Effects of hydrological change in fire‐prone wetland vegetation: An empirical simulation

Mason, Tanya J.; Popović, Gordana; McGillycuddy, Maeve; Keith, David A.

doi:10.1111/1365-2745.14078

Cited by 3 publications

(4 citation statements)

References 55 publications

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“…principal investigator academic level, time), averaging across levels of other variables. In cases when confidence intervals included the variance of the random slopes for gender, we used the Hessian matrix for parameter estimation (with code based on Mason et al 2023).…”

Section: [Insert Table 1]mentioning

confidence: 99%

Women are awarded more team grants than solo grants and lead more gender-balanced teams than men

Kingsley,

Slavich,

Harvey-Smith

et al. 2024

Preprint

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We modelled patterns of collaboration, team gender composition, and funding amounts across awarded Australian government-funded competitive team research grants from 2000–2020. Among mid- and senior-career researchers, the percentage of grants awarded to women was higher for team grants than sole investigator grants compared to men at those levels. Teams led by women tended to have a greater percentage of women co-investigators than teams led by men, but this was below gender parity regardless of team leader gender. Funding amounts per grant did not differ by principal investigator gender and reached parity in 2020 across teams with both high and low representation of women. Since teams tend to be more gender-balanced when led by women, women’s grant leadership may be an important mechanism for shifting overall representation of women in research. We offer public policy measures to address gender equities in the research sector.

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Section: [Insert Table 1]mentioning

confidence: 99%

Women are awarded more team grants than solo grants and lead more gender-balanced teams than men

Kingsley,

Slavich,

Harvey-Smith

et al. 2024

Preprint

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“…lead investigator academic level, time). Where confidence intervals include the variance of the random slopes for gender, we used the Hessian from the glmmTMB object (with code based on Mason et al 2023).…”

Section: Statistical Analysesmentioning

confidence: 99%

Gender differences in Australian research grant awards, applications, amounts, and workforce participation

Kingsley¹,

Harvey-Smith²,

Johnston³

et al. 2023

Preprint

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Gender differences in the outcomes of competitive grant programs have been detected, though the evidence is mixed. We modelled twenty years (2000–2020) of Australian national competitive grants and funding amounts according to lead investigator gender. We also explored if gender differences in awarded grants mirrored application rates and/or estimates of research workforce participation by gender. The dataset contained 50,733 awarded grants. We incorporated grant application and research workforce data. We found that fewer awarded grants were led by women than men; however, success rates of grant applications did not vary according to lead investigator gender. There were fewer women than men in the research workforce. The award rate (awarded grants relative to workforce participation) was slightly higher for women than men. All of the observed gender differences were largest at senior-career levels. Gender differences in the number of awarded grants reduced over the period of the study, with the strongest temporal trend amongst senior-career researchers. Gender differences in awarded grants varied by field of research, broadly mirroring differences in application and workforce participation rates within each field of research. Funding amounts per awarded grant did not vary by the gender of the lead investigator. Together these patterns imply that fewer women in the research workforce and leading grant applications have resulted in fewer awarded grants led by women than by men. Given that most awarded grants are to senior-career researchers, and that the largest gender differences exist amongst this cohort, large gender differences in awarded grants accumulate.

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“…Throughout, we will demonstrate the principles with two ecological examples: the wetland experiment, which examines how disturbances affect upland wetlands (Mason et al., 2022); and the bird study, which examines the relationships between hatching date and the expression of carotenoid‐based coloration in nestlings (Janas et al., 2020). A full workflow of the principles applied to these examples is available at https://github.com/gordy2x/principles.…”

Section: Introductionmentioning

confidence: 99%

“…They were then placed in tubs in a glasshouse, and tub water levels were manipulated to simulate different levels of groundwater availability. A fire event was simulated by sequentially applying biomass removal (clipping), heat and smoke to half of the mesocosms in each water treatment after 20 months (Mason et al., 2022, ssee Figure 2).…”

Section: Introductionmentioning

confidence: 99%

Four principles for improved statistical ecology

Popovic,

Mason,

Drobniak

et al. 2024

Methods Ecol Evol

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Increasing attention has been drawn to the misuse of statistical methods over recent years, with particular concern about the prevalence of practices such as poor experimental design, cherry picking and inadequate reporting. These failures are largely unintentional and no more common in ecology than in other scientific disciplines, with many of them easily remedied given the right guidance. Originating from a discussion at the 2020 International Statistical Ecology Conference, we show how ecologists can build their research following four guiding principles for impactful statistical research practices: (1) define a focussed research question, then plan sampling and analysis to answer it; (2) develop a model that accounts for the distribution and dependence of your data; (3) emphasise effect sizes to replace statistical significance with ecological relevance; and (4) report your methods and findings in sufficient detail so that your research is valid and reproducible. These principles provide a framework for experimental design and reporting that guards against unsound practices. Starting with a well‐defined research question allows researchers to create an efficient study to answer it, and guards against poor research practices that lead to poor estimation of the direction, magnitude, and uncertainty of ecological relationships, and to poor replicability. Correct and appropriate statistical models give sound conclusions. Good reporting practices and a focus on ecological relevance make results impactful and replicable. Illustrated with two examples—an experiment to study the impact of disturbance on upland wetlands, and an observational study on blue tit colouring—this paper explains the rationale for the selection and use of effective statistical practices and provides practical guidance for ecologists seeking to improve their use of statistical methods.

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Effects of hydrological change in fire‐prone wetland vegetation: An empirical simulation

Cited by 3 publications

References 55 publications

Women are awarded more team grants than solo grants and lead more gender-balanced teams than men

Women are awarded more team grants than solo grants and lead more gender-balanced teams than men

Gender differences in Australian research grant awards, applications, amounts, and workforce participation

Four principles for improved statistical ecology

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