The flavors and colors of facts in wildlife science

Guthery, Fred S.

doi:10.2193/0091-7648(2004)32[288:ctfaco]2.0.co;2

Cited by 6 publications

(5 citation statements)

References 34 publications

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“…As applied, IT-AIC might sometimes be weakly hypothetico-deductive (i.e., deduce outcomes from hypotheses and test for their occurrence; Romesburg 1981). Multinomial probability, logistic regression, multiple regression, and other types of models, which are a form of hypothesis (Guthery et al 2004), ostensibly are advanced before the fact of data collection, and then they are evaluated as to plausibility (i.e., the models may be retroductions, or after-the-fact hypotheses, advanced to explain patterns in existing knowledge). Occasionally, researchers posit a model that explicitly tests previous research findings (Brennan et al 1987).…”

Section: Place In Sciencementioning

confidence: 99%

“…The former is based on optimizing the bias-variance tradeoff, the latter (Ockham's Razor) on the metaphysical conjecture that a hypothesis with the lowest tally of assumptions is more likely to be true than alternative hypotheses. Although overparameterized models may be of no value (Ginzburg and Jensen 2004), and there is a modicum of logic in Ockham's Razor (Guthery 2004), counter examples to the razor are known: "Fifty years ago [ca. 1855] physicists considered, other things being equal, a simple law as more probable than a complicated law.…”

Section: Philosophical and Operational Weaknessesmentioning

confidence: 99%

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Invited Paper: Information Theory in Wildlife Science: Critique and Viewpoint

Guthery

Brennan

Peterson

et al. 2005

Journal of Wildlife Management

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150

111

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We question whether the growing popularity of model selection based on information theory (IT) and using the Akaike's Information Criterion (AIC) represent a useful paradigm shift in data analysis or a substitution of 1 statistical ritual for another, which leaves in place long-standing problems in wildlife science. We discuss the relevance of model selection in science, problems in the IT-AIC algorithm, errors of commission and omission in IT-AIC-based studies, and the role of IT-AIC in knowledge accrual. Model selection is just another minor tool in the grand panorama of science. The human mind, not statistical methods, produces scientific breakthroughs. Although IT-AIC might include elements of hypothetico-deductive science, it is arguably a form of sensitivity analysis, magnitude of effects estimation, or simple description as currently applied. Accordingly, it is largely an inductive approach to knowledge accrual and, therefore, subject to the pitfalls of induction. The algorithm tends to over fit data (i.e, use too many variables), resulting in models that contain useless variables and that generalize poorly. Errors of commission in IT-AIC-based papers include hopelessly uninformative lists of encrypted models and imposition of the model-selection approach on studies better executed in a simple, descriptive format. The major error of omission is an almost universal failure to test selected models on independent data. From our perspective, IT-AIC is a harmless human construct that is being ritualistically applied and therefore cannot be expected to correct long-standing problems in the conduct of wildlife science, such as failure to apply the hypothetico-deductive method. We view the growing application of IT-AIC as problematic because that growth might discourage use of the full panoply of available methods of inquiry. Accordingly, we urge colleagues to avail themselves of the rich pageant of available analytical techniques that can be applied in wildlife research under the hypothetico-deductive method and to keep ecology, rather than statistics, in the forefront of wildlife science. JOURNAL OF WILDLIFE MANAGEMENT 69(2):457-465; 2005

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Section: Place In Sciencementioning

confidence: 99%

Section: Philosophical and Operational Weaknessesmentioning

confidence: 99%

Invited Paper: Information Theory in Wildlife Science: Critique and Viewpoint

Guthery

Brennan

Peterson

et al. 2005

Journal of Wildlife Management

Self Cite

150

111

View full text Add to dashboard Cite

show abstract

“…Multiple hypotheses also help protect against fractional truths possibly derived by H-D experimentation. A third problem with H-D experimentation is that competing research hypotheses might lead to identical deductions (Guthery 2004). Hiller and Guthery (2005), for example, tested the competing hypotheses that heat avoidance versus predator avoidance governed midday covert selection by northern bobwhites (Colinus virginianus).…”

Section: H-d Experimentation and Wildlife Sciencementioning

confidence: 99%

Deductive and Inductive Methods of Accumulating Reliable Knowledge in Wildlife Science

Guthery

2007

J Wildl Manag

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My goal was to compare deductive and inductive methods of accumulating reliable knowledge in wildlife science. Under the hypotheticodeductive (H‐D) method, observations are used to formulate explanatory or causal hypotheses, which serve as the basis for deductions (predictions) of expected events. Field experiments are designed to determine whether the deductions hold, in which case hypotheses are tentatively accepted or otherwise rejected. The H‐D method provides the only way to test research hypotheses, but in field ecology it can lead to ambiguity and error. The method: 1) does not preclude confusion of correlation and cause, 2) might perform deceptively in multiple‐cause venues, 3) is algorithmically blind to the fact that different hypotheses can lead to the same deduction, and 4) lacks an impartial means of determining whether a deduction has been observed and, therefore, whether a hypothesis is meritorious. Under the process of induction, the results of a study are presumed to hold generally and taken as knowledge accordingly. Induction is much maligned by logicians and philosophers, and wildlife scientists have built false knowledge inductively. However, wildlife scientists have auxiliary knowledge such as facts of natural history to screen inductions for validity. Both the H‐D method and induction have important roles in the accumulation of reliable knowledge in wildlife science.

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“…Recent articles in the Wildlife Society Bulletin emphasized the need to critically read and comment on published wildlife research as a means of improving the quality of our work (Krausman et al 2003, Guthery 2004, Hutchinson 2004. In that regard, I wish to comment on a recent paper (Small et al 2004b) that compared the effects of several different methods of attaching transmitters to white-winged doves (Zenaida asiatica).…”

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confidence: 99%

Are Subcutaneous Transmitters Better Than Intracoelomic? The Relevance of Reporting Methodology to Interpreting Results

Mulcahy

2006

Wildlife Society Bulletin

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Biologists rely on published scientific papers to increase their knowledge and to guide their future work. Papers comparing techniques can be especially influential when several options exist for accomplishing a task. In this paper, I use a recent publication comparing the effects on birds of several methods for attaching or implanting radio transmitters to illustrate the need for clear and accurate reporting of the techniques used. Because of deficiencies in methodology, in stating methodology, and in following cited methodology I argue that the conclusions drawn by the authors are not supportable.

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The flavors and colors of facts in wildlife science

Cited by 6 publications

References 34 publications

Invited Paper: Information Theory in Wildlife Science: Critique and Viewpoint

Invited Paper: Information Theory in Wildlife Science: Critique and Viewpoint

Deductive and Inductive Methods of Accumulating Reliable Knowledge in Wildlife Science

Are Subcutaneous Transmitters Better Than Intracoelomic? The Relevance of Reporting Methodology to Interpreting Results

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