Bridging the divide between ecological forecasts and environmental decision making

被引:19
作者
Bodner, Korryn [1 ,2 ]
Firkowski, Carina Rauen [1 ,3 ,17 ]
Bennett, Joseph R. [4 ]
Brookson, Cole [5 ]
Dietze, Michael [6 ]
Green, Stephanie [5 ]
Hughes, Josie [7 ]
Kerr, Jeremy [8 ]
Kunegel-Lion, Melodie [9 ]
Leroux, Shawn J. [10 ]
McIntire, Eliot [11 ,12 ]
Molnar, Peter K. [1 ,2 ]
Simpkins, Craig [13 ,14 ,15 ]
Tekwa, Edward [16 ]
Watts, Alexander [17 ]
Fortin, Marie-Josee [1 ]
机构
[1] Univ Toronto, Dept Ecol & Evolut, Toronto, ON, Canada
[2] Univ Toronto Scarborough, Dept Biol Sci, Toronto, ON, Canada
[3] McGill Univ, Dept Biol, Montreal, PQ, Canada
[4] Carleton Univ, Dept Biol, Ottawa, ON, Canada
[5] Univ Alberta, Dept Biol Sci, Edmonton, AB, Canada
[6] Boston Univ, Dept Earth & Environm, Boston, MA USA
[7] Environm & Climate Change Canada, Natl Wildlife Res Ctr, Ottawa, ON, Canada
[8] Univ Ottawa, Dept Biol, Ottawa, ON, Canada
[9] Nat Resources Canada, Canadian Forest Serv, Northern Forestry Ctr, Edmonton, AB, Canada
[10] Mem Univ Newfoundland, Dept Biol, St John, NF, Canada
[11] Nat Resources Canada, Canadian Forest Serv, Pacific Forestry Ctr, Victoria, BC, Canada
[12] Univ British Columbia, Fac Forestry, Forest Resources Management, Vancouver, BC, Canada
[13] Univ Auckland, Sch Environm, Auckland, New Zealand
[14] Wilfrid Laurier Univ, Dept Biol, Waterloo, ON, Canada
[15] Georg August Univ Goettingen, Dept Ecol Modelling, Gottingen, Germany
[16] Univ British Columbia, Dept Zool, Vancouver, BC, Canada
[17] Esri Canada, Toronto, ON, Canada
关键词
co-production; decision support; forecast horizon; iterative; Open science; prediction; reproducibility; scenario analysis; science communication; team-building; uncertainty; validation; UNCERTAINTY; SCIENCE; CONSERVATION; ADAPTATION; PREDICTION; FISHERIES; FUTURE; NEEDS;
D O I
10.1002/ecs2.3869
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The rate of human-induced environmental change continues to accelerate, stimulating the need for rapid and science-based decision making. The recent availability of cyberinfrastructure, open-source data and novel techniques has increased opportunities to use ecological forecasts to predict environmental change. But to effectively inform environmental decision making, forecasts should not only be reliable, but should also be designed to address the needs of decision makers with their assumptions, uncertainties, and results clearly communicated. To help researchers better integrate forecasting into decision making, we outline ten practical guidelines to help navigate the interdisciplinary and collaborative nature of forecasting in social-ecological systems. Some guidelines focus on improving forecasting skills, including how to build better models, account for uncertainties and use technologies to improve their utility, while others are developed to facilitate the integration of forecasts with decision making, including how to form effective partnerships and how to design forecasts relevant to the specific decision being addressed. We hope these guidelines help researchers make forecasts more accurate, precise, transparent, and most pressingly, useful for informing environmental decisions.
引用
收藏
页数:13
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