For far too long, conservation scientists and practitioners have depended on intuition and anecdote to guide the design of conservation investments. If we want to ensure that our limited resources make a difference, we must accept that testing hypotheses about what policies protect biological diversity requires the same scientific rigor and state-of-the-art methods that we invest in testing ecological hypotheses. Our understanding of the ecological aspects of ecosystem conservation rests, in part, on well-designed empirical studies. In contrast, our understanding of the way in which policies can prevent species loss and ecosystem degradation rests primarily on case-study narratives from field initiatives that are not designed to answer the question “Does the intervention work better than no intervention at all?”Thus starts a paper by Paul J. Ferraro and Subhrendu K. Pattanayak in PLoS Biology (Money for nothing? A call for empirical evaluation of biodiversity conservation investments).
Budgets for biodiversity conservation are thinly stretched, and thus judging the effectiveness of conservation interventions in different contexts is absolutely essential to ensuring that scarce funds go as far as possible in achieving conservation outcomes.Despite the title and these initial statements, however, the paper only examines the question whether biological interventions have a discernible positive effect or not (and thus discusses sampling and design issues, and potential confounding factors) and does not deal with their cost-effectiveness. Still, the authors lament that very few conservation projects attempt to measure even whether they are having any environmental effect. "If these methods are so great, why isn't anyone using them?," they ask. One of their answers is that "[D]onors and government agencies that fund conservation projects typically know little about program evaluation methods, and the practitioners who implement the projects typically lack incentives for careful analysis and falsification of hypotheses." In other words, donors and government agencies fund biological interventions but do not further mind whether they work out or not. The paper ends with these words:
As noted in the introduction, we are not advocating that every conservation intervention be evaluated with an experimental or quasi-experimental design, or that every project collect data on outcomes and covariates from treatment and control units before and after the intervention. We are merely advocating that some of the hundreds of millions of dollars that are invested each year in biodiversity conservation initiatives be spent in this manner. The fate of the world's ecosystems and species depends on it.I would advocate that not only should effects be measured but that they should be compared to costs. Only projects expected to yield benefits larger than costs should be carried out. An example of getting this right is a study by Tracey J. Regan and collaborators published in Ecology Letters (Optimal eradication: when to stop looking for an invasive plant):
The notion of being sure that you have completely eradicated an invasive species is fanciful because of imperfect detection and persistent seed banks. [...] Rather than declaring eradication at some arbitrary level of confidence, we take an economic approach in which we stop looking when the expected costs outweigh the expected benefits.The authors study the eradication of Helenium amarum, a plant that invades Australian pastures and "is toxic to stock causing weakness, diarrhoea, vomiting, and bitter undrinkable milk if ingested by milk producing animals." They estimate the potential damages to the dairy industry and then estimate how much effort should be devoted to looking for plants in order to eliminate them.
We do this kind of thing all the time in everyday life. We use rules of thumb to estimate costs and benefits of alternative courses of action and make decisions accordingly. But "we" in this case means individuals paying the costs and reaping the benefits of their actions. Policy-makers do not have the right incentives to make efficient decisions because costs are paid not by them but by taxpayers.