Sahotra Sarkar

Embracing complexity: Organicism for the 21st century

Organicism (materialistic holism) has provided the philosophical underpinnings for embryology since the time of Kant. It had influenced the founders of developmental mechanics, and the importance of organicism to embryology was explicitly recognized by such figures as O. Hertwig, H. Spemann, R. Harrison, A. M. Dalq, J. Needham, and C. H. Waddington. Many of the principles of organicism remain in contemporary developmental biology, but they are rarely defined as such. A combination of genetic reductionism and the adoption of holism by unscientific communities has led to the devaluation of organicism as a fruitful heuristic for research. This essay attempts to define organicism, provide a brief history of its importance to experimental embryology, outline some sociologically based reasons for its decline, and document its value in contemporary developmental biology. Based on principles or organicism, developmental biology should become a science of emerging complexity. However, this does mean that some of us will have to learn calculus.

Operationalizing biodiversity for conservation planning

Biodiversity has acquired such a general meaning that people now find it difficult to pin down a precise sense for planning and policy-making aimed at biodiversity conservation. Because biodiversity is rooted in place, the task of conserving biodiversity should target places for conservation action; and because all places contain biodiversity, but not all places can be targeted for action, places have to be prioritized. What is needed for this is a measure of the extent to which biodiversity varies from place to place. We do not need a precise measure of biodiversity to prioritize places. Relative estimates of similarity or difference can be derived using partial measures, or what have come to be called biodiversity surrogates. Biodiversity surrogates are supposed to stand in for general biodiversity in planning applications. We distinguish between true surrogates, those that might truly stand in for general biodiversity, and estimator surrogates, which have true surrogates as their target variable. For example, species richness has traditionally been the estimator surrogate for the true surrogate, species diversity. But species richness does not capture the differences in composition between places; the essence of biodiversity. Another measure, called complementarity, explicitly captures the differences between places as we iterate the process of place prioritization, starting with an initial place. The relative concept of biodiversity built into the definition of complementarity has the level of precision needed to undertake conservation planning.

Malaria in Africa: Vector Species' Niche Models and Relative Risk Maps

A central theoretical goal of epidemiology is the construction of spatial models of disease prevalence and risk, including maps for the potential spread of infectious disease. We provide three continent-wide maps representing the relative risk of malaria in Africa based on ecological niche models of vector species and risk analysis at a spatial resolution of 1 arc-minute (9 185 275 cells of approximately 4 sq km). Using a maximum entropy method we construct niche models for 10 malaria vector species based on species occurrence records since 1980, 19 climatic variables, altitude, and land cover data (in 14 classes). For seven vectors (Anopheles coustani, A. funestus, A. melas, A. merus, A. moucheti, A. nili, and A. paludis) these are the first published niche models. We predict that Central Africa has poor habitat for both A. arabiensis and A. gambiae, and that A. quadriannulatus and A. arabiensis have restricted habitats in Southern Africa as claimed by field experts in criticism of previous models. The results of the niche models are incorporated into three relative risk models which assume different ecological interactions between vector species. The “additive” model assumes no interaction; the “minimax” model assumes maximum relative risk due to any vector in a cell; and the “competitive exclusion” model assumes the relative risk that arises from the most suitable vector for a cell. All models include variable anthrophilicity of vectors and spatial variation in human population density. Relative risk maps are produced from these models. All models predict that human population density is the critical factor determining malaria risk. Our method of constructing relative risk maps is equally general. We discuss the limits of the relative risk maps reported here, and the additional data that are required for their improvement. The protocol developed here can be used for any other vector-borne disease.

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.

Chagas Disease Risk in Texas

Background Chagas disease, caused by Trypanosoma cruzi, remains a serious public health concern in many areas of Latin America, including México. It is also endemic in Texas with an autochthonous canine cycle, abundant vectors (Triatoma species) in many counties, and established domestic and peridomestic cycles which make competent reservoirs available throughout the state. Yet, Chagas disease is not reportable in Texas, blood donor screening is not mandatory, and the serological profiles of human and canine populations remain unknown. The purpose of this analysis was to provide a formal risk assessment, including risk maps, which recommends the removal of these lacunae. Methods and Findings The spatial relative risk of the establishment of autochthonous Chagas disease cycles in Texas was assessed using a five–stage analysis. 1. Ecological risk for Chagas disease was established at a fine spatial resolution using a maximum entropy algorithm that takes as input occurrence points of vectors and environmental layers. The analysis was restricted to triatomine vector species for which new data were generated through field collection and through collation of post–1960 museum records in both México and the United States with sufficiently low georeferenced error to be admissible given the spatial resolution of the analysis (1 arc–minute). The new data extended the distribution of vector species to 10 new Texas counties. The models predicted that Triatoma gerstaeckeri has a large region of contiguous suitable habitat in the southern United States and México, T. lecticularia has a diffuse suitable habitat distribution along both coasts of the same region, and T. sanguisuga has a disjoint suitable habitat distribution along the coasts of the United States. The ecological risk is highest in south Texas. 2. Incidence–based relative risk was computed at the county level using the Bayesian Besag–York–Mollié model and post–1960 T. cruzi incidence data. This risk is concentrated in south Texas. 3. The ecological and incidence–based risks were analyzed together in a multi–criteria dominance analysis of all counties and those counties in which there were as yet no reports of parasite incidence. Both analyses picked out counties in south Texas as those at highest risk. 4. As an alternative to the multi–criteria analysis, the ecological and incidence–based risks were compounded in a multiplicative composite risk model. Counties in south Texas emerged as those with the highest risk. 5. Risk as the relative expected exposure rate was computed using a multiplicative model for the composite risk and a scaled population county map for Texas. Counties with highest risk were those in south Texas and a few counties with high human populations in north, east, and central Texas showing that, though Chagas disease risk is concentrated in south Texas, it is not restricted to it. Conclusions For all of Texas, Chagas disease should be designated as reportable, as it is in Arizona and Massachusetts. At least for south Texas, lower than N, blood donor screening should be mandatory, and the serological profiles of human and canine populations should be established. It is also recommended that a joint initiative be undertaken by the United States and México to combat Chagas disease in the trans–border region. The methodology developed for this analysis can be easily exported to other geographical and disease contexts in which risk assessment is of potential value.

Biodiversity and environmental philosophy : an introduction

Preface Acknowledgements 1. Introduction 2. Concerns for the environment 3. Intrinsic values and biocentrism 4. Tempered anthropocentrism 5. Problems of ecology 6. The consensus view of conservation biology 7. Incommensurability and uncertainty 8. Conclusion: issues for the future References Index.

Wilderness preservation and biodiversity conservation—keeping divergent goals distinct

C onservation biology, as developed and practiced in the United States, has the explicit aim of maintaining and encouraging biodiversity. The term “biodiversity” was introduced in 1986 by Walter Rosen as a shorthand for “biological diversity.” Although Rosen’s original intention was quite precise, biodiversity, according to a survey of US conservation biologists, has become a fashionable scientific—but no more precise—substitute for the undeniably vague term “nature” (Takacs 1996). These conceptions of biodiversity are actually quite different, and the differences matter when strategies for biodiversity conservation have to be devised. “Biological diversity” may be hard to define, but its intended meaning is not hard to fathom: It refers to diversity at all levels of biological organization, from alleles, to populations, to species, to communities, to ecosystems. “Nature,” by contrast, is a much more vague term: In the United States, at least, it seems mostly to refer to “wilderness” (Cronon 1996b). Meanwhile, “wilderness,” according to the 1964 US Wilderness Act, is a place “where man himself is a visitor and does not remain.” Humans are sometimes admitted as being part of a wilderness, especially if they are members of indigenous groups already resident in that “wilderness.” But from this Eurocentric point of view, these humans are not much different from other animals: Bereft of “civilized” culture, they do not destroy the sanctity of a pristine wilderness. Another aspect of “wilderness” is that the wilder a place, the more natural it is. An Antarctic landscape is more of a wilderness than the interior of an Amazonian rainforest—the latter has a higher density of human inhabitants. Biodiversity conservation, therefore, cannot be identical with wilderness preservation (see also Haila 1997). In this article, I explore the differences—that is, examine exactly how the two goals differ and what that difference entails, particularly for biologists. The goals differ not only with respect to their explicit and implicit long-term objectives, but also with respect to their justifications, their immediate targets and obstacles, and the strategies that are likely to achieve these targets (Table 1). In some instances, the tasks of biodiversity conservation and wilderness preservation converge, but at least as often they do not. When they do not, the conservation of biodiversity is often more feasible when that goal is not conflated with that of wilderness preservation. This point is important because there is a third factor that is often critical to conservation efforts: social interests, whether those of social justice movements (whose immediate goals often coincide with the interests of conservationists) or aspirations for economic improvement (which may or may not conflict with biodiversity conservation). If wilderness preservationism is cast aside as a predetermined goal, it can become easier for biodiversity conservationists to negotiate and, often, to achieve consensus with these social interests.

Models of reduction and categories of reductionism

A classification of models of reduction into three categories — theory reductionism, explanatory reductionism, and constitutive reductionism — is presented. It is shown that this classification helps clarify the relations between various explications of reduction that have been offered in the past, especially if a distinction is maintained between the various epistemological and ontological issues that arise. A relatively new model of explanatory reduction, one that emphasizes that reduction is the explanation of a whole in terms of its parts is also presented in detail. Finally, the classification is used to clarify the debate over reductionism in molecular biology. It is argued there that while no model from the category of theory reduction might be applicable in that case, models of explanatory reduction might yet capture the structure of the relevant explanations.

The philosophy and history of molecular biology : new perspectives

Editors Foreword S. Sarkar. What the Double Helix (1953) Has Meant for Basic Biomedical Science: A Personal Commentary J. Lederberg. Theory Structure and Knowledge Representation in Molecular Biology K.F. Schaffner. Redrawing the Boundaries of Molecular Biology: The Case of Photosynthesis D.T. Zallen. Underappreciated Pathways Toward Molecular Genetics as Illustrated by Jean Brachets Cytochemical Embryology R.M. Burian. Life as Technology: Representing, Interventing, and Molecularizing L.E. Kay. Enzymic Adaptation and the Entrance of Molecular Biology into Embryology S.F. Gilbert. The Molecularization of Immunology A.I. Tauber. The Hegemony of the Gene J. Beckwith. Introductory Note to the Contributions by Sarkar and Thaler S. Sarkar, D. Thaler. Biological Information: A Sceptical Look at Some Central Dogmas of Molecular Biology S. Sarkar. Paradox as Path: Pattern as Map - Classical Genetics as a Source of Non-Reductionism in Molecular Biology D. Thaler.

Place prioritization for biodiversity content

The prioritization of places on the basis of biodiversity content is part of any systematic biodiversity conservation planning process. The place prioritization procedure implemented in the ResNet software package is described. This procedure is primarily based on the principles of rarity and complementarity. Application of the procedure is demonstrated with two analyses, one data set consisting of the distributions of termite genera in Namibia, and the other consisting of the distributions of bird species in the Islas Malvinas/Falkland Islands. The attributes that data sets should have for the effective and reliable application of such procedures are discussed. The procedure used here is compared to some others that are also currently in use.