector B2. Here we present a revised version of table 1 from Attrill et al. (2007) to incorporate corrections to these transcription and data entry errors. These corrections alter some of the results in our original data table, mainly to increase and strengthen the number of significant relations we found (e.g., for sector B2 and whole sea area); all previous main results remain robustly significant. Following discussions with Dr. Lynam, two clarifications of statements made in Attrill et al. (2007) are also required. Page 482, Results, last line of first column: ‘‘There were no...robust, consistent relations between jellyfish frequency and any environmental variables for B and D… contrary to the findings of previous shorter time series (Lynam et al. 2005).’’ The Lynam et al. (2004, 2005) papers presented no data for the D sector and found no link in the B sector, contrary to our revised results. Page 482, Discussion, paragraph 1, last sentence: ‘‘… positive association … North of Scotland (Lynam et al. 2005) … does not appear to be maintained.’’ Our paper did not report on any data that covered Lynam et al.’s (2005) North of Scotland area so the statement is not directly supported, although their positive relation North of Scotland, when considered in conjunction with inflow, may agree with the C2 and B2 results of Attrill et al. (2007).