When a thriving marine fishery can increase its shrimp catch while reducing turtle bycatch, it’s an example of what scientists and environmental managers call a “win-win.” Models often predict that this ideal outcome is achievable, but stakeholders rarely see it manifest in the real world. Now, a study by the Cooperative Institute for Research in Environmental Sciences (CIRES) incorporates real-world complexity into models, explaining the gap, validating stakeholder concerns and providing more realistic expectations. for the future of environmental management.
“If a scientist’s model predicts that a fishery will catch a certain amount of fish with little bycatch, or predicts that a farm will harvest a certain amount of corn while reducing harmful fertilizers – but fishermen and farmers in the field report otherwise, which leads to frustration on both sides,” said Margaret Hegwood, a graduate student in environmental studies at the University of Colorado at Boulder working at CIRES and lead author of the new study published today in Natural durability.
“We used mathematics to show that real-world complexity makes win-wins more difficult to achieve – allowing scientists and stakeholders to make trade-offs and aim for more achievable and realistic goals regarding environmental impact, food production, biodiversity, economic return, etc.,” Hegwood added. , also a USDA Fellow in Food Technology and Food Safety. “As you add more variables, like another species, another stakeholder, additional regulation, the likelihood of a win-win starts to go down,” Hegwood said.
The team also analyzed 280 previous trade-off patterns and created algorithms to show how the severity of those trade-offs might change as more variables were added. The work allows modelers to better understand what managers are dealing with and allows managers to better understand models.
“At its core, this is a study of how to bridge a communication gap,” said co-author Ryan Langendorf, CIRES postdoctoral fellow and CU Boulder Environmental Studies. “There is this idea that there is a right and a wrong, but scientists and stakeholders are just thinking about the problem in different ways. We hope that our work will allow them to find common ground, so that the people can work together more productively.”
“It’s less about finding a better win-win and more about communicating what winning actually looks like,” Langendorf added. This could involve adjusting the goals to be more realistic: “Instead of asking, ‘Is this the ideal outcome for one goal?’ we have to change our way of thinking to ask ourselves ‘are we better than where we started?’ “, said Hegwood.
“Better” might mean sacrificing a little fish catch but drastically reducing bycatch, which happened, for example, in an Australian prawn fishery when it started adding turtle excluder devices to its trawls to protect sea turtles in 2001. Or “better” could mean reducing policy or regulatory barriers to achieving win-win outcomes. “If a win-win means a community needs certain resources qu ‘she can not afford, she will never achieve an ideal result. By identifying these barriers and minimizing them with proactive policies or technological advances, you make the win-win more accessible,” says Hegwood.
“Managers have always seemed to have a hunch that win-wins are harder to find in the real world than in models, because the real world is more complicated than models,” said Mattew Burgess, CIRES Fellow, Professor associate of Environmental Studies and Economics at CU Boulder and corresponding author of the study. “Our study shows, in a precise mathematical way, why the manager’s intuition is correct. By doing this, we hope that we have given modellers and managers a way to understand each other in a common language.”
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Material provided by University of Colorado Boulder. Note: Content may be edited for style and length.