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Correlates of time to first citation in ecology and taxonomy
Jhonny J. M. Guedes¹*; Isabella Melo¹; Igor Bione¹; Matheus Nunes¹
1 Programa de Pós-Graduação em Ecologia e Evolução, Departamento de Ecologia, Universidade Federal de Goiás, Goiânia, Goiás, 74690-
900, Brazil
* Corresponding author: E-mail: jhonnyguds@gmail.com
Abstract
Several metrics exists to evaluate the impact of publications and researchers, but most are
based on citation counts, which usually fail to capture the temporal aspect of citations. Time
to first citation represents a useful metric for research evaluation, and informs the speed at
which scientific knowledge is disseminated through the scientific community. Understanding
which factors affect such metrics is important as they impact resource allocation and career
progression, besides influencing knowledge promotion across disciplines. Many ecological
works rely on species identity, which is the ‘coin’ of taxonomy. Despite its importance,
taxonomy is a discipline in crisis lacking staff, funds and prestige, which ultimately may
affect the evaluation and dissemination of taxonomic works. We used a time-to-event
analysis to investigate whether taxonomic, socioeconomic, and scientometric factors
influence first citation speed across hundreds of ecological and taxonomic articles. Time to
first citation differed greatly between these areas. Ecological studies were first cited much
faster than taxonomic studies. Multitaxa articles received first citations earlier than studies
focused on single major taxonomic groups. Article length and h-index among authors were
negatively correlated with time to first citation, while the number of authors, number of
countries, and Gross Domestic Product was unimportant. Knowledge dissemination is faster
for lengthy, multitaxa, and ecological articles relative to their respective counterparts, as well
as for articles with highly prolific authors. We stress that using several unrelated metrics is
desirable when evaluating research from different–and even related–disciplines, particularly
in the context of professional progression and grant allocation.
Key words
h-index; research evaluation; scientometric analysis; survival analysis; time-to-event analysis;
time to first citation
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Introduction
The publication of scientific research is an essential step for the progress of science because it
allows for discussions within the scientific community about what has been done in a
particular field. The number of scientific articles published annually, both globally and in
specific areas, grows at high rates (Bornmann & Mutz 2015; Larsen & von Ins 2010).
However, the high volume of publications and, therefore, of research being performed,
implies that limited financial resources for scientific research (especially in developing
countries) may become increasingly scarce—i.e., if the increase of research projects is not
followed by a similar increase in research funding. Hence, resource allocation usually follows
some kind of technical criteria. Indeed, several metrics—mainly based on the number of
citations (Aksnes et al. 2019; Garfield 1972)—were developed in an attempt to assess
academic productivity and the impact of scientific research. Despite numerous criticisms
about the inadequacy of these metrics in evaluating the impact of scientific output and
researchers in some areas [e.g., medical sciences (Dinis-Oliveira 2019), taxonomy (Pyke
2014; Valdecasas et al. 2000), social sciences and humanities (Steele et al. 2006)] as well as
their impact outside academia (Ravenscroft et al. 2017), these metrics are still commonly
used by research funding institutions to decide where resources will be allocated (Fortin &
Currie 2013).
Several metrics have been proposed throughout the years and they may ‘behave’
differently between areas as well as be affected by different factors (Padial et al. 2010;
Tahamtan et al. 2016). In ecology, for example, variables such as number of authors, journal
impact factor, article size (number of pages), study results (positive or negative outcome),
among others, may influence the total number of citations (Borsuk et al. 2014; Leimu &
Koricheva 2005). However, some variables may be good predictors of the number of
citations in some areas, but not in others, so features of the study area in which the work is
inserted and its respective ‘audience’ represents another important factor to be considered
(Aksnes et al. 2019; Krell 2002). For instance, taxonomy differs from other areas of the
biological sciences due to several factors, such as the decrease in professional taxonomists
over time (Hopkins & Freckleton 2002; Wägele et al. 2011) and the increase in the number of
specialists in particular taxonomic groups (Joppa et al. 2011), with little interaction between
experts working in different groups (Venu & Sanjappa 2011). These factors may reduce the
short-term citation potential of taxonomic articles compared to articles from other disciplines.
That is, the process of citation accumulation in taxonomy is usually slow and gradual, and
may take decades to reach levels quickly observed in other disciplines (Venu & Sanjappa
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2011). Therefore, interdisciplinary differences in citation patterns must be taken into account
during, for example, resource allocation and professional progression.
Understanding which factors influence scientometric indices is important because
only then will we know under which contexts and areas these metrics will be relevant.
However, most of these metrics reflect ‘snapshots’ that do not characterize the temporal
behaviour of citations (Schubert & Glanzel 1986). For example, some articles—called
‘sleeping beauty’—receive belated recognition through citations by the academic community,
while others are immediately noticed, receive many citations, but are not much cited in the
following years (Van Dalen & Henkens 2005). Thus, it is also important to understand the
patterns and processes underlying the reception speed and recognition—or level of
acceptance—of articles by the scientific community, which can be measured by the time to
first citation (Bornmann & Daniel 2010a; Van Dalen & Henkens 2005; Egghe et al. 2011;
Glanzel & Rousseau 2012; Kumari et al. 2020; Schubert & Glanzel 1986). In this sense, both
the impact—thorough citation counts—and the time to first citation are important metrics to
consider when analysing the scientometric aspects of publications (Van Dalen & Henkens
2005). Still, the later could be, for instance, an early indicator of scientific performance
(Kumari et al. 2020). Although we have a good understanding of which factors affect the
total number of citations —and related metrics— in numerous areas, studies analysing which
factors affect the time to first citation and how it correlates with total citations are still scarce
(Hancock 2015; Kumari et al. 2020). So far, we know that in some disciplines such times
decrease with an increase in the number of authors, differs drastically between research areas,
and increases if the article was rejected before being published (Bornmann & Daniel 2010a;
Glanzel & Rousseau 2012; Hancock 2015).
Herein, we aim to understand which factors influence the time to first citation of
articles published in the areas of ecology and taxonomy. These two related—but distinct—
areas within biology interact directly with each other once, for instance, many ecological
analyses rely on species identity, such as regional species lists (Nekola & Horsák 2022),
which in turn is the ‘coin’ of taxonomy. Specifically, we will test the potential effects of the
i) number of pages, ii) number of authors, iii) number of countries (according to authors’
addresses), iv) maximum h-index among authors (this index measures both productivity and
impact, in terms of citations, from the publications of a researcher), v) maximum per capita
gross domestic product (GDP) of affiliation countries among authors, vi) study area, and vii)
taxonomic group studied. We expect the time to first citation will decrease with an increase in
the number of pages (greater amount of information presented), the number of authors and
4
countries (higher collaboration or multidisciplinarity), h-index (higher impact authors), and
GDP (greater influence of developed countries). Moreover, we expect lower times to first
citation in ecological than taxonomic articles due to intrinsic differences between areas as
mentioned above. We expect that studies on more charismatic groups, such as animals and
plants, which have more researchers working on them and are more appealing to the public
(Troudet et al. 2017), will receive their first citation faster than more neglected groups, such
as microorganisms (e.g. bacteria, protists). Lastly, we also discuss how this metric correlates
to the total number of citations among studies. Overall, this work seeks to improve our
understanding of potential factors influencing one of the many scientometric aspects of
scientific publications: the speed of the first citation.
Methodology
Data collection
To investigate potential factors influencing the time to first citation in taxonomic and
ecological works, we chose ten journals from each area (n = 20 journals; see Appendix 1) and
randomly selected using the sample_n function, without replacement, from the dplyr package
in software R (Wickham et al. 2020), 30 publications from the year 2015 for each journal (n
= 600 articles). We excluded articles that did not fit the study goals—e.g., theoretical or
simulation articles that did not analyse any species—and replaced them (also using the R
sample_n function) with other articles from the same journal to keep 30 publications per
journal. We selected journals based on three criteria: i) journals that were important channels
of information diffusion in each area; ii) journals whose scope involved only one of the areas
of interest, that is, we avoided multidisciplinary journals because it is difficult distinguishing
whether a paper was taxonomic or ecologic in scope, and iii) journals that were indexed in
the Web of Science (hereafter, WoS) database. In the case of taxonomy, we also selected
journals known for publishing many articles on species descriptions or natural history.
We searched the publications of each journal from the year 2015 through the WoS
database (search performed on 24 April 2021). Given we are interested in the time to first
citation, the six-year time period is sufficiently long to allow us to study the phenomenon of
interest. We used publications of the same year to reduce variation in potential correlates of
time to first citation, and to allow more direct comparisons among publications analysed
herein. Our search in WoS returned the publication list and several scientometric data related
to each publication, some of which were later used as predictors in our analysis (see below).
All publications represented either original articles or revisions (based on the ‘document
5
type’ category provided by WoS). For each one, we compiled data about eight potential
predictors of the time to first citation. Six were continuous covariates: 1) number of pages; 2)
number of authors; 3) number of countries (based on authors’ addresses); 4) maximum h-
index among authors (obtained from WoS); 5) maximum per capita GDP (in US$) of
affiliation countries among authors—obtained from the World Bank through the R package
wbstats (Piburn 2020). Two covariates were categorical and informed: 7) the study area
(ecology or taxonomy, based on the journal in which the article was published); and 8) the
focal taxonomic group studied: plants, animals, multitaxa (i.e., analysing species from
different kingdoms or domains), or ‘others’ (i.e., bacteria, fungi, protists, or chromists). We
measured the time to first citation as the number of months between the WoS publication date
and the date of first citation (excluding self-citations and considering WoS citation date).
Articles that were not cited or only received self-citations by April 2021 (cut-off date)
received maximum time to first citation—given their publication and search dates. Lastly, we
created a binary variable called ‘censor’ that informed whether articles were cited (1) or not
(0) by the cut-off date.
Statistical analyses
Before performing the statistical analysis, we log10-transformed some continuous variables
(number of pages, number of authors, number of countries, and h-index) due to high
skewness and kurtosis to increase linearity with our response variable —values between -2
and +2 are considered good evidence of a normal distribution, and hence, do not need
transformation (George & Mallery 2010). We standardized all continuous variables (mean =
0, std. deviation = 1) to directly compare their effect sizes and checked for multicollinearity
using the Variation Inflation Factors - VIFs (Mansfield & Helms 1982). VIF values higher
than 10 indicate that variables should be removed from the analysis (Kutner et al. 2005), but
since none of our variables reached VIFs higher than two (Supplementary Table S1), we kept
them all.
The time to first citation was investigated through time-to-event analysis, also known
as survival analysis (Bradburn et al. 2003; Clark et al. 2003). This analysis is commonly used
to investigate factors that may influence the probability of a particular event, such as time to
death or recovery, or failure time of equipment. Our event of interest—or survival time—is
the time to first citation after publication. Survival analysis incorporates censured data (i.e.,
observations that lack the event of interest at the end of data collection), which is an
advantage from commonly used statistical methods or previously proposed first-citation-
6
speed indexes (Bornmann & Daniel 2010a; Egghe et al. 2011), where censured data is
discarded despite containing valuable information. Specifically, we used an Accelerated
Failure Time (AFT) survival model, a parametric model that allows the evaluation of
covariate effects upon survival times (Bagdonavicius & Nikulin 2002). We applied an AICc-
based model selection approach to identify the best family error distribution (exponential,
Weibull, lognormal, log-logistic, gamma, and Gompertz) for the AFT model (Burnham &
Anderson 2002). The best family error distribution identified was the log-logistic
(Supplementary Table S2, Figure S1). Lastly, we checked the relationship between the time
to first citation and total citation counts through a linear model to investigate how one may
influence another. All analyses and plots were performed/created in the software R 4.0.2 (R
Core Team 2020) using the packages survival (Therneau 2021), flexsurv (Jackson 2016),
survminer (Kassambara et al. 2021), and ggplot2 (Wickham 2016).
Results
Time to first citation across ecological and taxonomic works combined ranged from zero to
75 months, with a median of 14 months. Among all articles analysed, 524 (or 87.3%) were
cited at least once by the cut-off date of this study. About one-quarter of all articles received
their first citation up to seven months after publication, but another quarter was first cited
only more than 30 months (two and a half years) after being published. However, time to first
citation varied significantly between study areas (Figure 1a; Table 1). Median survival time
across ecological studies was 10 months (range = 0—74), while in taxonomic studies it more
than doubled (26 months, range = 0—75). Five years after publication, more than one-quarter
of taxonomic works had not been cited once, while less than three percent of ecological
works remained to be first cited (Figure 1b).
Table 1: Accelerated Failure Time (AFT) survival model of the time to first citation as a function of taxonomic,
socioeconomic, and scientometric predictors. Continuous predictors were z-transformed before analysis to make
them comparable. Categorical predictors have a baseline level used for comparisons. Taxonomic studies are
being compared to ecological ones. Studies with animals are being compared to studies with plants, ‘others’ and
multitaxa.
Predictors
Estimate
Std. Error
z-value
p-value
(Intercept)
2.525
0.079
32
<0.001
LogN.Pages.z
-0.170
0.049
-3.5
<0.001
LogN.Authors.z
-0.041
0.053
-0.78
0.438
7
LogH.index.Max.z
-0.203
0.060
-3.4
0.001
LogN.Countries.z
-0.037
0.049
-0.76
0.449
GDP.Max.z
0.009
0.052
0.17
0.868
Taxonomy
0.698
0.120
5.8
<0.001
TaxOthers
0.129
0.171
0.76
0.449
TaxMultitaxa
-0.159
0.131
-1.21
0.225
TaxPlantae
-0.063
0.099
-0.64
0.520
Figure 1: Proportion of ecological and taxonomic articles to receive their first citation after publication. a)
Survival curves show probabilities of receiving first citation and their 95% confidence intervals. This probability
represents the chance of an article receiving its first citation at time t+1 given that it was not cited at time t.
Black dashed lines indicate the median time to first citation for each study area when survival probability was
50%. b) The number of articles remaining to be cited in n months since publication.
++ + +
++++
++++++++
0.00
0.25
0.50
0.75
1.00
0 20 40 60 80
Months since publication
Papers to be cited
++
Ecology Taxonomy
300 60 13 8 0
300 178 111 82 0
Taxo
Eco
0 20 40 60 80
Months since publication
Strata
Number at risk
a
b
8
We found that multitaxa studies—e.g., studies on interaction networks, food webs—
received their first citation much faster than studies focused on species from a single major
taxonomic group (Figure 2a-b). Median time to first citation was 9.5 months for multitaxa
studies, 14 months for articles focused on animals or plants, and more than two years (28
months) for studies on more neglected groups —mostly microorganisms. However,
differences among groups were not significant, likely due to high variability and overlap in
survival times (Table 1; Figure 2a).
Aside from the study area, the most important predictor—i.e., strongest effect size—
in explaining variation in time to first citation was the maximum h-index among authors.
Precisely, time to first citation decreases with increasing productivity and impact of
researchers. Likewise, the number of pages is negatively associated with the time to first
citation. That is, lengthy articles receive, on average, their first citation faster than shorter
ones. The number of authors, number of countries, and maximum GDP were unimportant in
explaining variation in the time to first citation (Table 1). Overall, our AFT model explained
26.4% of the variation in the time to first citation across ecological and taxonomic articles.
Lastly, time to first citation was negatively correlated with log-transformed total number of
citations (lm: coef. = -0.032, t = -20.4, p < 0.001), with a coefficient of determination of 41%
(Supplementary Figure S2).
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Figure 2: Proportion of articles based on different major taxonomic groups to receive first citation after
publication. a) Survival curves show probabilities —of receiving first citation— and their 95% confidence
intervals. Details are the same as for figure l. b) The number of articles remaining to be cited in n months since
publication. Legend: Others = Bacteria, Chromista, Fungi, and Protista combined.
Discussion
We analysed the effects of taxonomic, socioeconomic, scientometric, and field-related
predictors on first citation speed across hundreds of ecological and taxonomic articles more
than five years since their publication. We have shown that recognition and speed of
knowledge dissemination in the scientific community is much faster for articles in ecology
than taxonomy. In other words, there is a field-related bias regarding this particular metric.
We also showed that first citation speed is, on average, faster for lengthy articles and for
papers authored by high-impact researchers, while socioeconomic and collaboration
predictors were unimportant. Time to first citation can differ greatly among studies focused
on different taxonomic groups, particularly between multitaxa studies and those focused on
less charismatic and conspicuous taxa. Moreover, time to first citation shows a negative non-
++++++++++++
++ + +
++
++
+
+++++
0.00
0.25
0.50
0.75
1.00
0 20 40 60 80
Months since publication
Papers to be cited
+
+
+
+
Animalia
Others
Multitaxa
Plantae
314 132 75 50 0
42 28 12 9 0
82 18 420
162 60 33 29 0
Plantae
Multitaxa
Others
Animalia
0 20 40 60 80
Months since publication
Strata
Number at risk
a
b
10
linear relationship with the total number of citations and high variability among articles with
intermediate citation counts, which may hamper the use of this metric alone as a good
surrogate for future number of citations. Overall, our findings show that time to first citation
is lower for lengthy, multitaxa, and ecological articles relative to their respective
counterparts. Likewise, papers authored by more productive and prolific authors are likely to
receive their first citation earlier.
Since the proposal of using the number of citations as a metric for research
assessment (Garfield 1972), several studies have investigated factors that may affect this
metric and under which circumstances [for a review, see (Tahamtan et al. 2016)]. Conversely,
only a few studies have analysed which factors influence the time to first citation and how it
varies among disciplines (Hancock 2015; Kumari et al. 2020). Differently from the total
number of citations—usually perceived as the impact of scientific publications (Van Dalen &
Henkens 2005)—the time to first citation can be seem as the speed to which knowledge and
ideas in a given area are disseminated through the scientific community (Glanzel & Rousseau
2012; Hancock 2015). Thus, although these metrics are somehow related (Supplementary
Figure S2) and could, perhaps and to some extent, be used to predict one another (Kumari et
al. 2020), they provide information on different patterns about scientific publications. While
the number of citations can accumulate through time, usually at distinct rates among
disciplines, the time to first citation represents a particular event that somehow levels all
publications under comparison based on a specific temporal aspect of citations.
We have shown empirically that taxonomic articles usually receive their first citation
much later than ecological papers, which is in line with previous studies showing differences
in citation speed between distant and even closely related disciplines (Abramo et al. 2011;
Glanzel & Rousseau 2012; Hancock 2015; Oermann et al. 2010). Coupled with the slow and
gradual accumulation of citations in taxonomic studies through time (Venu & Sanjappa
2011), our findings highlight the inadequacy of simply using citation counts as a tool for
assessing impact and then comparing taxonomic and non-taxonomic studies. If comparisons
are needed such as for decisions on grant allocation or career development, alternative and
more appropriate metrics —citation-based or not— could be used (Pyke 2014; Valdecasas et
al. 2000). For instance, the Field-Weighted Citation Index (Zanotto & Carvalho 2021) is a
recently developed metric that compares related articles—i.e., from the same field—based on
their keywords and age. Differences in citation counts and time to first citation are expected
among areas due to intrinsic differences between them (Aksnes et al. 2019; Krell 2002). For
example, community size, publication rates, time for obsolescence, and citation practices
11
adopted in different areas can impact citation counts and other citation-based metrics. Across
all selected journals in this study, journal impact factors were much higher in ecology than
taxonomy (Supplementary Figure S3a), which highlights yet another difference between
areas that can, in turn, also affect time to first citation (Supplementary Figure S3b).
Therefore, although using simple metrics is tempting, applying less biased, more comparable,
or even a combination of metrics is desirable and should be encouraged, particularly in
funding agencies and universities, to reduce existing gaps between disciplines.
We found a negative relationship between time to first citation and maximum h-index
among authors. The h-index was a metric proposed to quantify author-level productivity and
impact based on a combination of the number of publications and citations (Hirsch 2005).
There are several critics about using this metric as researchers’ scientific achievements for
professional progression or funding allocation because, for instance, it does not accommodate
age disparities among researchers (Dinis-Oliveira 2019). Although this metric may indeed be
age-biased, higher h-indexes are likely related to very prolific researchers with equally higher
networks within the scientific community that, in turn, seems to contribute to the fast
dissemination of produced knowledge and ideas in their scientific field. One point of concern
that arises with such finding is that, for instance, good scientific work can be developed by
less prolific authors, but such works may take more time—if ever—to gain acknowledgment
by their peers. Additionally, high-impact authors may be ‘invited’ to contribute in works
where they have actually not contributed at all, be it intellectually or otherwise. Although the
latter possibility may be hard to investigate, it warrants attention since such practice can be
detrimental to science as a whole.
Similarly to the h-index, an increasing number of pages may decrease first citation
speed. That is, lengthy articles usually receive their first citation faster than do shorter ones.
Articles’ length is also known to affect citation frequency in ecology (Leimu & Koricheva
2005; Padial et al. 2010) and taxonomy —in the latter through recognition of major
contributions of revisions/monographs, although their citations are usually accumulated slow-
and gradually (Venu & Sanjappa 2011). Longer articles are likely cited earlier because they
have more citable content than shorter ones and may also have more visibility (Leimu &
Koricheva 2005). For instance, during taxonomic revisions an entire genus—or family—can
be revised, leading to discoveries of several new taxa or nomenclatural rearrangements (e.g.,
47) that are subsequently cited by scientists working in the revised groups. However, this
trend may not hold, or even be inverted, for papers published in high-impact
multidisciplinary journals, such as Science and Nature, where most publications are usually
12
only few-pages long. Additionally, ‘supplementary material’ may also contribute to the
reduction of time to first citation since it provides additional and citable content attached to
the main paper. The use of supplementary material is common ground in ecological works
nowadays, but it is likely less so in taxonomy. Incorporating supplementary information into
paper length would likely increase effect sizes.
Although we did not find significant differences between studies focused on different
major taxonomic groups, the time to first citation varied greatly among groups (Figure 2a-b).
Multitaxa studies had much lower times to first citation, particularly compared to studies
focused on less conspicuous and charismatic organisms, where the overlap of survival curves
and confidence intervals was minimal (Figure 2a). These studies may reach a larger audience
as they ‘cover two different worlds’, that is, scientists working on very different taxonomic
groups can potentially cite them. We acknowledge that our choice of grouping some
organisms, but particularly, of using a high hierarchical level during analysis could affect our
findings. For instance, a greater research effort to certain groups over others (Titley et al.
2017; Troudet et al. 2017) could ultimately influence first citation speed as well as other
citation-based metrics. Future studies on this topic could use smaller taxonomic scales or
even accommodate taxon identify as random structure into models. However, in the latter
scenario researchers would not be interested in the particular effect of taxonomies upon the
response variable under investigation, but only to control for dependence issues.
Contrarily to previous studies, we did not find an effect of collaboration on time to
first citation across ecological and taxonomic articles. For instance, increased collaboration is
associated with fast citation after publication in the fields of robotics and artificial
intelligence (Kumari et al. 2020), music (Hancock 2015), and chemistry (Bornmann & Daniel
2010b). Multiauthorship likely contributes to wider dissemination of published articles within
the scientific community and speeds up first citation (Bornmann & Daniel 2010b), but it may
also be related to increased self-citations (Herbertz 1995; Leimu & Koricheva 2005).
Differently from other studies, we removed self-citations herein, which likely contributed to
the non-significance of the number of authors and countries on first citation speed. The
impact of self-citations may be exacerbated across taxonomic articles, where it can play an
important role in citation counts, particularly in more restricted research groups—e.g., an
expert taxonomist working with an understudied and ‘understaffed’ group will likely end up
citing himself/herself frequently.
Conclusion
13
A plethora of scientometric indicators have been developed, many of which are based
primarily on the traditional total number of citations [for a review, see (De Rijcke et al.
2016)]. These metrics are increasingly becoming central components of evaluation systems of
scientific research and, consequently, of researchers themselves (Aksnes et al. 2019). In this
study, we used the time to first citation to empirically demonstrate intrinsic differences
between ecology and taxonomy. Despite their many differences, these two areas are directly
related to each other (Freeman & Pennell 2021) and understating how scientometric indices
behave in each of them may contribute, for instance, to a fairer distribution of research grants
across disciplines. Despite the growing use and popularity of scientometric indicators, it is
important to recognize which factors affect them, as well as their biases and pitfalls. Among
future directions for studies on the time to first citation, we highlight the importance to
investigate i) how different time intervals—from publication to cut-off dates—affects citation
speed variation, ii) how the inclusion/exclusion of self-citations changes first citation times,
particularly between different study areas, iii) how social and non-social media activity and
related altimetrics affect citation speed, and iv) how article accessibility—open access vs.
non-open access—is related to the time to first citation. Finally, we stress that no metric is
perfect and the blind use of single traditional metrics to compare studies, researchers, or
institutions can be highly pervasive. The combined use of several—and particularly
unrelated—metrics is strongly recommended, especially for important decisions as grant
allocation and career progression.
Appendix
Appendix 1. List of ecological and taxonomic journals analyzed in this study. We selected 30
papers published during 2015 from each journal. Ecology: Acta Oecologica, Austral Ecology,
Basic and Applied Ecology, Ecography, Ecology, Ecology Letters, Ecosphere, Journal of
Applied Ecology, Oecologia, Oikos. Taxonomy: Brittonia, European journal of taxonomy,
Mycotaxon, Phytotaxa, Systematic Botany, Taxon, Vertebrate Zoology, Zookeys, Zoological
Journal of the Linnean Society, Zoosystema.
Acknowledgments
We appreciate valuable friendly reviews in a previous version of this manuscript by Maurício
Bini, João Nabout, José A. F. Diniz-Filho, and four anonymous reviewers from the DPAC
course. We thank the Brazilian Coordenação de Aperfeiçoamento de Pessoal de Nível
14
Superior (CAPES) and the Conselho Nacional de Desenvolvimento Científico e Tecnológico
(CNPq) for financial support.
Funding
This work was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível
Superior - Brasil (CAPES) - as a PhD scholarship to JJMG, IR and MN, and by the Conselho
Nacional de Desenvolvimento Científico e Tecnológico - Brasil (CNPq) - as a PhD
scholarship to IB.
Competing interests
The authors declare they have no conflict of interest, financial or otherwise.
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Supplementary Information
Figure S1: Top-4 best fitted family error distribution to the Accelerated Failure Time (AFT) survival model for
the time to first citation in ecology and taxonomy. The best-fitted error distribution was the log logistic. See
table S2 (below) for model parameters and AICc values.
0 20 40 60
0.0 0.2 0.4 0.6 0.8 1.0
loglogistic
Time since publication
Papers to be cited
0 20 40 60
0.0 0.2 0.4 0.6 0.8 1.0
lognormal
Time since publication
Papers to be cited
0 20 40 60
0.0 0.2 0.4 0.6 0.8 1.0
gompertz
Time since publication
Papers to be cited
0 20 40 60
0.0 0.2 0.4 0.6 0.8 1.0
exponential
Time since publication
Papers to be cited
20
Figure S2: Correlation between the total number of citations (log-transformed) and the time to first citation
across 600 ecological and taxonomic articles published in 2015. Adjusted correlation (in blue) was fitted using a
second-order polynomial function and shows a negative relationship between the two metrics.
y= 65.2 −27 x+3.07 x2
R2= 0.41 , p< 0.001
0
20
40
60
024
Log times cited
Time to first citation (in months)
21
Figure S3: a) Differences in journal’s impact factors by area. b) The relationship between impact factor and
time to first citation.
Table S1: Variation Inflation Factor among continuous predictors for the time to first citation in ecology and
taxonomy.
Variables
VIF
LogN.Pages.z
1.040723
LogN.Authors.z
1.74842
LogH.index.Max.z
1.622732
LogN.Countries.z
1.468706
GDP.Max.z
1.367518
0.5
1.0
1.5
2.0
2.5
Ecology Taxonomy
Study area
Log journal impact factor
a
0
20
40
60
0.55 0.61 0.65 0.87 0.94 0.99 1.01 1.09 1.1 1.6 1.84 2.29 2.32 2.9 3.59 4.73 5.2 5.36 5.84 10.77
Journal impact factor
Time to first citation (in months)
Ecology
Taxonomy
b
22
Table S2: Results from the model selection approach to identify the best family error distribution for the
Accelerated Failure Time model. npars = are number of parameters for each distribution; AICc = Akaike
information criteria; delta AICc = differences from best model; wAICc = model weights.
Distribution
npars
AICc
deltaAICc
wAICc
loglogistic
2
4442.487
0.000
0.996
lognormal
2
4453.464
10.977
0.004
gompertz
2
4496.545
54.058
0.000
exponential
1
4527.628
85.141
0.000
gamma
2
4528.765
86.278
0.000
weibull
2
4528.978
86.491
0.000
