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Presentation_1_Regressions Fit for Purpose: Models of Locust Phase State Must Not Conflate Morphology With Behavior.ZIP
No full textPhenotypic plasticity often entails coordinated changes in multiple traits. The effects of two alternative environments on multiple phenotypic traits can be analyzed by multivariable binary logistic regression (LR). Locusts are grasshopper species (family Acrididae) with a capacity to transform between two distinct integrated phenotypes or “phases” in response to changes in population density: a solitarious phase, which occurs when densities are low, and a gregarious phase, which arises as a consequence of crowding and can form very large and economically damaging swarms. The two phases differ in behavior, physiology and morphology. A large body of work on the mechanistic basis of behavioral phase transitions has relied on LR models to estimate the probability of behavioral gregariousness from multiple behavioral variables. Mart́ın-Blázquez and Bakkali (2017; [10.1111/eea.12564]10.1111/eea.12564) have recently proposed standardized LR models for estimating an overall “gregariousness level” from a combination of behavioral and, unusually, morphometric variables. Here I develop a detailed argument to demonstrate that the premise of such an overall “gregariousness level” is fundamentally flawed, since locust phase transformations entail a decoupling of behavior and morphology. LR models that combine phenotypic traits with markedly different response times to environmental change are of very limited value for analyses of phase change in locusts, and of environmentally induced phenotypic transitions in general. I furthermore show why behavioral variables should not be adjusted by measures of body size that themselves differ between the two phases. I discuss the models fitted by Mart́ın-Blázquez and Bakkali (2017) to highlight potential pitfalls in statistical methodology that must be avoided when analysing associations between complex phenotypes and alternative environments. Finally, I reject the idea that “standardized models” provide a valid shortcut to estimating phase state across different developmental stages, strains or species. The points addressed here are pertinent to any research on transitions between complex phenotypes and behavioral syndromes.</p
Regressions Fit for Purpose: Models of Locust Phase State Must Not Conflate Morphology With Behavior
No full textPhenotypic plasticity often entails coordinated changes in multiple traits. The effects
of two alternative environments on multiple phenotypic traits can be analyzed by
multivariable binary logistic regression (LR). Locusts are grasshopper species (family
Acrididae) with a capacity to transform between two distinct integrated phenotypes or
“phases” in response to changes in population density: a solitarious phase, which occurs
when densities are low, and a gregarious phase, which arises as a consequence of
crowding and can form very large and economically damaging swarms. The two phases
differ in behavior, physiology and morphology. A large body of work on the mechanistic
basis of behavioral phase transitions has relied on LR models to estimate the probability
of behavioral gregariousness from multiple behavioral variables. Martín-Blázquez and
Bakkali (2017; doi: 10.1111/eea.12564) have recently proposed standardized LR models
for estimating an overall “gregariousness level” from a combination of behavioral and,
unusually, morphometric variables. Here I develop a detailed argument to demonstrate
that the premise of such an overall “gregariousness level” is fundamentally flawed,
since locust phase transformations entail a decoupling of behavior and morphology.
LR models that combine phenotypic traits with markedly different response times to
environmental change are of very limited value for analyses of phase change in locusts,
and of environmentally induced phenotypic transitions in general. I furthermore show why
behavioral variables should not be adjusted by measures of body size that themselves
differ between the two phases. I discuss the models fitted by Martín-Blázquez and
Bakkali (2017) to highlight potential pitfalls in statistical methodology that must be
avoided when analysing associations between complex phenotypes and alternative
environments. Finally, I reject the idea that “standardized models” provide a valid shortcut
to estimating phase state across different developmental stages, strains or species. The
points addressed here are pertinent to any research on transitions between complex
phenotypes and behavioral syndrome
Regressions Fit for Purpose: Models of Locust Phase State Must Not Conflate Morphology With Behavior
Full text linkPhenotypic plasticity often entails coordinated changes in multiple traits. The effects of two alternative environments on multiple phenotypic traits can be analyzed by multivariable binary logistic regression (LR). Locusts are grasshopper species (family Acrididae) with a capacity to transform between two distinct integrated phenotypes or “phases” in response to changes in population density: a solitarious phase, which occurs when densities are low, and a gregarious phase, which arises as a consequence of crowding and can form very large and economically damaging swarms. The two phases differ in behavior, physiology and morphology. A large body of work on the mechanistic basis of behavioral phase transitions has relied on LR models to estimate the probability of behavioral gregariousness from multiple behavioral variables. Mart́ın-Blázquez and Bakkali (2017; [10.1111/eea.12564]10.1111/eea.12564) have recently proposed standardized LR models for estimating an overall “gregariousness level” from a combination of behavioral and, unusually, morphometric variables. Here I develop a detailed argument to demonstrate that the premise of such an overall “gregariousness level” is fundamentally flawed, since locust phase transformations entail a decoupling of behavior and morphology. LR models that combine phenotypic traits with markedly different response times to environmental change are of very limited value for analyses of phase change in locusts, and of environmentally induced phenotypic transitions in general. I furthermore show why behavioral variables should not be adjusted by measures of body size that themselves differ between the two phases. I discuss the models fitted by Mart́ın-Blázquez and Bakkali (2017) to highlight potential pitfalls in statistical methodology that must be avoided when analysing associations between complex phenotypes and alternative environments. Finally, I reject the idea that “standardized models” provide a valid shortcut to estimating phase state across different developmental stages, strains or species. The points addressed here are pertinent to any research on transitions between complex phenotypes and behavioral syndromes
Regressions Fit for Purpose: Models of Locust Phase State Must Not Conflate Morphology With Behaviour
No full textAbstractLocusts are defined by their capacity to transform between two very distinct integrated phenotypes or ‘phases’ in response to changes in population density: a solitarious phase, which occurs when densities are low, and a gregarious phase, which arises as a consequence of crowding and can form very large and economically damaging swarms. The two phases differ fundamentally in their behaviour, physiology and morphology. A large body of work on the mechanistic basis of behavioural phase transitions has relied on multivariate logistic regression (LR) models to estimate the probability of behavioural gregariousness from multiple behavioural variables. Martín-Blázquez and Bakkali (2017, Entomologia Experimentalis et Applicata 163, 9–25) have recently proposed standardised LR models for estimating an overall ‘gregariousness level’ from a combination of behavioural and, unusually, morphometric variables. Here I develop a detailed argument to demonstrate that the premise of such an overall ‘gregariousness level’ is fundamentally flawed. Since locust phase transformations intrinsically entail a decoupling of behaviour and morphology, phase state cannot meaningfully be conflated onto a single axis. LR models that do so are therefore of very limited value for any analysis of phase transitions. I furthermore show why behavioural predictor variables should not be adjusted by measures of body size that themselves differ between phases. I discuss the models fitted by Martín-Blázquez and Bakkali (2017) to highlight potential pitfalls in statistical methodology that must be avoided when applying LR to the analysis of behavioural phase state. Finally, I reject the idea that ‘standardised models’ provide a valid shortcut to estimating phase state across different developmental stages, strains or species. The points addressed here are pertinent to any research on transitions between complex phenotypes and behavioural syndromes.</jats:p
Data_Sheet_1_Regressions Fit for Purpose: Models of Locust Phase State Must Not Conflate Morphology With Behavior.ZIP
No full textPhenotypic plasticity often entails coordinated changes in multiple traits. The effects of two alternative environments on multiple phenotypic traits can be analyzed by multivariable binary logistic regression (LR). Locusts are grasshopper species (family Acrididae) with a capacity to transform between two distinct integrated phenotypes or “phases” in response to changes in population density: a solitarious phase, which occurs when densities are low, and a gregarious phase, which arises as a consequence of crowding and can form very large and economically damaging swarms. The two phases differ in behavior, physiology and morphology. A large body of work on the mechanistic basis of behavioral phase transitions has relied on LR models to estimate the probability of behavioral gregariousness from multiple behavioral variables. Mart́ın-Blázquez and Bakkali (2017; [10.1111/eea.12564]10.1111/eea.12564) have recently proposed standardized LR models for estimating an overall “gregariousness level” from a combination of behavioral and, unusually, morphometric variables. Here I develop a detailed argument to demonstrate that the premise of such an overall “gregariousness level” is fundamentally flawed, since locust phase transformations entail a decoupling of behavior and morphology. LR models that combine phenotypic traits with markedly different response times to environmental change are of very limited value for analyses of phase change in locusts, and of environmentally induced phenotypic transitions in general. I furthermore show why behavioral variables should not be adjusted by measures of body size that themselves differ between the two phases. I discuss the models fitted by Mart́ın-Blázquez and Bakkali (2017) to highlight potential pitfalls in statistical methodology that must be avoided when analysing associations between complex phenotypes and alternative environments. Finally, I reject the idea that “standardized models” provide a valid shortcut to estimating phase state across different developmental stages, strains or species. The points addressed here are pertinent to any research on transitions between complex phenotypes and behavioral syndromes.</p
How should we quantify behavioural phase state in locusts across treatments, strains, and species?
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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