Note from Jeremy: This is a guest post from Allison Moody, a postdoc in conservation biology at the University of Maine. She’s a regular reader and commenter here, and has also corresponded with me on topics relating to my recent E. O. Wilson post and the blog more generally. Her comments are always very thoughtful, and so I invited her to share some of her thoughts in the form of a guest post. So here’s Allison, on the “implementation gap” in conservation biology, whether mathematical modeling is part of the problem (!), and how it could be part of the solution.
Conservation biology as an academic discipline is a relatively new field. The two major conservation biology journals, Biological Conservation and Conservation Biology (not the most creative bunch when it comes to naming) were founded in 1969 and 1986. Obviously, the published work in conservation biology has increase significantly since then (Figure 1). Conservation biology has a unique place in ecology because it’s a combination of theoretical science and applied science, although other ecological fields also have this combination (e.g. wildlife management and invasion biology to name two). It has also often been referenced as a ‘crisis-driven’ field; one that addresses problems after they occur and less frequently, tries to prevent problems from happening in the first place.
Fig. 1: Web of Science search for topic = conservation biology, showing published items in each year. Timescale runs from 1935-2013. Yep, it doesn’t go back farther than that.
All along there have been cries of What about implementation?! The research-implementation gap in conservation biology has been noted since the early days of the field. A survey of authors published in Conservation Biology between issues 1 and 12 (1986-1998) showed that of the 223 respondents, 78% (n = 173) had included management recommendations but of these, only 54% (n = 164) believed their recommendations were being used (Flashpohler, Bub and Kaplin 2000). A more recent survey of conservation assessments published between 1998 and 2002 indicated about a third (n = 29, total n = 88) of conservation assessments led to any implementation, and of these, only 14 were “highly effective”, whereas 21 were “poorly effective” or “ineffective” (Knight et al. 2008).
So, my question is, do the mathematics and statistics published in conservation biology serve as one of the barriers for getting research used by actual conservation practitioners?
Backing up, there is a difference between conservation biologists and conservation practitioners although sometimes these are the same people. Conservation biologists are generally employed by universities as academics and they have the general pressures of academics (teaching, tenure, publishing (publishing, publishing)). Conservation practitioners, on the other hand, are a much broader group that includes non-profit organizations, land managers, politicians, private landowners, etc. If you bought some land and decided you’d like to encourage more Eastern Bluebirds, congratulations, you’re a conservation practitioner! Conservation practitioners have little time to read the literature and often no access, especially in developing countries. They may have undergrad degrees or be many years out of school which means they may not have a thorough, up to date grounding in math and stats.
So, conservation practitioner, what are you going to preserve and how? The conservation biology literature is full of methods for prioritizing species, areas, and actions. Complex models have been developed that will tell you exactly where you need to conserve to preserve a specific suite of animals at some degree of redundancy. But, for you on the ground, you know that one specific patch that is really important for the conservation objective is right in the middle of a planned development and its cost has gone up 10 times since the paper was published. Sure, you could contact the authors of the paper and request they integrate a cost function, or you could just buy this other patch over there that you can afford. Conservation in practice isn’t just about ecology, it involves economics, politics and sociology. The math and statistics involved in modelling are just a couple tools among many that conservation biologists must have to be effective.
It’s cliché, but still my favourite saying – all models are wrong, but some are useful – but useful for whom? In conservation biology, as in any applied ecological field, it has to be useful for the practitioners, not just the people who generate the models. Remember Flaspohler, Bub and Kaplin’s paper above? The #3 reason (behind “agency initiative” and “agency recognition of problem”) authors felt their recommendations were being used, was “recommendations were easily understood” (12%, n = 24). Conservation decisions are always being made by practitioners and it’s important that their decisions are supported by science but to a large degree, it is the conservation biologists who must ensure the models or decision support tools they develop help practitioners directly.
What are the keys to making sure you’re making a useful model?
- Make sure you’re asking the right question. Academia and publishing have different objectives for a study (e.g. novelty, broad focus) than developing tools to help conservation practitioners. Conservation practitioners may be more interested in well-tested decision support tools and a local focus (although not always; Shaw, Wilson and Richardson 2010). To ensure you’re asking the right questions, practitioners have to be involved early in the process and have their input actually guide the process rather than just be for show.
- Model transparency. Explaining the biases and assumptions in a model is also key to having practitioners accept your model outcomes. To convince someone to make a decision using your decision support tool, the process must be transparent and you must be open to defending your process. Transparency also helps with buy-in because people know what they are agreeing to.
- Training. Getting practitioners in early to help develop the question(s) and the methodology for analyzing the problems also helps you explain the process. Remember that these people may not have taken a stats class in 10 years or ever. Technical terminology can be especially dense to practitioners. But conservation biologists also need to accept they need training to work with practitioners. There is a lot of literature out there about expert elicitation, decision theory, and risk analysis; all of which can be important aspects of conservation.
I think among the different ecology fields, the best, most interesting and cleverest modelling is happening in wildlife ecology and conservation biology (I predict this statement might be controversial). Most of my colleagues and I are math and/or stats nerds who are jumping at the chance to stretch our brains into multiple dimensions. We just need to remember that these fields are defined as ‘applied’ and that we need to take our models into the real world.
I want to end by thanking Jeremy for giving me the opportunity to write a guest post. I come from a different background than the front page posters here at the blog, and instead of Jeremy just saying ‘Well, we don’t do that so we won’t cover that’, he responded by asking me to share my point(s) of view. Obviously this post was spurred by the Wilson vs. Fox debate but this issue is something that I’ve been thinking about for a long time now. My first research was on animal behaviour and I’ve done some lab biology before switching to a more applied field. I’ve always been interested in politics and policy and making the switch to applied ecology, and specifically conservation biology, was a really fun and interesting jump. Even though my PhD is in conservation biology or wildlife ecology depending on who you ask (me or my PhD granting university, respectively), I am definitely still learning about the field and what is above is obviously my opinion.
Flaspohler, DJ, BR Bub, and BA Kaplin. 2000. Application of conservation biology research to management. Conservation Biology 14: 1898-1902.
Knight, AT, RM Cowling, M Rouget, A Balmford, AT Lombard, and BM Campbell. 2008. Knowing but not doing: selecting priority conservation areas and the research-implementation gap. Conservation Biology 22: 610-617.
Shaw, JD, JRU Wilson, and DM Richardson. 2010. Initiating dialogue between scientists and managers of biological invasions. Biological Invasions 12:4077-4083.