The ocean moderates anthropogenic climate change at the cost of profound alterations of its physics, chemistry, ecology, and services. Here, we evaluate and compare the risks of impacts on marine and coastal ecosystems—and the goods and services they provide—for growing cumulative carbon emissions under two contrasting emissions scenarios. The current emissions trajectory would rapidly and significantly alter many ecosystems and the associated services on which humans heavily depend. A reduced emissions scenario—consistent with the Copenhagen Accord’s goal of a global temperature increase of less than 2°C—is much more favorable to the ocean but still substantially alters important marine ecosystems and associated goods and services. The management options to address ocean impacts narrow as the ocean warms and acidifies. Consequently, any new climate regime that fails to minimize ocean impacts would be incomplete and inadequate.

/pdf/contrasting-futures-for-ocean-and-society-from-different-4ih2lstogv.pdf

Contrasting futures for ocean and society from different anthropogenic CO2 emissions scenarios

Global climate change is impacting organisms, biological communities and ecosystems around the world. While most research has focused on characterizing how the climate is changing, including modeling future climatic conditions and predicting the impacts of these conditions on biodiversity, it is also the case that climate change is altering the environmental impacts of chemical pollution. Future climate conditions are expected to influence both the worldwide distribution of chemicals and the toxi- cological consequences of chemical exposures to organisms. Many of the environmental changes associated with a warming global climate (e.g., increased average - and possibly extreme - temperatures; intense periods of drier and wetter conditions; reduced ocean pH; altered salinity dynamics in estuaries) have the potential to enhance organism susceptibility to chemical toxicity. Addi- tionally, chemical exposures themselves may impair the ability of organisms to cope with the changing environmental conditions of the shifting climate. Such reciprocity in the interactions between climate change and chemicals illustrates the complexity inherent in predicting the toxicological consequences of chemical exposures under future climate scenarios. Here, we summarize what is currently known about the potential reciprocal effects of climate change and chemical toxicity on wildlife, and depict current ap- proaches and ongoing challenges for incorporating climate effects into chemical testing and assessment. Given the rapid pace of new man-made chemistries, the development of accurate and rapid methods to evaluate multiple chemical and non-chemical stressors in an ecologically relevant context will be critical to understanding toxic and endocrine-disrupting effects of chemical pollutants under future climate scenarios (Current Zoology 61 (4): 669-689, 2015).

/pdf/forecasting-the-impacts-of-chemical-pollution-and-climate-f2p281dimn.pdf

Forecasting the impacts of chemical pollution and climate change interactions on the health of wildlife.

The production of marine protein from fishing and aquaculture is influenced by environmental conditions Ocean temperature, for example, can change the growth rate of cultured animals, or the distribution of wild stocks In turn these impacts may require changes in fishing or farming practices In addition to short-term environmental fluctuations, long-term climate-related trends are also resulting in new conditions, necessitating adjustment in fishing, farming and management approaches Longer-term climate forecasts, however, are seen as less relevant by many in the seafood sector owing to more immediate concerns Seasonal forecasts provide insight into upcoming environmental conditions, and thus allow improved decision making Forecasts based on dynamic ocean models are now possible and offer improved performance relative to statistical forecasts, particularly given baseline shifts in the environment as a result of climate change Seasonal forecasting is being used in marine farming and fishing operations in Australia, including wild tuna and farmed salmon and prawns, to reduce uncertainty and manage business risks Forecast variables include water temperature, rainfall and air temperature, and are considered useful up to approximately 4 months into the future, depending on the region and season of interest Species-specific habitat forecasts can also be made by combining these environment forecasts with biological habitat preference data Seasonal forecasts are useful when a range of options are available for implementation in response to the forecasts The use of seasonal forecasts in supporting effective marine management may also represent a useful stepping stone to improved decision making and industry resilience at longer timescales

Seasonal forecasting for decision support in marine fisheries and aquaculture

http://real.mtak.hu/31981/1/CrookAD_etal_ErosT_STE_ms.pdf

Human effects on ecological connectivity in aquatic ecosystems: Integrating scientific approaches to support management and mitigation

Behavioural fever, defined as an acute change in thermal preference driven by pathogen recognition, has been reported in a variety of invertebrates and ectothermic vertebrates. It has been suggested, but so far not confirmed, that such changes in thermal regime favour the immune response and thus promote survival. Here, we show that zebrafish display behavioural fever that acts to promote extensive and highly specific temperature-dependent changes in the brain transcriptome. The observed coupling of the immune response to fever acts at the gene–environment level to promote a robust, highly specific time-dependent anti-viral response that, under viral infection, increases survival. Fish that are not offered a choice of temperatures and that therefore cannot express behavioural fever show decreased survival under viral challenge. This phenomenon provides an underlying explanation for the varied functional responses observed during systemic fever. Given the effects of behavioural fever on survival and the fact that it exists across considerable phylogenetic space, such immunity–environment interactions are likely to be under strong positive selection.

/pdf/behavioural-fever-is-a-synergic-signal-amplifying-the-innate-3vukbcv046.pdf

Behavioural fever is a synergic signal amplifying the innate immune response

Temperature-dependent viral replication and antiviral apoptotic response in viral haemorrhagic septicaemia virus (VHSV)-infected olive flounder (Paralichthys olivaceus).

Regional differences in the response of mesozooplankton to oceanographic regime shifts in the northeast Asian marginal seas

To evaluate uncertainty and risk in biological reference points, we applied a bootstrapping method and a Bayesian procedure to estimate the related confidence intervals. Here we provide an example of the maximum sustainable yield (MSY) of turban shell, Batillus cornutus, estimated by the Schaefer and Fox models. Fitting the time series of catch and effort from 1968 to 2006 showed that the Fox model performs better than the Schaefer model. The estimated MSY and its bootstrap percentile confidence interval (CI) at ${\alpha}

Application of Bootstrap and Bayesian Methods for Estimating Confidence Intervals on Biological Reference Points in Fisheries Management

A transmission distribution estimation for real time Ebola virus disease epidemic model

Based on the detailed travel history of cases from 2006 to 2008 who reside in non-malarious areas, statistical estimates of the incubation periods were obtained The data suggest that cases fall into two categories with short- and long-term incubation periods, respectively 72 and 25 cases successfully met our criteria for inferring the durations of short- and long-term incubation periods The mean short- and long-term incubation periods were estimated to be 2542 days and 3286 days weeks, respectively

https://www.koreascience.kr:443/article/JAKO201013351016008.pdf

Estimation of the incubation period of P. vivax malaria in Korea from 2006 to 2008

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