How do major novel traits originate and diversify in natural populations? This question addresses one of the most fundamental, yet unresolved, issues in evolutionary biology. Over the past decade, a peculiar group of organisms, horned beetles, has emerged as a model system for understanding the ecological, developmental, and genetic mechanisms that operate during the early stages of innovation and diversification. Here I review this body of research and highlight surprising insights into the interplay between proximate and ultimate mechanisms in the origins of diversity in these organisms.

The modern world is characterized by an unprecedented fragmentation and specialization of knowledge, including scientific knowledge. Yet to solve the problems—especially environmental problems—created in part by the successful application of this knowledge to expanded agricultural and industrial production, scientists must bring together this dispersed knowledge to inform collective deliberation. In this introduction to the special Roundtable section on “collectively seeing complex systems,” we outline the problem and highlight the ways in which scientists have until now relatively unselfconsciously addressed it, using as an example the broad range of scientists who collaborate in the scientific support of modern agriculture. We look at the problems of judgment and deliberation in the scientific understanding of complex systems as they relate to democratic practices, and advance some modest suggestions for improving the ability of scientists to respond to the increasing demands for policy-relevant, interdisciplinary information.

Understanding the risks posed by anthropogenic climate change and the possible societal responses to those risks has generated a prototypical example of the challenge of “collectively seeing complex systems.” After briefly examining the ways in which problems like climate change reach the scientific and public agenda, we look at four different ways in which scientists collectively address the problem: general circulation models, integrated assessment models, formal assessments (e.g., the Intergovernmental Panel on Climate Change), and distributed learning networks. We examine the strengths and limitations of each of these methods, and suggest ways in which a greater self-consciousness of the need for plural approaches could improve the basis for learning and decisionmaking.

We explore the practical difficulties of interdisciplinary research in the context of a regional- or local-scale project. We posit four barriers to interdisciplinarity that are common across many disciplines and draw on our own experience and on other sources to explore how these barriers are manifested. Values enter into scientific theories and data collection through scientists' hidden assumptions about disciplines other than their own, through the differences between quantitative and interpretive social sciences, and through roadblocks created by the organization of academia and the relationship between academics and the larger society. Participants in interdisciplinary projects need to be self-reflective about the value judgments embedded in their choice of variables and models. They should identify and use a core set of shared concerns to motivate the effort, be willing to respect and to learn more about the “other,” be able to work with new models and alternative taxonomies, and allow for plurality and incompleteness.

Environmental problem solving needs science but also inevitably requires subjective judgment. Science can help in dealing with subjectivity, because scientists have long experience developing institutions and practices to address the subjective and value-laden choices that are essential to scientific progress. Democracy has also developed approaches to the problem. The underlying principles can be applied to environmental policymaking. This article explores these issues in the context of decisions about environmental risks, drawing on the work of the National Research Council and other sources. It suggests some guidelines for risk deliberation—including broad-based participation, commitment to scientific quality, explicit attention to values, transparency of deliberative processes, and rules for closure and reconsideration—and recommends that an experimental approach be employed to learn how best to use deliberative methods.

In ecosystem science, understanding the link between spatial heterogeneity and ecological processes is an active area of current research that requires repeatable, quantifiable methods of comparison. Our research has suggested that interpreting landscape pattern measures across large, contiguous areas can improve our understanding of the statistical and spatial properties of these measures, and can suggest links between patterns and processes. In this paper, we introduce METALAND, a publicly available software tool and attendant database for the research community's use. In two applications, we illustrate how this framework can be employed (a) to establish a statistical regional context for a given landscape and (b) to assist sampling design and hypothesis generation at the regional scale. We offer this toolbox and its large and growing set of intercomparable landscapes to aid ecologists who wish to understand the sources and patterns of spatial variability in ecosystems across large areas.

“How much is enough?” is a question that conservationists, scientists, and policymakers have struggled with for years in conservation planning. To answer this question, and to ensure the long-term protection of biodiversity, many have sought to establish quantitative targets or goals based on the percentage of area in a country or region that is conserved. In recent years, policy-driven targets have frequently been faulted for their lack of biological foundation. In this manuscript, we reviewed 159 articles reporting or proposing 222 conservation targets and assessed differences between policy-driven and evidence-based approaches. Our findings suggest that the average percentages of area recommended for evidence-based targets were nearly three times as high as those recommended in policy-driven approaches. Implementing a minimalist, policy-driven approach to conservation could result in unanticipated decreases in species numbers and increases in the number of endangered species.

American adults and K–12 students frequently report nonrationalist views about creationism and evolution. Efforts to force educators to include material on “intelligent design” theory are causing widespread concern in the science education community. I report here the effects of a modified approach to a majors-oriented college introductory biology course. The course was modified to connect with the experiences, knowledge, and beliefs that most students bring to college, with the intent of engaging prior learning about creationism and evolution and of emphasizing the nature of science. The effects of this approach on student creationist or evolutionist attitudes were compared with the effects of two other sections of the same course that were taught by different instructors during the same academic quarter. The modified approach produced more attitude change than the other approaches. It included some material whose use has been discouraged by science educators, including discussion of creation myths and use of an intelligent design–oriented book as a foil to a mainstream book on evolution in seminar discussions.