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We present the results of a study of the connectivity between Pacific cod spawning and nursery areas, and settlement of Pacific cod in the Gulf of Alaska. This work was conducted to address the hypothesis that spatial and temporal patterns of recruitment are related to variability in connectivity between spawning and nursery areas. To examine this hypothesis, we developed a Lagrangian, biophysical, individual-based model of Pacific cod early life history and dispersal using the Dispersal Model for Early Life Stages (DisMELS) framework. This model is driven by currents and scalars such as temperature from a version of the Regional Oceanographic Model System (ROMS) developed for the Gulf of Alaska. Results of our study show connectivity patterns predicted by the model that agree with our understanding (based on genetic analyses) that there is a high degree of localized retention in Pacific cod. The results indicate that the Shumagin Islands and Prince William Sound regions may serve as important collectors of Pacific cod recruits from upstream spawning areas. We also find correlations between individual-based model outputs and several large-scale climate indicators that appear to show settlement in several important nursery areas, and recruitment overall, are positively affected by slower gyre circulation in the Gulf of Alaska. We hypothesize that this is due to enhancement of retention, settlement in the Shumagin Island region, and reduction of transport of young cod out of the Gulf of Alaska to the southwest.

Little is known about the mechanism of transport that enables age-0 sablefish (Anoplopoma fimbria) to reach suitable nursery sites from spawning locations far offshore, or the strength of the connection between individual spawning sites and nursery areas, or how variability in the strength of these connections may impact recruitment success. Using a model for the early life stages of sablefish, we explored the variability in connectivity between spawning and recruitment sites that can arise solely from interannual variability in environmental forcing and its impact on transport. Our major findings are that 1) the model indicates young sablefish settling in nursery areas in the Gulf of Alaska were most likely spawned in the eastern Gulf; 2) sablefish spawned in the western Gulf of Alaska are unlikely to settle anywhere in the Gulf, and are more likely to be advected farther west, perhaps to settle in the Aleutian islands or Bering Sea (to contribute to the Alaska population, they would have to undergo an active return migration as they mature); 3) total connectivity between all spawning sites and nursery areas showed stronger correlation with recruitment estimates than the strength of connections to or from specific regions; and 4) transport to St. John Baptist Bay, a known sablefish nursery area, was not the most probable end point for sablefish spawned throughout our Gulf of Alaska model domain. This suggests that young individuals arrive at this persistent nursery area due to directional swimming behavior, highly localized spawning, or small-scale currents not captured in the hydrographic model. The fact that no single correlate in our analysis had a very strong relationship to sablefish recruitment indicates that recruitment variability arises from complex interactions between the environment and the individual, and a possible disconnect in spatial scales between the Gulf of Alaska sablefish IBM and the broader sablefish stock assessment, which includes both the GOA and the Eastern Bering Sea, as well as possible contributions from Canadian stocks to the south. Our analyses determined that although the timing and extent of this transport shows significant interannual variability, both the location of likely sablefish spawning (source) areas and the comparative strength of connectivity between spawning and nursery sites appear to be relatively consistent year-to-year.

Little is known regarding the importance of early-life transport and dispersion mechanisms in determining recruitment variability for Pacific ocean perch (POP) in the Gulf of Alaska (GOA). These mechanisms influence the degree of, and variability in, connectivity between offshore natal areas (parturition sites) and inshore demersal nursery habitats for young-of-the year juveniles, and may thus play an important role in the “gauntlet” that individuals must survive from parturition to recruitment. As a first attempt to assess interannual variability in connectivity between natal and nursery areas for POP in the GOA in a synthetic manner, we developed a coupled biophysical individual-based model (IBM) for POP early life history and dispersal with simple representations of active vertical movement, passive horizontal movement, growth, and settlement in appropriate nursery habitat to integrate known early-life traits with variability in environmental forcing. We used an oceanographic model for the GOA based on the Regional Ocean Modeling system (ROMS) to provide the underlying daily physical environment to force the IBM for 1996–2011 and simulated hundreds of thousands of individual POP from parturition along the shelf break to settlement in inshore demersal nursery habitats as young-of-the-year. We used the IBM results to assess spatial patterns of annual “maximum potential” connectivity between presumed natal and nursery areas at alongshore scales of ~ 150 km, as well as the interannual variability in these patterns. Results showed that, even in the absence of mortality, most (> 70%) individuals were unsuccessful in dispersing from presumed natal areas along the continental shelf break to inshore nursery areas. For those that were successful, connectivity was directed in a counterclockwise fashion (southeast to northwest) around the GOA following prevailing current patterns. Typical dispersion distances were on the order of 100's of km alongshore, much larger than those inferred from genetic sampling. Natal areas from which the highest fractions of successful individuals originated were in the southeast GOA, while the nursery areas most frequently reached by those successful individuals were in the central GOA. POP from natal areas in the western GOA were consistently exported from the system and likely contribute little to the GOA population, although they may contribute to populations in the Aleutian Islands and eastern Bering Sea. We also found that annual indices derived from the connectivity matrices were not very strongly related to any of a suite of basin- and regional-scale environmental indices, reflecting the overall complexity and scale of the pathways POP in the GOA may undertake during their early life stages and suggesting that multiple drivers operating at different spatial and temporal scales influence connectivity patterns. Finally, while our results indicate that interannual variability in physical transport may have a substantial impact on connectivity, we found little support for the hypothesis that this alone drives variability in POP recruitment.

17 USC 105 interim-entered record; under review. The article of record as published may be found at https://doi.org/10.3390/atmos11101090 Rivers of the Arctic will become ever more important for the global climate, since they carry a majority of continental dissolved organic carbon flux into the rapidly changing polar ocean. Aqueous organics comprise a wide array of functional groups, several of which are likely to impact coastal and open water biophysical properties. Light attenuation, interfacial films, aerosol formation, gas release and momentum exchange can all be cited. We performed Lagrangian kinetic modeling for the evolution of riverine organic chemistry as the molecules in question make their way from the highlands to Arctic outlets. Classes as diverse as the proteins, sugars, lipids, re-condensates, humics, bio-tracers and small volatiles are all included. Our reduced framework constitutes an idealized northward flow driving a major hydrological discharge rate and primarily representing the Russian Lena. Mountainous, high solute and tundra sources are all simulated, and they meet up at several points between soil and delta process reactors. Turnover rates are parameterized beginning with extrapolated coastal values imposed along a limited tributary network, with connections between different terrestrial sub-ecologies. Temporal variation of our total dissolved matter most closely resembles the observations when we focus on the restricted removal and low initial carbon loads, suggesting relatively slow transformation along the water course. Thus, channel combinations and mixing must play a dominant role. Nevertheless, microbial and photochemical losses help determine the final concentrations for most species. Chemical evolution is distinct for the various functionalities, with special contributions from pre- and post-reactivity in soil and delta waters. Several functions are combined linearly to represent the collective chromophoric dissolved matter, characterized here by its absorption. Tributaries carry the signature of lignin phenols to segregate tundra versus taiga sources, and special attention is paid to the early then marine behaviors of low molecular weight volatiles. Heteropolycondensates comprise the largest percentage of reactive carbon in our simulations due to recombination/accumulation, and they tend to be preeminent at the mouth. Outlet concentrations of individual structures such as amino acids and absorbers lie above threshold values for biophysical influence, on the monolayer and light attenuation. The extent of coastal spreading is examined through targeted regional box modeling, relying on salinity and color for calibration. In some cases, plumes reach the scale of peripheral arctic seas, and amplification is expected during upcoming decades. Conclusions are mapped from the Lena to other boreal discharges, and future research questions are outlined regarding the bonding type versus mass release as permafrost degrades. Dynamic aqueous organic coupling is recommended for polar system models, from headwaters to coastal diluent. This research was supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling (EESM) program, within the U.S. Department of Energy’s Office of Science. It is a direct contribution to the HiLAT-RASM project. Funds were also provided by the closely related RUBISCO biogeochemistry validation effort, home to ILAMB and IOMB (International Land and Ocean Model Benchmarking). This research was funded by U.S. Department of Energy: OBER RGMA.

We combined field data and the output from a climate-to-fish coupled biophysical model to calculate weekly climatologies and 1971–2009 time series of physical and biological drivers for 16 distinct regions of the eastern Bering Sea shelf and slope. We focus on spatial trends and physical-biological interactions as a framework to compare model output to localized or season-specific observations. Data on pollock (≥8 cm) diet were used to evaluate energy flows and zooplankton dynamics predicted by the model. Model validation shows good agreement to sea-ice cover albeit with a one month delay in ice retreat. Likewise, the timing of spring phytoplankton blooms in the model were delayed approximately one month in the south and extend further into summer, but the relative timing between the spring and fall bloom peaks was consistent with observations. Ice-related primary producers may shift the timing of the spring bloom maximum biomass earlier in years when sea ice was still present after mid-March in the southern regions. Including the effects of explicit, dynamic fish predation on zooplankton in the model shifts the seasonal spring peak and distribution of zooplankton later in the year relative to simulations with implicit predation dependent only on zooplankton biomass and temperature; the former capturing the dynamic demand on zooplankton prey by fish. Pollock diets based on stomach samples collected in late fall and winter from 1982–2013 show overwintering euphausiids and small pollock as key prey items in the outer and southern Bering Sea shelf; a characteristic not currently present in the model. The model captured two large-scale gradients, supported by field data, characterizing the overall dynamics: 1) inshore to off-shelf physical and biological differences with a gradient in inter-annual variability from higher frequency inshore to lower frequency offshore; and 2) latitudinal gradients in the timing of events. The combined effects of length of day, bathymetry, and tides, which are consistent from year to year, and the two large-scale gradients, characterize the environment on which regional differences were based and restrict their inter-annual and seasonal variability. Thus, the relative timing and sequence of events remained consistent within regions. The combination of model outputs and observational data revealed specific ecosystem processes: (1) The spatial progression in the timing, peaks and sequence of events over the shelf is driven by wind, sea ice, and stratification and creates a seasonal expansion and contraction of the warmer pelagic and bottom habitat suitable to pollock. (2) The seasonal warming of air temperature and the spring-summer expansion of the warm pelagic and bottom habitats influence the ice retreat and the associated ice edge and open water spring blooms, as well as subsequent production/abundance of copepods and euphausiids. (3) These warmer conditions favor pelagic energy flows to pollock (≥10 cm) and allow their distribution to expand shoreward and northward along the shelf break. (4) The fall-winter expansion of the seasonal ice cover drives the contraction of warmer waters towards the outer and southwest shelf and favors benthic energy flows over most of the shelf. There, fall blooms allow for additional lipid storage by large copepods and euphausiids that sink close to the bottom where they either go into diapause or have a restricted diel migration over winter. (5) During these cold months, the preferred pollock habitat shifts and contracts towards the outer and southwest shelf where their increased density and reduced prey availability leads to winter pollock cannibalism and consumption of overwintering euphausiids. Our project highlights the benefits of linking continuous and long-term field work with the development and implementation of highly complex models. In the face of uncertainty, simulations such as these, tightly coupled to field programs, will be instrumental as testbeds for process exploration and management evaluation, increasing their relevance for future fisheries and ecosystem management and strategic planning.

Three global climate simulations from the Intergovernmental Panel on Climate Change Fourth Assessment (AR4) were used as physical forcing to drive a regional model that includes both physical and biological elements of the Bering Sea. Although each downscaled projection indicates a warming of 1–2 °C between 2010 and 2040 on the Bering Sea shelf, the interannual and interdecadal details of this trend vary considerably among the three realizations. In each case, the magnitude of presently observed interannual variability of bottom temperatures and ice cover is found in the models to be maintained out to at least 2040, but with a steadily increasing probability of warm years with less ice on the southern shelf. The overall trends indicate warmer temperatures and the retreat of ice in the southeastern Bering Sea, but continued ice cover in the northeastern Bering Sea. Sensitivity analyses suggest both increasing air temperature and northward wind stress as primary drivers of higher water-column temperatures. Based on currently available models, changes in shortwave radiation are not likely to have a significant role in this warming. Warming trends on the outer shelf may lead to decreased production of large crustacean zooplankton at that location, but could increase such production on the inner shelf.

Euphausiids are an important component of the eastern Bering Sea marine ecosystem. We synthesized information on the ecological roles of two species, Thysanoessa raschii, which predominates over the Middle and Inner Shelf Domains, and Thysanoessa inermis, which predominates over the Outer Shelf Domain. Although estimates of euphausiid biomass across the shelf are not well constrained, we estimated that, between April and July, 2004–2010, euphausiid biomass was 3.08–5.25 g C m−2 on the outer shelf and 1.95–3.92 g C m−2 on the middle shelf. Modeled estimates of euphausiid production, for spring and summer combined, varied between 0.043 g C m−2 d−1 and 0.051 g C m−2 d−1, depending on location, with a mean of 0.048 g C m−2 d−1. Recently reported field measurements of annual primary production over the southeastern Bering Sea in 2008–2009 vary between 0.06 and 6.65 g C m−2 d−1, with a mean of 1.262 g C m−2 d−1±2.049 g C m−2 d−1 in spring and summer combined, a level sufficient to support euphausiids, at least on an annualized basis. Walleye pollock (Gadus chalcogrammus, hereafter pollock) is the single most important consumer of euphausiids over the eastern Bering Sea shelf. We estimated that pollock consumed between 0.0042 and 0.019.7 g C m−2 d−1 of euphausiids, depending on year, with a mean of 0.011 g C m−2 d−1 in summer averaged over 1999–2009. This consumption is equivalent to between 17% and 29% of summer euphausiid production, depending on location. Over the period for which data were available (2004–2012), we observed a strong negative relationship between euphausiid biomass as determined in acoustic surveys and pollock biomass as estimated in the eastern Bering Sea pollock stock assessment (r2=0.82). During this time period, sea-surface temperature was the second strongest predictor of euphausiid biomass, (r2=0.63). However, for the period 2004–2010, bottom temperature (r2=0.94) was the strongest predictor, followed by pollock biomass from the pollock stock assessment (r2=0.82), and sea-surface temperature (r2=0.81). Mean pollock density in the acoustic surveys was not a powerful predictor of euphausiid biomass during either period. In spatially explicit multiple regression analyses for the periods 2004–2012 and 2004–2010 those formulations that included sea-surface and bottom temperatures as well as survey estimates of pollock had the greatest explanatory value. However, when either or both temperature terms were dropped, the explanatory value of the models dropped considerably. When pollock biomass was dropped from the models, there was little change in explanatory value compared to the full model. Euphausiid production and pollock consumption data coupled with a negative relationship between euphausiid biomass and stock assessment estimates of pollock biomass indicate a top-down predation effect. However, strong negative relationships between euphausiid biomass and water temperatures indicate the influence of a bottom-up mechanism. The apparent differences in these results may relate to the different spatial and temporal scales used to assess the pollock biomass used in the analyses. Alternatively, euphausiid biomass may be strongly controlled during a restricted portion of the year, such as spring, if critical food needs are not met in some years. We lack the data necessary to resolve these alternative hypotheses.

We have recently argued that marine interfacial surface tension must have a distinctive biogeography because it is mediated by fresh surfactant macromolecules released locally through the food web. Here we begin the process of quantification for associated climate flux implications. A low dimensionality (planar) equation of state is invoked at the global scale as our main analysis tool. For the reader&rsquo, s convenience, fundamental surfactant physical chemistry principles are reviewed first, as they pertain to tangential forces that may alter oceanic eddy, ripple, and bubble fields. A model Prandtl (neutral) wind stress regime is defined for demonstration purposes. It is given the usual dependence on roughness, but then in turn on the tension reduction quantity known as surface pressure. This captures the main net influences of biology and detrital organics on global microlayer physics. Based on well-established surrogate species, tangent pressures are related to distributed ecodynamics as reflected by the current marine systems science knowledge base. Reductions to momentum and related heat-vapor exchange plus gas and salt transfer are estimated and placed on a coarse biogeographic grid. High primary production situations appear to strongly control all types of transfer, whether seasonally or regionally. Classic chemical oceanographic data on boundary state composition and behaviors are well reproduced, and there is a high degree of consistency with conventional micrometeorological wisdom. But although our initial best guesses are quite revealing, coordinated laboratory and field experiments will be required to confirm the broad hypotheses even partially. We note that if the concepts have large scale validity, they are super-Gaian. Biological control over key planetary climate-transfer modes may be accomplished through just a single rapidly renewed organic monolayer.

Interpretation of zooplankton field observations on the Gulf of Alaska (GOA) shelf is complicated by the complex physical environment of currents, eddies and meanders which mix oceanic and coastal water masses to varying degrees. We therefore developed a lower trophic level model embedded in an ocean circulation model to examine the effects of wind, runoff and temperature on transport, biomass and production of microzooplankton and copepods on the northern GOA shelf and adjacent ocean. Mean microzooplankton biomass varied from 10–90 and 10–50 mg C m− 3 in the upper 50 m for field measurements and simulations respectively. Mean simulated and measured copepod biomass in the upper 100 m was about 1–40 g C m− 3. Field data indicated that Neocalanus biomass was negatively correlated with salinity in May. Simulations indicated that the negative correlation was due to elevated primary and secondary production on the shelf relative to the adjacent ocean. Floats programmed to simulate the ontogenetic vertical migrations of Neocalanus indicated that ~ 10 to 50% of Neocalanus originating near the shelf break spend at least some time on the shelf, depending on location. Residence time of floats on the shelf was affected primarily by wind, secondarily by runoff. Primary and secondary production in the simulations were highly correlated (r > 0.9). Simulated secondary production was 10–90 g C m− 2 y− 1, with highest values in Lower Cook Inlet, around Kodiak and west of Kodiak.

Coupled physical/biological models can be used to downscale global climate change to the ecology of subarctic regions, and to explore the bottom-up and top-down effects of that change on the spatial structure of subarctic ecosystems—for example, the relative dominance of large vs. small zooplankton in relation to ice cover. Here we utilize a multivariate statistical approach to extract the emergent properties of a coupled physical/biological hindcast of the Bering Sea for years 1970–2009, which includes multiple episodes of warming and cooling (e.g. the recent cooling of 2005–2009), and a multidecadal regional forecast of the coupled models, driven by an IPCC global model forecast of 2010–2040. Specifically, we employ multivariate empirical orthogonal function (EOF) analysis to derive the spatial covariance among physical and biological timeseries from our simulations. These are compared with EOFs derived from spatially gridded measurements of the region, collected during multiyear field programs. The model replicates observed relationships among temperature and salinity, as well as the observed inverse correlation between temperature and large crustacean zooplankton on the southeastern Bering Sea shelf. Predicted future warming of the shelf is accompanied by a northward shift in both pelagic and benthic biomass.

The Eastern Bering Sea shelf is divided into distinct hydrographic domains by structural fronts. Despite frontal obstructions to cross-shelf transport, each year large oceanic copepods—primarily Neocalanus spp.—are known to dominate the biomass of the outer-shelf zooplankton communities, and in some years are advected into the middle-shelf domain. Using ROMS (the Regional Ocean Modeling System), coupled with a float tracking model designed to represent ontogenetic vertical migration behavior of Neocalanus, we explored the mechanisms, timing, and location of the transport of oceanic zooplankton onto the eastern Bering Sea shelf from overwintering sources along the Gulf of Alaska and Bering Sea shelf breaks, under a variety of environmental conditions. Our float tracking experiments suggest that the timing of on-shelf transport and the distribution of oceanic zooplankton on the shelf can vary substantially between one year and another. The Bering, Pribilof, and Zhemchug Canyons and Cape Navarin were all regions of elevated on-shelf float transport. Wind direction was the primary factor controlling inter-annual variability in the timing, amount, and location of the on-shelf transport of our Neocalanus floats. Float transport across the northern and southern shelves responded in opposite directions to inter-annual differences in wind forcing: southeasterly wind enhanced on-shelf transport of the Neocalanus floats along the southern shelf but suppressed on-shelf transport over the northern shelf. Conversely, northwesterly wind suppressed on-shelf zooplankton transport onto the southern shelf but promoted enhanced transport around Cape Navarin on the northern shelf. Transport of the Neocalanus floats onto the shelf can be very episodic, reflecting the short duration of winds that promote on-shelf transport. Relatively short (days to weeks) periods of southeasterly wind between March and April significantly impacted the number of floats transported onto the shelf. The relative importance of different source areas to supplying oceanic zooplankton to the Bering Sea shelf does not appear to vary much from year to year. Our model results suggest that the Neocalanus found on the southern shelf most likely originate from overwintering sites in the Alaska Stream or the Eastern Bering Sea shelf break south of the Pribilof Islands, while Neocalanus found on the northern shelf most likely originate from sites north of the Pribilof Islands.

We use a series of Monte Carlo experiments to explore simultaneously the sensitivity of the BEST marine ecosystem model to environmental forcing, initial conditions, and biological parameterizations. Twenty model output variables were examined for sensitivity. The true sensitivity of biological and environmental parameters becomes apparent only when each parameter is allowed to vary within its realistic range. Many biological parameters were important only to their corresponding variable, but several biological parameters, e.g., microzooplankton grazing and small phytoplankton doubling rate, were consistently very important to several output variables. Assuming realistic biological and environmental variability, the standard deviation about simulated mean mesozooplankton biomass ranged from 1 to 14 mg C m− 3 during the year. Annual primary productivity was not strongly correlated with temperature but was positively correlated with initial nitrate and light. Secondary productivity was positively correlated with primary productivity and negatively correlated with spring bloom timing. Mesozooplankton productivity was not correlated with water temperature, but a shift towards a system in which smaller zooplankton undertake a greater proportion of the secondary production as the water temperature increases appears likely. This approach to incorporating environmental variability within a sensitivity analysis could be extended to any ecosystem model to gain confidence in climate-driven ecosystem predictions.

Modeling the coastal Gulf of Alaska (CGOA) is complicated by the highly diverse physical and biological features influencing productivity and energy flow through the region. The GOA consists of the offshore oceanic environment, characterized by iron limitation, high-nutrients and low-chlorophyll. The coastal environment is consistently downwelling, with high iron levels from glacial melt water and runoff, but lower concentrations of macronutrients, and with a spring bloom, nutrient depletion cycle (low-nutrient, high-chlorophyll). Cross-shelf movement of water masses mixes coastal and oceanic ecosystem elements. Simulations and field data indicate that the minimum model complexity necessary to characterize lower trophic-level production and biomass in the offshore and coastal regions includes 10 boxes: iron, nitrate, ammonium, small phytoplankton, large phytoplankton, small microzooplankton, large microzooplankton, small copepods, large oceanic copepods and detritus, with copepod mortality as a model closure term. We present the model structure, equations required (and initial parameters used) to simulate onshore and offshore lower trophic-level production in the Gulf of Alaska, along with the information from field data and simulations used to construct the model. We show the results of simulations with and without iron, and with and without two size classes of phytoplankton. These simulations indicate that our method of inclusion of iron works well to distinguish the coastal and the oceanic ecosystems, and that the inclusion of two size categories of phytoplankton is also necessary to generate the differences between these two ecosystems.

Using numerical techniques, we explored the dynamics of a one-dimensional, six-component nutrient-phytoplankton-zooplankton (NPZ) model in which zooplankton grazed on a mixed prey field. Five alternative functional forms were implemented to describe zooplankton grazing, and the form for predation on mesozooplankton was prescribed by a product of a specific predation rate (h) and the mesozooplankton concentration raised to a power (q), which we varied between one and two. With all five grazing functions. Hopf bifurcations, where the form of the solution transitioned between steady equilibrium and periodic limit cycles, persisted across the q-h parameter space. Regardless of the values ofh and q, with some forms of the grazing function, we were unable to find steady equilibrium solutions that simultaneously comprised non-zero concentrations for all six model components. Extensions of Michaelis-Menten-based single resource grazing formulations to multiple resources resulted in periodic solutions for a large portion of the q-h space. Conversely, extensions of the signwidal grazing formulation to multiple resources resulted in steady solutions for a large portion of q-h parameter space. Our results demonstrate the consequences of the functional form of biological processes on the form of the model solutions. Both the steady or oscillatory nature of state variable concentrations and the likelihood of their elimination are important considerations for ecosystem-modelling studies, particularly when attempting to model an ecosystem in which multiple phytoplankton and zooplankton components are thought to persist simultaneously for at least a portion of the seasonal cycle.

Phylogenetic relationships were examined for 29 southern African West Nile virus (formal name West Nile virus [WNV]) isolates from various sources in four countries from 1958 to 2001. In addition, sequence data were retrieved from GenBank for another 23 WNV isolates and Kunjin and Japanese encephalitis viruses. All isolates belonged to two lineages. Lineage 1 isolates were from central and North Africa, Europe, Israel, and North America; lineage 2 isolates were from central and southern Africa and Madagascar. No strict correlation existed between grouping and source of virus isolate, pathogenicity, geographic distribution, or year of isolation. Some southern African isolates have been associated with encephalitis in a human, a horse, and a dog and with fatal hepatitis in a human and death of an ostrich chick.

At this early stage of modeling marine ecosystems and biogeochemical cycles in the Pacific Arctic Region (PAR), numerous challenges lie ahead. Observational data used for model development and validation remain sparse, especially across seasons and under a variety of environmental conditions. Field data are becoming more available, but at the same time PAR is rapidly changing. Biogeochemical models can provide the means to capture some of these changes. This study introduces and synthesizes ecosystem modeling in PAR by discussing differences in complexity and application of one-dimensional, regional, and global earth system models. Topics include the general structure of ecosystem models and specifics of the combined benthic, pelagic, and ice PAR ecosystems, the importance of model validation, model responses to climate influences (e.g. diminishing sea ice, ocean acidification), and the impacts of circulation and stratification changes on PAR ecosystems and biogeochemical cycling. Examples of modeling studies that help place the region within the context of the Pan-Arctic System are also discussed. We synthesize past and ongoing PAR biogeochemical modeling efforts and briefly touch on decision makers’ use of ecosystem models and on necessary future developments.

In May 2003, an outbreak of fatal hemorrhagic fever, caused by yellow fever virus, occurred in southern Sudan. Phylogenetic analysis showed that the virus belonged to the East African genotype, which supports the contention that yellow fever is endemic in East Africa with the potential to cause large outbreaks in humans.

The Arctic Ocean is one of the fastest changing oceans, plays an important role in global carbon cycling and yet is a particularly challenging ocean to study. Hence, observations tend to be relatively sparse in both space and time. How the Arctic functions, geophysically, but also ecologically, can have significant consequences for the internal cycling of carbon, and subsequently influence carbon export, atmospheric CO 2 uptake and food chain productivity. Here we assess the major carbon pools and associated processes, specifically summarizing the current knowledge of each of these processes in terms of data availability and ranges of rates and values for four geophysical Arctic Ocean domains originally described by Carmack & Wassmann (2006): inflow shelves, which are Pacific-influenced and Atlantic-influenced; interior, river-influenced shelves; and central basins. We attempt to bring together knowledge of the carbon cycle with the ecosystem within each of these different geophysical settings, in order to provide specialist information in a holistic context. We assess the current state of models and how they can be improved and/or used to provide assessments of the current and future functioning when observational data are limited or sparse. In doing so, we highlight potential links in the physical oceanographic regime, primary production and the flow of carbon within the ecosystem that will change in the future. Finally, we are able to highlight priority areas for research, taking a holistic pan-Arctic approach. Keywords: Sea ice; climate change; ecosystem function; carbon cycling. (Published: 15 April 2015) Citation: Polar Research 2015, 34 , 24252, http://dx.doi.org/10.3402/polar.v34.24252