Potential Climate Change Effects on the Habitat of Antarctic Krill in the Weddell Quadrant of the Southern Ocean

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.

Biologging, Remotely-Sensed Oceanography and the Continuous Plankton Recorder Reveal the Environmental Determinants of a Seabird Wintering Hotspot

Marine environments are greatly affected by climate change, and understanding how this perturbation affects marine vertebrates is a major issue. In this context, it is essential to identify the environmental drivers of animal distribution. Here, we focused on the little auk (Alle alle), one of the world’s most numerous seabirds and a major component in Arctic food webs. Using a multidisciplinary approach, we show how little auks adopt specific migratory strategies and balance environmental constraints to optimize their energy budgets. Miniature electronic loggers indicate that after breeding, birds from East Greenland migrate .2000 km to overwinter in a restricted area off Newfoundland. Synoptic data available from the Continuous Plankton Recorder (CPR) indicate that this region harbours some of the highest densities of the copepod Calanus finmarchicus found in the North Atlantic during winter. Examination of large-scale climatic and oceanographic data suggests that little auks favour patches of high copepod abundance in areas where air temperature ranges from 0uC to 5uC. These results greatly advance our understanding of animal responses to extreme environmental constraints, and highlight that information on habitat preference is key to identifying critical areas for marine conservation.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Multicenter Randomized Controlled Trial of Withdrawal of Inhaled Corticosteroids in Cystic Fibrosis

Rationale: Lung inflammation and injury is critical in cystic fibrosis. An ideal antiinflammatory agent has not been identified but inhaled corticosteroids are widely used despite lack of evidence.

Objectives: To test the safety of withdrawal of inhaled corticosteroids with the hypothesis this would not be associated with an earlier onset of acute chest exacerbations.

Methods: Multicenter randomized double-blind placebo-controlled trial in 18 pediatric and adult UK centers. Eligibility criteria included age > 6.0 yr, FEV1 ? 40% predicted, and corticosteroid use > 3 mo. During the 2-mo run-in period, all patients received fluticasone; they then took either fluticasone or placebo for 6 mo.

Measurements and Main Results: Fluticasone group: n = 84, median age 14.6 yr, mean (SD) FEV1 76% (18); placebo group: n = 87, median age 15.8 yr, mean (SD) FEV1 76% (18). There was no difference in time to first exacerbation (primary outcome) with hazard ratio (95% confidence interval) of 1.07 (0.68 to 1.70) for fluticasone versus placebo. There was no effect of age, atopy, corticosteroid dose, FEV1, or Pseudomonas aeruginosa status. There was no change in lung function or differences in antibiotic or rescue bronchodilator use. Fewer patients in the fluticasone group withdrew from the study due to lung-related adverse events (9 vs. 15%); with a relative risk (95% confidence interval) of 0.59 (0.23–1.48) fluticasone versus placebo.

Conclusions: In this study population (applicable to 40% of patients with cystic fibrosis in the UK), it appears safe to consider stopping inhaled corticosteroids. Potential advantages will be to reduce the drug burden on patients, reduce adverse effects, and make financial savings.

Development of a modified flyash as a permeable reactive barrier media for a former manufactured gas plant site Northern Ireland

A sequential biological permeable reactive barrier (PRB) was determined to be the best option for remediating groundwater that has become contaminated with a wide range of organic contaminants (i.e., benzene, toluene, ethylbenzene, xylene and polyaromatic hydrocarbons), heavy metals (i.e., lead and arsenic), and cyanide at a former manufactured gas plant after 150 years of operation in Portadown, Northern Ireland. The objective of this study was to develop a modified flyash that could be used in the initial cell within a sequential biological PRB to filter complex contaminated groundwater containing ammonium. Flyash modified with lime (CaOH) and alum was subjected to a series of batch tests which investigated the modified cation exchange capacity (CEC) and rate of removal of anions and cations from the solution. These tests showed that a high flyash composition medium (80%) could remove 8.65 mol of ammonium contaminant for every kilogram of medium. The modified CEC procedure ruled out the possibility of cation exchange as the major removal mechanism. The medium could also adsorb anions as well as cations (i.e., Pb and Cr), but not with the same capacity. The initial mechanism for Pb and Cr removal is probably precipitation. This is followed by sorption, which is possibly the only mechanism for the removal of dichromate anions. Scanning electron microscopic analysis revealed very small (