1,721,039 research outputs found
Pathway for personality development: juvenile red knots vary more in diet and exploratory behaviour than adults
No full textSelin Ersoy; Christine E. Beardsworth; Elif Duran; Marcel T.J. van der Meer; Theunis Piersma; Ton G. G. Groothuis & Allert Bijleveld
Title: "Pathway for personality development: juvenile red knots vary more in diet and exploratory behaviour than adults"
Authors: Selin Ersoy, Christine E. Beardsworth, Elif Duran, Marcel T.J. van der Meer, Theunis Piersma, Ton G. G. Groothuis, Allert I. Bijleveld
GENERAL INFORMATION
Titles of the Dataset: Juv-Adult_Expl_Allyears (Exploration speed (mean speed cm/sec) in mobile arena), isotope data (plasma and red blood cell)
Date of the data collection: Catching between 14 August 2018 - 19 October 2021
3. Geographic location of data collection: Western Dutch Wadden Sea (53°15'N, 5°15'E)
4. Corresponding author information: Selin Ersoy, NIOZ Royal Netherlands Institute for Sea Research, Department of Coastal Systems, PO Box 59, 1790 AB Den Burg, Texel, The Netherlands, [email protected]
METHODS
Isotope data: Red blood cell and plasma d13C and d15N isotopes collected from the blood samples of red knots.
Exploration speed: Movement tracjectories were collected from the recordings of the top camera during experiments in the mobile arena. We used the distance between estimated positions to calculate speed. Errors in the positioning algorithm were filtered by excluding speeds higher than 200 cm/s. An individual’s exploration speed was calculated as the average speed during each 20 min trial. The dataset includes two repeats of exploration speed.
DATA & FILE OVERVIEW
Juv-Adult_Expl_Allyears : Exploration speed repeated measures from Juvenile and Adult red knots
Column 1: FB: Unique metal ring number of red knots. Ring were put on the legs
Column 2: Exp: Repeat number of the exploration assay trials
Column 3: Age: Adult (3) or juvenile (1) age
Column 4: Mean: Exploratory score of individual measured in mobile arena (mean speed cm/sec) measured through automated tracking
Column 5: Year: Year of the testing
Isotope : Red blood cell and plasma d13C and d15N isotopes collected from the blood samples of juvenile and adult red knots
Column 1: RingNr: Unique metal ring number of red knots. Ring were put on the legs
Column 2: Type: Blood type plasma or red blood cell
Column 3: Repeat: If there is a repeated samples of an individual
Column 4: d15N: Nitrogen 15 Isotope value
Column 5: d13C: Carbon 13 Isotope value
Column 6: ProcessDate:Process date of blood samples
Column 7: Comments: important commments about samples
Column 8: AGE: Adult (3) or juvenile (1) age
Column 9: CatchDate: Cathing date of the individuals
Column 10: CATCH_YEAR: Catching year of the individuals (taken from CatchDate)
SIBER-2021-12-21.csv: Isotope data was organised for SIBER analysis
#https://cran.r-project.org/web/packages/SIBER/vignettes/Introduction-to-SIBER.html
iso1: RingNr: Unique metal ring number of red knots. Ring were put on the legs
iso2: Type: Blood type plasma or red blood cell
group: equals to AGE in isotope dataset (1=Juvenile, 2=Second-calendar year which is not used for this study, 3=Adult)
community: equals to CATCH_YEAR in isotope dataset (1= 2018, 3= 2019 *which are not used for this analyses, 2= 2021)
R file includes code for all the statistics and visualization of the data
Pathway for personality development: juvenile red knots vary more in diet and exploratory behaviour than adults
No full textSelin Ersoy; Christine E. Beardsworth; Elif Duran; Marcel T.J. van der Meer; Theunis Piersma; Ton G. G. Groothuis & Allert Bijleveld
Title: "Pathway for personality development: juvenile red knots vary more in diet and exploratory behaviour than adults"
Authors: Selin Ersoy, Christine E. Beardsworth, Elif Duran, Marcel T.J. van der Meer, Theunis Piersma, Ton G. G. Groothuis, Allert I. Bijleveld
GENERAL INFORMATION
Titles of the Dataset: Juv-Adult_Expl_Allyears (Exploration speed (mean speed cm/sec) in mobile arena), isotope data (plasma and red blood cell)
Date of the data collection: Catching between 14 August 2018 - 19 October 2021
3. Geographic location of data collection: Western Dutch Wadden Sea (53°15'N, 5°15'E)
4. Corresponding author information: Selin Ersoy, NIOZ Royal Netherlands Institute for Sea Research, Department of Coastal Systems, PO Box 59, 1790 AB Den Burg, Texel, The Netherlands, [email protected]
METHODS
Isotope data: Red blood cell and plasma d13C and d15N isotopes collected from the blood samples of red knots.
Exploration speed: Movement tracjectories were collected from the recordings of the top camera during experiments in the mobile arena. We used the distance between estimated positions to calculate speed. Errors in the positioning algorithm were filtered by excluding speeds higher than 200 cm/s. An individual’s exploration speed was calculated as the average speed during each 20 min trial. The dataset includes two repeats of exploration speed.
DATA & FILE OVERVIEW
Juv-Adult_Expl_Allyears : Exploration speed repeated measures from Juvenile and Adult red knots
Column 1: FB: Unique metal ring number of red knots. Ring were put on the legs
Column 2: Exp: Repeat number of the exploration assay trials
Column 3: Age: Adult (3) or juvenile (1) age
Column 4: Mean: Exploratory score of individual measured in mobile arena (mean speed cm/sec) measured through automated tracking
Column 5: Year: Year of the testing
Isotope : Red blood cell and plasma d13C and d15N isotopes collected from the blood samples of juvenile and adult red knots
Column 1: RingNr: Unique metal ring number of red knots. Ring were put on the legs
Column 2: Type: Blood type plasma or red blood cell
Column 3: Repeat: If there is a repeated samples of an individual
Column 4: d15N: Nitrogen 15 Isotope value
Column 5: d13C: Carbon 13 Isotope value
Column 6: ProcessDate:Process date of blood samples
Column 7: Comments: important commments about samples
Column 8: AGE: Adult (3) or juvenile (1) age
Column 9: CatchDate: Cathing date of the individuals
Column 10: CATCH_YEAR: Catching year of the individuals (taken from CatchDate)
SIBER-2021-12-21.csv: Isotope data was organised for SIBER analysis
#https://cran.r-project.org/web/packages/SIBER/vignettes/Introduction-to-SIBER.html
iso1: RingNr: Unique metal ring number of red knots. Ring were put on the legs
iso2: Type: Blood type plasma or red blood cell
group: equals to AGE in isotope dataset (1=Juvenile, 2=Second-calendar year which is not used for this study, 3=Adult)
community: equals to CATCH_YEAR in isotope dataset (1= 2018, 3= 2019 *which are not used for this analyses, 2= 2021)
R file includes code for all the statistics and visualization of the data
Pathway for personality development: juvenile red knots vary more in diet and exploratory behaviour than adults
No full textTitle: "Pathway for personality development: juvenile red knots vary more in diet and exploratory behaviour than adults"
Authors: Selin Ersoy, Christine E. Beardsworth, Elif Duran, Marcel T.J. van der Meer, Theunis Piersma, Ton G. G. Groothuis, Allert I. Bijleveld
GENERAL INFORMATION
Titles of the Dataset: Juv-Adult_Expl_Allyears (Exploration speed (mean speed cm/sec) in mobile arena), isotope data (plasma and red blood cell)
Date of the data collection: Catching between 14 August 2018 - 19 October 2021
3. Geographic location of data collection: Western Dutch Wadden Sea (53°15'N, 5°15'E)
4. Corresponding author information: Selin Ersoy, NIOZ Royal Netherlands Institute for Sea Research, Department of Coastal Systems, PO Box 59, 1790 AB Den Burg, Texel, The Netherlands, [email protected]
METHODS
Isotope data: Red blood cell and plasma d13C and d15N isotopes collected from the blood samples of red knots.
Exploration speed: Movement tracjectories were collected from the recordings of the top camera during experiments in the mobile arena. We used the distance between estimated positions to calculate speed. Errors in the positioning algorithm were filtered by excluding speeds higher than 200 cm/s. An individual’s exploration speed was calculated as the average speed during each 20 min trial. The dataset includes two repeats of exploration speed.
DATA & FILE OVERVIEW
Juv-Adult_Expl_Allyears : Exploration speed repeated measures from Juvenile and Adult red knots
Column 1: FB: Unique metal ring number of red knots. Ring were put on the legs
Column 2: Exp: Repeat number of the exploration assay trials
Column 3: Age: Adult (3) or juvenile (1) age
Column 4: Mean: Exploratory score of individual measured in mobile arena (mean speed cm/sec) measured through automated tracking
Column 5: Year: Year of the testing
Isotope : Red blood cell and plasma d13C and d15N isotopes collected from the blood samples of juvenile and adult red knots
Column 1: RingNr: Unique metal ring number of red knots. Ring were put on the legs
Column 2: Type: Blood type plasma or red blood cell
Column 3: Repeat: If there is a repeated samples of an individual
Column 4: d15N: Nitrogen 15 Isotope value
Column 5: d13C: Carbon 13 Isotope value
Column 6: ProcessDate:Process date of blood samples
Column 7: Comments: important commments about samples
Column 8: AGE: Adult (3) or juvenile (1) age
Column 9: CatchDate: Cathing date of the individuals
Column 10: CATCH_YEAR: Catching year of the individuals (taken from CatchDate)
SIBER-2021-12-21.csv: Isotope data was organised for SIBER analysis
#https://cran.r-project.org/web/packages/SIBER/vignettes/Introduction-to-SIBER.html
iso1: RingNr: Unique metal ring number of red knots. Ring were put on the legs
iso2: Type: Blood type plasma or red blood cell
group: equals to AGE in isotope dataset (1=Juvenile, 2=Second-calendar year which is not used for this study, 3=Adult)
community: equals to CATCH_YEAR in isotope dataset (1= 2018, 3= 2019 *which are not used for this analyses, 2= 2021)
R file includes code for all the statistics and visualization of the data
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
Male-Male Competition as a Force in Evolutionary Diversification: Evidence in Haplochromine Cichlid Fish
Full text linkIt has been suggested that intrasexual competition can be a source of negative frequency-dependent selection, causing agonistic character displacement and facilitating speciation and coexistence of (sibling) species. In this paper we synthesise the evidence that male-male and female-female competition contributes to cichlid diversification, showing that competition is stronger among same-coloured individuals than those with different colours. We argue that intrasexual selection is more complex because there are several examples where males do not bias aggression towards their own type. In addition, sibling species or colour morphs often show asymmetric dominance relationships. We briefly discuss potential mechanisms that might promote the maintenance of covariance between colour and aggression-related traits even in the face of gene-flow. We close by proposing several avenues for future studies that might shed more light on the role of intrasexual competition in cichlid diversification.</jats:p
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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