Jay Odenbaugh

Managed Relocation: Integrating the Scientific, Regulatory, and Ethical Challenges

Managed relocation is defined as the movement of species, populations, or genotypes to places outside the areas of their historical distributions to maintain biological diversity or ecosystem functioning with changing climate. It has been claimed that a major extinction event is under way and that climate change is increasing its severity. Projections indicating that climate change may drive substantial losses of biodiversity have compelled some scientists to suggest that traditional management strategies are insufficient. The managed relocation of species is a controversial management response to climate change. The published literature has emphasized biological concerns over difficult ethical, legal, and policy issues. Furthermore, ongoing managed relocation actions lack scientific and societal engagement. Our interdisciplinary team considered ethics, law, policy, ecology, and natural resources management in order to identify the key issues of managed relocation relevant for developing sound policies that support decisions for resource management. We recommend that government agencies develop and adopt best practices for managed relocation.

Complex Systems, Trade-Offs and Theoretical Population Biology: Richard Levin`s 'Strategy of Model Building in Population Biology' Revisited

Ecologist Richard Levins argues population biologists must trade‐off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levinss thesis that there is a necessary trade‐off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sobers arguments fail since Levinss thesis concerns the pragmatic features of model building not just the formal properties of models.

Philosophical Issues in Ecology: Recent Trends and Future Directions

Philosophy of ecology has been slow to become established as an area of philosophical interest, but it is now receiving considerable attention. This area holds great promise for the advancement of both ecology and the philosophy of science. Insights from the philosophy of science can advance ecology in a number of ways. For example, philosophy can assist with the development of improved models of ecological hypothesis testing and theory choice. Philosophy can also help ecologists understand the role and limitations of mathematical models in ecology. On the other side, philosophy of science will be advanced by having ecological case studies as part of the stock of examples. Ecological case studies can shed light on old philosophical topics as well as raise novel issues for the philosophy of science. For example, understanding theoretical terms such as “biodiversity” is important for scientific reasons, but such terms also carry political importance. Formulating appropriate definitions for such terms is thus not a purely scientific matter, and this may prompt a reevaluation of philosophical accounts of defining theoretical terms. We consider some of the topics currently receiving attention in the philosophy of ecology and other topics in need of attention. Our aim is to prompt further exchange between ecology and philosophy of science and to help set the agenda for future work in the philosophy of ecology. The topics covered include: the role of mathematical models, environmental problem formulation, biodiversity, and environmental ethics.

This American Life

Given the complexity of John Nolt’s overall argument (Nolt, 2011), I summarise it at the outset. First, focusing on the mean emissions of the United States, ignoring the ‘porousness’ of nations, and including carbon sinks, the total greenhouse gas emissions (GHG) to US population ratio is approximately 19.8 metric tons CO2 equivalent. Given that the average American lifespan is 80 years, the average American emits 1584 metric tons CO2 equivalent. Second, over the next millennium (the longevity of our emissions), on average there will be 7.5 billion people along with three generations present at any given time. Thus, approximately 100 billion people (2.5 billion 40 generations) will be affected by climate change impacts. Supposing this American life occurs between 1960–2040, the total increase in CO2 during her lifetime of the total increase is 78%. Given the total number of Americans and this percentage increase, then she will have contributed about one two-billionth of the GHG from anthropogenic climate change by 2040. So, if over the next 1000 years, two billion people are harmed (ignoring benefits and including only non-discounted harms to humans—namely suffering and death), then the average American is responsible for the suffering and/or death of one future person. In this short commentary, I raise several worries for Nolt’s analysis and end with a qualified defense of his approach. First, Nolt assumes that the lifespan of a greenhouse gases are roughly 1000 years; but this figure is a source of controversy (Inman, 2008). It has been common for climate scientists, including the Intergovernmental Panel on Climate Change (IPCC), to suggest the lifespan of CO2 is between 50–200 years (most other GHG have shorter lifespans). If correct, this Nolt overestimates the predicted harms. Specifically, assuming the atmospheric lifetime of CO2 is 200 years, we should be considering only the next eight generations and thus 20 billion people. If 2% of people are harmed, then this is 40 million or 2% of a person. More recently, scientists have refused to provide a numerical estimate of the atmospheric lifetime. The 2007 IPCC report states that ‘[a]bout 50% of a CO2 increase will be removed from the atmosphere within 30 years, and a further 30% will be removed within a few

Seeing the Forest and the Trees: Realism about Communities and Ecosystems

In this essay I first provide an analysis of various community concepts. Second, I evaluate two of the most serious challenges to the existence of communities—gradient and paleoecological analysis respectively—arguing that, properly understood, neither threatens the existence of communities construed interactively. Finally, I apply the same interactive approach to ecosystem ecology, arguing that ecosystems may exist robustly as well.

True Lies: Realism, Robustness, and Models

In this essay, I argue that uneliminated idealizations pose a serious problem for scientific realism. I consider one method for “de-idealizing” models—robustness analysis. However, I argue that unless idealizations are eliminated from an idealized theory and robustness analysis need not do that, scientists are not justified in believing that the theory is true. I consider one example of modeling from the biological sciences that exemplifies the problem.

Message in the Bottle: The Constraints of Experimentation on Model Building

Some ecologists have argued that theoretical model building in population and community ecology has gone evidentially unconstrained. In the essay, I argue that “bottle experiments” offer ecological model building evidential constraints and illustrate this by considering work on chaotic models tested by the dynamics of flour beetles. Critics reply that these experiments are importantly unlike nonmanipulated natural systems and thus do not constitute genuine tests of the models. I conclude by considering two responses to this worry and a suggestion on how to move forward on this debate.

Nothing in ethics makes sense except in the light of evolution? Natural goodness, normativity, and naturalism

Abstract Foot (2001), Hursthouse (1999), and Thompson (2008), along with other philosophers, have argued for a metaethical position, the natural goodness approach, that claims moral judgments are, or are on a par with, teleological claims made in the biological sciences. Specifically, an organism’s flourishing is characterized by how well they function as specified by the species to which they belong. In this essay, I first sketch the Neo-Aristotelian natural goodness approach. Second, I argue that critics who claim that this sort of approach is inconsistent with evolutionary biology due to its species essentialism are incorrect. Third, I contend that combining the natural goodness account of natural-historical judgments with our best account of natural normativity, the selected effects theory of function, leads to implausible moral judgments. This is so if selected effects function are understood in terms of evolution by natural selection, but also if they are characterized in terms of cultural evolution. Thus, I conclude that proponents of the natural goodness approach must either embrace non-naturalistic vitalism or troubling moral revisionism.

Philosophical themes in the work of Robert H. Macarthur

Publisher Summary This chapter provides a historical overview of MacArthurs work with an eye toward this question in “Philosophical Themes in the Work of Robert MacArthur.” Discussion of island biogeography begins with the “species-area” effect and two factors that drive diversity on islands: the area of the island and its distance from the mainland. MacArthurs approach to ecological models illustrates a robust understanding of various causal factors including evolution, competition, immigration, and extinction that must inform ecological thinking with clever formal ways of trying to get some useful inferential mileage out of these factors, despite the richness and complexity of the underlying phenomena. Conclusion emphasizes the importance of integration rather than unification in MacArthurs work; integration is a broader term (whats unified is integrated, but not necessarily vice versa). One might say that the difference lies in the fact that integration allows a more piecemeal approach to arriving at models and inferences that combine elements from different sciences, while unification demands a more theoretically structured, general program for producing models. The generality or scope of such an integrated perspective is limited, because the wide variety of cases that actually arise generally includes circumstances where the models fail. The integrative approach is open to the existence of circumstances where a models regularities and explanatory usefulness break down: After all, the claim is not to have given a general recipe for unification, but only local and limited ones whose applicability depends on conditions, though these conditions can often be inferred from the structure of the models themselves.

Models, models, models: a deflationary view

In this essay, I first consider a popular view of models and modeling, the similarity view. Second, I contend that arguments for it fail and it suffers from what I call “Hughes’ worry.” Third, I offer a deflationary approach to models and modeling that avoids Hughes’ worry and shows how scientific representations are of apiece with other types of representations. Finally, I consider an objection that the similarity view can deal with approximations better than the deflationary view and show that this is not so.