Prediction, precaution, and policy under global change

Emphasize robustness, monitoring, and flexibility A great deal of research to inform environmental conservation and management takes a predict-and-prescribe strategy in which improving forecasts about future states of ecosystems is the primary goal. But sufficiently thorough understanding of ecosystems needed to reduce deep uncertainties is probably not achievable, seriously limiting the potential effectiveness of the predict-and-prescribe approach. Instead, research should integrate more closely with policy development to identify the range of alternative plausible futures and develop strategies that are robust across these scenarios and responsive to unpredictable ecosystem dynamics.

[1]  N Oreskes,et al.  Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences , 1994, Science.

[2]  P. Cury,et al.  Integrating the invisible fabric of nature into fisheries management , 2013, Proceedings of the National Academy of Sciences.

[3]  S. Carpenter,et al.  Ecological forecasts: an emerging imperative. , 2001, Science.

[4]  Kirk R. Klausmeyer,et al.  Resource management in a changing and uncertain climate , 2010 .

[5]  Juan Carlos Castilla,et al.  Latin American benthic shellfisheries: emphasis on co-management and experimental practices , 2001, Reviews in Fish Biology and Fisheries.

[6]  J. Franklin,et al.  Modeling plant species distributions under future climates: how fine scale do climate projections need to be? , 2013, Global change biology.

[7]  Ben Collen,et al.  Complexity is costly: a meta‐analysis of parametric and non‐parametric methods for short‐term population forecasting , 2014 .

[8]  Jon T. Schnute,et al.  Use and abuse of fishery models , 2001 .

[9]  R. Stouffer,et al.  Stationarity Is Dead: Whither Water Management? , 2008, Science.

[10]  C. S. Holling.  Understanding the Complexity of Economic, Ecological, and Social Systems , 2001, Ecosystems.

[11]  M. Schlesinger,et al.  Robust Strategies for Abating Climate Change , 2000 .

[12]  Carl J. Walters,et al.  Adaptive Management of Renewable Resources , 1986 .

[13]  Gene E. Likens,et al.  Who needs environmental monitoring , 2007 .

[14]  George Sugihara,et al.  Model-free forecasting outperforms the correct mechanistic model for simulated and experimental data , 2013, Proceedings of the National Academy of Sciences.

[15]  S. Levin.  The problem of pattern and scale in ecology , 1992 .

[16]  Ransom A. Myers,et al.  When Do Environment–recruitment Correlations Work? , 1998, Reviews in Fish Biology and Fisheries.

[17]  C. Walters,et al.  Uncertainty, resource exploitation, and conservation: lessons from history. , 1993, Science.

[18]  Amy W. Ando,et al.  Optimal portfolio design to reduce climate-related conservation uncertainty in the Prairie Pothole Region , 2012, Proceedings of the National Academy of Sciences.

[19]  Stephen R. Carpenter,et al.  Scenario Planning: a Tool for Conservation in an Uncertain World , 2003, Conservation Biology.

[20]  R. Hilborn,et al.  Population diversity and the portfolio effect in an exploited species , 2010, Nature.

[21]  P. Schoemaker.  Scenario Planning: A Tool for Strategic Thinking , 1995 .

[22]  S. Carpenter,et al.  Anticipating Critical Transitions , 2012, Science.

[23]  Hiroyuki Matsuda,et al.  Co-management in Japanese coastal fisheries: institutional features and transaction costs , 2005 .

[24]  Harald Kunstmann,et al.  The Hydrological Cycle in Three State-of-the-Art Reanalyses: Intercomparison and Performance Analysis , 2012 .