Application of Seasonal to Decadal Climate Predictions for Marine Resource Management Workshop

Manuscripts referenced in presentations

Day 1 morning

• Bundy et al. 2012 . Common patterns, common drivers: comparative analysis of aggregate surplus production across ecosystems.
• Holsman et al. 2012. Comparative analysis of cod and herring production dynamics across 13 northern hemisphere marine ecosystems.
• Verges et al. 2014. The tropicalization of temperate marine ecosystems: climate-mediated changes in herbivory and community phase shifts.
• Gaichas et al. 2014. A risk-based approach to evaluating northeast US fish community vulnerability to climate change.
• Large et al. 2014. Quantifying patterns of change in marine ecosystem response to multiple pressures.
• Vert-pre et al. 2013. Frequency and intensity of productivity regime shifts in marine fish stocks.
• Pinsky et al. 2013. Marine taxa track local climate velocities.
• Myers. 1998. When do environment?recruitment correlations work?
• Pinsky and Mantua. 2014. Emerging adaptations approaches for climate ready fisheries management.
• Hilborn et al. 2003. Biocomplexity and fisheries sustainability.
• Schindler et al. 2010. Population diversity and the portfolio effect in an exploited species.
• Astthorsson et al. 2012. Climate-related variations in the occurrence and distribution of mackerel (Scomber scombrus) in Icelandic waters.
• Collie et al. 2012. A fisheries risk-assessment framework to evaluate trade-offs among management options in the presence of time-varying productivity.
• Scheffer et al. 2009. Early-warning signals for critical transitions.
• Bell et al. 2014. Externally driven changes in the abundance of summer and winter flounder.
• Cooley et al. 2015. An integrated assessment model for helping the United States sea scallop (Placopecten magellanicus) fishery plan ahead for ocean acidification and warming.
• Nye et al. 2013. The relative impact of warming and removing top predators on the Northeast US large marine biotic community.

Day 1 Afternoon

• Yang et al. 2013. A Predictable AMO-like pattern in the GFDL fully coupled ensemble initialization and decadal forecasting system.
• Wittenberg et al. 2014. ENSO modulation: is it decadally predictable?
• Vecchi et al. 2014. On the seasonal forecasting of regional tropical cyclone activity.
• Msadek et al. 2014. Importance of initial conditions in seasonal predictions of Arctic sea ice extent.
• Kirtman et al. 2014. The North American Multi-Model Ensemble (NMME): Phase-1 seasonal to interannual prediction, Phase-2 toward developing intra-seasonal prediction.
• Becker et al. 2014. Predictability and forecast skill in NMME.

Day 2

• Hobday and Pecl. 2014. Identification of global marine hotspots: sentinels for change and vanguards for adaptation action.
• Hobday and Hartmann. 2006. Near real-time spatial management based on habitat predictions for a longline bycatch species.
• Hobday et al. 2010. Dynamic spatial zoning to manage southern bluefin tuna (Thunnus maccoyii) capture in a multi-species longline fishery.
• Hobday et al. 2011. Seasonal forecasting of tuna habitat for dynamic spatial management.
• Spillman and Hobday. 2014. Dynamical seasonal ocean forecasts to aid salmon farm management.
• Spillman et al. 2015. Predicting environmental drivers for prawn aquaculture production to aid improved farm management.
• Eveson et al. 2015. Seasonal forecasting of tuna habitat in the Great Australian Bight.
• Seferian et al. 2014. Multiyear predictability of tropical marine productivity.y.
• Liu e tal. 2014. Reef-scale thermal stress monitoring of coral ecosystems: new 5-km global products from NOAA Coral Reef Watch.Liu e tal. 2014. Reef-scale thermal stress monitoring of coral ecosystems: new 5-km global products from NOAA Coral Reef Watch.
  
• Liu et al. 2014. NOAA Coral Reef Watch’s next-generation 5 km satellite coral bleaching thermal stress monitoring.
• Eakin et al. 2012. Ghost of bleaching future: seasonal outlooks from NOAA’s operational climate forecast system.
• Liu et al. 2009. NOAA Coral Reef Watch coral bleaching outlook system.
• Logan et al. 2014. Incorporating adaptive responses into future projections of coral bleaching.

Day 3

• Barsugli JJ, et al. 2013. The Practitioner?s dilemma: how to sssess the credibility of downscaled climate projections.
• Yang et al. 2013. A predictable AMO-like pattern in GFDL’s fully-coupled ensemble initialization and decadal forecasting system.
• Lenton. 2011. Early warning of climate tipping points.
• Ling et al. 2009. Overfishing reduces resilience of kelp beds to climate-driven catastrophic phase shift.
• Bestelmeyer et al. 2011. Analysis of abrupt transitions in ecological systems.
• Barange et al. 2014. Impacts of climate change on marine ecosystem production in societies dependent on fisheries.
• Holsman and Aydin. 2015. Comparative methods for evaluating climate change impacts on the foraging ecology of Alaskan groundfish.
• Scheffer et al. 2009. Early-warning signals for critical transitions.
• Scheffer et al. 2012. Anticipating critical transitions.
• Boettiger and Hastings. 2013. Tipping points: From patterns to predictions.
• Boettiger et al. 2013. Early warning signals: the charted and uncharted territories.
• Holling. 1996. Surprise for science, resilience for ecosystems, and incentives for people.
• Doak et al. 2008. Understanding and predicting ecological dynamics: are major surprises inevitable?
• Essington et al. 2015. Fishing amplifies forage fish population collapses.
• Shelton et al. 2014. Assessing trade-offs to inform ecosystem-based fisheries management of forage fish.
• Cury et al. 2011. Global seabird response to forage fish depletion?one-third for the birds.
• Pauly et al. 1998. Fishing down marine food webs.
• Essington et al. 2005. Fishing through marine food webs. Branch et al. 2010. The trophic fingerprint of marine fisheries.
• Schindler and Hilborn. 2015. Prediction, precaution, and policy under global change.