Per capita sperm metabolism is density dependent

ABSTRACT From bacteria to metazoans, higher density populations have lower per capita metabolic rates than lower density populations. The negative covariance between population density and metabolic rate is thought to represent a form of adaptive metabolic plasticity. A relationship between density and metabolism was actually first noted 100 years ago, and was focused on spermatozoa; even then, it was postulated that adaptive plasticity drove this pattern. Since then, contemporary studies of sperm metabolism specifically assume that sperm concentration has no effect on metabolism and that sperm metabolic rates show no adaptive plasticity. We did a systematic review to estimate the relationship between sperm aerobic metabolism and sperm concentration, for 198 estimates spanning 49 species, from protostomes to humans from 88 studies. We found strong evidence that per capita metabolic rates are concentration dependent: both within and among species, sperm have lower metabolisms in dense ejaculates, but increase their metabolism when diluted. On average, a 10-fold decrease in sperm concentration increased per capita metabolic rate by 35%. Metabolic plasticity in sperm appears to be an adaptive response, whereby sperm maximize their chances of encountering eggs.

cooled state.Diluent type was categorized as either an activator (i.e., caused sperm to become active/motile or undergo capacitation) or extender (i.e., keep sperm inactive to extend longevity).
We followed a traditional meta-analytic approach to help build our database but used comparative analyses to test our hypothesis.We used this 'hybrid' approach because we were interested in estimating the biological scaling relationship between sperm concentration and metabolism.It is not possible to estimate the effect sizes and then analyse their scaling because the response variable is partly biological and partly statistical.Traditional metaanalyses calculate formal error and effect size for each study.We cannot scale our data by their error because doing so would remove the quantitative relationship that we are interested inhow metabolism covaries with density.We have included an analysis that uses log response ratio to provide an effect size index (in-text).The studies within our dataset have sample sizes that range from 2 to 176 (mostly between 4-6 replicates).We re-ran our analyses with studies that had 4 replicates or more and found no qualitative difference in our results to those that included the entire dataset (in-text).

Deviations from registration
We followed our original plans and procedures and did not deviate from them.

Description 1
Studies were included if they presented sperm metabolism as oxygen consumed over time (i.e., l O 2 sperm concentration -1 h -1 ) and could be converted into a common unit for comparison.If studies used other units that could not be readily converted into oxygen consumption units, they were excluded from the dataset.

2
Studies that measure sperm oxygen consumption under control conditions were included in the dataset.Studies that added a metabolic uncoupler or inhibitor and did not report a control, were excluded from the dataset.

3
Studies that reported the actual sperm density (i.e., density that sperm was diluted to for measuring metabolism) where included in the dataset.Studies that did not report the actual sperm density and only reported a 'standardized' sperm density (see Materials and Methods: Misestimation) were excluded from the dataset.If studies reported the number of sperm per chamber volume along with the chamber volume, those studies were included in the dataset.

4
Studies that reported the ambient temperature that sperm metabolism was measured at, were included in the dataset.If the study manipulated temperature (i.e., used temperature as a treatment), only the metabolic estimate for the control temperature was used.

5
The data needs to be accessible (i.e., table, in-text or figure) and easy to extract.
Summary statistics (mean, standard deviation, standard error) need to be provided or easily calculated from the information reported.

6
Methods need to be clear and transparent.Sperm handling methods (fresh, frozen, cooled), extraction methods (ejaculated or extracted) and diluent used (seawater, Ringers solution, etc), all need to be reported.
Table S4.Oxygen Saturation Data.This table contains information for oxygen saturation data for species in our dataset which reported chamber volume, temperature and duration over which sperm oxygen consumption was measured.If the study did not report one of these factors, they were omitted from this table.VO 2 (ml O 2 conc -1 h -1 ) = oxygen consumption rate, VO2 Conc = sperm concentration (sperm ml -1 ), Incubation (hours) = time over which VO 2 was taken, chamber volume (L), temperature (ºC), solubility (ml O 2 L -1 ) (Cameron 1986)

Fig. S1 .
Fig. S1.PRIMSA flow chart.Summarizing the search methods, number of studies excluded and reasons for exclusions.

Fig. S2 .
Fig. S2.Density-dependent Metabolism and Fertilization Mode.Plot shows the relationship between log 10 ejaculate-level metabolic rate (l O 2 h -1 ) and log 10 sperm concentration.Fitted lines represent line of best fit based on a linear mixed-effects model using all the data in the dataset.Each point represents an observation from a single species for 49 species.Colours indicate different fertilization modes (Internal [Red; N = 126] and External [Blue; N = 72]).
Journal of Experimental Biology: doi:10.1242/jeb.246674:Supplementary information Journal of Experimental Biology • Supplementary information