Paleoecology grand challenge

Exactly 50 years ago, in 1964, a landmark article whose two-word title, “Strong inference,” revealed little and evoked plenty, appeared in the hallowed pages of Science (Platt, 1964). Simply stated, Platt’s view of scientific research in its highest form proceeds through three steps: development of alternative hypotheses; design of crucial experiments to exclude one or more hypotheses; execution of careful studies to obtain clear-cut results. It was a powerful reminder of how problem solving can be performed, written in a style both informal and authoritative. In those days it was not unusual for the most prestigious scientific outlets to publish articles whose language seems to nowadays have been relegated to blog posts. Just seven years earlier, another Science paper had appeared with a whimsical title, “Biological clock in the unicorn” (Cole, 1957), addressing the excessive reliance on statistical analysis of cycles and correlations that was plaguing the biologists of the time. Among the many citable passages in either one of those articles, one may dwell on a segment in Platt’s text: “Whether it is hand-waving or number-waving or equation-waving, a theory is not a theory unless it can be disproved. That is, unless it can be falsified by some possible experimental outcome.” Literal interpretations of such statements, especially when translated to all possible scientific research, are problematic, and Platt’s impact is best described as “more an inspirational tract than the development of a formal scientific methodology” (Davis, 2006). It is in that vein that I decided to open this Grand Challenge editorial by evoking a paper from half a century earlier. Paleoecology, as any other branch of retrospective science, does not easily lend itself to experimentation. Not because of any fault of its own, but simply because there is no experimental outcome capable of reversing the unidirectionality of time. Elsewhere (Biondi, 2013) I have explored the tension created by the imperative to understand ecosystem legacies and past environmental drivers against the impossibility of distinguishing between true and false when dealing with the past. As it turned out, I was partly rephrasing the meaning of “historicity,” i.e., “the necessity of working with complex and unique events in time” (Gould, 1980). In the same vein, but even earlier, Nagel (1952) had discussed in detail the distinction and connections between the “nomothetic” aspects of science, “which seek to establish abstract general laws for indefinitely repeatable processes,” and the “idiographic” ones, “which aim to understand the unique and nonrecurrent.” These issues cut across the timescales used by Jackson (2001) to distinguish between “real time” (for modern ecology), “Qtime” (for Quaternary ecology), and “deep time” (for paleobiology and paleontology, which is the subject of another section of this journal). Prescribing, even more than describing, the type of research that this journal section is aiming to attract and publish requires some epistemological considerations. Science is a method for reducing uncertainty (Lindley, 2006): thus, paleoecology could be considered a method for reducing uncertainty about past ecological patterns and processes. A subdivision into preliminary, exploratory, and confirmatory research has been proposed (Flueck and Brown, 1993), although the last term suggests an inherent bias, as even “validation” and “verification” are not truly possible when dealing with open systems (Oreskes et al., 1994). Choice of words notwithstanding, the most productive approach to science was demonstrated recently by the insightful views on exploratory vs. confirmatory research made by Wagenmakers et al. (2012) with regard to psychology—another discipline where experimentation is rarely an option. What they define as confirmatory is in fact the type of rigorous scientific inquiry that begins with a priori definitions of expected outcomes. This practice is diametrically opposed to a posteriori analyses and rationalizations that are inevitably more influenced by investigator’s bias. Their language is explicit, as in stating that “In fact, the advice to torture the data until they confess is not wrong—just as long as this torture is clearly acknowledged in the research report.” For clarity, I have found useful to categorize studies as (a) experimental, which are performed under controlled conditions in a laboratory or in the field with random assignment of treatments to subjects; (b) observational, when conditions are not entirely controlled or the assignment of treatments to subjects is not random; (c) iterative, whereby no treatments are possible, but a specific question is asked a priori and constantly refined by comparing predictions with outcomes (e.g., forecasting, opinion polls); (d) monitoring, when questions may not exist or are asked a posteriori (e.g., surveys, inventories, proxy reconstructions, data mining, remote sensing, cartography, automated recording). It is better to envisage these categories as part of a continuum rather than as discrete entities, so that at one end of the spectrum are experiments, and at the other end are observations designed to obtain descriptive measures of natural phenomena without including control units or manipulation of any