1.3: The Value of Scientific Methods

The field of conservation biology applies scientific methods to achieving its goals. Like the medical sciences, which apply principles from physiology, anatomy, and genetics to problems of human health, conservation biologists solve biodiversity problems using principles from fields, such as mathematics, veterinary medicine, social sciences, and several natural sciences (Figure 1.3). Conservation biology differs from these and other component disciplines in that its primary goal is the long-term preservation of biodiversity. Unlike many other scientific fields, conservation biology can also be described as a crisis discipline (Soulé, 1985; Kareiva and Marvier, 2012). That is, conservation biologists are often required to take creative steps to respond to imminent threats, typically without a complete knowledge of the systems requiring attention. Conservation scientists must also articulate long-term visions for conservation beyond solving immediate problems.

Figure 1.3 Conservation biology draws from many other sciences to protect biodiversity. It is closely related to natural resource management, which aims to manage biodiversity primarily for the benefit of humans. Integrated conservation and development projects (ICDP) are projects that manage nature for the benefit of both humans and biodiversity. After Kareiva and Marvier, 2012; Temple, 1991, CC BY 4.0.

To be effective, conservation biologists must demonstrate the relevance of their findings to a range of stakeholders. To be successful in this task, the importance of sound scientific principles cannot be over-emphasised. Nature is a complex network of many interdependent connections and feedback loops. Science is underpinned by principles that provide conservationists the necessary quantitative and qualitative tools to better measure and control for all these different aspects of biodiversity. Such measurements allow us to gain a better understanding of complex natural systems, and the consequences of human activities. Reliable, unbiased data obtained from sound and transparent scientific methods also facilitate policy making that is too often based on value judgments by non-experts who must balance many needs and different sources of information (Ntshotsho et al., 2015).

One of the cornerstones of modern science is to identify a hypothesis (a proposed explanation for a specific observation) to evaluate. The best hypotheses, often expressed as goals or objectives, are usually those that are SMART:

Setting specific, measurable, realistic and timebound goals and objectives is essential for effective conservation.

Specific: not overly general;

Measurable: has both units and a method of measurement;

Attainable: realistic to achieve;

Relevant: related to what needs to be accomplished;

Time-bound: achievable within a specific timeframe.

Identifying SMART goals and objectives is an essential aspect of conservation biology. Without such benchmarks, practitioners cannot know whether their tasks were successful, or when management actions should be adjusted to achieve success. While this may seem obvious, many previous conservation projects have failed because biologists neglected to set SMART goals and objectives (Tear et al., 2005). While lofty, “We’re going to save all species” is not a SMART conservation goal because it is overly general, hard to measure, unrealistic, and not time bound. In contrast, “We want to protect 25% of our country’s wetlands within the next 10 years” is a SMART goal because it sets a very clear and measurable objective. In general, it is wise to set smaller short-term (e.g. quarterly), and medium-term (e.g. annual) goals as one works towards long-term (e.g. 5–10 years) objectives; this allows one to constantly assess progress, which in turn provides opportunities for celebrations and strategic adjustments as and when needed.

Too many conservation decisions are based on biased anecdotes, personal intuition, and myths.

Another scientific standard that conservation practitioners must adopt at a larger scale is the transfer of knowledge gained from unique and specialist experiences. Conservation activities are too often hampered by the lack of guidance from credible and available sources. This forces conservationist managers to base important decisions on biased anecdotes, personal intuition, and even myths (Sutherland et al., 2004). Successful conservation actions on the other hand often rely on results and guidelines that were disseminated to the broader community by practitioners who faced similar challenges earlier. To maximise this learning from each other’s successes and mistakes, it is crucial for conservation scientists and managers to make every effort to ensure knowledge transfer, by carefully tracking their activities, and publishing their results and experiences in scientific journals and reports.

Public outreach builds on the public’s existing connection to nature and helps them better understand the value of local biodiversity.

Biodiversity conservation, however, is not accomplished by simply setting SMART goals, measuring outcomes, and publishing results in scientific journals and reports. It is also important for conservation biologists to engage in public outreach activities, during which they can build on the public’s existing connection to nature, help them better understand the value of biodiversity in their local area, and enable them to actively contribute in conservation projects. When interacting with the public, conservation practitioners must be sensitive to the complicated emotions and diverging interests of different groups of people (Milfont et al., 2017), especially vulnerable peoples who may be negatively impacted—hopefully only in the short term—by conservation actions. This requires a sense of emotional awareness, because the words we choose matter when we encourage others to care for and reduce their impact on nature. Equally important, conservation biologists, as with any field of science, should be sceptical of their results. The process of generating data is not equal to generating facts, because data can be fraught with bias, imprecision, and uncertainty. This is perhaps even more important when sharing findings with lay people, as scientists have rigorous training in understanding uncertainty and connecting cause and effect. Putting scientific findings in context with adequate and clear explanation is a challenge to all scientists, but it is necessary, especially when partnering with conservationists not specifically trained as scientists.