Mapping socio-geographical disparities in the occurrence of teenage maternity in Colombia using multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA).

BACKGROUND: The prevalence of teenage pregnancy in Colombia is higher than the worldwide average. The identification of socio-geographical disparities might help to prioritize public health interventions. AIM: To describe variation in the probability of teenage maternity across geopolitical departments and socio-geographical intersectional strata in Colombia. METHODS: A cross-sectional study based on live birth certificates in Colombia. Teenage maternity was defined as a woman giving birth aged 19 or younger. Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) was applied using multilevel Poisson and logistic regression. Two different approaches were used: (1) intersectional: using strata defined by the combination of health insurance, region, area of residency, and ethnicity as the second level (2) geographical: using geopolitical departments as the second level. Null, partial, and full models were obtained. General contextual effect (GCE) based on the variance partition coefficient (VPC) was considered as the measure of disparity. Proportional change in variance (PCV) was used to identify the contribution of each variable to the between-strata variation and to identify whether this variation, if any, was due to additive or interaction effects. Residuals were used to identify strata with potential higher-order interactions. RESULTS: The prevalence of teenage mothers in Colombia was 18.30% (95% CI 18.20-18.40). The highest prevalence was observed in Vichada, 25.65% (95% CI: 23.71-27.78), and in the stratum containing mothers with Subsidized/Unaffiliated healthcare insurance, Mestizo, Rural area in the Caribbean region, 29.08% (95% CI 28.55-29.61). The VPC from the null model was 1.70% and 9.16% using the geographical and socio-geographical intersectional approaches, respectively. The higher PCV for the intersectional model was attributed to health insurance. Positive and negative interactions of effects were observed. CONCLUSION: Disparities were observed between intersectional socio-geographical strata but not between geo-political departments. Our results indicate that if resources for prevention are limited, using an intersectional socio-geographical approach would be more effective than focusing on geopolitical departments especially when focusing resources on those groups which show the highest prevalence. MAIHDA could potentially be applied to many other health outcomes where resource decisions must be made.

A quantitative approach to the intersectional study of mental health inequalities during the COVID-19 pandemic in UK young adults.

PURPOSE: Mental health inequalities across social identities/positions during the COVID-19 pandemic have been mostly reported independently from each other or in a limited way (e.g., at the intersection between age and sex or gender). We aim to provide an inclusive socio-demographic mapping of different mental health measures in the population using quantitative methods that are consistent with an intersectional perspective. METHODS: Data included 8,588 participants from two British cohorts (born in 1990 and 2000-2002, respectively), collected in February/March 2021 (during the third UK nationwide lockdown). Measures of anxiety and depressive symptomatology, loneliness, and life satisfaction were analysed using Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) models. RESULTS: We found evidence of large mental health inequalities across intersectional strata. Large proportions of those inequalities were accounted for by the additive effects of the variables used to define the intersections, with some of the largest gaps associated with sexual orientation (with sexual minority groups showing substantially worse outcomes). Additional inequalities were found by cohort/generation, birth sex, racial/ethnic groups, and socioeconomic position. Intersectional effects were observed mostly in intersections defined by combinations of privileged and marginalised social identities/positions (e.g., lower-than-expected life satisfaction in South Asian men in their thirties from a sexual minority and a disadvantaged childhood social class). CONCLUSION: We found substantial inequalities largely cutting across intersectional strata defined by multiple co-constituting social identities/positions. The large gaps found by sexual orientation extend the existing evidence that sexual minority groups were disproportionately affected by the pandemic. Study implications and limitations are discussed.

Adaption, neutrality and life-course diversity.

Heterogeneity among individuals in fitness components is what selection acts upon. Evolutionary theories predict that selection in constant environments acts against such heterogeneity. But observations reveal substantial non-genetic and also non-environmental variability in phenotypes. Here, we examine whether there is a relationship between selection pressure and phenotypic variability by analysing structured population models based on data from a large and diverse set of species. Our findings suggest that non-genetic, non-environmental variation is in general neither truly neutral, selected for, nor selected against. We find much variations among species and populations within species, with mean patterns suggesting nearly neutral evolution of life-course variability. Populations that show greater diversity of life courses do not show, in general, increased or decreased population growth rates. Our analysis suggests we are only at the beginning of understanding the evolution and maintenance of non-genetic non-environmental variation.

Individual life histories: neither slow nor fast, just diverse.

The slow-fast continuum is a commonly used framework to describe variation in life-history strategies across species. Individual life histories have also been assumed to follow a similar pattern, especially in the pace-of-life syndrome literature. However, whether a slow-fast continuum commonly explains life-history variation among individuals within a population remains unclear. Here, we formally tested for the presence of a slow-fast continuum of life histories both within populations and across species using detailed long-term individual-based demographic data for 17 bird and mammal species with markedly different life histories. We estimated adult lifespan, age at first reproduction, annual breeding frequency, and annual fecundity, and identified the main axes of life-history variation using principal component analyses. Across species, we retrieved the slow-fast continuum as the main axis of life-history variation. However, within populations, the patterns of individual life-history variation did not align with a slow-fast continuum in any species. Thus, a continuum ranking individuals from slow to fast living is unlikely to shape individual differences in life histories within populations. Rather, individual life-history variation is likely idiosyncratic across species, potentially because of processes such as stochasticity, density dependence, and individual differences in resource acquisition that affect species differently and generate non-generalizable patterns across species.

LRBmat: A novel gut microbial interaction and individual heterogeneity inference method for colorectal cancer.

The gut microbial community has been shown to play a significant role in various diseases, including colorectal cancer (CRC), which is a major public health concern worldwide. The accurate diagnosis and etiological analysis of CRC are crucial issues. Numerous methods have utilized gut microbiota to address these challenges; however, few have considered the complex interactions and individual heterogeneity of the gut microbiota, which are important issues in genetics and intestinal microbiology, particularly in high-dimensional cases. This paper presents a novel method called Binary matrix based on Logistic Regression (LRBmat) to address these concerns. The binary matrix in LRBmat can directly mitigate or eliminate the influence of heterogeneity, while also capturing information on gut microbial interactions with any order. LRBmat is highly adaptable and can be combined with any machine learning method to enhance its capabilities. The proposed method was evaluated using real CRC data and demonstrated superior classification performance compared to state-of-the-art methods. Furthermore, the association rules extracted from the binary matrix of the real data align well with biological properties and existing literature, thereby aiding in the etiological analysis of CRC.

Reproductive senescence and mating tactic interact and conflict to drive reproductive success in a passerine.

An understanding of the drivers of individual fitness is a fundamental component of evolutionary ecology and life-history theory. Reproductive senescence, mate and mating tactic choice and latent heterogeneity in individual quality interact to affect individual fitness. We sought to disentangle the effects of these fitness drivers, where longitudinal data are required to understand their respective impacts. We used reproductive allocation and success data from a long-term (1989-2018) study of white-throated dippers Cinclus cinclus in Switzerland to simultaneously examine the effects of female and male age, mating tactic, nest initiation date and individual heterogeneity on reproductive performance. We modelled quadratic and categorical effects of age on reproductive parameters. The probability of polygyny increased with age in both sexes before declining in older age classes. Similarly, hatching probability in monogamous pairs and the number of nestlings hatched in both monogamous and polygynous pairs increased with female age before declining later in life. As predicted, offspring survival in monogamous pairs increased with male age before declining in older age classes, but male age had no effect on offspring survival in polygynous nesting attempts. Our results demonstrate that parental age, mating tactic and individual heterogeneity all affect reproductive success, and that the impacts of senescent decline are expressed across different demographic components as a function of sex-specific senescent decline and mating tactic.

Evaluating the importance of individual heterogeneity in reproduction to Weddell seal population dynamics using integral projection models.

Identifying and accounting for unobserved individual heterogeneity in vital rates in demographic models is important for estimating population-level vital rates and identifying diverse life-history strategies, but much less is known about how this individual heterogeneity influences population dynamics. We aimed to understand how the distribution of individual heterogeneity in reproductive and survival rates influenced population dynamics using vital rates from a Weddell seal population by altering the distribution of individual heterogeneity in reproduction, which also altered the distribution of individual survival rates through the incorporation of our estimate of the correlation between the two rates and assessing resulting changes in population growth. We constructed an integral projection model (IPM) structured by age and reproductive state using estimates of vital rates for a long-lived mammal that has recently been shown to exhibit large individual heterogeneity in reproduction. Using output from the IPM, we evaluated how population dynamics changed with different underlying distributions of unobserved individual heterogeneity in reproduction. Results indicate that the changes to the underlying distribution of individual heterogeneity in reproduction cause very small changes in the population growth rate and other population metrics. The largest difference in the estimated population growth rate resulting from changes to the underlying distribution of individual heterogeneity was less than 1%. Our work highlights the differing importance of individual heterogeneity at the population level compared to the individual level. Although individual heterogeneity in reproduction may result in large differences in the lifetime fitness of individuals, changing the proportion of above- or below-average breeders in the population results in much smaller differences in annual population growth rate. For a long-lived mammal with stable and high adult-survival that gives birth to a single offspring, individual heterogeneity in reproduction has a limited effect on population dynamics. We posit that the limited effect of individual heterogeneity on population dynamics may be due to canalization of life-history traits.

Hurricanes affect diversification among individual life courses of a primate population.

Extreme climatic events may influence individual-level variability in phenotypes, survival and reproduction, and thereby drive the pace of evolution. Climate models predict increases in the frequency of intense hurricanes, but no study has measured their impact on individual life courses within animal populations. We used 45 years of demographic data of rhesus macaques to quantify the influence of major hurricanes on reproductive life courses using multiple metrics of dynamic heterogeneity accounting for life course variability and life-history trait variances. To reduce intraspecific competition, individuals may explore new reproductive stages during years of major hurricanes, resulting in higher temporal variation in reproductive trajectories. Alternatively, individuals may opt for a single optimal life-history strategy due to trade-offs between survival and reproduction. Our results show that heterogeneity in reproductive life courses increased by 4% during years of major hurricanes, despite a 2% reduction in the asymptotic growth rate due to an average decrease in mean fertility and survival by that is, shortened life courses and reduced reproductive output. In agreement with this, the population is expected to achieve stable population dynamics faster after being perturbed by a hurricane ( ρ = 1.512 ; 95% CI: 1.488, 1.538), relative to ordinary years ρ = 1.482 ; 1.475 , 1.490 . Our work suggests that natural disasters force individuals into new demographic roles to potentially reduce competition during unfavourable environments where mean reproduction and survival are compromised. Variance in lifetime reproductive success and longevity are differently affected by hurricanes, and such variability is mostly driven by survival.

When the going gets tough, the tough get going: Effect of extreme climate on an Antarctic seabird's life history.

Individuals differ in many ways. Most produce few offspring; a handful produce many. Some die early; others live to old age. It is tempting to attribute these differences in outcomes to differences in individual traits, and thus in the demographic rates experienced. However, there is more to individual variation than meets the eye of the biologist. Even among individuals sharing identical traits, life history outcomes (life expectancy and lifetime reproduction) will vary due to individual stochasticity, that is to chance. Quantifying the contributions of heterogeneity and chance is essential to understand natural variability. Interindividual differences vary across environmental conditions, hence heterogeneity and stochasticity depend on environmental conditions. We show that favourable conditions increase the contributions of individual stochasticity, and reduce the contributions of heterogeneity, to variance in demographic outcomes in a seabird population. The opposite is true under poor conditions. This result has important consequence for understanding the ecology and evolution of life history strategies.

A model for leveraging animal movement to understand spatio-temporal disease dynamics.

The ongoing explosion of fine-resolution movement data in animal systems provides a unique opportunity to empirically quantify spatial, temporal and individual variation in transmission risk and improve our ability to forecast disease outbreaks. However, we lack a generalizable model that can leverage movement data to quantify transmission risk and how it affects pathogen invasion and persistence on heterogeneous landscapes. We developed a flexible model 'Movement-driven modelling of spatio-temporal infection risk' (MoveSTIR) that leverages diverse data on animal movement to derive metrics of direct and indirect contact by decomposing transmission into constituent processes of contact formation and duration and pathogen deposition and acquisition. We use MoveSTIR to demonstrate that ignoring fine-scale animal movements on actual landscapes can mis-characterize transmission risk and epidemiological dynamics. MoveSTIR unifies previous work on epidemiological contact networks and can address applied and theoretical questions at the nexus of movement and disease ecology.

Snared in an Evil Time: How Age-Dependent Environmental and Demographic Variability Contribute to Variance in Lifetime Outcomes.

AbstractTo what degree is lifetime success determined by innate individual quality versus external events and random chance, whether success is measured by lifetime reproductive output, life span, years that a tree spends in the canopy, or some other measure? And how do external events and chance interact with development (survival and growth) to drive success? To answer these questions, we extend our earlier age partitioning of luck in lifetime outcomes in two ways: we incorporate effects of external environmental variation, and we subdivide demographic luck into contributions from survival and growth. Applying our methods to four case studies, we find that luck in survival, in growth, or in environmental variation can all be the dominant driver of success, depending on life history, but variation in individual quality remains a lesser driver. Luck in its various forms is most important at very early ages and again close to the time when individuals typically first begin to be successful (e.g., entering the canopy, reaching reproductive maturity), but different forms of luck peak at different times. For example, a favorable year can boost a tree into the canopy, while luck in survival is required to take full advantage of that fortunate event.

A Single-Cell Raman Spectroscopy Analysis of Bone Marrow Mesenchymal Stem/Stromal Cells to Identify Inter-Individual Diversity.

The heterogeneity of stem cells represents the main challenge in regenerative medicine development. This issue is particularly pronounced when it comes to the use of primary mesenchymal stem/stromal cells (MSCs) due to a lack of identification markers. Considering the need for additional approaches in MSCs characterization, we applied Raman spectroscopy to investigate inter-individual differences between bone marrow MSCs (BM-MSCs). Based on standard biological tests, BM-MSCs of analyzed donors fulfill all conditions for their characterization, while no donor-related specifics were observed in terms of BM-MSCs morphology, phenotype, multilineage differentiation potential, colony-forming capacity, expression of pluripotency-associated markers or proliferative capacity. However, examination of BM-MSCs at a single-cell level by Raman spectroscopy revealed that despite similar biochemical background, fine differences in the Raman spectra of BM-MSCs of each donor can be detected. After extensive principal component analysis (PCA) of Raman spectra, our study revealed the possibility of this method to diversify BM-MSCs populations, whereby the grouping of cell populations was most prominent when cell populations were analyzed in pairs. These results indicate that Raman spectroscopy, as a label-free assay, could have a huge potential in understanding stem cell heterogeneity and sorting cell populations with a similar biochemical background that can be significant for the development of personalized therapy approaches.

Demystifying individual heterogeneity.

Among-individual variation in vital rates, such as mortality and birth rates, exists in nearly all populations. Recent studies suggest that this individual heterogeneity produces substantial life-history and fitness differences among individuals, which in turn scale up to influence population dynamics. However, our ability to understand the consequences of individual heterogeneity is limited by inconsistencies across conceptual frameworks in the field. Studies of individual heterogeneity remain filled with contradicting and ambiguous terminology that introduces risks of misunderstandings, conflicting models and unreliable conclusions. Here, we synthesise the existing literature into a single and comparatively straightforward framework with explicit terminology and definitions. This work introduces a distinction between potential vital rates and realised vital rates to develop a coherent framework that maps directly onto mathematical models of individual heterogeneity. We suggest the terms "fixed condition" and "dynamic condition" be used to distinguish potential vital rates that are permanent from those that can change throughout an individual's life. To illustrate, we connect the framework to quantitative genetics models and to common classes of statistical models used to infer individual heterogeneity. We also develop a population projection matrix model that provides an example of how our definitions are translated into precise quantitative terms.

Slower environmental cycles maintain greater life-history variation within populations.

Populations in nature are comprised of individual life histories, whose variation underpins ecological and evolutionary processes. Yet the forces of environmental selection that shape intrapopulation life-history variation are still not well-understood, and efforts have largely focused on random (stochastic) fluctuations of the environment. However, a ubiquitous mode of environmental fluctuation in nature is cyclical, whose periodicities can change independently of stochasticity. Here, we test theoretically based hypotheses for whether shortened ('Fast') or lengthened ('Slow') environmental cycles should generate higher intrapopulation variation of life history phenotypes. We show, through a combination of agent-based modelling and a multi-generational laboratory selection experiment using the tidepool copepod Tigriopus californicus, that slower environmental cycles maintain higher levels of intrapopulation variation. Surprisingly, the effect of environmental periodicity on variation was much stronger than that of stochasticity. Thus, our results show that periodicity is an important facet of fluctuating environments for life-history variation.

Effects of intrinsic environmental predictability on intra-individual and intra-population variability of plant reproductive traits and eco-evolutionary consequences.

BACKGROUND AND AIMS: It is widely accepted that changes in the environment affect mean trait expression, but little is known about how the environment shapes intra-individual and intra-population variance. Theory suggests that intra-individual variance might be plastic and under natural selection, rather than reflecting developmental noise, but evidence for this hypothesis is scarce. Here, we experimentally tested whether differences in intrinsic environmental predictability affect intra-individual and intra-population variability of different reproductive traits, and whether intra-individual variability is under selection. METHODS: Under field conditions, we subjected Onobrychis viciifolia to more and less predictable precipitation over 4 generations and 4 years. We analysed effects on the coefficient of intra-individual variation (CVi-i) and the coefficient of intra-population variation (CVi-p), assessed whether the coefficients of intra-individual variation (CsVi-i) are under natural selection and tested for transgenerational responses (ancestor environmental effects on offspring). KEY RESULTS: Less predictable precipitation led to higher CsVi-i and CsVi-p, consistent with plastic responses. The CsVi-i of all studied traits were under consistent stabilizing selection, and precipitation predictability affected the strength of selection and the location of the optimal CVi-i of a single trait. All CsVi-i differed from the optimal CVi-i and the maternal and offspring CsVi-i were positively correlated, showing that there was scope for change. Nevertheless, no consistent transgenerational effects were found in any of the three descendant generations, which contrasts with recent studies that detected rapid transgenerational responses in the trait means of different plant species. This suggests that changes in intra-individual variability take longer to evolve than changes in trait means, which may explain why high intra-individual variability is maintained, despite the stabilizing selection. CONCLUSIONS: The results indicate that plastic changes of intra-individual variability are an important determinant of whether plants will be able to cope with changes in environmental predictability induced by the currently observed climatic change.

Widespread inter-individual gene expression variability in Arabidopsis thaliana.

A fundamental question in biology is how gene expression is regulated to give rise to a phenotype. However, transcriptional variability is rarely considered although it could influence the relationship between genotype and phenotype. It is known in unicellular organisms that gene expression is often noisy rather than uniform, and this has been proposed to be beneficial when environmental conditions are unpredictable. However, little is known about inter-individual transcriptional variability in multicellular organisms. Using transcriptomic approaches, we analysed gene expression variability between individual Arabidopsis thaliana plants growing in identical conditions over a 24-h time course. We identified hundreds of genes that exhibit high inter-individual variability and found that many are involved in environmental responses, with different classes of genes variable between the day and night. We also identified factors that might facilitate gene expression variability, such as gene length, the number of transcription factors regulating the genes and the chromatin environment. These results shed new light on the impact of transcriptional variability in gene expression regulation in plants.

Decomposing demographic contributions to the effective population size with moose as a case study.

Levels of random genetic drift are influenced by demographic factors, such as mating system, sex ratio and age structure. The effective population size (Ne ) is a useful measure for quantifying genetic drift. Evaluating relative contributions of different demographic factors to Ne is therefore important to identify what makes a population vulnerable to loss of genetic variation. Until recently, models for estimating Ne have required many simplifying assumptions, making them unsuitable for this task. Here, using data from a small, harvested moose population, we demonstrate the use of a stochastic demographic framework allowing for fluctuations in both population size and age distribution to estimate and decompose the total demographic variance and hence the ratio of effective to total population size (Ne /N) into components originating from sex, age, survival and reproduction. We not only show which components contribute most to Ne /N currently, but also which components have the greatest potential for changing Ne /N. In this relatively long-lived polygynous system we show that Ne /N is most sensitive to the demographic variance of older males, and that both reproductive autocorrelations (i.e., a tendency for the same individuals to be successful several years in a row) and covariance between survival and reproduction contribute to decreasing Ne /N (increasing genetic drift). These conditions are common in nature and can be caused by common hunting strategies. Thus, the framework presented here has great potential to increase our understanding of the demographic processes that contribute to genetic drift and viability of populations, and to inform management decisions.

Individual variation creates diverse migratory portfolios in native populations of a mountain ungulate.

Ecological theory and empirical studies have demonstrated population-level demographic benefits resulting from a diversity of migratory behaviors with important implications for ecology, conservation, and evolution of migratory organisms. Nevertheless, evaluation of migratory portfolios (i.e., the variation in migratory behaviors across space and time among individuals within populations) has received relatively little attention in migratory ungulates, where research has focused largely on the dichotomous behaviors (e.g., resident and migrant) of partially migratory populations. Using GPS data from 361 female bighorn sheep (Ovis canadensis) across 17 (4 restored, 6 augmented, 7 native) populations in Montana and Wyoming, USA, we (1) characterized migratory portfolios based on behavioral and spatial migratory characteristics and (2) evaluated the relative influence of landscape attributes and management histories on migratory diversity. Native populations, which had been extant on the landscape for many generations, had more diverse migratory portfolios, higher behavioral switching rates, reduced seasonal range fidelity, and broad dispersion of individuals across summer and winter ranges. In contrast, restored populations with an abbreviated history on the landscape were largely non-migratory with a narrow portfolio of migratory behaviors, less behavioral switching, higher fidelity to seasonal ranges, and less dispersion on summer and winter ranges. Augmented populations were more variable and contained characteristics of both native and restored populations. Differences in migratory diversity among populations were associated with management histories (e.g., restored, augmented, or native). Landscape characteristics such as the duration and regularity of green-up, human landscape alterations, topography, and snow gradients were not strongly associated with migratory diversity. We suggest a two-pronged approach to restoring migratory portfolios in ungulates that first develops behavior-specific habitat models and then places individuals with known migratory behaviors into unoccupied areas in an effort to bolster migratory portfolios in restored populations, potentially with synergistic benefits associated with variation among individuals and resulting portfolio effects. Management efforts to restore diverse migratory portfolios may increase the abundance, resilience, and long-term viability of ungulate populations.

Early-life conditions determine the between-individual heterogeneity in plasticity of calving date in reindeer.

Phenotypic plasticity has become a key concept to enhance our ability to understand the adaptive potential of species to track the pace of climate change by allowing a relatively rapid adjustment of life-history traits. Recently, population-level trends of an earlier timing of reproduction to climate change have been highlighted in many taxa, but only few studies have explicitly taken into consideration between-individual heterogeneity in phenotypic plasticity. Using a long-term data of a semi-domesticated reindeer (Rangifer tarandus) population, we demonstrated that females differed greatly in their mean calving date but only slightly in the magnitude of their plastic response to the amount of precipitation in April. We also showed that despite the absence of a population trend, females individually responded to the amount of precipitation in April by delaying their calving dates. Females' calving date under average climatic conditions was best predicted by their birthdate, by their physical condition in March-April-May before their first calving season and by their first calving date. The degree of their phenotypic plasticity was not dependent on any of the females' attributes early in life tested in this study. However, females who delayed their calving dates in response to a higher amount of precipitation in April slightly produced less calves over their reproductive life. These findings confirmed that early-life conditions of female reindeer can shape their phenotypic value during reproductive life, supporting the importance of maternal effects in shaping individuals' lifetime reproductive success. Whether females differed in the magnitude of their plastic response to climatic changes has received contrasted responses for various ungulate species. This calls for more research to enhance our understanding of the underlying mechanisms, leading to the complexity of plastic responses among populations to cope with current climate change.

Proximate causes and fitness consequences of double brooding in female barn owls.

Multiple brooding, reproducing twice or more per year, is an important component of life-history strategies. However, what proximate factors drive the frequency of multiple brooding and its fitness consequences for parents and offspring remains poorly known. Using long-term longitudinal data, we investigated double brooding in a barn owl population in France. We assessed the effects of both extrinsic and intrinsic factors and the consequences of double brooding on fledgling recruitment and female lifetime reproductive success. The occurrence of double brooding in the population, ranging from 0 to 87%, was positively related to the number of rodent prey stored at the nest. Females laying early in the season were more likely to breed twice and the probability of double brooding increased with smaller initial brood size, female age and the storage of wood mice at the nest early in the season. Fledglings from first broods recruited more often (8.2%) than those from single broods (3.8%) or second broods (3.3%), but this was primarily the consequence of laying dates, not brood type per se. Females producing two broods within a year, at least once in their lifetime, had higher lifetime reproductive success and produced more local recruits than females that did not (15.6 ± 8.1 vs. 6.1 ± 3.8 fledglings, 0.96 ± 1.2 vs. 0.24 ± 0.6 recruits). Our results suggests that the fitness benefits of double brooding exceed costs and that within-year variability in double brooding may be related to heterogeneity in individual/territory quality.