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Natural populations may suffer negatively from increased environmental variability due to climate change; however, several mechanisms can mitigate those effects by changing the vital rates of a population (e.g., survival, reproduction). Despite important analytical and theoretical advances, we still do not know how and to what extent environmental regimes, life history traits, and evolutionary history determine the buffering capacity of natural populations. To address these questions, we parameterise a Bayesian generalised linear mixed model with high-resolution vital rate data from 121 natural populations across 78 plant species. We show that population responses to environmental variability vary four orders of magnitude along a 'demographic buffering continuum'. Furthermore, the position of a given population along said continuum is predicted by a survival-reproduction trade-off and by the degree of aridity the population experiences. Our findings open a promising avenue of research to improve ecological forecasts and management of natural populations in the Anthropocene.
Nine geographically distinct populations of plateau zokors (Eospalax baileyi) from Qinghai Province were selected for metagenomic analysis to investigate the composition of gut microbial communities among different populations. The results showed that the core gut microbiota of plateau zokors from different geographic populations was dominated by Firmicutes, Bacteroidetes, and Proteobacteria, with significant differences in community composition among populations. Alpha diversity analysis revealed marked variation in gut microbial diversity and richness across the different geographic populations. Functional prediction further demonstrated significant differences in multiple metabolic pathways, including carbohydrate metabolism, amino acid metabolism, replication and repair, and membrane transport. Notably, carbohydrate-active enzymes associated with the degradation of cellulose, hemicellulose, and lignin exhibited significant differences among populations. In addition, correlation analyses between environmental factors and the gut microbiota indicated that environmental variables such as altitude, annual precipitation, and isothermality had significant effects on gut microbial community structure. Regression analysis between genetic and geographic distances showed that genetic distance among plateau zokor populations increased with increasing geographic distance. Overall, these results suggest that geographic isolation and environmental heterogeneity may jointly drive the differentiation of gut microbial communities in plateau zokors. This study provides microbiological evidence and theoretical support for understanding the ecological adaptation of plateau zokors and offers a scientific basis for the integrated management of grassland rodent pests. The online version contains supplementary material available at 10.1186/s12866-026-05069-6.
Small, isolated, and fragmented populations often exhibit low levels of genetic diversity as a result of genetic drift, limited gene flow, and inbreeding. Huemul (Hippocamelus bisulcus) is a medium-sized South American deer categorized as endangered by the International Union for Conservation of Nature (IUCN). Huemul in its northernmost range was previously distributed in Central Chile between 36° S and 37° S, but its current distribution and conservation status in the region are poorly documented. We used non-invasive genetic approaches to assess the genetic diversity, population connectivity, and demographic history of the huemul's northernmost population using nuclear microsatellite markers from fecal samples of wild individuals. Observed nuclear DNA genetic variation (Ho = 0.2958 ± 0.0318) was moderate, and allelic richness was low (Ar = 3.43-4.01), consistent with the theoretical expectation that isolated populations may retain heterozygosity while losing allelic richness more rapidly. However, the estimated nuclear DNA effective population size was low (Ne = 47; 95% CI: 19.2-∞). Demographic simulations project continued loss of genetic diversity under all scenarios modeled. Our results provide a foundation for further study of this population and provide the genetic data necessary to design detailed management plans to ensure the persistence of healthy populations of this rare and elusive deer.
Investigating the effects of sublethal pesticide doses on pest population succession and physiological metabolism is crucial for IPM and resistance delaying. This study evaluated sublethal effects of abamectin on Diaphorina citri using two-sex life tables, population modeling, and measurements of hormone levels, energy reserves, and gene expression to reveal its transgenerational impacts. Results showed dose-dependent and transgenerational effects: both F0 and F1 generations experienced prolonged development and reduced longevity under LC25/LC50 stress. Life-table parameters (r, λ, R0, GRR, T) declined, and the model predicted a sharp population decrease after 60 days (from 10,357 to 1711 and 372 individuals under LC25 and LC50, respectively). The findings indicated that abamectin suppresses population growth by delaying development and limiting adult recruitment. Following abamectin treatment, hormone levels (20E and JH) showed dynamic fluctuations with delayed peaks in the treated groups, while energy reserves (glycogen and triglycerides) were generally reduced. Vitellogenin gene expression was mostly suppressed, except for a transient increase in Vg-1 and Vg-A1 (LC25, day 9), whereas VgR was generally up-regulated except in the LC25 group. Both LC25 and LC50 treatments suppressed D. citri development and reproduction by disrupting hormone balance and energy metabolism, without inducing hormesis. These findings provide a theoretical basis for optimizing field application strategies and support the use of abamectin in IPM programs to reduce outbreak risk and delay resistance development.
Multilevel selection has important implications for understanding the origin, ecology, and evolution of host-associated microbiomes. Selection on the host-level can have a substantial impact on the evolution of microbial lineages, favoring microbes that are beneficial to the host. However, previous research has focused on the evolution of interactions among only two types. We alter this perspective by examining the role of multilevel selection in shaping the interaction dynamics of a population with many microbial types-a case of particular relevance for microbiomes. We ask how multilevel selection influences the selection of interactions among various microbial types, whether it promotes microbial diversity within the population, and whether it increases the likelihood of microbial lineages evolving beneficial interactions with their host and other microbes. To address these questions, we simulate a multitype population structured into groups, where individuals interact within groups through an evolutionary game that determines their fitness. We classify pairwise interactions by their dynamical outcomes: dominance, coexistence, or bistability. We find that multilevel selection reshapes interactions dynamics in complex ways, depending on the details of the population structure. We show the impact of the interaction patterns emerging in such a system.
Reproductive value (RV) and evolutionarily stable primary sex ratios are fundamentally linked, centrally important topics in evolutionary biology. Recent theoretical studies have advanced our understanding of (i) the relationship between the RV of juveniles of the two sexes under arbitrary transmission genetics, age structures, and fecundity schedules, and (ii) sex ratio evolution under facultative asexual reproduction. Here, we unite and build upon these two strands of work. We derive the relative RVs of daughters and sons in an age-structured population with arbitrary transmission genetics when both sexes can reproduce asexually and can produce offspring of either sex. We then apply this result to sex ratio evolution and derive a general expression for the primary sex ratio of the sexual pathway. A key finding is that the primary sex ratio of the sexual pathway is unaffected by asexual reproduction by either sex when asexually produced offspring are of the same sex as their parents. If asexual reproduction produces offspring of the opposite sex, the sex ratio of the sexual pathway is altered. The post-hatching population sex ratio results derived in earlier studies are recovered as special cases.
Cancer cell populations often exhibit remarkably similar growth laws despite their heterogeneity. Explanations of universal cell population growth remain partly unresolved to this day. Here, we present a growth-law unification by investigating the connection between the microscopic assumptions that affect the expected contact inhibition leading to five classical tumor growth laws: exponential, radial growth, fractal growth, generalized logistic, and Gompertzian growth. All five can be seen as manifestations of a single microscopic model. Agent-based simulations substantiate our theory, and we can explain differences in growth curves in experimental data from in vitro cancer cell population growth. Thus, our framework offers a possible explanation for many mean-field laws used to empirically capture seemingly unrelated cancer or microbial growth dynamics. Our results highlight that the interplay between contact inhibition and other assumptions (e.g., well-mixed) can influence our quantitative understanding of how cancer cells grow and, in turn, how they may interact.
Microbial populations exhibit a broad spectrum of nutrient utilization strategies, ranging from those utilizing diverse nutrients, called "generalists," to those highly adapted to specific nutrients, called "specialists." Identifying the conditions for the diversification of nutrient utilization strategies is one of the central questions in ecology. Previous theoretical studies have shown that trade-offs among different resource utilization functions in which cells cannot utilize broad types of substrates at nearly optimal efficiency are crucial for the emergence of diverse strategies. Additionally, in natural settings, nutrient availability often fluctuates over time, imposing another trade-off on the cells; cells that grow rapidly under nutrient-rich conditions tend to have a higher death rate under nutrient-poor conditions, leading to a growth-death trade-off. This additional trade-off can contribute to the emergence of diverse strategies. Here, we introduce a mathematical model that simultaneously incorporates the resource-use trade-off and the growth-death trade-off. Nutrient supply was modeled as discrete stochastic events, mimicking temporal changes in nutrient availability. We show that the phenotype with a higher ratio of growth rate to death rate dominates the population; that is, the strength of the growth-death trade-off plays a crucial role in the emergence of distinct strategies. We also found that a sparse and uncertain nutrient supply favors specialists, increasing their temporally averaged abundance. Our findings highlight the crucial role of temporal environmental variation and the resulting growth-death trade-off in driving diversification of microbial nutrient utilization strategies.
Pufferfish are well-known for their toxicity, yet they also exhibit a remarkable diversity of pigment patterns. Mushifugu (Takifugu exascurus) is a pufferfish endemic to Japan's coastal waters and is characterized by conspicuous labyrinthine patterns. Despite being recorded along both the Sea of Japan and the Pacific coasts, it has a limited distribution and is rarely observed. Aside from its unique body pattern, mushifugu shows little to no morphological differences from other Takifugu species, often leading to speculation that it may be an interspecific hybrid. In addition, previous theoretical and empirical studies have shown that complex camouflage-like labyrinthine patterns can emerge through the 'pattern blending' caused by hybridization between spotted species, providing support for this possibility. Here, we investigate the phylogenetic origin of mushifugu and its distinctive pattern through population structure analysis and demographic inference in comparison with its closest spotted relative, komonfugu (T. flavipterus). Mitochondrial DNA (mtDNA) analysis revealed two regional haplogroups within mushifugu-one in the Sea of Japan (SJ) and the other in the Pacific Ocean (PO). In the haplotype network, the SJ haplogroup formed a distinct cluster, whereas the PO haplogroup appeared as its own cluster connected to the komonfugu haplogroup. By contrast, genome-wide single nucleotide polymorphism (SNP) analyses indicated limited structure between the SJ and PO mushifugu populations, while clearly separating mushifugu from komonfugu. Coalescent-based demographic inference suggested that the two species diverged following a bottleneck event in the early Pleistocene. These results confirm that mushifugu is a distinct species rather than a recent interspecific hybrid. Nevertheless, evidence of introgression was detected in both mitochondrial and nuclear genomes, suggesting multiple episodes of past hybridization between mushifugu and komonfugu, highlighting the potentially complex evolutionary processes shaping Takifugu species and their pigment patterns.
Understanding the selective forces acting upon HIV early in infection is crucial to design prevention strategies. By leveraging deep sequencing and the short diagnostic intervals of the FRESH and RV217 cohorts between the last-negative and first-positive RNA tests (median 4 days), we captured a precise and early snapshot of acute HIV infection. The frequency of multiple transmitted viruses of 37% in these as well as placebo recipients from the AMP trials (NCT02716675 and NCT02568215) was higher than previously published, with the true frequency likely to be higher. The relative abundance of lineages fluctuated substantially over time in two-thirds of the multilineage infections, generating uncertainty in identifying the specific viruses that were transmitted and founding the infection. At the population level, viral populations exhibited limited diversity and selection on the Gag and Env proteins at the earliest times examined, with sites inferred to be undergoing negative selection most evident. These data may help explain vaccination failures and provide new targets for prevention.
In sexually reproducing populations, the challenge of finding mates at low densities can impose a strong demographic Allee effect. Environmental change can cause a population to fall below its Allee threshold by reducing the population size or by increasing the threshold if the latter depends on affected life-history traits. Evolutionary rescue then relies on overcoming the Allee effect, which gets increasingly difficult as the population declines. Despite mate-finding Allee effects being common, most models of evolutionary rescue assume that mating is assured even at low densities. Here, we set up a population genetic model to study the potential for evolutionary rescue of a population below its Allee threshold. For the analysis, we combine stochastic computer simulations with mathematical arguments. As expected, mate limitation can severely impede rescue, but the extent differs across sexual systems. We further show that it shifts the optimal sex ratio for dioecious but not for androdioecious populations, alters optimal evolutionary routes when there are trade-offs between increasing mate-finding efficiency and fecundity, and enhances the importance of standing genetic variation relative to de novo mutants. Overall, our results highlight the importance of accounting for positive density dependence in the assessment of a population's scope for evolutionary rescue.
Ghana exhibits geographic variation across northern and southern regions alongside differences between urban and rural communities, which may influence SARS-CoV-2 exposure and immune response. This study aimed to assess the differences in seroprevalence, and seroconversion status after exposure to SARS-CoV-2 in selected urban and rural Ghanaian communities. A longitudinal study design was employed. Serum samples (n = 987) were collected during a baseline survey (August 2023-February 2024) with longitudinal follow-up (n = 212) sampling after one year (August 2024-February 2025) among consenting community participants aged ≥10 years selected through household-based sampling in urban and rural settings. Socio-demographic data, clinical symptoms, and vaccination status were collected using structured questionnaires. Serum samples were inactivated and tested with semi-quantitative Anti-SARS-CoV-2 IgG ELISA assays targeting spike (S) and nucleocapsid (N) proteins. Presence of SARS-CoV-2 neutralizing antibodies in serum was determined by a surrogate virus neutralization assay. Of 987 participants aged 10-88 years (67.3% female), SARS-CoV-2 seroprevalence was comparable between urban (47.4%) and rural (47.7%) areas. Among the 212 participants followed longitudinally, 50.9% (108 participants) had both infection or vaccine-induced anti-spike and infection-induced anti-nucleocapsid antibodies after one year, indicating sustained immune responses from prior exposure or vaccination. There was a significant increase in paired spike and nucleocapsid antibody responses between baseline and follow-up (McNemar's test, χ²(1) = 104.00, p < 0.0001), reflecting ongoing immune boosting despite evidence of antibody waning. Neutralizing antibodies, were detected in 147/148 (99.3%) individuals at timepoint-1 and in all 12 (100%) selected individuals for follow-up at timepoint-2, demonstrating robust functional immunity. This study demonstrates widespread serological evidence of prior SARS-CoV-2 exposure and vaccine-induced immunity in both urban and rural Ghana. Functional neutralising antibodies were detected in a longitudinal subset, suggesting persistence of antibody-mediated protection in some individuals. Larger longitudinal studies with repeated functional immune assessments are needed to better define durable protection in West African settings.
Genome-wide polymorphism data are increasingly used in conservation biology, and new developments in theoretical population genomics generate refined statistical inference methods. Most theories and methods remain based on human life-history traits and genome characteristics, namely, that the ratio of the population rates of recombination over mutation is approximately one. However, most fungal, invertebrate or plant species exhibit violations of the classic population genetics models due to their peculiar life cycles, such as long-life span and generation overlap, dormancy, clonality, selfing and large variance in offspring production (sweepstakes reproduction). We first present applicable inference methods accounting for these life-history traits. Second, we highlight new inference methods to estimate the timing and magnitude of changes in these traits over evolutionary times. We suggest that methodological and theoretical novelties pave the way to dissect the causes and consequences of changes in ecological and evolutionary (life-history) traits in plant species and in multi-species assemblages (communities) in response to changing environments.
Classic theoretical models of cortical oscillations are based on the interactions between two populations of excitatory and inhibitory neurons. Nevertheless, experimental studies and network simulations suggest that interneuron subclasses such as parvalbumin (PV) and somatostatin (SOM) exert distinct control over oscillatory dynamics. Yet, we lack a theoretical understanding of the mechanisms underlying oscillations in E-PV-SOM circuits and of the differences with respect to the classical mechanisms for oscillations in simpler E-I networks. Here, we derive a biologically realistic mean-field model of a canonical three-population E-PV-SOM circuit. This model robustly generates oscillations whose features are consistent with experimental observations, including the relative timing of PV and SOM activity and the effects of optogenetic perturbations. By reducing the model to a linear analytical form, we demonstrate that gamma oscillations emerge directly from the cell-specific connectivity of the three-population circuit. This connectivity motif alone accounts for experimentally observed phase relationships, with PV activity consistently leading that of SOM neurons. Together, this mean field model identifies a distinct structural mechanism giving rise to oscillations in canonical E-PV-SOM circuits and provides theoretical primitives for constructing large-scale, cell-type-specific models of cortical dynamics.
Modern imaging technologies produce vast collections of cellular and subcellular structures, calling for principled methods that enable shape comparison across individuals and populations. We introduce the stratified Wasserstein framework, which treats each shape as an unstructured point cloud and embeds it into Euclidean space via ranked local distance profiles. This embedding yields an isometry-invariant Euclidean distance and a positive-definite kernel for population analysis, with a consistent sample-based estimator that supports large datasets in near-quadratic time. By leveraging kernel methods, the framework enables statistically rigorous tasks such as nonparametric hypothesis testing, providing theoretical guarantees as well as interpretability. We demonstrate our framework's applicability to large-scale biological datasets. Analyzing 2D cancer cell contours, we quantify population-level discrepancies and identify representative cells contributing most strongly to the observed differences. Using 3D volumes of cell envelope and nucleus, we reveal progression patterns that capture morphological changes across cell populations both at the level of individual shapes. These results establish a simple and principled tool for population-level biological shape analysis, with potential impact across diverse domains of computational imaging and data science.
The human gut microbiome is shaped by diverse selective forces that originate from host and environmental factors and it substantially influences health and disease. Whereas the association of microbial lineages with various health conditions has been shown at different taxonomic levels1-5, the extent to which unifying adaptive mechanisms sort microbial lineages into ecologically differentiated populations remains poorly understood. Here we show that genome-wide selective sweeps are a pervasive mechanism that differentiates bacteria in the microbiome. This mechanism leads to population structures akin to global epidemics across geographically and ethnically diverse human populations. Such sweeps arise when an adaptation allows a clone to outcompete others in its niche followed by rediversification, and they manifest as clusters of closely related genomes on long branches in phylogenetic trees. This structure is revealed by excluding recombination events that mask the clonal descent of the genomes. Indeed, we show that genome-wide sweeps originate under a wide range of recombination rates in at least 66 taxa from 25 bacterial families. Estimated ages of divergence suggest that sweep clusters can spread globally within decades and that this process has occurred throughout human history. Sweep clusters are associated with different host conditions-such as age, colorectal cancer, inflammatory bowel diseases and type 2 diabetes-as an indication of their ecological differentiation. Our results reveal an evolutionary mechanism for the observation of stably inherited strains with differential associations and provide a theoretical foundation for analysing adaptation among microbial populations.
Transposable Elements (TEs) have the ability to transpose, and have populated all known eukaryotic genomes to date. Nowadays, their role in many aspects of biology, from population diversity to gene regulatory networks is well recognized. OMICS technologies, thanks to their genome-wide scale, provide an unparalleled resource to understand TE biology. However, due to their repetitive nature, TE analysis is not routinely carried out. In this chapter, I will provide the basic theoretical framework that will allow researchers to gain a first understanding of TEs without the need of significant alteration to established analysis pipelines. Then, I will present an overview on how TE analyses have been carried out for different OMICS data, as well as advantages and disadvantages on these approaches. Collectively, this chapter will provide the necessary background to explore TE contribution, so prospective researchers continue to reveal the multifaceted role of TEs in healthy and disease biology.
Individuals, even with matched genetics and environment, show substantial phenotypic variability. This variability may be part of a bet-hedging strategy, where populations express a range of phenotypes to ensure survival in unpredictable environments. In addition, phenotypic variability between individuals ('bet-hedging'), individuals also show variability in their phenotype across time, even absent external cues. There are few evolutionary theories that explain random shifts in phenotype across an animal's life, which we term drift in individual phenotype. We use individuality in locomotor handedness in Drosophila melanogaster to characterize both bet-hedging and drift. We use a continuous circling assay to show that handedness spontaneously changes over timescales ranging from seconds to the lifespan of a fly. We compare the amount of drift and bet-hedging across a number of different fly strains and show independent strain-specific differences in bet-hedging and drift. We show manipulation of serotonin changes the rate of drift, indicating a potential circuit substrate controlling drift. We then develop a theoretical framework for assessing the adaptive value of drift, demonstrating that drift may be adaptive for populations subject to selection pressures that fluctuate on timescales similar to the lifespan of an animal. We apply our model to real-world environmental signals and find patterns of fluctuations that favor random drift in behavioral phenotype, suggesting that drift may be adaptive under some real-world conditions. These results demonstrate that drift plays a role in driving variability in a population and may serve an adaptive role distinct from population-level bet-hedging.
Environmental change is rapidly occurring. Theoretical and experimental work predicts that evolution can facilitate population persistence in novel and changing environments [evolutionary rescue (ER)]. Recent examples now allow for testing foundational ER hypotheses in wild systems. We propose a more nuanced view for identifying ER by emphasizing the probabilistic role of evolution in reducing extinction risk through the examination of multiple lines of evidence. Using this approach, we identify a range of evolving traits, evolutionary pathways, and population outcomes from ER. Across systems, reducing environmental stress, maintaining genetic diversity, and protecting adaptive alleles can facilitate ER when relevant and desirable. The ways population-level ER might affect higher levels of biological organization and ecosystem resilience likely constitute the next chapter in understanding ER.