Applied Ecology: Hallmarks of science missing from North American wildlife management

These findings come at a time of heightened controversy in wildlife management, when contentious policy is often defended by agencies claiming adherence to science-based approaches.

A map of North America and then in text it says, An assessment of 667 wildlife management systems across Canada and the USA found that key hallmarks of science were missing...

A new study, “Hallmarks of science missing from North American wildlife management”, published by Science Advances , challenges a widespread assumption that wildlife management in North America is science-based.

Scientists from Raincoast Conservation Foundation, Simon Fraser University, University of Victoria, and the University of Wisconsin – Madison examined management documents relating to most hunted species across Canada and the USA. They found the key hallmarks of science often missing.

The research identifies four key hallmarks expected of science-based management:

  1. clear objectives,
  2. use of evidence,
  3. transparency, and
  4. external review.

Combined, these hallmarks provide the checks and balances that give rigour to science-based approaches. Using this framework, the research team assessed all publicly-available documents describing 667 hunt management systems (species-jurisdictions, for example “Moose in Alaska” and “Deer in British Columbia”). These included 27 species groups across 62 US and Canadian states and provinces.

The study found that most systems (60%) contained fewer than half of the indicator criteria assessed. Some of the most basic assumptions of a scientific approach were almost entirely absent from wildlife management documents.

“Our framework provides guidance for adopting a science-based approach to safeguard not only wildlife but also agencies from potential social, legal, and political conflict.”

Read the full paper

Abstract

Resource management agencies commonly defend controversial policy by claiming adherence to science-based approaches. For example, proponents and practitioners of the “North American Model of Wildlife Conservation,” which guides hunting policy across much of the United States and Canada, assert that science plays a central role in shaping policy. However, what that means is rarely defined. We propose a framework that identifies four fundamental hallmarks of science relevant to natural resource management (measurable objectives, evidence, transparency, and independent review) and test for their presence in hunt management plans created by 62 U.S. state and Canadian provincial and territorial agencies across 667 management systems (species-jurisdictions). We found that most (60%) systems contained fewer than half of the indicator criteria assessed, with more criteria detected in systems that were peer-reviewed, that pertained to “big game,” and in jurisdictions at increasing latitudes. These results raise doubt about the purported scientific basis of hunt management across the United States and Canada. Our framework provides guidance for adopting a science-based approach to safeguard not only wildlife but also agencies from potential social, legal, and political conflict.

First published 2018 03 07

Introduction

Governments often assert, and society often assumes, that science comprises the foundation of natural resource management. In the United States and Canada, for example, state and provincial agencies responsible for managing bird and mammal hunting [the primary focus of wildlife management in the area; (1, 2)] commonly state that they a here to the North American Model of Wildlife Conservation. This model is predicated on seven tenets, one of which states that “science is the proper tool to discharge policy”.

Despite widespread use and endorsement of the North American Model, however, its proponents and practitioners rarely articulate what science-based management entails. In addition, no one has comprehensively assessed whether assumptions or claims of science-based management are supported. That knowledge gap is troubling given the “science-based” justifications for policy decisions commonly offered by agencies, the substantial public investments that support these agencies, and the considerable influence that hunting can have on otherwise self-regulating wildlife populations. In many taxa, adult mortality from hunting exceeds mortality from all other predators combined.

To address this gap, we identified four fundamental, interrelated hallmarks expected of science-based natural resource management (measurable objectives, evidence, transparency, and independent review) and 11 specific criteria as indicators of those hallmarks (for example, “Is the technique for setting hunting quotas explained?” for our transparency hallmark; Table 1; Materials and Methods; Supplementary Text). We assessed how many of these criteria appeared in 667 management systems, using hunt management plans (produced by agencies to describe how hunted species are managed) for 27 species (or groups of species) across 62 states, provinces, and territories in the United States and Canada (database S1). We limited our assessments to management under the jurisdiction of U.S. states and Canadian territories and provinces, which comprise most of the hunted areas in both countries.

Citation

K. A. Artelle, J. D. Reynolds, A. Treves, J. C. Walsh, P. C. Paquet, C. T. Darimont, Hallmarks of science missing from North American wildlife management. Sci. Adv. 4, eaao0167 (2018).

Select figures

Figure 1

Figure 1 of Hallmarks of Science paper on wildlife management: demonstrates the lack of science-basis for most management systems.

Figure 1. Percent of management systems across Canadian provinces/territories and U.S. states (N = 667 plans) in which indicator criteria for hallmarks of scientific management (measurable objectives, evidence, transparency, and independent review) were present.

figure 2

Hallmarks of science, Figure two, showing criteria that are met.

Figure 2. Number of criteria out of 9, with both independent review hallmark criteria excluded as part of the response (see fig. S2). Coefficients shown are odds ratios from a multilevel model, with thick and thin bars representing 50 and 95% confidence intervals, respectively, and plotted on a log scale.

Affiliations

Earth to Ocean Research Group, Department of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, Canada.
Kyle A. Artelle, John D. Reynolds & Jessica C. Walsh

Raincoast Conservation Foundation, Sidney, British Columbia, Canada.
Kyle A. Artelle, Paul C. Paquet & Chris T. Darimont

Hakai Institute, Heriot Bay, British Columbia, Canada.
Kyle A. Artelle & Chris T. Darimont

Nelson Institute for Environmental Studies, University of Wisconsin–Madison, Madison, WI, USA.
Adrian Treves

Department of Geography, University of Victoria, Victoria, British Columbia, Canada.
Paul C. Paquet & Chris T. Darimont

Acknowledgements

We thank M. van Roy, K. Field, J. Pendray, C. Gwilliam, and D. Chan for assisting with data collection, assessment, and review; S. C. Anderson, A. B. Cooper, A. K. Salomon, P. S. Levin, the Reynolds laboratory at Simon Fraser University, the Applied Conservation Science laboratory at the University of Victoria, Wilburforce Fellows, B. Crabtree, and many management agencies for helpful feedback throughout; and three anonymous reviewers who improved this manuscript considerably. Funding: K.A.A. was supported by a Vanier Fellowship and the Tula Foundation. J.D.R. was supported by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant and the Tom Buell Endowment with contributions from the Pacific Salmon Foundation, the BC Leading Edge Endowment Fund, and Simon Fraser University. C.T.D. was supported by NSERC Discovery Grant 435683 and investments by the Tula, Wilburforce, and Willow Grove Foundations.

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