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Predictive Science (predictive + science)

Distribution by Scientific Domains
Life Sciences75%

Selected Abstracts

Community responses to contaminants: Using basic ecological principles to predict ecotoxicological effects

ENVIRONMENTAL TOXICOLOGY & CHEMISTRY, Issue 9 2009
William H. Clements
Abstract Community ecotoxicology is defined as the study of the effects of contaminants on patterns of species abundance, diversity, community composition, and species interactions. Recent discoveries that species diversity is positively associated with ecosystem stability, recovery, and services have made a community-level perspective on ecotoxicology more important than ever. Community ecotoxicology must explicitly consider both present and impending global change and shift from a purely descriptive to a more predictive science. Greater consideration of the ecological factors and threshold responses that determine community resistance and resilience should improve our ability to predict how and when communities will respond to, and recover from, xenobiotics. A better understanding of pollution-induced community tolerance, and of the costs of this tolerance, should facilitate identifying contaminant-impacted communities, thus forecasting the ecological consequences of contaminant exposure and determining the restoration effectiveness. Given the vast complexity of community ecotoxicology, simplifying assumptions, such as the possibility that the approximately 100,000 registered chemicals could be reduced to a more manageable number of contaminant classes with similar modes of action, must be identified and validated. In addition to providing a framework for predicting contaminant fate and effects, food-web ecology can help to identify communities that are sensitive to contaminants, contaminants that are particularly insidious to communities, and species that are crucial for transmitting adverse effects across trophic levels. Integration of basic ecological principles into the design and implementation of ecotoxicological research is essential for predicting contaminant effects within the context of rapidly changing, global environmental conditions. [source]

Recent innovations in marine biology

MARINE ECOLOGY, Issue 2009
Ferdinando Boero
Abstract Modern ecology arose from natural history when Vito Volterra analysed Umberto D'Ancona's time series of Adriatic fisheries, formulating the famous equations describing the linked fluctuations of a predator,prey system. The shift from simple observation to careful sampling design, and hypothesis building and testing, often with manipulative approaches, is probably the most relevant innovation in ecology, leading from descriptive to experimental studies, with the use of powerful analytical tools to extract data (from satellites to molecular analyses) and to treat them, and modelling efforts leading to predictions. However, the historical component, time, is paramount in environmental systems: short-term experiments must cope with the long term if we want to understand change. Chaos theory showed that complex systems are inherently unpredictable: equational, predictive science is only feasible over the short term and for a small number of variables. Ecology is characterized by a high number of variables (e.g. species) interacting over wide temporal and spatial scales. The greatest recent conceptual innovation, thus, is to have realized that natural history is important, and that the understanding of complexity calls for humility. This is not a return to the past, because now we can give proper value to statistical approaches aimed at formalizing the description and the understanding of the natural world in a rigorous way. Predictions can only be weak, linked to the identification of the attractors of chaotic systems, and are aimed more at depicting scenarios than at forecasting the future with precision. Ecology was originally split into two branches: autecology (ecology of species) and synecology (ecology of species assemblages, communities, ecosystems). The two approaches are almost synonymous with the two fashionable concepts of today: ,biodiversity' and ,ecosystem functioning'. A great challenge is to put the two together and work at multiple temporal and spatial scales. This requires the identification of all variables (i.e. species and their ecology: biodiversity, or autoecology) and of all connections among them and with the physical world (i.e. ecosystem functioning, or synecology). Marine ecosystems are the least impacted by human pressures, compared to terrestrial ones, and are thus the best arena to understand the structure and function of the natural world, allowing for comparison between areas with and areas without human impact. [source]

Measurements of area and the (island) species,area relationship: new directions for an old pattern

OIKOS, Issue 10 2008
Kostas A. Triantis
The species,area relationship is one of the strongest empirical generalizations in geographical ecology, yet controversy persists about some important questions concerning its causality and application. Here, using more accurate measures of island surface size for five different island systems, we show that increasing the accuracy of the estimation of area has negligible impact on the fit and form of the species,area relationship, even though our analyses included some of the most topographically diverse island groups in the world. In addition, we show that the inclusion of general measurements of environmental heterogeneity (in the form of the so-called choros model), can substantially improve the descriptive power of models of island species number. We suggest that quantification of other variables, apart from area, that are also critical for the establishment of biodiversity and at the same time have high explanatory power (such as island age, distance, productivity, energy, and environmental heterogeneity), is necessary if we are to build up a more predictive science of species richness variation across island systems. [source]

Theory, Stylized Heuristic or Self-Fulfilling Prophecy?

PUBLIC ADMINISTRATION, Issue 1 2004
The Status of Rational Choice Theory in Public Administration
Rational choice is intimately associated with positivism and naturalism, its appeal to scholars of public administration lying in its ability to offer a predictive science of politics that is parsimonious in its analytical assumptions, rigorous in its deductive reasoning and overarching in its apparent applicability. In this paper I re-examine the ontology and epistemology which underpins this distinctive approach to public administration, challenging the necessity of the generally unquestioned association between rational choice and both positivism and naturalism. Rational choice, I contend, can only defend its claim to offer a predictive science of politics on the basis of an ingenious, paradoxical, and seldom acknowledged structuralism and a series of analytical assumptions incapable of capturing the complexity and contingency of political systems. I argue that analytical parsimony, though itself a condition of naturalism, is in fact incompatible with the deduction of genuinely explanatory/causal inferences. This suggests that the status of rational choice as an explanatory/predictive theory needs to be reassessed. Yet this is no reason to reject rational choice out of hand. For, deployed not as a theory in its own right, but as a heuristic analytical strategy for exploring hypothetical scenarios, it is a potent and powerful resource in post-positivist public administration. [source]