Four boxes represent the four sections of the book. Horizontal box (Section: Recognise the problem) is highlighted indicating the current section. This box sits above three greyed-out vertical boxes side by side. Arrow points from left of horizontal box to left vertical box (Section: Create demand for evidence use) and from right of horizontal box to right vertical box (Section: Collate and assess evidence). Arrow from left and right vertical boxes point to central vertical box (Section: Deliver change)

1. Introduction

The Evidence Crisis and the Evidence Revolution

William J. Sutherland1,2

© 2022 William J. Sutherland, CC BY-NC 4.0

Alongside many examples of highly effective practice, there are numerous studies showing ineffective practice. These studies suggest substantial improvements in efficiency are possible, meaning considerably more could be achieved for the same budget. Other fields, such as medicine and aviation, have shown how large improvements can be achieved through collecting and applying evidence effectively. A number of barriers hinder more effective practice, such as the challenges of accessing appropriate information and evidence complacency, where evidence is not sought despite being available. This chapter thus outlines the problems: the subsequent chapters provide the solutions.

Four boxes represent the four sections of the book. Horizontal box (Section: Recognise the problem) contains a smaller horizontal box (Chapter: Acknowledge evidence crisis) which is highlighted indicating the current chapter. The horizontal box sits above three greyed-out vertical boxes side by side. Arrow points from left of horizontal box to left vertical box (Section: Create demand for evidence use) and from right of horizontal box to right vertical box (Section: Collate and assess evidence). Arrow from left and right vertical boxes point to central vertical box (Section: Deliver change)

1 Conservation Science Group, Department of Zoology, University of Cambridge, The David Attenborough Building, Pembroke Street, Cambridge, UK

2 Biosecurity Research Initiative at St Catharine’s (BioRISC), St Catharine’s College, Cambridge, UK

1.1 The Aim of the Book

This book seeks to convince policy makers and practitioners that there are considerable problems with how decisions are usually made and that they need to take this seriously. It seeks to outline a range of straightforward practical solutions that can improve the use of evidence, improve the decision-making process and then embed evidence into practice. This increase in efficiency could either reduce expenditure or allow greater impact with the same budget. Furthermore, this increased efficiency could well make the field more attractive to fund. The overall aim is that better, and more, practice will result in a better planet.

1.2 The Evidence Crisis

There are innumerable success stories in which problems have been revealed and solved through a mix of science, policy and practice. These include many stunning protected areas (with Yellowstone in the USA as a pioneering example); improved species management meaning numerous species have been restored that would otherwise almost certainly have gone extinct (Bolam et al., 2021); numerous effective reintroduction projects (such as the beaver to numerous locations); reducing the problem of acid rain on forests and lakes by regulating to reduce sulphur dioxide and nitrogen oxide emissions; the Montreal Protocol restricting the use of various chemicals that cause the degradation of the ozone layer; the banning of dichlorodiphenyltrichloroethane (DDT) and related pesticides due to evidence of severe impacts of wildlife; the spread of many once severely persecuted species such as lynx due to reductions in persecution; and the recovery of the great whales from overexploitation.

Alongside these wonderful examples of effective use of evidence, there are many examples (Box 1.1) of poor evidence use and decision-making that lead to downright poor decisions to the detriment of both nature and people.

Although there are clearly substantial gains to be made by adopting effective practice, various studies (e.g. Pullin et al., 2004; Sutherland et al., 2004; Bayliss et al., 2011; Young and Van Aarde, 2011; Cvitanovic et al., 2014) have shown that conservation managers tend not to use scientific evidence to support their decision making. Instead they mainly rely on personal experience, anecdotes and the advice of colleagues. Walsh et al. (2015) asked 92 conservation managers, predominantly from Australia, New Zealand and the UK, whose work involved reducing predation on threatened birds, to provide opinions on 28 management techniques to reduce this problem. Managers were asked their opinions before and after giving them a summary of the literature about the interventions’ effectiveness. On average, each survey participant changed their likelihood of implementing 45% of the interventions after reading the evidence of effectiveness. Unsurprisingly they switched to preferring actions shown to be effective and avoided the ineffective ones. This shows how enabling practitioners to access evidence can considerably change their preferred decisions toward more effective practices.

In his PhD, Andrea Santangeli (Santangeli, 2013) presented experimental tests of the effectiveness of ten conservation measures for protecting birds of prey on the resulting production of fledglings. Six were beneficial, two made no difference and two were detrimental. In a subsequent paper, Santangeli and Sutherland (2017) calculated that a programme solely carrying out the effective measures would save about €78,854 (or 21.9% of the budget) annually. They then calculated the gain from this research: given the initial investment of about €156,211 for a PhD thesis, the financial return over a 10-year period ranges between 292% and 326%, depending on how costs are estimated. This shows that research on the effectiveness of actions can be hugely cost effective.

1.3 Why is Poor Decision Making So Common?

There are a host of practical reasons that hinder the use of evidence in decision making. The lack of availability of evidence can be a significant issue, due to (1) the subject being obscure or having not yet been researched resulting in a lack of relevant information, (2) the key information being behind a paywall, or (3) the evidence having not been compiled for a particular issue making it difficult to find or use. However, there is also an extensive range of further challenges to using evidence. Walsh et al. (2019) collated a comprehensive inventory of 230 factors that facilitate or limit the use of scientific evidence in conservation management decisions (Figure 1.1).

A flow diagram with 'research production' flowing to 'research use' and back to 'research production' at the centre around 'knowledge exchange and mediation'. Around these are 7 lists of barriers titled 'nature of the evidence', 'research-practice links' and 'decision context', and those for characteristics of knowledge actors as 'researchers and research organisations', 'practitioners', 'management organisations', 'other stakeholders' and 'wider community'.

Figure 1.1 Taxonomy of 230 barriers and enablers to using scientific evidence in conservation management and planning decisions. (Source: Walsh et al., 2019, CC-BY-4.0)

However, alongside these many understandable reasons, there is also the widespread failure to use evidence even when it is easily available and practical to do so. There seem to be four main reasons for such poor decision making.

Conflict of interest

Conflict issues include cases of corruption because of financial or political gain. For example, the oil industry was aware of climate change yet undermined the crucial science (Oreskes and Conway, 2010). More commonly, personal values, interests and preferences (such as preferring a particular project or individual or disliking a particular outcome) can influence decisions; such motivational bias can lead to an unfavourable decision.

System 1 thinking

The Nobel Prize-winning psychologist Daniel Kahneman, in his book Thinking Fast and Slow (2011), made the distinction between two processes for thinking. System 1 is ‘fast, instinctive and emotional’, and well suited to the majority of quick, daily decisions. System 2 is ‘slower, more deliberative and more logical’, and suited to the occasional serious challenge. Evoking System 1 thinking for more complex decisions instead of slow, careful, analytical thinking (System 2) can lead to poor decisions.

Overconfidence effect

The overconfidence effect is an unwarranted confidence in ability. This can be illustrated by three phenomena: (1) people routinely overestimate their actual performance (e.g. the number of answers they got right); (2) people routinely overestimate their performance relative to others (e.g. most believing they are in the top 10%); (3) when asked to give an estimate range within which the answer lies, people are unjustifiably precise in their accuracy – so the correct answer regularly lies outside the stated range (Moore and Healy, 2008). These phenomena have been shown in repeated studies, including by those who are identified as experts (Burgman, 2015).

Evidence complacency

Almost 20 years ago, Sutherland et al. (2004) identified the serious challenges facing conservation practitioners wishing to read the scientific literature. These included journal paywalls, the lack of effective search engines and the challenges of extracting messages from scientific papers, resulting in practitioners making limited use of the available science. Since then, the power of search engines, open access papers and the development of evidence-based conservation has reduced these barriers, yet some of the challenges shown in Figure 1.1 remain. Although some conservation organisations produce and use excellent science, Sutherland and Wordley (2017) suggest that a culture of ‘evidence complacency’ remains in many areas of policy and practice. They used this term to describe a way of working in which, despite availability, evidence is not sought or used to make decisions, and the impact of actions is not tested.

As illustrated by the continuation of mistaken guidance to place babies on their fronts to sleep (see Section 1.4), ideas can become standard practices without consideration of the evidence or without a process of testing and evaluation. Another example is building bat bridges (placed to encourage bats to fly higher to reduce the risk of vehicle collisions), which were shown to be ineffective (Berthinussen and Altringham, 2012) yet continued to be installed with high financial cost. Such failures to test or search the literature wastes money and effort and also undermines confidence in expertise. Innovation is important, but novel ideas require testing before widespread adoption.

This book describes processes that can be adopted to reduce conflicts of interest, System 1 thinking, overconfidence and evidence complacency from undermining effective decision-making to the detriment of society.

1.4 The Evidence Revolution

We define evidence as ‘relevant information used to assess one or more assumptions related to a question of interest’ (modified from Salafsky et al., 2019). This includes published studies as well as reports, observations, citizen science and local knowledge.

Sackett et al. (1996) described evidence-based clinical decision making as combining research evidence with clinical expertise, alongside consideration of the preferences of the patient. Clinical expertise is the proficiency and judgement that individual clinicians acquire through clinical experience and clinical practice (Satterfield et al., 2009). Figure 1.2 similarly shows how scientific evidence, values, and experience and local knowledge can be combined and how a combination of all three is usually essential.

A Venn diagram containing three intersecting circles. The intersection between the circle titled 'experience and local knowledge' and the circle titled 'values' is labelled 'evidence complacency'. The intersection between the 'values' circle and the circle titled 'Scientific evidence' is labelled 'inappropriately applied conservation'. The intersection between the 'scientific evidence' and 'experience and knowledge' circles is labelled 'inappropriate solutions'. The central intersection of all three circles is labelled 'evidence-based conservation'.
A Venn diagram containing three intersecting circles. The intersection between the 'experience and local knowledge' circle and 'values' circle is labelled 'install bat gantires'. The intersection between the 'values' and 'Scientific evidence' circles is labelled 'install green bridge far from bat commuting route'. The intersection between the 'scientific evidence' and 'experience and knowledge' circles is labelled 'install unlit pedestrian and bat underpass prompting safety fears'. The central intersection of all three circles is labelled 'install evidence-based acceptable underpass'.

Figure 1.2 The role of evidence in evidence-based conservation, where values incorporate ethical, social, political and economic concerns. Top: how the components interact. Bottom: an example of how this might be applied to the problem of bats being killed when flying across a road (Source: author, with thanks to Claire Wordley).

The idea of systematically using evidence has a long history. Box 1.2 outlines some components of this history of evidence use in medicine and conservation.

Medicine provides the classic example of policy and practice being transformed by evidence. Seventeen million parents owned and followed a copy of Spock’s (1946) book, The Common Sense Book of Baby and Child Care. One key issue was whether to place babies on their front or back whilst sleeping. Spock’s suggestion was to place the baby on its front, for the common sense reason of reducing the risk of choking following vomiting; sleeping on the front was routinely recommended in books up to 1988 (Gilbert et al., 2005). Gilbert and colleagues’ 2005 analysis showed that by 1970 the published data indicated that there was a statistically significant increased risk of sudden infant death syndrome for front-sleeping babies. They concluded that had the evidence been reviewed and adopted in 1970, those results might have prevented over 10,000 infant deaths in the UK, with many more globally. Surely few things are more important than unnecessary baby deaths, yet the research was not converted into practice. A series of evidence reviews have also similarly shown fallacies in common sense treatments (enemas for women in labour [Cuervo et al., 1999], resting in bed after heart attacks [Sackett et al., 1996], giving corticosteroids to women about to have a premature baby to help the baby breathe [Liggins and Howie, 1972]). Medicine has been transformed with multiple mechanisms in place to reduce the chance of practising actions known to be ineffective or damaging.

But is evidence-based practice actually more effective? Emparanza et al. (2015) took advantage of the creation of an evidence-based practice unit in a hospital in Spain in 2003. They compared the fate of patients before and after the creation of the unit and in comparison with the rest of the hospital, which remained unchanged. Patients in the evidence-based unit had a significantly lower risk of death, 6.27% vs 7.75%, and a shorter length of stay, 6.01 vs 8.46 days, than those receiving standard practice. This is a 19% reduction in deaths and a 29% reduction in hospital stays.

Other fields show how improvements in decision making can be made. Aircraft flight safety has an impressive record: the total number of annual fatalities has tumbled 5–10 fold since the 1970s (Aviation Safety Network database despite enormous increases in passengers carried over that time (Gössling and Humpe, 2020). Each aircraft disaster is followed by review, reflection and, if necessary, changes in practice. As an early example, after a series of crashes in the B-17 aircraft in 1942, Alphonso Chapanis interviewed pilots who had survived such crashes. He identified the problem of pilots muddling the adjacent, and similar-looking, landing gear and wing flap levers, which sometimes led to disastrous consequences (Syed, 2015). Adding wheel-shaped symbols to the landing gear lever and wedge-shaped symbols to the wing flap levers overcame the problem and became routine.

As another example, the manager of the low-budget Oakland Athletics baseball team used statistical analysis over the opinions of scouts in selecting team members. Following a 20-game winning streak, this evidence-based approach has become universal across baseball teams (Lewis, 2003).

Whilst the conservation community could review previous problematic programmes such as the Common Agricultural Policy, Indian tree-planting project, or the various unsuccessful mangrove planting schemes (Box 1.1) and incorporate the lessons in future plans, this feedback loop does not form a routine part of current processes, leading to the perpetuation of mistakes. Similar transformations to medicine are possible (and crucial) for other fields. As described in Chapters 2 and 3, for conservation, evidence collation is being delivered at scale, and a number of conservation organisations have restructured themselves around the use of evidence in delivering action (Chapter 11).

The need for evidence is being increasingly recognised. Figure 1.3 is an attempt to bring together the challenges and options for change. The idea is that crises, such as evidence failures, drive demands for change. This book describes how to deliver tools and approaches that may change how practitioners, policy makers, businesses, and funders work, leading to an improved world.

A flow diagram with five boxes labelled from left to right as 'problem', 'challenge', 'enablers', 'changers' and 'consequences'. The ultimate consequence being 'markedly improved environment with better funded and more effective practice'.

Figure 1.3 How the various evidence crises are likely to create demands for change that the enablers described in this book could help deliver, resulting in a series of improvements and a markedly better planet. References: (a) Coleman et al. (2021); (b) Downey et al. (2022); (c) Dicks et al. (2014); Pe’er et al. (2020); (d) European Court of Auditors (2020); Giakoumi et al. (2018); Wauchope et al. (2022); (e) Hunter et al. (2021); Laurance (2022); (f) Burgman (2015); Kahneman et al. (2021); Kahneman (2011); Pinker (2021); Tetlock (2009). (Source: author)

1.5 The Case for Adopting Evidence Use

The main argument for increasing the use of evidence is that it will improve practice resulting in better outcomes and reduced costs. It is also likely that improving effectiveness will attract or secure further funding (Box 1.3).

1.5.1 The potential gains from transforming conservation

This chapter outlines what seems to be an overwhelming case for taking evidence use much more seriously. This includes billions of euros, dollars and pounds spent on practices known to be ineffective, and numerous studies showing that evidence is rarely used, alongside studies showing guidance is typically out of date and poorly evidence-based. Table 1.1 lists those studies that test gains from improving efficiency as reviewed in Section 1.2 showing the clear opportunity to improve following the good practice.

Subsequent chapters will show similar, equally serious problems in other stages of the decision-making process: as examples, it is rare to start by considering the full range of possible options; experts are usually used in ways that extensive research shows are likely to enhance bias and produce wrong answers; decision-making rarely follows processes known to be effective; costs are usually not presented in the manner that makes them comparable; other sources of knowledge are typically used haphazardly; there is ineffective learning from failures and there is rarely any effective learning.

Table 1.1 Summary of studies looking at inefficiencies or potential gains in investment from using evidence.


Percentage change in effectiveness


Test of applying evidence-based medicine

19% reduction in deaths; 29% reduction in hospital stays

Emparanza et al. (2015)

Marine protected areas

29% not positively influencing fish populations

Gill et al. (2017)

The Common Agricultural Policy agri-environment measures

Compared to controls, 6% of studies showed decreases in species richness or abundance, 17% showed increases for some species and decreases for other species, 23% showed no change at all in response to agri-environment schemes (46% in total) and 54% showed increases.

There has been no increase in the effectiveness of measures over time.

Kleijn and Sutherland (2003)

Batáry et al. (2015)

Experimental tests of the effectiveness of 10 conservation measures for protecting birds of prey

Just carrying out effective measures could achieve the same outcomes for 22% less expense

Santangeli and Sutherland (2017)

Estimated effectiveness orangutan Pongo spp. conservation measures in relation to investment (US$1.2 billion)

Some actions (habitat protection; patrolling activities) 300–400% more cost effective than others (habitat restoration, rescue and rehabilitation, and translocation)

Santika et al. (2022)

Review of the papers in Conservation Evidence Journal that test effectiveness of actions

Of those applied interventions that were tested 31% could be considered as unsuccessful

Spooner et al. (2015)

Effectiveness of protected areas for waterbirds

27% of all populations positively impacted by protected areas; 21% negatively impacted; 48% no detectable impact

Wauchope et al. (2022)

1.6 The Inefficiency Paradox

The paradox described in this chapter is that society could relatively easily be more effective and save considerable amounts of money, but fails to be. Identifying solutions to this paradox is central to this book. Thus, the key chapters may seem to be those describing evidence assessment, expert elicitation or structured decision-making. Actually, they are the chapters describing how to achieve the cultural shift in which evidence becomes embedded in processes or organisational cultures.

Funders could achieve greater impact, governments could deliver more (or spend less), organisations could be more ambitious, consultants could be more effective, and businesses could reduce harm and increase benefits. Some pioneer organisations are taking evidence use seriously (see Chapter 11): they will lead the way in the necessary revolution.

1.7 Transforming Decision Making

It is conventional to illustrate decision making as a policy cycle with a logical flow of steps from identifying problems to determining the policy; it is, however, generally accepted that policy making rarely, if ever, proceeds this way (Owens, 2015). As shown in Figure 1.4, in practice, there is rarely a single assessment of each stage (i.e. as if going once round the outer loop). In reality, decisions may start at any of the stages and the process of making the decision means each stage becomes more focused spiralling inwards towards a final decision. Evidence is embedded in many of these stages.

The figure shows four concentric hexagons, with the largest concerned with broad scale, the next more focussed, the next specific and the central hexagon labelled 'decision'. The six segments are labelled as the legend describes, each leading round to the next.

Figure 1.4 The Policy Hexagon. The logic is identifying responsibilities, identifying problems, finding options, considering effectiveness, and making a decision leading to the implementation of a policy or practice. (Source: author)

With this framework, the decision-making process is complex and does not always start at the same stage. For example, it may start with considering a responsibility, such as what to do to protect a threatened species on your land, or by considering a threat and the range of options, or sometimes with someone promoting a solution and the need to consider whether this is appropriate. Table 1.2 shows how thinking usually progresses from the general to the specific as the decision becomes articulated.

Table 1.2 How the components of decision making shown in Figure 1.4 become more precise as thinking moves around and inwards around the hexagon towards making a decision.


Initial consideration

More specific consideration

Decision-making stage

Tools (and section numbers)

Identifying interests and responsibilities

Overall interests and responsibilities in this field

More specific consideration of priorities

Precise target of actions

Identifying stakeholders (6)

Defining the scope of the project and its targets (7.2)

Identifying problems relating to these interests and responsibilities

General problems

More specific problems relating to interests and threats

Precise problem that proposed actions will deal with

Determining feature status (7.3.1)

Assessing changes in feature status (7.3.2)

Characterising current threats (7.4.1)

Diagnosis: identifying the likely cause of declines (7.4.2)

Horizon scanning to explore potential futures (7.4.4)

Scenario planning for potential futures (7.4.5)

Identifying possible options

Broad range of options for dealing with threat

Consultation for other solutions

Fine tuning of options

Solution scanning (7.6.1)

Innovating to devise novel solutions (7.6.2)

Evaluating likely effects of actions (7.6.3)

Theory of change (7.6.5)

Developing questions and assumptions in situation models and theories of change (7.7.1)

Identifying priority questions for policy and practice (7.7.2)

Unpacking questions (7.7.3)

Assessing likely effectiveness of options

General effectiveness of actions

Searching for further options and modifications

Specific consideration of likely effectiveness of exact options for precise conditions

A framework for assessing the weight of evidence (2.2)

Weighing the evidence (2.3)

Subjects of evidence (2.4)

Sources of evidence (2.5)

Types of evidence (2.6)

Models (2.6.5)

Decision making

Broad consideration of likely options

Reducing list of options and refining those remaining

Final decision considering evidence and all factors

Deciding whether to invest in decision making (8.2)

Decision sketching (8.3.1)

Cost-benefit/cost-effectiveness analysis (8.3.2)

Sketching means-ends networks (8.3.4)

Consequences tables (8.5.1)

Addressing trade-offs (8.5.7)

Strategy tables (8.6)

Decision trees (8.9)

Creating models (8.10)

Achieving consensus (8.11)

Dealing with conflict (8.11.1)

Agreeing policies or practice

Initial thoughts of policies

Fine-tuned policy

Specific detailed policy or practice

General principles for embedding evidence into practices (9.2)

Evaluating evidence use (9.3)

Evidence-based species and habitat management plans (9.4)

Evidence-based guidance (9.5)

Evidence-based policy (9.6)

Evidence-based business decisions (9.7)

Evidence-based writing and journalism (9.8)

Evidence-based funding (9.9)

Evidence-based decision-support tools (9.10)

Evidence-based models (9.11)

The approaches describe above seems to apply equally to other areas of practice. Table 1.3 lists a set of ten questions for identifying the extent of good practice.

Table 1.3 Suggested questions for determining the extent of good practice.


Good practice

Weak practice

How have you determined the main issue that needs resolving?

Priorities identified, threats assessed and main problems diagnosed.

Assumed knowledge of what the main issue is (but cannot exclude other options).

How have you engaged with the community so they feel appropriately involved?

Identification of those who should be consulted, informed and involved in decision making followed by involvement.

Some discussions with local community.

Do you know how others deal with the problem (e.g. ask, ‘how do they deal with the issue in Japan*?’)?

An extensive range of options initially considered, for example as derived by a broad international group.

Consider the well-known options.

Has the published evidence been collated?

Reasonably comprehensive collation of evidence, in multiple languages, has been carried out by someone.

Uses literature that their experts are aware of.

How is the evidence used in making decisions?

Routinely include the process of assessing and reflecting on collated evidence.

Assume experts have knowledge of the evidence.

How has local knowledge been embedded in decisions?

Relevant knowledge, including on uses, values and beliefs, documented and used.

Informal consultation with locals.

How do experts contribute to decision making?

For key issues, methods are used to reduce bias.

Take views of an expert or the consensus of a group.

What is the process by which decisions are made?

Important decisions made using a structured decision-making approach.

Decision agreed by discussion.

Is the logic for the decision documented so it can be used by others?

Reasons for decisions documented so others can learn.

Lessons learnt and shared.

Is there ever any formal testing?

For important areas of uncertainty tests are routinely embedded into practice.

Occasionally try things out to see if they work and share verbally. Promote successes as case studies.

*or, ‘how do they deal with the issue in the UK?’ if in Japan

1.8 Structure of the Book

This book brings together the leading experts in the different elements of the process of improving decision making in conservation. The logic of the book follows two elements (presenting evidence and transforming culture) that feed into the decision-making process (Figure 1.5). The idea of using information and experts to make judgements is, of course, routine and unsurprising. The differences sought here are aiming to improve rigour, transparency and repeatability.

Four boxes represent the four sections of the book. Horizontal box (Section: Recognise the problem) sits above three vertical boxes side by side. Arrow points from left of horizontal box to left vertical box (Section: Create demand for evidence use) and from right of horizontal box to right vertical box (Section: Collate and assess evidence). Arrow from left and right vertical boxes point to central vertical box (Section: Deliver change)

Figure 1.5 How the book sections and chapters (numbered) link together. The recognition of the evidence crisis leads to both a demand for evidence use (left) and processes for collating and assessing evidence and reducing bias in judgements (right). The central decision-making process running from identifying who should be involved to learning from the decision is driven by the demand for evidence and fed by evidence and judgements. (Source: author)


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