Preparing for a Northwest Passage: A Workshop on the Role of New England in Navigating the New Arctic

Preparing for a Northwest Passage: A Workshop on the Role of New England in Navigating the New Arctic (March 25 - 27, 2018 -- The University of New Hampshire) paired two of NSF\u27s 10 Big Ideas: Navigating the New Arctic and Growing Convergence Research at NSF. During this event, participants assessed economic, environmental, and social impacts of Arctic change on New England and established convergence research initiatives to prepare for, adapt to, and respond to these effects. Shipping routes through an ice-free Northwest Passage in combination with modifications to ocean circulation and regional climate patterns linked to Arctic ice melt will affect trade, fisheries, tourism, coastal ecology, air and water quality, animal migration, and demographics not only in the Arctic but also in lower latitude coastal regions such as New England. With profound changes on the horizon, this is a critical opportunity for New England to prepare for uncertain yet inevitable economic and environmental impacts of Arctic change

Prediction of monthly Arctic sea ice concentrations using satellite and reanalysis data based on convolutional neural networks

Changes in Arctic sea ice affect atmospheric circulation, ocean current, and polar ecosystems. There have been unprecedented decreases in the amount of Arctic sea ice due to global warming. In this study, a novel 1-month sea ice concentration (SIC) prediction model is proposed, with eight predictors using a deep-learning approach, convolutional neural networks (CNNs). This monthly SIC prediction model based on CNNs is shown to perform better predictions (mean absolute error - MAE - of 2.28 %, anomaly correlation coefficient - ACC - of 0.98, root-mean-square error - RMSE - of 5.76 %, normalized RMSE - nRMSE - of 16.15 %, and NSE - Nash-Sutcliffe efficiency - of 0.97) than a random-forest-based (RF-based) model (MAE of 2.45 %, ACC of 0.98, RMSE of 6.61 %, nRMSE of 18.64 %, and NSE of 0.96) and the persistence model based on the monthly trend (MAE of 4.31 %, ACC of 0.95, RMSE of 10.54 %, nRMSE of 29.17 %, and NSE of 0.89) through hindcast validations. The spatio-temporal analysis also confirmed the superiority of the CNN model. The CNN model showed good SIC prediction results in extreme cases that recorded unforeseen sea ice plummets in 2007 and 2012 with RMSEs of less than 5.0 %. This study also examined the importance of the input variables through a sensitivity analysis. In both the CNN and RF models, the variables of past SICs were identified as the most sensitive factor in predicting SICs. For both models, the SIC-related variables generally contributed more to predict SICs over ice-covered areas, while other meteorological and oceanographic variables were more sensitive to the prediction of SICs in marginal ice zones. The proposed 1-month SIC prediction model provides valuable information which can be used in various applications, such as Arctic shipping-route planning, management of the fishing industry, and long-term sea ice forecasting and dynamics

Seamounts as refugia from ocean acidification for cold-water stony corals

Cold-water stony corals create habitat for a diverse range of deep-water species but are thought to be threatened by ocean acidification due to oceanic uptake of anthropogenic CO2. Knowledge of the severity of this threat is hampered by our limited understanding of the distribution and habitat requirements of these corals. Here we estimate the global acidification threat to these organisms using a global database of cold-water stony coral records and a species distribution modelling approach. We parameterised the models using present-day environmental data, and then replaced these data with future projections of ocean chemistry from the year 2099. We found suitable coral habitat to be very heterogeneously distributed, being concentrated in the northern North Atlantic and around New Zealand. Projected changes in ocean chemistry induced a pronounced reduction in habitat suitability in the North Atlantic, and a low-to-moderate impact elsewhere under both the IPCC IS92a and S650 scenarios. Seamount summits are impacted by these changes, but consistently provide more suitable habitat than the surrounding seafloor, with around 98% of seamount summits having higher suitability in both future scenarios; this is because they lie in shallower waters with a higher aragonite saturation state. These results suggest that anthropogenic-induced changes in ocean chemistry are likely to severely impact cold-water stony coral habitat in the deep-sea of the North Atlantic, and that impacts will be less severe elsewhere. We predict that coral communities on the summits and upper slopes of seamounts will be less susceptible to ocean acidification during this century than those on the surrounding seafloor, and thus that seamounts may serve as temporary refugia. © 2010 Blackwell Verlag GmbH

ABC for Climate: Dealing with Expensive Simulators

A single molecule or molecule complex detection method is disclosed in certain aspects, comprising nano- or micro-fluidic channels.U

Predicting global habitat suitability for stony corals on seamounts

Aim Globally, species distribution patterns in the deep sea are poorly resolved, with spatial coverage being sparse for most taxa and true absence data missing. Increasing human impacts on deep-sea ecosystems mean that reaching a better understanding of such patterns is becoming more urgent. Cold-water stony corals (Order Scleractinia) form structurally complex habitats (dense thickets or reefs) that can support a diversity of other associated fauna. Despite their widely accepted ecological importance, records of scleractinian corals on seamounts are patchy and simply not available for most of the global ocean. The objective of this paper is to model the global distribution of suitable habitat for stony corals on seamounts. Location Seamounts worldwide. Methods We compiled a database containing all accessible records of scleractinian corals on seamounts. Two modelling approaches developed for presence-only data were used to predict global habitat suitability for seamount scleractinians: maximum entropy modelling (Maxent) and environmental niche factor analysis (ENFA). We generated habitat-suitability maps and used a cross-validation process with a threshold-independent metric to evaluate the performance of the models. Results Both models performed well in cross-validation, although the Maxent method consistently outperformed ENFA. Highly suitable habitat for seamount stony corals was predicted to occur at most modelled depths in the North Atlantic, and in a circumglobal strip in the Southern Hemisphere between 20° and 50° S and shallower than around 1500 m. Seamount summits in most other regions appeared much less likely to provide suitable habitat, except for small near-surface patches. The patterns of habitat suitability largely reflect current biogeographical knowledge. Environmental variables positively associated with high predicted habitat suitability included the aragonite saturation state, and oxygen saturation and concentration. By contrast, low levels of dissolved inorganic carbon, nitrate, phosphate and silicate were associated with high predicted suitability. High correlation among variables made assessing individual drivers difficult. Main conclusions Our models predict environmental conditions likely to play a role in determining large-scale scleractinian coral distributions on seamounts, and provide a baseline scenario on a global scale. These results present a first-order hypothesis that can be tested by further sampling. Given the high vulnerability of cold-water corals to human impacts, such predictions are crucial tools in developing worldwide conservation and management strategies for seamount ecosystems. © 2009 Blackwell Publishing Ltd

Oceanus.

v. 37, no. 2 (1994