The scientific enterprise involves a combination of observation and structured inference. We may, for example, measure the density of Arctic grayling in selected streams to determine their status and temporal trends. If we also measure ancillary variables, such as water temperature, water quality, and intensity of angling, we may begin to infer causal relationships. In time, such causal relationships can be assembled into a conceptual model that explains how the overall grayling system works. If the model components are sufficiently robust, the model can be used to make quantitative predictions about how the system is likely to respond to specific management actions.

The general process of observation, inference, and model building is not unique to science. Each of us builds our own mental model of how the world works based on our life experience and what we learn from others. For example, anglers use their personal models to determine the best spots to fish. This approach also underlies Indigenous traditional ecological knowledge.

What differentiates and ultimately defines science is the methodology used to guide the process. Established techniques exist for designing studies, making observations, and analyzing data. These methods optimize the utility and reliability of observations and allow uncertainty to be quantified (Mills and Clark 2001). Furthermore, conclusions are treated as hypotheses, not facts, and are subjected to peer challenge and continued testing. Scientific information is by no means infallible, but science is the best approach available for separating true relationships from chance associations and developing a robust understanding of how the natural world works.

As discussed in Chapter 1, science supports conservation by informing the decision-making processes that determine conservation actions. The specific contributions that science makes vary according to the stage of the process (Mills and Clark 2001; Barbour et al. 2008; Arlettaz et al. 2010):

• Setting objectives. Objectives define what we would like to achieve in a policy or planning setting. They express what is important to us, implying an origin in societal values rather than science. The role of science is to identify threats to our values and to quantify the level of risk, thereby motivating action. Thus, science plays an important role in agenda setting.
• Identifying options. Most conservation problems are a consequence of human activity, in one form or another. Therefore, conservation usually entails searching for alternative, more benign, approaches for interacting with nature. Science contributes to this process by elucidating the causes of ecological problems and identifying potential remedies.
• Making a decision. The last step in the decision-making process is formulating a management response, which entails assessing the available management options and selecting the best. In conservation applications, this is typically a political process because it involves judgments about societal risk tolerance and trade-offs among values. Science supports the process by predicting outcomes under the different management options and by quantifying uncertainties.
• Monitoring and learning. Scientifically rigorous monitoring and research can reduce management uncertainties and provide the information needed to evaluate the effectiveness of past decisions. This changes decision making from a linear process to a cyclical process of continuous improvement. Monitoring also serves to identify new and evolving problems.

In subsequent chapters, we will examine how these various aspects of science are applied in practice. Real-world applications are messy and often fall short of the ideal. Therefore, we will pay close attention to the differences between theory and practice as we proceed.

Policy-Relevant Research

By the early 2000s, it was increasingly apparent that a disconnect existed between the academic study of conservation and the “on-the-ground” practice of conservation. The scientific literature was biased to conservation theory and not well suited to real-world applications (Knight et al. 2008). Commentators referred to this as an “implementation crisis” (Biggs et al. 2011).

The disconnect between research and practice reflected a reluctance by academic scientists to stray very far from their professional comfort zone. In the words of Knight et al. (2006 p. 410), “Few academic conservation planners regularly climb down from their ivory towers to get their shoes muddy in the messy political trenches, where conservation actually takes place.” In part, this was a consequence of the reward structures within academic institutions, which were geared toward publication in high-profile journals rather than the support of “hands-on” conservation (Hallett et al. 2017). Scientific journals, for their part, placed a priority on novelty and were little concerned with the particulars of specific management applications. Finally, the reality was that problems that were interesting were not always important, and problems that were important were not always interesting (Cook et al. 2013). Moreover, many researchers had a personal aversion to the policy arena, which they perceived as a foreign and unfriendly landscape.

In recent years, an effort has been made to build support for policy-relevant research, also referred to as translational ecology, and to develop principles and guidelines for its implementation (Reed et al. 2014; Enquist et al. 2017; Hallett et al. 2017). Policy-relevant research is science with a mission. Success is not measured in terms of where a paper is published or how many citations it receives but in its utility in supporting practical conservation decision making and action. One might argue that this is what conservation biology has always been about. But the implementation crisis suggests that, in the past, this has been more of an aspiration than a reality.

The foundation of policy-relevant research is direct communication with other participants in the decision-making process (Biggs et al. 2011; Reed et al. 2014). This communication needs to be “a two-way process based on effective relationships rather than on simply telling” (Forbes 2011, p. 221). Applied researchers also should understand how policy and planning decisions are made.

A solid grasp of the social dimensions of the issue at hand is another prerequisite (Game et al. 2015). This requires engagement at the local level. What are the main concerns? What perspectives do key stakeholders hold? What are the major points of conflict and barriers to implementation? Who will implement the decisions, and what constraints do they operate under?

Policy-relevant research also requires careful attention to study design. Studies should be situated within a broader decision-making framework and orientated toward implementation (Knight et al. 2008). The key attributes of policy-relevant research are salience, credibility, and legitimacy (Cook et al. 2013). Salience assures that the research is relevant and timely and that the format, timing, and resolution are appropriate. Credibility assures that a study is perceived as authoritative, believable, and trusted because of a transparent and robust scientific process. Legitimacy assures that the research process takes account of the values, concerns, and interests of all relevant actors, as well as practical constraints on decision making such as economic cost and existing policy.

Another important aspect of study design is determining how far to extend the research into the domain of social decision making. In the past, the tendency has been to focus on the ecological aspects of a problem and then pass the baton. Reserve design is a prominent example. Countless reserve designs have been generated that represent optimal reserve configurations from a purely biocentric perspective. These are dutifully passed on to government decision makers who often dismiss the recommendations on the grounds of impracticability (Knight et al. 2008).

Better conservation outcomes can be achieved if socio-economic trade-offs are incorporated into the reserve design process (see Chapter 8). By doing so, reserve designs can be identified that achieve stated conservation objectives while minimizing conflict with other values. Such designs are more likely to be implemented than designs that focus only on the biotic dimension. Doing this effectively requires collaboration between researchers, land managers, and stakeholders. The same principles apply to other forms of conservation research.

Policy-relevant research is most challenging when existing policy is itself part of the problem (Karr 2006). In such cases, research into policy alternatives may be of greater benefit to biodiversity than supporting the implementation of an existing policy. However, research of this nature may be disregarded by decision makers, at least in the short term, because of a perceived lack of alignment and legitimacy. Thus, the dilemma facing researchers is deciding which course of action—supporting an existing policy or challenging it—will be of greatest benefit to conservation. This is part of the agenda-setting role of science.

Because policy-relevant research has an applied focus, it is possible, and indeed imperative, to learn from experience. Ehrenfeld (2000) states:

We must give up the self-serving belief that an increase in our scientific knowledge by itself will always move us toward effective conservation. To help identify conservation strategies that work, conservation biology must close critical feedback loops by emulating medicine and regularly monitoring the effectiveness of its research and recommendations. (p. 105)

The final component of policy-relevant research is knowledge transfer (Reed et al. 2014). Simply publishing findings in research journals is not sufficient. Few managers have time to read and synthesize the relevant primary literature (Pullin et al. 2004). Also, it cannot be assumed that the facts speak for themselves. Instead, the scientists who conduct the research are in the best position to interpret the findings and recommend how they apply to specific policy or management decisions (Noss 2007).

Knowledge transfer to decision makers is achieved by channelling research findings into review articles and summaries and into decision support systems (Dicks et al. 2014). It is also achieved through direct collaboration in decision-making processes (Enquist et al. 2017). Researchers should make an effort to frame the information in a way that is understandable and actionable (Weber and Word 2001; Forbes 2011). Aspects of the research that impinge directly on management decisions and implementation issues should be emphasized. Finally, outreach efforts should target not only government decision makers, but other actors in the policy process, including ENGOs, industry, and other stakeholders (Lach et al. 2003). In Chapter 10, we will discuss how this can be accomplished within a structured decision-making framework.

In summary, policy-relevant research provides a vital bridge between basic biological science, conservation theory, and conservation as it is practiced in the field. Policy-relevant research does not replace basic science and theory; it is an extension of them. Different skill sets are involved, so a degree of specialization is to be expected. Moreover, individual researchers may emphasize different roles over the course of their careers, as their knowledge and interests evolve.

Challenges

Making science relevant to decision makers is not the only challenge in its application to conservation. Capacity constraints are a major limitation, both in terms of funding and the availability of researchers with relevant expertise. Another problem is that ecological research is inherently time-consuming, which means that knowledge gaps related to pressing management issues cannot be addressed quickly (Mills and Clark 2001). In practice, decision making must often proceed with incomplete knowledge. The value of research tends to be realized over the longer term, in successive iterations of the policy and planning cycle. Finally, because ecological systems are highly complex, research results are usually accompanied by caveats and contingencies. This can frustrate decision makers seeking straightforward answers to their problems.

Also, though it may seem obvious that incorporating scientific information produces better decisions than simply muddling through, it is not always welcome. Science may be rebuffed when it draws unwelcome attention to policy failures or is seen as a challenge to the status quo (Wilson 1998). As we saw in Chapter 3, political leaders and government bureaucrats often find change threatening and may resist it. As a result, scientific information concerning ecological threats is sometimes willfully disregarded and management solutions ignored, to the frustration of conservation practitioners.

In the worst case, governments may actively discourage the creation and dissemination of scientific information or attempt to intimidate or discredit individuals and organizations engaged in generating it (Carroll et al. 2017). In Canada, we saw this happen with the Harper government’s “War on Science,” and it was also a key feature of the Trump administration in the US (Turner 2013).

We are now also witnessing the rise of an anti-science movement among factions of the public, with widespread skepticism of climate change and vaccination as prominent examples. The causes of this movement are manifold and complex; however, one of the main factors is increased polarization of society, abetted by media fragmentation (Carmichael et al. 2017). What you believe increasingly depends on which “tribe” you belong to (Hayhoe and Schwartz 2017). The replacement of reasoned debate with arguments over “alternative facts” is extremely retrogressive and bodes poorly for conservation and policy development in general.