The algorithmic turn in conservation biology: Characterizing progress in ethically-driven sciences.

As a discipline distinct from ecology, conservation biology emerged in the 1980s as a rigorous science focused on protecting biodiversity. Two algorithmic breakthroughs in information processing made this possible: place-prioritization algorithms and geographical information systems. They provided defensible, data-driven methods for designing reserves to conserve biodiversity that obviated the need for largely intuitive and highly problematic appeals to ecological theory at the time. But the scientific basis of these achievements and whether they constitute genuine scientific progress has been criticized. We counter by pointing out important inaccuracies about the science and rejecting the apparent theory-first focus. More broadly, the case study reveals significant limitations of the predominant epistemic-semantic conceptions of scientific progress and the considerable merits of pragmatic, practically-oriented accounts.

The crucial but underrepresented role of philosophy in conservation science curricula.

Article impact statement: Normative scientists must be trained in current thinking of the philosophy that underlies their fields, an issue not fully realized in conservation.

X-Phi and Carnapian Explication.

The rise of experimental philosophy (x-phi) has placed metaphilosophical questions, particularly those concerning concepts, at the center of philosophical attention. X-phi offers empirically rigorous methods for identifying conceptual content, but what exactly it contributes towards evaluating conceptual content remains unclear. We show how x-phi complements Rudolf Carnap's underappreciated methodology for concept determination, explication. This clarifies and extends x-phi's positive philosophical import, and also exhibits explication's broad appeal. But there is a potential problem: Carnap's account of explication was limited to empirical and logical concepts, but many concepts of interest to philosophers (experimental and otherwise) are essentially normative. With formal epistemology as a case study, we show how x-phi assisted explication can apply to normative domains.

Voting systems for environmental decisions.

Voting systems aggregate preferences efficiently and are often used for deciding conservation priorities. Desirable characteristics of voting systems include transitivity, completeness, and Pareto optimality, among others. Voting systems that are common and potentially useful for environmental decision making include simple majority, approval, and preferential voting. Unfortunately, no voting system can guarantee an outcome, while also satisfying a range of very reasonable performance criteria. Furthermore, voting methods may be manipulated by decision makers and strategic voters if they have knowledge of the voting patterns and alliances of others in the voting populations. The difficult properties of voting systems arise in routine decision making when there are multiple criteria and management alternatives. Because each method has flaws, we do not endorse one method. Instead, we urge organizers to be transparent about the properties of proposed voting systems and to offer participants the opportunity to approve the voting system as part of the ground rules for operation of a group.

Buying into conservation: intrinsic versus instrumental value.

Many conservation biologists believe the best ethical basis for conserving natural entities is their claimed intrinsic value, not their instrumental value for humans. But there is significant confusion about what intrinsic value is and how it could govern conservation decision making. After examining what intrinsic value is supposed to be, we argue that it cannot guide the decision making conservation requires. An adequate ethical basis for conservation must do this, and instrumental value does it best.

Influence of representation targets on the total area of conservation-area networks.

Systematic conservation planning typically requires specification of quantitative representation targets for biodiversity surrogates such as species, vegetation types, and environmental parameters. Targets are usually specified either as the minimum total area in a conservation-area network in which a surrogate must be present or as the proportion of a surrogate's existing spatial distribution required to be in the network. Because the biological basis for setting targets is often unclear, a better understanding of how targets affect selection of conservation areas is needed. We studied how the total area of conservation-area networks depends on percentage targets ranging from 5% to 95%. We analyzed 12 data sets of different surrogate distributions from 5 regions: Korea, Mexico, Québec, Queensland, and West Virginia. To assess the effect of spatial resolution on the target-area relationship, we also analyzed each data set at 7 spatial resolutions ranging from 0.01 degrees x 0.01 degrees to 0.10 degrees x 0.10 degrees. Most of the data sets showed a linear relationship between representation targets and total area of conservation-area networks that was invariant across changes in spatial resolution. The slope of this relationship indicated how total area increased with target level, and our results suggest that greater surrogate representation requires significantly more area. One data set exhibited a highly nonlinear relationship. The results for this data set suggest a new method for setting targets on the basis of the functional form of target-area relationships. In particular, the method shows how the target-area relationship can provide a rationale for setting targets solely on the basis of distributional information about surrogates.

The principle of complementarity in the design of reserve networks to conserve biodiversity: a preliminary history.

Explicit, quantitative procedures for identifying biodiversity priority areas are replacing the often ad hoc procedures used in the past to design networks of reserves to conserve biodiversity. This change facilitates more informed choices by policy makers, and thereby makes possible greater satisfaction of conservation goals with increased efficiency. A key feature of these procedures is the use of the principle of complementarity, which ensures that areas chosen for inclusion in a reserve network complement those already selected. This paper sketches the historical development of the principle of complementarity and its applications in practical policy decisions. In the first section a brief account is given of the circumstances out of which concerns for more explicit systematic methods for the assessment of the conservation value of different areas arose. The second section details the emergence of the principle of complementarity in four independent contexts. The third section consists of case studies of the use of the principle of complementarity to make practical policy decisions in Australasia, Africa, and America. In the last section, an assessment is made of the extent to which the principle of complementarity transformed the practice of conservation biology by introducing new standards of rigor and explicitness.