Shared ancestry, sexual size dimorphism, and reproductive strategies jointly explain sex differences in adult lifespan in insects      

Shared ancestry, sexual size dimorphism, and reproductive strategies jointly explain sex differences in adult lifespan in insects | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 8 April 2026 V3 Latest version Share on Shared ancestry, sexual size dimorphism, and reproductive strategies jointly explain sex differences in adult lifespan in insects Authors : Barbora Žabová , Michal Knapp , Ants Kaasik , and Tiit Teder 0000-0001-6587-9325 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.175594177.76103117/v3 827 views 322 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Sex differences in lifespan provide a valuable framework for understanding lifespan evolution more broadly. Although such differences are widespread across animals, research on their evolutionary drivers remains strongly biased toward vertebrates. Comparative studies have substantially advanced knowledge of the extent and determinants of sex differences in lifespan in vertebrates, yet comparable research in invertebrates remains scarce and taxonomically limited, despite the wealth of available species-level data. Here, we present a broad-scale comparative analysis of sex differences in adult lifespan (SDL) in insects, using literature-derived data on 395 species spanning 17 orders. Across this dataset, female adults outlived males in 65% of species, and their median lifespan was 9% longer than that of males. Mean adult lifespan was consistently female-biased across taxonomic and functional groups, although the magnitude of this bias varied considerably. Phylogeny explained a relatively modest 28% of the variation in SDL, with qualitatively contrasting patterns of SDL occurring within most orders, and even among congeneric species. SDL was positively, albeit weakly, associated with sexual size dimorphism. Lifespan differences between sexes were generally more female-biased in functional groups in which extended lifespan is expected to more strongly enhance female reproductive success, either because of time-consuming resource acquisition for egg production (e.g., predators), or prolonged search for suitable oviposition substrates (e.g., parasitoids). Overall, our findings indicate that shared ancestry, sexual size dimorphism, and sex-specific reproductive strategies each contribute to variation in sex differences in adult lifespan, without any single factor clearly predominating. Introduction Lifespan, as a fundamental aspect of an organism’s life-history strategy, is one of the most thoroughly studied life-history traits, with broad implications for evolutionary biology, ecology, and demography. Research on a few model organisms, such as Mus , Drosophila and Caenorhabditis , has greatly advanced our understanding of genetic, cellular and physiological mechanisms that govern aging and lifespan in animals (1–4). At the same time, evidence accumulated from numerous single-species studies conducted in diverse contexts shows that the genetically and physiologically determined potential for longevity (hereafter intrinsic lifespan), varies widely among species (5–8), as well as within species, including among populations (9) and between sexes (10–12). Extending the scope of lifespan studies to a broader range of species by exploiting explicitly comparative, multispecies approaches is therefore essential for achieving conceptual progress in understanding lifespan evolution (4, 8, 13, 14). It has been known since Aristotle that larger species tend to live longer than smaller ones (15). This pattern is supported by comparative analyses of lifespan across both vertebrates and invertebrates (6, 16–18). This broad cross-species relationship between body size and lifespan has traditionally been attributed to metabolic scaling: smaller species typically exhibit higher mass-specific metabolic rates, which are thought to accelerate physiological wear and shorten lifespan (19). Despite the overall scaling relationship, lifespan varies widely among species of similar size (e.g., 20, 21). Such variations are often interpreted as adaptive responses to selection pressures acting on survival and reproductive schedules, shaped by ecological differences among species (6). For example, high extrinsic mortality is expected to favor earlier reproduction and reduced investment in somatic maintenance, resulting in faster senescence and shorter lifespans. In support of this view, several ecological traits known to influence extrinsic mortality have been shown to be associated with interspecific differences in lifespan in birds and mammals (6). Sex differences in lifespan provide a valuable complementary framework for understanding how ecologically driven selection pressures may modify physiologically based lifespan patterns. If the well-established relationship between body size and lifespan among species is primarily driven by physiological mechanisms, the same causal mechanism behind it might be expected to operate within species as well: all else being equal, the larger sex would be expected to live longer than the smaller one. However, even though conspecific males and females share nearly identical genomes and typically develop in the same environment, sexes often differ in their relative investment in reproduction and behavioral patterns (22). These differences can result in sex-specific selection pressures on life-history traits, leading to divergent evolutionary optima (23). Accordingly, deviations from size-predicted lifespan within species may reflect sex-specific optimization of lifespan (24, 25). Insects are particularly well-suited for disentangling the effects of body size and sex-specific life-history optimization on lifespan due to their extensive variation in sexual size dimorphism (SSD) (26, 27) and remarkable diversity of reproductive strategies along multiple axes. To illustrate this with a few examples, female insects show considerable variation in egg production strategies, ranging from capital-breeding species that primarily rely on resources accumulated during the juvenile stage to income breeders that can substantially increase their reproductive output through resources acquired during adulthood (28). High among-species variation in oviposition behavior provides another illustrative example: while females of some species deposit eggs rather indiscriminately, others, such as many parasitoids, engage in highly selective egg-laying that involves time-consuming and energetically costly location and assessment of suitable hosts (29). Such differences in reproductive strategies are likely to generate variation among species in the selection pressures acting on sex-specific lifespan (30). Furthermore, reproductive behaviors often influence sex-specific patterns of extrinsic mortality, which can further shape the evolution of lifespan differences between males and females (25). The clear separation between juvenile and adult life stages by metamorphosis provides another distinct advantage for lifespan research in insects. It allows for the independent examination of factors contributing to the length of the growing (juvenile development time) and reproductive (adult lifespan) phases. This contrasts with vertebrates, in which somatic growth and reproductive activity often substantially overlap. While several comparative studies have addressed sex differences in juvenile development time and their underlying determinants in insects (31–33), comparable research focusing on sex differences in adult lifespan remains scarce (4). In this study, we synthesize available data on sex differences in adult lifespan (hereafter SDL) across insects. Although numerous empirical case studies, conducted in a wide range of contexts, have reported male and female longevity for a wide range of species, no study has systematically integrated these data to characterize patterns of SDL across the insect clade as a whole. We further assess the evolutionary conservatism of SDL by examining its phylogenetic signal. As a next step, we examine the variation of SDL across taxonomic and functional groups. We predict more female-biased SDL in groups in which female reproduction relies primarily on adult-derived resources and where oviposition entails a time-consuming search and assessment of suitable substrates. Finally, we investigate the extent to which among-species variation in SDL is associated with sexual size dimorphism (hereafter SSD). A strong association between SSD and SDL would be interpreted as evidence that sex differences in lifespan are primarily shaped by size-dependent physiological factors. Results We assembled data on sex differences in adult lifespan for 395 insect species representing 17 orders and 119 families (Figure 1; SI Dataset S1). The meta-analytically weighted, phylogeny-adjusted mean effect size for sex differences in adult lifespan was significantly positive, indicating a general tendency for females to outlive males across species (mean SDL = 0.14; SE = 0.045; t = 3.09; df= 309; p = 0.002; Figure 2; SI Table S1 for detailed R model outputs). This result was robust to the inclusion of four outliers (see Statistical Analysis ) and exclusion of studies in which adults were not provided with food and/or mating opportunities (SI Tables S2–S4). Consistently, species with female-biased adult lifespan were more common in our dataset (257 species; 65.1%) than those with male-biased lifespan (138 species; 34.9%, includes a few species with equal sex-specific lifespans) (Figure 1; SI Dataset S1) and females had a median lifespan approximately 9% longer than that of conspecific males. Mean meta-analytic SDL’s estimated separately for hemi- and holometabolous insects were both positive; the estimate for hemimetabolous insects was statistically significant, whereas that for holometabolous insects was marginally non-significant (Figure 3; SI Table S5). Consistently, order-specific mean effect sizes for all 17 orders were also uniformly positive, indicating that there is a general tendency toward female-biased adult lifespan across taxonomic clades (Figure 2; SI Table S6). Despite these general tendencies, nearly all orders included a considerable proportion of species exhibiting male-biased adult lifespan (Figures 1, 2). Qualitative differences in SDL could be evident even among congeneric species examined in the same study (e.g., 34; SI Dataset S1). Taken together, these patterns are consistent with the relatively low phylogenetic signal observed, with only 28% of the total variance attributable to phylogeny (Figure 1). The magnitude of female bias in adult lifespan substantially varied among functional groups (Figures 4, 5; SI Tables S7, S8). In predatory species, adult females lived significantly longer than males, irrespective of whether adults (Figure 4) or larvae (Figure 5) (or, often, both) were predatory. A strong female bias in SDL was also observed in parasitoid species, where females outlived males in more than 80% of cases (Figure 5). SDL was also predominantly female-biased in species with non-feeding adults (Figure 4). In contrast, herbivorous species (Figures 4, 5) and nectarivorous species (Figure 4) showed no consistent tendency toward female-biased SDL. Across species, SDL was positively associated with SSD (estimate = 0.15, SE = 0.038, t = 4.04, df = 264, p < 0.0001; Figure 6; SI Table S9). Consistently, in species with female-biased SSD, female lifespan typically exceeded that of males (64.8%), whereas the opposite pattern was prevailing in species with male-biased SSD (73.1%) (Figure 6). Despite this overall trend, SSD accounted for a relatively small portion of the variation in SDL, as evidenced by the extensive scatter in the data points and a relatively low marginal R ² value of 0.089. Moreover, the relationship between SDL and SSD showed considerable heterogeneity among insect orders (SI Figure S1), though none of the order-level associations were statistically significant (SI Table S10). Discussion Empirical studies have documented sex-specific patterns of adult lifespan for a multitude of insect species across a wide range of applied, ecological and evolutionary contexts, but a broad-scale synthesis of sex differences in adult lifespan (SDL) across the insect clade has been lacking. We addressed this gap by conducting a phylogenetically controlled comparative analysis of SDL across 395 species spanning 17 insect orders and 119 families. Overall, our analysis revealed a tendency for females to outlive males across species (Figure 2): they were the longer-lived sex in 65.1% of species, with a median lifespan approximately 9% greater than that of males. Mean SDL was consistently female-biased across all insect orders, although the magnitude of this bias varied substantially among orders. Our analyses indicate that common ancestry, sex differences in body size, as well as species’ ecological attributes each contribute to variation in SDL. Despite the overall female bias in adult lifespan, substantial heterogeneity in SDL was evident across and within clades. For example, in Hemiptera and Lepidoptera, female- and male-biased SDL occurred at similar frequencies, whereas in some other orders, such as Hymenoptera and Odonata, females were the longer-lived sex in most species (Figures 1, 2). Variation was also apparent at finer taxonomic levels, with even congeneric species in some cases differing in the direction of SDL (e.g., Drosophila ; Figure 1). Consistent with this pattern, the phylogenetic signal in SDL was rather weak (0.28), indicating high evolutionary lability. Together, these findings suggest that although shared ancestry contributes to variation in SDL, sex differences in adult lifespan are only loosely constrained by phylogenetic relatedness. Notably, the low phylogenetic signal observed for SDL contrasts sharply with the strong phylogenetic conservatism reported for traits such as body size in insects (e.g., 35). Across species, SDL was positively associated with sexual size dimorphism (SSD), with the larger sex tending to have a longer adult lifespan (Figure 6). This pattern is consistent with findings from comparative studies showing that larger-bodied species tend to live longer than smaller ones in some groups of insects ( Drosophila : 14; geometrid moths: 36). Nevertheless, despite the pronounced interspecific variation in SSD, the overall relationship between SSD and SDL in our dataset was rather weak, with SSD accounting for 8.9% of the total variation in SDL. Moreover, the association between SSD and SDL showed some qualitative inconsistency across taxonomic groups (SI Figure S1). A similarly weak association between SSD and SDL has been reported in mammals; however, in that group the relationship tends to be negative (8). Our data also provide evidence that sex-specific reproductive strategies likely contribute to cross-species variation in SDL. In particular, selection should favor longer lifespan in the sex whose reproductive success benefits more from extended survival (30, 37). In most insects, male fitness depends largely on their ability to locate and mate with receptive females. As a result, adult lifespan of males is expected to evolve primarily in response to the duration and timing of mating opportunities, which are typically dictated by female reproductive schedules. By contrast, female fitness, and by extension, female lifespan, can be expected to be shaped by a more diverse suite of factors, including the rate of oogenesis, the timing and rate of egg laying, and the availability and specificity of oviposition sites. Although a comprehensive analysis of SDL in relation to sex-specific reproductive strategies in insects must await the accumulation of detailed species-level data, a few broad-brush insights can be drawn based on the observed patterns, primarily with respect to female reproductive strategies. One scenario where females likely benefit from a longer adult life, compared to males, is when laying eggs involves a time-consuming search for suitable oviposition substrates, as is a common situation in parasitoids. This extended search effort increases the time required to convert mature eggs into realized offspring, thereby favoring increased female survival to maximize their lifetime reproductive success. Consistent with this expectation, female bias in SDL was particularly pronounced among parasitoids, in which female adult lifespans exceeded those of males in over 80% of the species (Figure 5). Selection for extended female lifespan is also likely to depend on the time costs of acquiring resources for egg production, particularly in income-breeding species that rely on adult-derived resources (28). This reasoning may explain why female-biased SDL was more pronounced in predatory species than in nectar- or plant-feeding taxa (Figure 4). Because prey are typically dispersed and spatially unpredictable, predatory foraging generally entails greater time costs than exploiting more readily accessible resources, such as nectar or plant tissues (38). As a result, in predatory species, female reproductive success may be more strongly constrained by time, increasing the selective advantage of prolonged adult lifespan. In contrast, in nectarivores and herbivores, where resources are more readily acquired, the marginal fitness benefits of extended lifespan are likely to be smaller. A related prediction concerns differences between income and capital breeders. When reproduction depends on resources acquired during adulthood, extended lifespan can directly enhance fecundity in females. By contrast, in strict capital breeders, whose adults do not feed and whose reproduction and somatic maintenance thus rely entirely on reserves accumulated during the larval stage, females are expected to gain little additional fitness benefit from prolonged survival once their egg complement has been exhausted (39). This reasoning predicts stronger female bias in SDL in income breeders. However, our findings provide no clear support for this prediction: the proportions of species with female-biased SDL were similar in capital-breeding and income-breeding taxa (67% and 61%, respectively; Figure 4). Clarifying the mechanisms underlying this counterintuitive pattern will require more targeted research on sex-specific reproductive patterns in capital-breeding insects. Adult lifespan is a highly plastic trait that can also be shaped by a range of proximate factors, some affecting both sexes, while others acting in a sex-specific manner. Although it is virtually impossible to fully control the effects of environmentally induced plasticity in large-scale comparative analyses of lifespan, we took deliberate steps to minimize its influence when compiling our dataset. First, the adult lifespan of income breeders is strongly reduced under food deprivation (e.g., 40, 41), but often extended under moderate dietary restriction (42). To reduce confounding effects of nutritional stress, we explicitly prioritized data from studies (or experimental treatments within studies) in which adult insects were provided food ad libitum. This criterion was met by the vast majority of (income-breeding) species included in our final dataset. Second, adult lifespan can be substantially influenced by mating opportunities (43). While repeated matings can influence lifespan in both directions (44), the absence of any mating opportunities tends to prolong adult life in both males and females (45, 46). Accordingly, whenever this information was available, we gave preference to studies in which insects were given the opportunity to mate. Third, the availability of oviposition substrates, such as specific host plants for herbivores or host insects for parasitoids, is another major factor that can potentially affect adult lifespan at the proximate level (47, 48), with consequences largely limited to females. In most studies reporting this detail, appropriate oviposition substrates were provided to insects. Importantly, our main results were robust to the inclusion or exclusion of studies in which adults lacked food and/or mating opportunities. We therefore believe that such environmental variation introduced random noise rather than systematically caused bias in our findings and conclusions. Our study explicitly focused on intrinsic lifespan, i.e. genetically and physiologically determined potential for longevity. We therefore deliberately did not consider any field data, where adult lifespan can be significantly shortened by external mortality inflicted by various natural enemies (e.g., 49, 50), a factor whose influence on longevity is frequently sex-specific (51–53). Nevertheless, although most source studies aimed to approximate field conditions by providing food, mating opportunities, and oviposition substrates, laboratory environments still differ in important ways that may also influence intrinsically determined lifespan, and in turn, SDL. For example, ad libitum access to food resources may accurately represent a typical natural situation for generalist herbivores, but many other insects may need to invest substantial time and energy to locate suitable food sources in the wild. Similar meaningful differences exist between laboratory and natural environments in the context of egg laying. In the spatially confined conditions of the laboratory, the time and energy required to locate oviposition substrates are minimal. In contrast, for example, specialist herbivores searching for appropriate host plants or parasitoids seeking suitable host insects in natural settings often face substantial energetic and temporal costs. Therefore, while our results capture the intrinsic potential lifespan of each sex under controlled conditions, caution is warranted when extrapolating these findings to natural environments, as the ecological costs associated with foraging, mating, and oviposition in field settings may significantly alter lifespan and may also affect SDL. Conclusions Our study presents a broad-scale comparative analysis of sex differences in adult lifespan (SDL) across a diverse array of insect taxa. Overall, females tend to be the longer-lived sex across taxonomic and functional groups, yet the pattern varies substantially both among and within groups. Our findings indicate that shared ancestry, sexual size dimorphism and sex-specific reproductive strategies jointly shape sex differences in adult lifespan in insects, with no single factor emerging as strongly predominating. Future research integrating more detailed sex-specific ecological data and field-based lifespan estimates will be essential to advance our understanding of the evolutionary forces shaping adult lifespan and sex differences in this trait in natural environments. Materials and methods Data collection We aimed to collect data on sex differences in adult lifespan representing a taxonomically and ecologically broad range of insect species. Data were gathered from published case studies using two complementary approaches. The larger portion, roughly two-thirds of the data, was obtained through targeted searches in Google Scholar and Clarivate Web of Science (B.Ž. and T.T.) conducted in 2023 and 2025. Since lifespan data are often reported as secondary outcomes and may not be mentioned in titles or abstracts, Google Scholar’s full-text search capability was particularly useful for locating such data. Our search queries included combinations of four generic terms that were neutral with respect to the magnitude and direction of our focal variable (i.e., SDL): one of several synonyms for adult lifespan (‘longevity’, ‘life span’, ‘lifespan’), ‘males’, ‘females’, and ‘insect*’ (or the name of a specific insect order). The rest of the data was collected by one of the authors (T.T.) through systematic screening of the tables of contents of a broad list of journals in entomology, ecology, and evolutionary biology. This effort involved both a one-time retrospective screening (primarily targeting articles published prior to 2003) and ongoing screening for articles published thereafter (until 2025). The screening process included regularly examining journals' tables of contents and reviewing the full-text of papers whose titles indicated they might contain relevant data. As lifespan data are typically presented in tables and figures, their identification within articles was generally straightforward. Because studies reporting sex-specific lifespan estimates in insects vary widely in their contexts, aims, and terminology for adult lifespan, assembling a complete set of published information for the more speciose orders (e.g., Lepidoptera, Coleoptera, Hymenoptera, Diptera) was not considered feasible from the outset. Although extensive, our dataset still should be regarded as a representative sample rather than complete record of the available data for these taxonomic groups. For smaller and less-studied orders, our targeted searches likely allowed us to assemble most of the published information on sex-specific adult lifespan. Inevitably, taxonomic and functional groups are not evenly represented in our dataset, reflecting differences in research focus as well as the practical challenges inherent to studying particular taxa. Where reported, sex-specific data on adult (or pupal) body size were extracted from the same studies reporting adult lifespan. Additional sex-specific body size data were derived from several previously published syntheses (26, 33, 54, 55). Further body size data on specific species were obtained through targeted literature searches in Google Scholar using the species’ scientific name combined with relevant body mass-related terms (‘adult weight’, ‘adult mass’, ‘pupal weight’, ‘pupal mass’, ‘body size’). Data extraction and criteria for eligibility With the scope of the synthesis clearly defined, the eligibility of the identified studies was evaluated during the data collection process. The primary criterion for inclusion was that a study had to report mean values of both male and female adult lifespan of an insect species. Six studies presenting median values of lifespan were also accepted. Only laboratory-based data were considered, where major external sources of mortality, predators and parasitoids in particular, were explicitly excluded. From studies that included multiple treatments, lifespan data were derived from the treatment that most closely approximated optimal conditions (see also Discussion). Specifically, we prioritized treatments that ensured: 1) ad libitum access to water and food, 2) the opportunity to mate, 3) the availability of an oviposition substrate (e.g., host plant), 4) the highest food quality (defined as the treatment associated with the highest larval survival, shortest development time, or largest body size, depending on the data available), and 5) optimal temperature regime (assessed based on survival rates or conditions typical for the species’ biogeographic realm). We explicitly excluded data from stress treatments, such as exposure to chill coma, heat shock, or biological and artificial toxins. When data for a particular species were available from multiple studies, the same criteria were applied, with priority given to the dataset with the largest sample size when all other things were equal. While we generally did not impose any taxonomic restrictions on the insects included in this study, we did not consider those with complex caste systems, such as ants, social bees and wasps. Also, we did not include a few studies in which the species' lifespan included diapause. Volume-based measures (i.e., fresh or dry body mass) were the preferred metric for sex-specific body size, although linear measurements were also accepted when body mass data were unavailable. When body size and lifespan data were reported together, both were extracted from the same study and treatment. If size data came from a different study, we used data from treatments where the conditions for juvenile development were likely closest to optimal. The choice of treatment was guided primarily by measures of pre-adult survival (egg-to-adult, larval-pupal, or larval, depending on availability) or, when survival data were unavailable, by juvenile development time. Both metrics are commonly used indicators of developmental environment in insects, with higher survival and shorter development time generally reflecting more benign (laboratory) conditions (56, 57). Although SSD can show some population-level variation within species, it is typically limited relative to the variation observed among insect species (58). Graphically presented lifespan and body size data were extracted using WebPlotDigitizer 4.3 (59). Species were categorized into functional groups, where possible, based on the feeding ecology of their adult and larval stages. Deriving SDL and SSD values from collected data For each species, we calculated the natural logarithm of the ratio of mean female to mean male adult lifespan. This metric served as the effect size quantifying sex differences in adult lifespan (SDL) in our meta-analytic models. The resulting species-specific SDL values are symmetrically distributed around zero, with SDL = 0 indicating no sex difference in adult lifespan, and positive and negative SDL values indicating female-biased and male-biased lifespan, respectively. This choice of effect size permits direct calculation of the standard error of SDL when the standard errors of the sex-specific means are available (60), as was the case for most species in our dataset. SSD was quantified using the widely used algorithm of Lovich and Gibbons (61): [(size of the larger sex) / (size of the smaller sex)] – 1, with a positive sign assigned to the resulting values when females are larger and a negative sign when males are larger. Because body size was reported either as body mass (for most species) or as various linear measurements, we standardized all size data to ensure comparability of SSD estimates across species. When body mass was available, it was used directly in the calculations. When only linear measurements (e.g., body length, head width) were available, these were converted to mass equivalents prior to estimating SSD. In particular, when body length was provided, we used published taxon-specific allometric equations to estimate body mass. For other linear size measures lacking appropriate allometric relationships, we applied cube transformation to approximate mass under isometric scaling assumptions before calculating SSD. Statistical analysis To examine among-species variation in SDL, and the factors potentially explaining this variation, we employed multilevel mixed-effects meta-analytic models (62). In all models, we incorporated phylogenetic relationships by specifying a random effect based on a phylogenetic variance-covariance matrix (63). Since a comprehensive phylogenetic tree encompassing all insect species is currently unavailable, we inferred phylogenetic information from the Open Tree of Life database (64) using the R package rotl v. 3.1.0 (65). Phylogenetic information was directly available for most target species; however, for a small number of species, we substituted data from congeneric species. A phylogenetic correlation matrix was built using the R package ape v. 5.8.1 (66). We also included study-, species- and observation-level random effects to account for the hierarchical structure of the data and allow proper partitioning of variance (63). To estimate the overall phylogeny-adjusted SDL across species, we first fitted an intercept-only model. The degree of phylogenetic signal in the overall variance of SDL was quantified following the approach suggested by Cinar et al. (67). Furthermore, we fitted separate models in which insect order, development mode (hemi- vs. holometabolous), and ecological categories defined by larval and adult feeding ecology were each included as moderators in turn, thereby deriving meta-analytic, phylogeny-adjusted mean SDL estimates for each subgroup. We further tested whether SDL depends on species-specific sex differences in body size by fitting a model with SSD as a moderator. The adequacy of the fitted meta-analytic models was assessed by visual inspection of residual and random-effects distributions. Based on these diagnostics, a small number of species (n = 4) with exceptionally high female-biased SDL values were identified as outliers and excluded from the main analyses. We further examined profile likelihood plots of the random-effects parameters to identify potential convergence issues. For each meta-analytic model, we tested for residual heterogeneity, and estimated marginal R 2 for models with moderators (63). Finally, potential publication bias was assessed using an extension of Egger's regression test for multilevel meta-analytic models (e.g., 68). All meta-analytic procedures were performed in R version 4.5.1 (69) using the metafor package v. 4.8.0 (70). Meta-analytic figures were generated using the R package orchaRd v. 2.1.3 (71). Acknowledgements We sincerely thank all the authors of the empirical studies from which we obtained the data used in this research. This work was supported by the Estonian Research Council (grant no. PRG2618) and by the Internal Grant Agency of the Faculty of Environmental Sciences, Czech University of Life Sciences Prague (projects 2023B0024 and 2025B0026). References 1. Hulbert, A.J., Pamplona, R., Buffenstein, R. & Buttemer, W.A. (2007) Life and death: metabolic rate, membrane composition, and life span of animals. Physiological Reviews , 87, 1175–1213. 2. Kenyon, C.J. (2010) The genetics of ageing. Nature , 464, 504–512. 3. DiLoreto, R. & Murphy, C.T. (2015) The cell biology of aging. Molecular Biology of the Cell , 26, 4524–4531. 4. Promislow, D.E.L., Flatt, T. & Bonduriansky, R. (2022) The biology of aging in insects: from Drosophila to other insects and back. Annual Review of Entomology , 67, 83–103. 5. Ricklefs, R.E. (2010) Life-history connections to rates of aging in terrestrial vertebrates. Proceedings of the National Academy of Sciences of the United States of America , 107, 10314–10319. 6. Healy, K., Guillerme, T., Finlay, S., Kane, A., Kelly, S.B.A., McClean, D., Kelly, D.J., Donohue, I., Jackson, A.L. & Cooper, N. (2014) Ecology and mode-of-life explain lifespan variation in birds and mammals. Proceedings of the Royal Society B: Biological Sciences , 281, 20140298. 7. Rogell, B., Widegren, W., Hallsson, L.R., Berger, D., Björklund, M. & Maklakov, A.A. (2014) Sex-dependent evolution of life-history traits following adaptation to climate warming. Functional Ecology , 28, 469–478. 8. Lemaître, J.F., Ronget, V., Tidière, M., Allainé, D., Berger, V., Cohas, A., Colchero, F., Conde, D.A., Garratt, M., Liker, A., Marais, G.A.B., Scheuerlein, A., Szekely, T. & Gaillard, J.-M. (2020) Sex differences in adult lifespan and aging rates of mortality across wild mammals. Proceedings of the National Academy of Sciences of the United States of America , 117, 8546–8553. 9. Tayeh, A., Hufbauer, R.A., Estoup, A., Ravigné, V., Frachon, L. & Facon, B. (2015) Biological invasion and biological control select for different life histories. Nature Communications , 6, 7268. 10. Austad, S.N. & Fischer, K.E. (2016) Sex differences in lifespan. Cell Metabolism , 23, 1022–1033. 11. Griffin, R.M., Hayward, A.D., Bolund, E., Maklakov, A.A. & Lummaa, V. (2018) Sex differences in adult mortality rate mediated by early-life environmental conditions. Ecology Letters , 21, 235–242. 12. Bronikowski, A.M., Meisel, R.P., Biga, P.R., Walters, J.R., Mank, J.E., Larschan, E., Wilkinson, G.S., Valenzuela, N., Conard, A.M., de Magalhães, J.P., Duan, J., Elias, A.E., Gamble, T., Graze, R.M., Gribble, K.E., Kreiling, J.A. & Riddle, N.C. (2022) Sex-specific aging in animals: perspective and future directions. Aging Cell , 21, e13542. 13. Holmes, D.J. & Kristan, D.M. (2008) Comparative and alternative approaches and novel animal models for aging research: introduction to special issue. Age , 30, 63–73. 14. Macartney, E.L. & Bonduriansky, R. (2022) Does female resistance to mating select for live-fast-die-young strategies in males? A comparative analysis in the genus Drosophila . Journal of Evolutionary Biology , 35, 192–200. 15. Speakman, J.R. (2005) Correlations between physiology and lifespan – two widely ignored problems with comparative studies. Aging Cell , 4, 167–175. 16. Holm, S., Davis, R.B., Javoiš, J., Õunap, E., Kaasik, A., Molleman, F. & Tammaru, T. (2016) A comparative perspective on longevity: the effect of body size dominates over ecology in moths. Journal of Evolutionary Biology , 29, 2422–2435. 17. Bakewell, A.T., Davis, K.E., Freckleton, R.P., Isaac, N.J.B. & Mayhew, P.J. (2020) Comparing life histories across taxonomic groups in multiple dimensions: how mammal-like are insects? The American Naturalist , 195, 70–81. 18. Kuparinen, A., Yeung, E. & Hutchings, J.A. (2023) Correlation between body size and longevity: new analysis and data covering six taxonomic classes of vertebrates. Acta Oecologica , 119, 103917. 19. Lindstedt, S.L. & Calder, W.A. (1981) Body size, physiological time, and longevity of homeothermic animals. The Quarterly Review of Biology , 56, 1–16. 20. Munshi-South, J. & Wilkinson, G.S. (2010) Bats and birds: exceptional longevity despite high metabolic rates. Ageing Research Reviews , 9, 12–19. 21. Scharf, I., Feldman, A., Novosolov, M., Pincheira-Donoso, D., Das, I., Böhm, M., Uetz, P., Torres-Carvajal, O., Bauer, A., Roll, U. & Meiri, S. (2015) Late bloomers and baby boomers: ecological drivers of longevity in squamates and the tuatara. Global Ecology and Biogeography , 24, 396–405. 22. Somjee, U., Shankar, A. & Falk, J.J. 2022. Can sex-specific metabolic rates provide insight into patterns of metabolic scaling? Integrative and Comparative Biology, 62, 1460–1470. 23. Badyaev, A.V. (2002) Growing apart: an ontogenetic perspective on the evolution of sexual size dimorphism. Trends in Ecology and Evolution , 17, 369–378. 24. Carey, J.R. (2001) Insect biodemography. Annual Review of Entomology , 46, 79–110. 25. Maklakov, A.A. & Lummaa, V. (2013) Evolution of sex differences in lifespan and aging: causes and constraints. BioEssays , 35, 717–724. 26. Teder, T. & Tammaru, T. (2005) Sexual size dimorphism within species increases with body size in insects. Oikos , 108, 321–334. 27. Stillwell, R.C., Blanckenhorn, W.U., Teder, T., Davidowitz, G. & Fox, C.W. (2010) Sex differences in phenotypic plasticity affect variation in sexual size dimorphism in insects: from physiology to evolution. Annual Review of Entomology , 55, 227–245. 28. Tammaru, T. & Haukioja, E. (1996) Capital breeders and income breeders among Lepidoptera: consequences to population dynamics. Oikos , 77, 561–564. 29. Thompson, J.N. & Pellmyr, O. (1991) Evolution of oviposition behavior and host preference in Lepidoptera. Annual Review of Entomology , 36, 65–89. 30. Clutton-Brock, T.H. & Isvaran, K. (2007) Sex differences in ageing in natural populations of vertebrates. Proceedings of the Royal Society B: Biological Sciences , 274, 3097–3104. 31. Blanckenhorn, W.U., Dixon, A.F.G., Fairbairn, D.J., Foellmer, M.W., Gibert, P., van der Linde, K., Meier, R., Nylin, S., Pitnick, S., Schoff, C., Signorelli, M., Teder, T. & Wiklund, C. (2007a) Proximate causes of Rensch’s rule: does sexual size dimorphism in arthropods result from sex differences in development time? The American Naturalist , 169, 245–257. 32. Teder, T. (2014) Sexual size dimorphism requires a corresponding sex difference in development time: a meta-analysis in insects. Functional Ecology , 27, 479–486. 33. Teder, T., Kaasik, A., Taits, K. & Tammaru, T. (2021) Why do males emerge before females? Sexual size dimorphism drives sexual bimaturism in insects. Biological Reviews , 96, 2461–2475. 34. Wit, J., Loeschcke, V. & Kellermann, V. (2015) Life span variation in 13 Drosophila species: a comparative study on life span, environmental variables and stress resistance. Journal of Evolutionary Biology, 28, 1892–1900. 35. Seifert, C.L., Strutzenberger, P. & Fiedler, K. (2025) Larval diet type and voltinism are linked with adult body size in European Erebidae (Lepidoptera). Evolutionary Ecology, 39, 391–411. 36. Holm, S., Kaasik, A., Javoiš, J., Molleman, F., Õunap, E. & Tammaru, T. (2022) A comparative study on insect longevity: tropical moths do not differ from their temperate relatives. Evolutionary Ecology , 36, 251–262. 37. Bonduriansky, R., Maklakov, A., Zajitschek, F. & Brooks, R. (2008) Sexual selection, sexual conflict and the evolution of ageing and life span. Functional Ecology , 22, 443–453. 38. Hassell, M.P. & Southwood, T.R.E. (1978) Foraging strategies of insects. Annual Review of Ecology and Systematics, 9, 75–98. 39. Davis, R.B., Javoiš, J., Kaasik, A., Õunap, E. & Tammaru, T. (2016) An ordination of life histories using morphological proxies: capital vs. income breeding in insects. Ecology , 97, 2112–2124. 40. Blanckenhorn, W.U., Fanti, J. & Reim, C. (2007) Size-dependent energy reserves, energy utilization and longevity in the yellow dung fly. Physiological Entomology , 32, 372–381. 41. Straser, R.K. & Wilson, H. (2022) Food deprivation alters reproductive performance of biocontrol agent Hadronotus pennsylvanicus . Scientific Reports , 12, 7129. 42. Nakagawa, S., Lagisz, M., Hector, K.L. & Spencer, H.G. (2012) Comparative and meta-analytic insights into life extension via dietary restriction. Aging Cell , 11, 401–409. 43. Ridley, M. (1988) Mating frequency and fecundity in insects. Biological Reviews , 63, 509–549. 44. Arnqvist, G. & Nilsson, T. (2000) The evolution of polyandry: multiple mating and female fitness in insects. Animal Behaviour , 60, 145–164. 45. De Loof, A. (2011) Longevity and aging in insects: is reproduction costly; cheap; beneficial or irrelevant? A critical evaluation of the “trade-off” concept. Journal of Insect Physiology , 57, 1–11. 46. Scharf, I., Peter, F. & Martin, O.Y. (2013) Reproductive trade-offs and direct costs for males in arthropods. Evolutionary Biology , 40, 169–184. 47. Åsman, K. & Ekbom, B. (2006) Responses of ovipositing moths to host plant deprivation: life history aspects and implications for intercropping. Agricultural and Forest Entomology , 8, 213–219. 48. Harwood, J.F., Chen, K., Müller, H.-G., Wang, J.-L., Vargas, R.I. & Carey, J.R. (2013) Effects of diet and host access on fecundity and lifespan in two fruit fly species with different life-history patterns. Physiological Entomology , 38, 81–88. 49. Tanhuanpää, M., Ruohomäki, K. & Kaitaniemi, P. (2003) Influence of adult and egg predation on reproductive success of Epirrita autumnata (Lepidoptera: Geometridae). Oikos , 102, 263–272. 50. Sang, A. & Teder, T. (2011) Dragonflies cause spatial and temporal heterogeneity in habitat quality for butterflies. Insect Conservation and Diversity , 4, 257–264. 51. Jennings, D.T. & Houseweart, M.W. (1989) Sex-biased predation by web-spinning spiders (Araneae) on spruce budworm moths. Journal of Arachnology , 17, 179–194. 52. Acharya, L. (1995) Sex-biased predation on moths by insectivorous bats. Animal Behaviour , 49, 1461–1468. 53. Stefanescu, C., Pla-Narbona, C., Ubach, A., Jarrett, C., Renelies-Hamilton, J. & Colom, P. (2025) Predation risk in a migratory butterfly increases southward along a latitudinal gradient. Ecography , 2025, e07308. 54. Teder, T., Taits, K., Kaasik, A. & Tammaru, T. (2022) Limited sex differences in plastic responses suggest evolutionary conservatism of thermal reaction norms: a meta-analysis in insects. Evolution Letters , 6, 394–411. 55. Teder, T. & Kaasik, A. (2023) Early-life food stress hits females harder than males in insects: a meta-analysis of sex differences in environmental sensitivity. Ecology Letters , 26, 1419–1431. 56. Nylin, S. & Gotthard, K. (1998) Plasticity in life-history traits. Annual Review of Entomology , 43, 63–83. 57. Teder, T., Vellau, H. & Tammaru, T. (2014) Age and size at maturity: a quantitative review of diet-induced reaction norms in insects. Evolution , 68, 3217–3228. 58. Blanckenhorn, W.U., Meier, R. & Teder, T. (2007c) Rensch’s rule in insects: patterns among and within species. In Fairbairn, D.J., Blanckenhorn, W.U., Szekely, T., (eds) Sex, Size and Gender Roles: Evolutionary Studies of Sexual Size Dimorphism. New York: Oxford University Press, pp. 60–70. 59. Rohatgi, A. (2019) WebPlotDigitizer (Version 4.3). Available at: https://automeris.io/WebPlotDigitizer. 60. Hedges, L.V., Gurevitch, J. & Curtis, P.S. (1999) The meta-analysis of response ratios in experimental ecology. Ecology, 80, 1150–1156. 61. Lovich, J.E. & Gibbons, J.W. (1992) A review of techniques for quantifying sexual size dimorphism. Growth, Development, and Aging , 56, 269–281. 62. Koricheva, J., Gurevitch, J. & Mengersen, K. (Eds) (2013) Handbook of meta-analysis in ecology and evolution. Princeton, NJ: Princeton University Press. 63. Nakagawa, S., Noble, D.W.A., Senior, A.M. & Lagisz, M. (2017) Meta-evaluation of meta-analysis: ten appraisal questions for biologists. BMC Biology, 15, 18. 64. OpenTree of Life, Cranston, K.A., Redelings, B., Sanchez Reyes, L.L., Allman, J., McTavish, E.J. & Holder, M.T. (2019) Open Tree of Life Taxonomy (3.2). Zenodo . https://doi.org/10.5281/zenodo.3937751. 65. Michonneau, F., Brown, J.W. & Winter, D.J. (2016) Rotl: an R package to interact with the Open Tree of Life data. Methods in Ecology and Evolution , 7, 1476–1481. 66. Paradis, E. & Schliep, K. (2019) Ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics , 35, 526–528. 67. Cinar, O., Nakagawa, S., & Viechtbauer, W. (2021) Phylogenetic multilevel meta-analysis: A simulation study on the importance of modelling the phylogeny. Methods in Ecology and Evolution, 13, 383–395. 68. Fernandez-Castilla, B., Declercq, L., Jamshidi, L., Beretvas, S.N., Onghena P. & Van den Noortgate, W. (2021) Detecting selection bias in meta-analyses with multiple outcomes: A simulation study. The Journal of Experimental Education, 89, 125–144. 69. R Core Team (2025) R: A language and environment for statistical computing. Version 4.5.1. Vienna, Austria: R Foundation for Statistical Computing. 70. Viechtbauer, W. (2010) Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36, 1–48. 71. Nakagawa, S., Lagisz, M., O’Dea, R.E., Pottier, P., Rutkowska, J., Senior, A.M., Yang, Y. & Noble, D.W.A. (2023) orchaRd 2.0: An R package for visualising meta-analyses with orchard plots. Methods in Ecology and Evolution, 14, 2003–2010. Figures Figure 1. Distribution of male- and female-biased adult lifespan among the studied species. Species names shown in red indicate female-biased lifespan, whereas blue names indicate male-biased lifespan. The phylogenetic relationships of the included insect species were obtained from the Open Tree of Life database (OpenTree et al. 2019) using the R package rotl (Michonneau et al. 2016). Branch colours denote different insect orders. Phasmatodea was omitted from the figure due to unresolved phylogeny. This is a caption Figure 2. Sex differences in adult lifespan (SDL) within individual insect orders and across all insects. Darker points with whiskers represent the mean phylogeny-adjusted values of SDL (expressed as the natural logarithm of the ratio of mean female to mean male adult lifespan) and their 95% confidence intervals. Lighter points of the same tone denote species-level SDL values within each taxonomic group. SDL values are positive when females were longer-lived, negative when males were longer-lived, and zero when sexes did not differ in adult lifespan. Numbers following each order name indicate the total numbers of species analysed, with the number of studies given in parentheses. See SI Tables S1 and S6 for the corresponding R model output. Meta-analytic mean SDL values for taxonomic groups with five or less species available are not presented; however, in all cases they were positive, consistent with the pattern observed in other groups, indicating that females outlived males (meta-analytic means of these groups: Blattodea: 0.40, Dermaptera: 0.16, Ephemeroptera: 0.14, Mantodea: 0.62, Mecoptera: 0.39, Phasmatodea: 0.37, Plecoptera: 0.12, Thysanoptera: 0.55, Trichoptera: 0.49). This is a caption Figure 3. Sex differences in adult lifespan (SDL) in hemi- and holometabolous insects. See Figure 2 for detailed explanations, and SI Table S5 for the corresponding R model output. This is a caption Figure 4. Sex differences in adult lifespan (SDL) across functional groups defined by adult diet. See Figure 2 for detailed explanations, and SI Table S7 for the corresponding R model output. This is a caption Figure 5. Sex differences in adult lifespan (SDL) across functional groups defined by larval diet. See Figure 2 for detailed explanations, and SI Table S8 for the corresponding R model output. This is a caption Figure 6. Relationship between sex difference in adult lifespan (SDL) and sexual size dimorphism (SSD) across species. Each point represents a single species. Positive SDL and SSD values indicate larger trait values in females, while negative values correspond to larger trait values in males. A value of zero denotes no sex difference. The trendline and its 95% confidence interval were derived from a multilevel mixed-effects meta-analytic model (see Table S9 for the corresponding R model output). Information & Authors Information Version history V1 Version 1 23 August 2025 V2 Version 2 13 March 2026 V3 Version 3 08 April 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords body size life history longevity meta-analysis survival Authors Affiliations Barbora Žabová Czech University of Life Sciences Prague View all articles by this author Michal Knapp Czech University of Life Sciences Prague View all articles by this author Ants Kaasik University of Tartu View all articles by this author Tiit Teder 0000-0001-6587-9325 [email protected] University of Tartu View all articles by this author Funding Information Eesti Teadusagentuur PRG2618 Tiit Teder, Ants Kaasik Metrics & Citations Metrics Article Usage 827 views 322 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Barbora Žabová, Michal Knapp, Ants Kaasik, et al. 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