All eggs are made equal: meta‐analysis of egg sexual size dimorphism in birds

Rutkowska, Joanna; Dubiec, Anna; Nakagawa, Shinichi

doi:10.1111/jeb.12282

Cited by 20 publications

(13 citation statements)

References 70 publications

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“…The absence of any sex difference on the maternaloffspring mass relationship was an unexpected result, which indicates that mothers allocate the same relative amount of energy to male and female offspring irrespective of their body mass. Similar results were found in birds with no sex-biased allocation to egg size (Rutkowska, Dubiec & Nakagawa, 2014). In polygynous species the disproportionate mass or size advantage of offspring males is expected to be higher than in promiscuous species (Clutton-Brock, 1991) but we did not find any interaction between offspring sex and mating system.…”

Section: Discussionsupporting

confidence: 88%

Causes and consequences of variation in offspring body mass: meta‐analyses in birds and mammals

et al. 2017

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Early survival is highly variable and strongly influences observed population growth rates in most vertebrate populations. One of the major potential drivers of survival variation among juveniles is body mass. Heavy juveniles are better fed and have greater body reserves, and are thus assumed to survive better than light individuals. In spite of this, some studies have failed to detect an influence of body mass on offspring survival, questioning whether offspring body mass does indeed consistently influence juvenile survival, or whether this occurs in particular species/environments. Furthermore, the causes for variation in offspring mass are poorly understood, although maternal mass has often been reported to play a crucial role. To understand why offspring differ in body mass, and how this influences juvenile survival, we performed phylogenetically corrected meta-analyses of both the relationship between offspring body mass and offspring survival in birds and mammals and the relationship between maternal mass and offspring mass in mammals. We found strong support for an overall positive effect of offspring body mass on survival, with a more pronounced influence in mammals than in birds. An increase of one standard deviation of body mass increased the odds of offspring survival by 71% in mammals and by 44% in birds. A cost of being too fat in birds in terms of flight performance might explain why body mass is a less reliable predictor of offspring survival in birds. We then looked for moderators explaining the among-study differences reported in the intensity of this relationship. Surprisingly, sex did not influence the intensity of the offspring mass-survival relationship and phylogeny only accounted for a small proportion of observed variation in the intensity of that relationship. Among the potential factors that might affect the relationship between mass and survival in juveniles, only environmental conditions was influential in mammals. Offspring survival was most strongly influenced by body mass in captive populations and wild populations in the absence of predation. We also found support for the expected positive effect of maternal mass on offspring mass in mammals (r = 0.387). As body mass is a strong predictor of early survival, we expected heavier mothers to allocate more to their offspring, leading them to be heavier and so to have a higher survival. However, none of the potential factors we tested for variation in the maternal mass-offspring mass relationship had a detectable influence. Further studies should focus on linking these two relationships to determine whether a strong effect of offspring size on early survival is associated with a high correlation coefficient between maternal mass and offspring mass.

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Section: Discussionsupporting

confidence: 88%

Causes and consequences of variation in offspring body mass: meta‐analyses in birds and mammals

et al. 2017

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“…Coupled with the nonsignificant meta‐analytic mean that they observed (Rutkowska et al. ), this low I 2 indicates that birds do not bias egg size based on the sex of the chick, and that observations to the contrary are likely Type I errors.…”

Section: Discussionmentioning

confidence: 88%

“…For example, in their analysis of egg size and chick sexual‐size dimorphism in birds, Rutkowska et al. () report I 2 of only 12.7%. Coupled with the nonsignificant meta‐analytic mean that they observed (Rutkowska et al.…”

Section: Discussionmentioning

confidence: 99%

Heterogeneity in ecological and evolutionary meta‐analyses: its magnitude and implications

Senior

Grueber

Kamiya

et al. 2016

Ecology

214

223

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Meta-analysis is the gold standard for synthesis in ecology and evolution. Together with estimating overall effect magnitudes, meta-analyses estimate differences between effect sizes via heterogeneity statistics. It is widely hypothesized that heterogeneity will be present in ecological/evolutionary meta-analyses due to the system-specific nature of biological phenomena. Despite driving recommended best practices, the generality of heterogeneity in ecological data has never been systematically reviewed. We reviewed 700 studies, finding 325 that used formal meta-analysis, of which total heterogeneity was reported in fewer than 40%. We used second-order meta-analysis to collate heterogeneity statistics from 86 studies. Our analysis revealed that the median and mean heterogeneity, expressed as I , are 84.67% and 91.69%, respectively. These estimates are well above "high" heterogeneity (i.e., 75%), based on widely adopted benchmarks. We encourage reporting heterogeneity in the forms of I and the estimated variance components (e.g., τ ) as standard practice. These statistics provide vital insights in to the degree to which effect sizes vary, and provide the statistical support for the exploration of predictors of effect-size magnitude. Along with standard meta-regression techniques that fit moderator variables, multi-level models now allow partitioning of heterogeneity among correlated (e.g., phylogenetic) structures that exist within data.

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“…We extracted data from each study using WebPlotDigitizer (Rohatgi, ), a free software program that has high interrater reliability and validity and has been used for data extraction in other systematic reviews and meta‐analyses (Drevon, Fursa, & Malcolm, , Rutkowska, Dubiec, & Nakagawa, ; Wagner et al, ). The figures from each study were converted into image files (JPEG) for each treatment evaluation.…”

Section: Methodsmentioning

confidence: 99%

Efficacy of functional analysis for informing behavioral treatment of inappropriate mealtime behavior: A systematic review and meta‐analysis

Saini

Jessel

Iannaccone

et al. 2019

Behavioral Interventions

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Children diagnosed with a feeding disorder often exhibit inappropriate mealtime behavior such as throwing or swiping food, which can exacerbate feeding difficulties during treatment. We conducted a meta-analysis of 86 behavioral treatments for inappropriate mealtime behavior from 23 studies to assess the extent to which treatments based on a pretreatment functional analysis were more efficacious than those treatments not based on a functional analysis. Procedural escape extinction and attention extinction for inappropriate mealtime behavior, as well as differential reinforcement for food acceptance or consumption, represented the most common treatments independent of whether a functional analysis was conducted. No difference was detected between treatments that were and were not based on a functional analysis, and mean effect size across measures was identical (79%). The requirement of a pretreatment functional analysis for inappropriate mealtime behavior is equivocal given that standard care often includes efficacious treatment components that are not informed by a functional analysis. KEYWORDS feeding disorders, food refusal, functional analysis, inappropriate mealtime behavior, meta-analysis

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All eggs are made equal: meta‐analysis of egg sexual size dimorphism in birds

Cited by 20 publications

References 70 publications

Causes and consequences of variation in offspring body mass: meta‐analyses in birds and mammals

Causes and consequences of variation in offspring body mass: meta‐analyses in birds and mammals

Heterogeneity in ecological and evolutionary meta‐analyses: its magnitude and implications

Efficacy of functional analysis for informing behavioral treatment of inappropriate mealtime behavior: A systematic review and meta‐analysis

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