Meta-analysis shows no consistent evidence for senescence in ejaculate traits across animals

Male reproductive traits such as ejaculate size and quality, are expected to decline with advancing age due to senescence. It is however unclear whether this expectation is upheld across taxa. We perform a meta-analysis on 379 studies, to quantify the effects of advancing male age on ejaculate traits across 157 species of non-human animals. Contrary to predictions, we find no consistent pattern of age-dependent changes in ejaculate traits. This result partly reflects methodological limitations, such as studies sampling a low proportion of adult lifespan, or the inability of meta-analytical approaches to document non-linear ageing trajectories of ejaculate traits; which could potentially lead to an underestimation of senescence. Yet, we find taxon-specific differences in patterns of ejaculate senescence. For instance, older males produce less motile and slower sperm in ray-finned fishes, but larger ejaculates in insects, compared to younger males. Notably, lab rodents show senescence in most ejaculate traits measured. Our study challenges the notion of universal reproductive senescence, highlighting the need for controlled methodologies and a more nuanced understanding of reproductive senescence, cognisant of taxon-specific biology, experimental design, selection pressures, and life-history.

Supplementary Fig. 1: PRISMA diagram describing the search results in di erent search engines and the di erent steps of selecting articles for inclusion in the meta-analysis.Depicted are the number of studies excluded at each stage and then those extracted, screened, and included in the meta-analysis.

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Supplementary Fig. 12: A. E ect of male's 'control' over ejaculation on advancing male age.See Supplementary section 7 for definitions.B. E ect of advancing male age on ejaculates for each type of ejaculate collection method.The size of each data point represents the precision of the e ect size (1/SE).The

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Supplementary Fig. 15: A. E ect of advancing male age on ejaculates for studies with 'control' vs 'manipulated' males (see Supplementary section 9 for definitions), B. E ects of advancing male age on ejaculates for each type of manipulation/treatment including manipulated males only.The size of each data point represents the precision of the e ect size (1/SE).The X axis represents values of e ect sizes as Fisher's z-transformed correlation coe cient (Zr), while the Y axis shows the density distribution of e ect sizes.

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Supplementary Fig. 16: A. E ect of advancing male age on the type of fitness trait measured in unmanipulated males.B. E ects of advancing male age on reproductive output and on ejaculates from studies which measure both traits.See Supplementary section 9 for definitions.The X axis represents values of e ect sizes as Fisher's z-transformed correlation coe cient (Zr), while the Y axis shows the density distribution of e ect sizes.The position of the overall e ect is shown by the dark circle, with negative values depicting senescence in ejaculate traits and positive values showing improvement in ejaculate traits with advancing male age.Bold error bars (95% C.I) show whether the overall e ect size is significantly di erent from zero (i.e.not overlapping zero), while light error bars show the 95% prediction interval (P.I.) of e ect sizes.Sample sizes reported as: k = number of e ect sizes (in brackets: number of studies).Supplementary Fig. 20: The overall effect of advancing male age on ejaculates for studies with >10% of lifespan sampled Study Aim Proportion of lifespan sampled by study 23 Supplementary Fig. 23: Means and 95% CI of lifespan sampled for studies that explicitly test for senescence (Yes; i.e. -studies that used the words -ageing, aging, senescence, senescent, or senescing in their abstracts or titles and determined to be interested in senescence) vs studies that do not explicitly test for senescence (No).Each point refers to the average lifespan sampled from a study.Supplementary Fig. 24: E ect of method used to calculate e ect sizes.E ect sizes were calculated from statistical tests (Test stat), standardized mean di erence (SMD -when only two age groups were available) or through a simulation (when more than two age groups were available).The size of each data point represents the precision of the e ect size (1/SE).The X axis represents values of e ect sizes as Fisher's z-transformed correlation coe cient (Zr), while the Y axis shows the density distribution of e ect sizes.The position of the overall e ect is shown by the dark circle, with negative values depicting senescence in ejaculate traits and positive values showing improvement in ejaculate traits with advancing male age.Bold error bars (95% C.I) show whether the overall e ect size is significantly di erent from zero (i.e.not overlapping zero), while light error bars show the 95% prediction interval (P.I.) of e ect sizes.Sample sizes reported as: k = number of e ect sizes (in brackets: number of studies).

Supplementary notes 1: Search string
We first conducted a scoping search on Google Scholar.Our scoping search was done using the keywords "male age sperm -human", and we used the first 48 papers (i.e.all papers from the first 5 pages out of 11800 pages of the search) to build a word cloud to discern the most common words used in these studies.We used the most commonly occurring relevant words from this word cloud to create keywords for our search string.
The For all studies, we collected data on ejaculate traits as reported by the original paper.When a study reported data for multiple traits, data on all traits were collected.Although, when a study reported data on a whole trait (e.g. % of total motile sperm; % sperm with morphological defects) as well as sub traits (e.g. % progressively motile sperm, % sperm with mid-piece defects), only data from the whole trait was recorded.Due to differences in terminology when describing similar traits between different studies, we created a broad category to describe different types of traits.The categorization of these traits is described below.

Ejaculate traits
In

Multiplier and signs
If an increase in a trait signified a deleterious effect with increasing age, for example, an increase in sperm abnormal morphology, or sperm DNA damage, we assigned it a multiplier of "-1", whereas if increase in a trait suggested improvement with age, we assigned it a positive multiplier, i.e. "+1".Similarly, when a test statistic was reported (e.g.R sq., correlation coefficient.F values from ANOVA), where older males had worse sperm or ejaculates than younger males, we assigned it a negative multiplier of "-1".Conversely, if older males had better sperm or ejaculates than younger males, we assigned it a multiplier of "+1".Thus, for all the effect sizes in our models, a negative sign indicated reproductive senescence with increasing age, while a positive sign indicated reproductive improvement with increasing age.

Comparing calculation methods
To ensure that the three different effect size calculation methods did not affect the overall outcome in our meta-analysis, we compared the meta-analytical mean obtained from each method (i.e.SMD, simulation, and test-statistics).These did not differ from each other (see Supplementary Fig. 24), hence we analysed effect sizes calculated from SMD, simulation, and test-statistics together in subsequent models.

1 kSupplementary Fig. 3 :. 4 :
E ect of male age on ejaculates for each class.The size of each data point represents the precision of the e ect size (1/SE).The X axis represents values of e ect sizes as Fisher's z-transformed correlation coe cient (Zr), while the Y axis shows the density distribution of e ect sizes.The position of the overall e ect is shown by the dark circle, with negative values depicting senescence in ejaculate traits and positive values showing improvement in ejaculate traits with advancing male age.Bold error bars (95% C.I) show whether the overall e ect size is significantly di erent from zero (i.e.not overlapping zero), while light error bars show the 95% prediction interval (P.I.) of e ect sizes.Sample sizes reported as: k = number of e ect sizes (in brackets: number of studies).E ect of advancing male age on various ejaculate traits for A. Fish, B. Birds, C. Mammals.The size of each data point represents the precision of the e ect size (1/SE).The X axis represents values of e ect sizes as Fisher's z-transformed correlation coe cient (Zr), while the Y axis shows the density distribution of e ect sizes.The position of the overall e ect is shown by the dark circle, with negative values depicting senescence in ejaculate traits and positive values showing improvement in ejaculate traits with advancing male age.Bold error bars (95% C.I) show whether the overall e ect size is significantly di erent from zero (i.e.not overlapping zero), while light error bars show the 95% prediction interval (P.I.) of e ect sizes.Sample sizes reported as: k = number of e ect sizes (in brackets: number of studies).

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Relationship between gonadosomatic index (GSI) and e ect sizes for ejaculate senescence.Grey lines indicate 95% C.I. E ects of standardised male age (X axis) on standardised ejaculate trait values (Y axis).These are separately shown for % morphologically normal sperm, % motile sperm, and % viable sperm).Standardised male age was calculated as the proportion of maximum adult lifespan represented by the specific age class.Standardised trait value was calculated as percentage of morphologically normal sperm (N= 85 studies, k= 153 e ect sizes), percentage of motile sperm (N= 137 studies, k= 294 e ect sizes), or percentage of viable sperm (N= 81 studies, k= 193 e ect sizes).Shaded lines indicate 95% C.I. Medians (50%) and interquartile ranges (5%, 25%, 75%, 95%) of proportion of maximum adult lifespan sampled for A. Di erent population types, B. Four most common species in our dataset, and C. Di erent animal classes (note that animal classes with less than 25 e ect sizes were grouped together in 'Other').Each point depicts the average lifespan sampled from a study.Relationship between the youngest and oldest age sampled (as proportion of adult lifespan sampled) for each study (n = 362).Colours indicate the proportion of maximum adult lifespan sampled k = 1774(362) Relationship between the youngest age sampled (as proportion of maximum lifespan sampled) and e ect sizes for ejaculate senescence k = 1774(362) Relationship between the oldest age sampled (as proportion of maximum lifespan sampled) and e ect sizes for ejaculate senescence k = 1167(256) k = 85(20) k = 108(52) k = 620(164) k = 457(71) k = 494(73) k = 29(4)

Supplementary Fig. 14 :
X axis represents values of e ect sizes as Fisher's z-transformed correlation coe cient (Zr), while the Y axis shows the density distribution of e ect sizes.The position of the overall e ect is shown by the dark circle, with negative values depicting senescence in ejaculate traits and positive values showing improvement in ejaculate traits with advancing male age.Bold error bars (95% C.I) show whether the overall e ect size is significantly di erent from zero (i.e.not overlapping zero), while light error bars show the 95% prediction interval (P.I.) of e ect sizes.Sample sizes reported as: k = number of e ect sizes (in brackets: number of studies).k= 73(19) k = 129(37) k = 793(212) Fig.13: E ect of advancing male age on ejaculate traits for di erent types of population.The size of each data point represents the precision of the e ect size (1/SE).The X axis represents values of e ect sizes as Fisher's z-transformed correlation coe cient (Zr), while the Y axis shows the density distribution of e ect sizes.The position of the overall e ect is shown by the dark circle, with negative values depicting senescence in ejaculate traits and positive values showing improvement in ejaculate traits with advancing male age.Bold error bars (95% C.I) show whether the overall e ect size is significantly di erent from zero (i.e.not overlapping zero), while light error bars show the 95% prediction interval (P.I.) of e ect sizes.Sample sizes reported as: k = number of e ect sizes (in brackets: number of studies).E ect of advancing male age on ejaculates for studies with longitudinal vs crosssectional sampling on males' ejaculates.The size of each data point represents the precision of the e ect size (1/SE).The X axis represents values of e ect sizes as Fisher's z-transformed correlation coe cient (Zr), while the Y axis shows the density distribution of e ect sizes.The position of the overall e ect is shown by the dark circle, with negative values depicting senescence in ejaculate traits and positive values showing improvement in ejaculate traits with advancing male age.Bold error bars (95% C.I) show whether the overall e ect size is significantly di erent from zero (i.e.not overlapping zero), while light error bars show the 95% prediction interval (P.I.) of e ect sizes.Sample sizes reported as: k = number of e ect sizes (in brackets: number of studies).

Supplementary Fig. 17 :. 18 :
Funnel plot of the precision (1/SE) and the residual e ect (Observed outcome) from the null model to explore the existence of outliers in the dataset.Relationship between A. Standard error and e ect size estimates (Zr), and B. Year of publication and e ect size estimates (Zr).The points are scaled according to the inverse of their variance, so that larger points are given greater weight in the model and represent more reliable estimates.Shaded lines indicate 95% C.I. Supplementary Fig.19: Results of a step function selection model based on several cut-points for a model without any moderators.
table below shows the most frequent words from our scoping search collected from 48 relevant abstracts generated through a word cloud.Words used in our search string are highlighted in bold and italics.The selection of words was made such that they were not specific to a single species, nor biologically broad.AB= (male AND (age OR ageing OR senesc* OR aging OR old OR young ) AND ( sperm OR ejaculate OR semen ) NOT ( human OR men) ) OR TI= (male AND (age OR ageing OR senesc* OR aging OR old OR young ) AND ( sperm OR ejaculate OR semen ) NOT ( human OR men) )" Where n1 and n2 are sample sizes of the younger and older age groups respectively 5. From z-score to r  =  √ Where N is the sample size of unique number of males 6.For Converting T from Seigel's T test, and converting P values from Mann Whitney U test, to r, the Campbell Collaboration website was used (https://www.campbellcollaboration.org/researchresources/effect-size-calculator.html) 7.For converting R squared and adjusted R squared values to r  = √ 2 8.For converting Chisq.values from Chisq.test with one degree of freedom, to r