Biogeographic responses of the copepod Calanus glacialis to a changing Arctic marine environment.

Dramatic changes have occurred in the Arctic Ocean over the past few decades, especially in terms of sea ice loss and ocean warming. Those environmental changes may modify the planktonic ecosystem with changes from lower to upper trophic levels. This study aimed to understand how the biogeographic distribution of a crucial endemic copepod species, Calanus glacialis, may respond to both abiotic (ocean temperature) and biotic (phytoplankton prey) drivers. A copepod individual-based model coupled to an ice-ocean-biogeochemical model was utilized to simulate temperature- and food-dependent life cycle development of C. glacialis annually from 1980 to 2014. Over the 35-year study period, the northern boundaries of modeled diapausing C. glacialis expanded poleward and the annual success rates of C. glacialis individuals attaining diapause in a circumpolar transition zone increased substantially. Those patterns could be explained by a lengthening growth season (during which time food is ample) and shortening critical development time (the period from the first feeding stage N3 to the diapausing stage C4). The biogeographic changes were further linked to large-scale oceanic processes, particularly diminishing sea ice cover, upper ocean warming, and increasing and prolonging food availability, which could have potential consequences to the entire Arctic shelf/slope marine ecosystems.

Pushing the limit: Resilience of an Arctic copepod to environmental fluctuations.

Life history strategies such as multiyear life cycles, resting stages, and capital breeding allow species to inhabit regions with extreme and fluctuating environmental conditions. One example is the zooplankton species Calanus hyperboreus, whose life history is considered an adaptation to the short and unpredictable growth season in the central Arctic Ocean. This copepod is commonly described as a true Arctic endemic; however, by statistically analyzing compiled observational data, we show that abundances are relatively low and later stages and adults dominate in the central Arctic Ocean basins, indicating expatriation. Combining data analyses with individual-based modeling and energy requirement estimation, we further demonstrate that while C. hyperboreus can reach higher abundances in areas with greater food availability outside the central Arctic basins, the species' resilience to environmental fluctuations enables the life cycle to be completed in the central Arctic basins. Specifically, the energy level required to reach the first overwintering stage-a prerequisite for successful local production-is likely met in some-but not all-years. This fine balance between success and failure indicates that C. hyperboreus functions as a peripheral population in the central Arctic basins and its abundance will likely increase in areas with improved growth conditions in response to climate change. By illustrating a key Arctic species' resilience to extreme and fluctuating environmental conditions, the results of this study have implications for projections of future biogeography and food web dynamics in the Arctic Ocean, a region experiencing rapid warming and sea ice loss.

Recent Progress and Future Prospect of CRISPR/Cas-Derived Transcription Activation (CRISPRa) System in Plants.

Genome editing technology has become one of the hottest research areas in recent years. Among diverse genome editing tools, the Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated proteins system (CRISPR/Cas system) has exhibited the obvious advantages of specificity, simplicity, and flexibility over any previous genome editing system. In addition, the emergence of Cas9 mutants, such as dCas9 (dead Cas9), which lost its endonuclease activity but maintains DNA recognition activity with the guide RNA, provides powerful genetic manipulation tools. In particular, combining the dCas9 protein and transcriptional activator to achieve specific regulation of gene expression has made important contributions to biotechnology in medical research as well as agriculture. CRISPR/dCas9 activation (CRISPRa) can increase the transcription of endogenous genes. Overexpression of foreign genes by traditional transgenic technology in plant cells is the routine method to verify gene function by elevating genes transcription. One of the main limitations of the overexpression is the vector capacity constraint that makes it difficult to express multiple genes using the typical Ti plasmid vectors from Agrobacterium. The CRISPRa system can overcome these limitations of the traditional gene overexpression method and achieve multiple gene activation by simply designating several guide RNAs in one vector. This review summarizes the latest progress based on the development of CRISPRa systems, including SunTag, dCas9-VPR, dCas9-TV, scRNA, SAM, and CRISPR-Act and their applications in plants. Furthermore, limitations, challenges of current CRISPRa systems and future prospective applications are also discussed.

Sea Ice Properties in High-Resolution Sea Ice Models.

An Arctic sea ice-ocean model is run with three uniform horizontal resolutions (6, 4, and 2 km) and identical sea ice and ocean model parameterizations, including an isotropic viscous-plastic sea ice rheology, a mechanical ice strength parameterization, and an ice ridging parameterization. Driven by the same atmospheric forcing, the three model versions all produce similar spatial patterns and temporal variations of ice thickness and motion fields, resulting in almost identical magnitude and seasonal evolution of total ice volume and mean ice concentration, ice speed, and fractions of ice of various thickness categories over the Arctic Ocean. Increasing model resolution from 6 to 2 km does not significantly improve model performance when compared to NASA IceBridge ice thickness observations. This suggests that the large-scale sea ice properties of the model are insensitive to varying high resolutions within the multifloe scale (2-10 km), and it may be unnecessary to adjust model parameters constantly with increasingly high resolutions. This is also true with models within the aggregate scale (10-75 km), indicating that model parameters used at coarse resolution may be used at high or multiscale resolution. However, even though the three versions all yield similar mean state of sea ice, they differ in representing anisotropic properties of sea ice. While they produce a basic pattern of major sea ice leads similar to satellite observations, their leads are distributed differently in space and time. Without changing model parameters and sea ice spatiotemporal variability, the 2-km resolution model tends to capture more leads than the other two models.

Bowhead and beluga whale acoustic detections in the western Beaufort Sea 2008-2018.

The Distributed Biological Observatory (DBO) was established to detect environmental changes in the Pacific Arctic by regular monitoring of biophysical responses in each of 8 DBO regions. Here we examine the occurrence of bowhead and beluga whale vocalizations in the western Beaufort Sea acquired by acoustic instruments deployed from September 2008-July 2014 and September 2016-October 2018 to examine inter-annual variability of these Arctic endemic species in DBO Region 6. Acoustic data were collected on an oceanographic mooring deployed in the Beaufort shelfbreak jet at ~71.4°N, 152.0°W. Spectrograms of acoustic data files were visually examined for the presence or absence of known signals of bowhead and beluga whales. Weekly averages of whale occurrence were compared with outputs of zooplankton, temperature and sea ice from the BIOMAS model to determine if any of these variables influenced whale occurrence. In addition, the dates of acoustic whale passage in the spring and fall were compared to annual sea ice melt-out and freeze-up dates to examine changes in phenology. Neither bowhead nor beluga whale migration times changed significantly in spring, but bowhead whales migrated significantly later in fall from 2008-2018. There were no clear relationships between bowhead whales and the environmental variables, suggesting that the DBO 6 region is a migratory corridor, but not a feeding hotspot, for this species. Surprisingly, beluga whale acoustic presence was related to zooplankton biomass near the mooring, but this is unlikely to be a direct relationship: there are likely interactions of environmental drivers that result in higher occurrence of both modeled zooplankton and belugas in the DBO 6 region. The environmental triggers that drive the migratory phenology of the two Arctic endemic cetacean species likely extend from Bering Sea transport of heat, nutrients and plankton through the Chukchi and into the Beaufort Sea.

Should Sea-Ice Modeling Tools Designed for Climate Research Be Used for Short-Term Forecasting?

In theory, the same sea-ice models could be used for both research and operations, but in practice, differences in scientific and software requirements and computational and human resources complicate the matter. Although sea-ice modeling tools developed for climate studies and other research applications produce output of interest to operational forecast users, such as ice motion, convergence, and internal ice pressure, the relevant spatial and temporal scales may not be sufficiently resolved. For instance, sea-ice research codes are typically run with horizontal resolution of more than 3 km, while mariners need information on scales less than 300 m. Certain sea-ice processes and coupled feedbacks that are critical to simulating the Earth system may not be relevant on these scales; and therefore, the most important model upgrades for improving sea-ice predictions might be made in the atmosphere and ocean components of coupled models or in their coupling mechanisms, rather than in the sea-ice model itself. This paper discusses some of the challenges in applying sea-ice modeling tools developed for research purposes for operational forecasting on short time scales, and highlights promising new directions in sea-ice modeling.

Future sea ice conditions and weather forecasts in the Arctic: Implications for Arctic shipping.

The ability to forecast sea ice (both extent and thickness) and weather conditions are the major factors when it comes to safe marine transportation in the Arctic Ocean. This paper presents findings focusing on sea ice and weather prediction in the Arctic Ocean for navigation purposes, in particular along the Northeast Passage. Based on comparison with the observed sea ice concentrations for validation, the best performing Earth system models from the Intergovernmental Panel on Climate Change (IPCC) program (CMIP5-Coupled Model Intercomparison Project phase 5) were selected to provide ranges of potential future sea ice conditions. Our results showed that, despite a general tendency toward less sea ice cover in summer, internal variability will still be large and shipping along the Northeast Passage might still be hampered by sea ice blocking narrow passages. This will make sea ice forecasts on shorter time and space scales and Arctic weather prediction even more important.

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models.

The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959-2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free versus ice-influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling.

Accuracy of short-term sea ice drift forecasts using a coupled ice-ocean model.

Arctic sea ice drift forecasts of 6 h-9 days for the summer of 2014 are generated using the Marginal Ice Zone Modeling and Assimilation System (MIZMAS); the model is driven by 6 h atmospheric forecasts from the Climate Forecast System (CFSv2). Forecast ice drift speed is compared to drifting buoys and other observational platforms. Forecast positions are compared with actual positions 24 h-8 days since forecast. Forecast results are further compared to those from the forecasts generated using an ice velocity climatology driven by multiyear integrations of the same model. The results are presented in the context of scheduling the acquisition of high-resolution images that need to follow buoys or scientific research platforms. RMS errors for ice speed are on the order of 5 km/d for 24-48 h since forecast using the sea ice model compared with 9 km/d using climatology. Predicted buoy position RMS errors are 6.3 km for 24 h and 14 km for 72 h since forecast. Model biases in ice speed and direction can be reduced by adjusting the air drag coefficient and water turning angle, but the adjustments do not affect verification statistics. This suggests that improved atmospheric forecast forcing may further reduce the forecast errors. The model remains skillful for 8 days. Using the forecast model increases the probability of tracking a target drifting in sea ice with a 10 km × 10 km image from 60 to 95% for a 24 h forecast and from 27 to 73% for a 48 h forecast.

The great 2012 Arctic Ocean summer cyclone enhanced biological productivity on the shelves.

[1] A coupled biophysical model is used to examine the impact of the great Arctic cyclone of early August 2012 on the marine planktonic ecosystem in the Pacific sector of the Arctic Ocean (PSA). Model results indicate that the cyclone influences the marine planktonic ecosystem by enhancing productivity on the shelves of the Chukchi, East Siberian, and Laptev seas during the storm. Although the cyclone's passage in the PSA lasted only a few days, the simulated biological effects on the shelves last 1 month or longer. At some locations on the shelves, primary productivity (PP) increases by up to 90% and phytoplankton biomass by up to 40% in the wake of the cyclone. The increase in zooplankton biomass is up to 18% on 31 August and remains 10% on 15 September, more than 1 month after the storm. In the central PSA, however, model simulations indicate a decrease in PP and plankton biomass. The biological gain on the shelves and loss in the central PSA are linked to two factors. (1) The cyclone enhances mixing in the upper ocean, which increases nutrient availability in the surface waters of the shelves; enhanced mixing in the central PSA does not increase productivity because nutrients there are mostly depleted through summer draw down by the time of the cyclone's passage. (2) The cyclone also induces divergence, resulting from the cyclone's low-pressure system that drives cyclonic sea ice and upper ocean circulation, which transports more plankton biomass onto the shelves from the central PSA. The simulated biological gain on the shelves is greater than the loss in the central PSA, and therefore, the production on average over the entire PSA is increased by the cyclone. Because the gain on the shelves is offset by the loss in the central PSA, the average increase over the entire PSA is moderate and lasts only about 10 days. The generally positive impact of cyclones on the marine ecosystem in the Arctic, particularly on the shelves, is likely to grow with increasing summer cyclone activity if the Arctic continues to warm and the ice cover continues to shrink.