Ecological Understanding, Second Edition: The Nature of Theory and the Theory of Nature
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Furthermore, as was seen in this example, the fact that Mendel's theory of inheritance was amenable to mathematical analyses led to the discovery of the Hardy—Weinberg principle, which, in turn, increased our understanding of factors affecting microevolutionary change, thus furthering theory development. Several deductive frameworks that fit our description of efficient theory have emerged in ecology and evolutionary ecology. In this section, we review and compare some of these theories to orient readers to key characteristics of deductive theory that we consider highly efficient and useful.
From these comparisons, we argue that efficient theory in ecology is simple, parsimonious, derived from first principles, quantitative, and mathematical, with few inputs and many predictions. The argument behind Fisher's sex ratio theory is that the relative reproductive value to parents of sons rather than daughters is equal to the relative selection pressure favoring the production of sons. Theory includes the assumption that parents determine the sex of their offspring and a definition of reproductive value.
Fisher defined reproductive value in the context of populations with age structure, such that, given that an individual survives to age x, its expected reproduction from age x onward is v x. Fisher's canonical example assumed a nongrowing population of a species in which each offspring had a mother and a father.
In this case, the predicted equilibrium sex ratio is parity. When we observe deviations from a one-to-one sex ratio in species with two parents, we do not claim to have falsified Fisher's theory. Rather, we ask whether the reproductive value of daughters and sons is indeed equal. Therefore, a failure of predictions to match observations suggests follow-up hypotheses about sources of differential reproductive value of each sex of offspring e. An underlying premise of the theory is that metabolic rate is fundamental to ecology, because it is through metabolism that organisms interact with their environments.
Over the last 10 years, the MTE has yielded two general classes of models. The first predicts how two variables—body size and temperature—affect the metabolic rates of organisms e. The second class of models explores the consequences of metabolic rate at different levels of biological organization, from genomes to ecosystems.
Empirical data are generally consistent with predictions of the MTE that size and temperature constrain diverse rate processes, including DNA evolution e. Since the MTE yields predictions for these diverse phenomena, given only two parameters—body size and temperature—it represents an efficient theory in ecology. Importantly, however, the variance left unexplained by MTE models can be substantial, as has been noted in some critiques e. This variation probably reflects the effects of other traits or determinants of metabolic rate and of other ecological and evolutionary processes e.
The MTE provides a common frame of reference to make comparisons among organisms that, notwithstanding their different evolutionary histories and ecological settings, obey the same first principles linked to metabolism, size, and temperature. Specifically, the MTE predicts a universal growth trajectory that all organisms obey—or collapse to—once they are put into the same reference frame rescaled time and size , which is provided by the theory. Scale collapse means that when different systems are brought into the same frame of reference, which is accomplished by rescaling, different realizations of the same phenomenon the insets can be shown to obey the same universal relationship predicted by a theory.
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In panel a , the theory allows for a rescaling of time and size into dimensionless variables, which shows that ontogenetic trajectories corresponding to 13 different species, identified by different symbols, follow the same general law. Four of these species are plotted in the inset.
In panel b , the plot shows how the slope of different species—area curves change as a function of the ratio of the total number of individuals N and species richness S observed at a particular area. The inset shows three particular cases of how the number of species changes with area. Information theory in the form of the MaxEnt inference procedure Jaynes provides the foundation for the maximum entropy theory of ecology METE , which predicts realistic functions describing major patterns in macroecology.
In analogy with thermodynamics, in which the state variables pressure, volume, temperature, and particle number characterize a system, in the METE, knowledge of the state variables S 0 the number of species , N 0 the number of individuals , E 0 the metabolic rate summed over individuals , and A 0 the area of the system provide the constraints that are used to derive predictions, and with the additional state variable L 0 the number of trophic links in a network , MaxEnt predicts link distributions Williams This validated prediction is dramatically different from power-law behavior, in which different species—area relationships would show up as horizontal lines, with intercepts varying from one ecosystem to another.
Although tests of the METE using census data for plants, birds, and arthropods from a variety of habitats and over spatial scales ranging from square meters to thousands of square kilometers indicate that the theory predicts observed patterns without any adjustable parameters, some systematic discrepancies are noted for communities that are relatively rapidly changing—for example, following a disturbance Harte Patterns in the deviation from theory of rapidly changing systems may allow extension of the METE from a static theory to a dynamic theory. The neutral theory of biodiversity NTB is focused on understanding the role of stochastic demographic processes in controlling the structure and dynamics of communities at ecological to macroevolutionary timescales Hubbell The theory yields a rich set of predictions on diverse phenomena, including the frequency distribution of species abundance, species—area relationships, phylogenetic-tree structure, and the relationship of species richness to the macroevolutionary rates of speciation and extinction Hubbell Moreover, it does so using remarkably few parameters, by assuming demographic equivalence among species with respect to per capita i.
Therefore, the NTB represents an efficient theory. It demonstrates how variation among species in relative abundance can arise solely from simple, stochastic rules that apply to all species composing a community and thus provides a useful baseline against which to compare empirical data Hubbell , Leigh This focus on species similarities rather than species differences represents a major challenge to the niche paradigm, which has predominated in community ecology since the s.
However, we would argue that the ability to falsify the NTB represents a virtue of this theory—and of efficient ecological theories in general—because it paves the way for more-realistic models and a deeper understanding of ecological systems based on underlying dynamical processes. When efficient theories fail, they do so in informative ways.
As Bateson said, Treasure your exceptions! When there are none, the work gets so dull that no one cares to carry it further. Keep them always uncovered and in sight. Exceptions are like the rough brickwork of a growing building which tells that there is more to come and shows where the next construction is to be. We contend that first and foremost, exceptions to efficient theories help the purpose of advancing scientific knowledge on firm ground.
For the sake of clarity, we think it useful to highlight some theories that are not efficient. We do not imply that they should be dismissed as of limited value, but they do not fit some of the characteristics used to define efficient theories.
It also predicts coexistence of two species when the growth rate of each species is limited by a different nutrient. When resources are heterogeneously distributed, the number of species can be larger than the number of limiting resources, thereby resolving Hutchinson's paradox of the plankton. However, it has proven difficult to test, because it has a large number of free parameters a minimum of three parameters per species—resource combination, in addition to death rates and resource supply rates , which must all be measured to yield predictions.
Although the theory is based on the first principles relating population growth to resource supply and consumption, it is not efficient because of its large number of free parameters, which restricts it scope of application and the possibility of field testing. Nonetheless, it has proven to have heuristic value, which has given rise to several extensions Leibold , Daufresne and Hedin The dynamic energy budget theory DEB is intended to explain the life history of organisms in an environment with a given amount of resources on the basis of a mathematical description of the rates at which individuals assimilate and use energy and materials from resources to sustain the processes of maintenance, growth, reproduction, and development.
DEB is based on the first principles dictated by the kinetics and thermodynamic of energy and material fluxes but is data demanding and rich in free parameters see Kooijman Throughout the present article, we have emphasized the importance of theory in the inductive—deductive cycle. There are situations, however, in which the complexity of the system under study and the lack of adequate theories hinder progress in understanding.
In this situation, the use of simulations or individual agent based models e. Agent-based models, which are parameter rich and rest on massive simulations, can be powerful in generating hypotheses and in helping to test alternative ones for patterns seen in nature e. However, we see this approach only as a stage in the process of understanding that may lead to the identification of first principles and, eventually, to the development of efficient theories.
Deductive, quantitative theories based on first principles continually expand and, in doing so, may come close to or overlap with the domains of other theories, thereby increasing the potential for synthesis and unification. Although understanding biodiversity from a theoretical perspective clearly represents a formidable challenge e. Efficient theories based on first principles foster synthesis and unification. For example, although the MTE and the NTB are focused on different aspects of ecological complexity—energy and stochasticity, respectively—they share a fundamental point of contact that affords opportunities for synthesis.
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Specifically, each theory postulates that ecosystems are governed by universal principles and processes that operate at the level of the individual organism and, therefore, transcend species identities in shaping patterns of biodiversity. There are several ways in which the potential for unification among these theories could be realized. For example, one of the key assumptions of the NTB is that all individuals have identical demographic rates, independent of their size.
For example, the integration of the two theories allows for the prediction of alternative-currency distributions, such as the species biomass distribution e. Advances in science are largely due to the iterative process of induction and deduction, prediction and testing. We believe that greater recognition of the positive role of this interplay in discovery will significantly enhance scientific progress in biology—and in ecology, in particular.
Fifty years ago, John Platt embraced the interplay between induction and deduction and enjoined scientists to pursue a program that he dubbed strong inference, which directly links data acquisition to well-posed hypotheses. Strong inference entails following a simple but rigorous protocol of experimental science, efficiently designed to falsify alternative hypotheses. Platt's paper had a tremendous impact on the practice of experimental science and, more recently, in modeling e.
A clarifying discussion of theory types and their roles in discovery, as we have attempted here, may have a similar effect on ecology. The preeminence of inductive approaches in biology—and in ecology, in particular—is reflected in the fascination with gathering information about the world, as if we were to find understanding in its accumulation. This trend is becoming even more acute in recent times because of technological breakthroughs that are providing unprecedented quantities and varieties of information about organisms, from microbes to trees, and about environments, from local to global scales.
The emergence of new subdisciplines, such as bioinformatics and ecoinformatics, along with monumental scientific efforts currently under way, such as the sequencing of complete genomes and metagenomes and the establishment of large-scale and long-term ecological monitoring networks e. However, we believe that for such efforts to fully bear fruit, they will need to be both guided by and more directly coupled to the development of efficient theory.
Data is of great importance, but without theory, we have only phenomenology and correlation, and we lose the opportunity to yoke the complexity of ecological systems using simple, quantitative principles; as was suggested by Harte , we need a better integration of Newtonian and Darwinian worldviews.
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As was clearly stated by the Nobel laureate Sydney Brenner, Biological research is in crisis…. Technology gives us the tools to analyze organisms at all scales, but we are drowning in a sea of data and thirsting for some theoretical framework with which to understand it.
Although many believe that more is better, history tells us that least is best. We need theory and a firm grasp on the nature of the objects we study to predict the rest. Brenner , p. Understanding biodiversity from a theoretical perspective clearly represents a formidable challenge, but we are optimistic that, by aiming at developing efficient theories, significant progress can be made. We think that efficient theories provide a solid foundation for advancing science in the big data era.
In this article, we argued for clarifying and expanding the role of theory in ecology to accelerate scientific progress, enhance our ability to address environmental challenges, and foster the development of synthesis and theory unification. Our primary goal was to identify characteristics of ecological theories that lead to more-rapid advancement.
We showed that more-efficient theories tend to make fewer, simpler, and more-fundamental assumptions and generate a greater number of testable predictions per free parameter than do less-efficient theories. Finally, we argued that ecology will advance much faster if ecologists embrace efficient, approximate theories and improve on them through a process of successive refinements.
The development of efficient theories, we contend, provides a robust epistemological framework to foster progress and synthesis in ecology. DEB and projects no. ICM P, no. Ask Seller a Question. Title: Ecological Understanding, Second Edition This widely anticipated revision of the groundbreaking book, Ecological Understanding, updates this crucial sourcebook of contemporary philosophical insights for practicing ecologists and graduate students in ecology and environmental studies.
- On Theory in Ecology | BioScience | Oxford Academic.
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The second edition contains new ecological examples, an expanded array of conceptual diagrams and illustrations, new text boxes summarizing important points or defining key terms, and new reference to philosophical issues and controversies. Although the first edition was recognized for its clarity, this revision takes the opportunity to make the exposition of complex topics still clearer to readers without a philosophical background.
Readers will gain an understanding of the goals of science, the structure of theory, the kinds of theory relevant to ecology, the way that theory changes, what constitutes objectivity in contemporary science, and the role of paradigms and frameworks for synthesis within ecology and in integration with other disciplines. Finally, how theory can inform and anchor the public use of ecological knowledge in civic debates is laid out.
Ecology Understanding offers the reader an interesting and thoughtful discussion of theory development, ecological integration, and scientific understanding from a philosophical viewpoint. Visit Seller's Storefront. Please contact me if you are not satisfied with your order in any manner. Darwin explained how both shape and color were oriented toward the insect pollinator. Eight chapters describe and illustrate different kinds of orchids and explain their pollination mechanisms.