Ecology and Evolution最新文献

Dormancy has been widely recognized as an evolutionarily conserved strategy that enables cells and organisms to endure environmental stress, resource scarcity, or developmental arrest. While transcriptional regulation has been extensively studied in this context, increasing attention is being directed toward post-transcriptional mechanisms that allow rapid and energy-efficient control of gene expression. Among these, epitranscriptomic modifications, chemical marks added to RNA, have emerged as dynamic and reversible regulators of mRNA fate. In this perspective, it is proposed that RNA modifications can play a central role in establishing and maintaining dormancy across diverse biological systems. Evidence from plant seeds, microbial persisters, stem cells, and dormant cancer cells suggests that specific RNA marks, such as N6-methyladenosine (m⁶A), influence mRNA stability, translation, and localization in a context-dependent manner. It is argued that these modifications serve as a molecular interface between environmental signals and cellular responses, fine-tuning the transition between active and paused states. This article presents a unifying model, grounded in epitranscriptomics, in which RNA modifications modulate entry into, maintenance of, and exit from dormancy across taxa by tuning mRNA stability, translation, and localization—an underexplored regulatory layer in inactive states—and highlights key mechanistic insights, evolutionary parallels, and outstanding questions at the intersection of RNA regulation and cellular dormancy.

In an increasingly fragmented natural world, understanding how different ecological phenomena vary with patch size has many motivations. Examples include the assembly of biodiversity, ecosystem service provision and the suitability of fragments for habitat specialist species. A common approach to such questions divides fragments into small and large size classes for separate analysis. However, lack of an objective definition and means to differentiate ‘small’ from ‘large’ patches limits our ability to compare findings across studies, arguably impeding progress toward any unified views. Because larger and smaller fragments tend, on average, to respectively over-represent narrow- and wide-range species, an ‘area for unbiased species representation’ (A_USR) can be defined at some intermediate fragment size predicted to contain species at incidence frequencies approximating that of the overall landscape. A central tendency for A_USR has previously been estimated for patchy habitats (islands, habitat islands and fragments), providing a benchmark to compare this threshold of small fragment size between studies. However, if A_USR can be readily determined within individual study systems, it would also provide an objective threshold to separate small and large fragments under the A_USR definition. Here we assess this potential for 138 published datasets from various fragmented landscapes using an index comparing species incidence frequencies in each fragment with that of the overall landscape. Regressing this index on fragment area yielded an estimate for A_USR in over 90% of cases, suggesting broad applicability as an objective way to separate fragments into two size classes. Regression slopes provide further information on the relative representation of narrow- vs. wide-range species, with ~80% being numerically consistent with the overall negative trend. Requiring only the same data as the island species-area relationship, A_USR can provide useful insights on the relative importance of narrow- vs. wide-ranging species for studies of patch-size dependence in ecological phenomena.

Gut microbiota generally undergoes dynamic remodeling in concert with multifaceted self-regulation of amphibian hosts during key life stages, such as metamorphosis and hibernation. However, the spatiotemporal dynamics of amphibian gut microbiomes across the lifecycle remain poorly understood. In this study, we applied 16S rRNA gene amplicon sequencing to characterize the gut microbiomes of cultivated Black-spotted frog (Pelophylax nigromaculatus) across seasons. The gut microbiomes exhibited tissue-specific succession, and structural discrepancies between gut regions fluctuated temporally. Both small- and large-intestine microbiomes showed temporal decay patterns in abundance-unweighted intercommunity indices, but not in abundance-weighted indices. Compared with large-intestine microbiomes, small-intestine microbiomes were more randomized yet more centralized in terms of amplicon sequence variants, particularly within Proteobacteria (especially Pseudomonas). The alpha diversity of small-intestine microbiomes was comparatively lower, and their taxonomic composition was more stable over time. We further elucidated the assembly mechanisms of gut microbiomes by systematically analyzing dominant driving factors, ecological processes, phylogenetic traits, source-sink relationships, and co-occurrence networks. Stochastic processes played a dominant role in gut microbiome assembly, while deterministic processes (e.g., habitat filtering and microbial interaction) contributed more strongly to large gut microbiomes than to small gut microbiomes. Overall, this study provides insights into the ecological dynamics and assembly mechanisms of amphibian gut microbiomes across the lifecycle and may inform targeted microbiome modification for amphibian breeding and conservation.

Linepithema humile is a well-known invasive alien species that was first detected in 2019 at the cargo handling area of Busan Station in South Korea and has since established a population near the discovery site. Despite sufficient time for potential spread, no additional occurrence records have been reported outside the initial detection site. To predict its potential distribution across South Korea, we constructed species distribution models (SDMs) using occurrence data from its native range in South America and invasive range in North America. Modeling was conducted with the BIOMOD2 platform using five algorithms (ANN, GBM, MARS, MAXENT, and RF) and six environmental variables (Bio03, Bio04, Bio13, Bio16, Bio18, and the mean annual cumulative soil temperature degree-days above 15.9°C). Model performance was evaluated with Kappa, ROC, and TSS, and only models meeting thresholds (Kappa ≥ 0.7, ROC ≥ 0.7, and TSS ≥ 0.5) were used for ensemble modeling via EMmean, EMwmean, and EMca methods. Projection accuracy was assessed using chi-square tests based on occurrence data not used in model training. The predicted potential distribution included southern and southwestern coastal areas, which was consistent with the record in Busan. This study demonstrates the utility of SDMs trained on occurrence data from outside Korea in predicting the potential distribution of L. humile with limited domestic records and highlights high-risk areas beyond Busan. Such approaches may support early detection and management strategies in the initial stages of biological invasion.

Substantial interspecific variation in both drought responses and soil functioning among woody species poses significant challenges for predicting drought impacts on soil functioning in species-rich tropical and subtropical forests. However, critical knowledge gaps remain regarding how soil functions respond to drought across different plant species. We conducted a three-phase (10 months of well-watered conditions, 1 month of drought treatment, and 2 months of rewetting) seedling experiment to assess how drought impacts on eight rhizosphere soil functions related to carbon, nitrogen, and phosphorus cycling vary across 10 woody species. We tested whether plant species' preferences to arid versus moist habitats and functional traits could predict variation in the resistance and recovery of soil functions to drought. We found that soil functions of species adapted to the arid habitat or those possessing stronger drought-tolerant traits (e.g., lower leaf water potential at turgor loss point) showed comparable resistance to their counterparts. Species with lower root N:P ratios and root non-structural carbon concentrations consistently recovered faster in all four measured soil enzyme activities. Our results demonstrate that root chemical traits, particularly root N:P ratios and root non-structural carbon concentrations, strongly predict soil enzyme activity recovery from drought. These findings significantly improve our understanding and prediction of drought impacts on soil functioning in species-rich forests.

This study explores the genetic and physiological facets of personality variations in the yellow-rumped flycatcher (Ficedula zanthopygia), with a focus on potential sex-specific associations between simple sequence repeat (SSR) polymorphisms, body condition index (BCI) and behavioral traits. During the 2020 breeding seasons at Zuojia Nature Reserve, northeast China, we conducted field investigations using several stress tests to quantify personality as reflected in breathing rates. This metric demonstrated significant reproducibility between life stages, thereby validating its use as a reliable association with individual boldness. We further examined the influence of genetic diversity by genotyping 10 highly polymorphic SSR loci and calculating individual heterozygosity. As a reflection of stronger personalities, we found significant associations between individual heterozygosity and breathing rates in female adults, with greater heterozygosity correlated with lower breathing rates. The opposite pattern was observed in male nestlings, and no significant correlations were observed in male adults or male chicks. In addition, the BCI tended to be negatively correlated with breathing rates in female adults, suggesting that individuals with better body conditions were less fearful. These findings underscore the importance of genetic diversity and body condition in modulating personality traits, particularly in females. Overall, our results highlight the likelihood that the sex of these birds underlies their behavioral variations. Moreover, this study provides insight into the genetic basis of personality in cavity-nesting birds and emphasizes the need for further research to elucidate specific genetic pathways that influence these traits.

With increasing human domination of ecosystems, wildlife must either relocate or adapt its behaviour to anthropogenic impacts in order to survive. Vervet monkeys (Chlorocebus pygerythrus), whose natural habitats have been progressively encroached upon by urban expansion, have successfully adapted to urbanised environments because of their flexible and generalist feeding behaviour. Characterising diet composition of vervet monkeys can therefore reveal how they exploit anthropogenic resources and uncover opportunistic foraging behaviours. However, accurately determining complete diets through direct observations is challenging. In this study, we used an environmental DNA (eDNA) approach investigating the DNA mixtures present in faecal samples as a non-invasive complementary method for assessing diet and foraging strategies. We identified the dietary components of vervet monkeys through DNA metabarcoding of 447 faecal samples collected from two monkey groups over 4 months in a semi-urban neighbourhood in South Africa. We further compared the results with observational data on foraging to describe how vervet monkeys exploit anthropogenic resources. Subsequently, we evaluated whether dietary patterns can be distinguished between groups and within matrilineal levels. We found DNA metabarcoding data to be consistent with observational data, but the former revealed a broader diversity of consumed taxa. Additionally, we detected a difference in diet between the two investigated groups, and a tendency for similar dietary patterns among matrilineal pairs compared to other group members. Our results support the use of the DNA metabarcoding methodology, both to determine the complex diet of omnivorous species in urbanised ecosystems and to address interindividual foraging behaviours.

Passive Acoustic Monitoring (PAM) is an increasingly common method for monitoring birds and other sound-producing organisms at scale, but methods that digest these data streams into ecological insight remain underdeveloped. Specifically, using PAM and classification algorithms powered by artificial intelligence (AI) to uncover the phenology of vocal animals is an emerging use of these data but currently lacks standardized, repeatable methods with verified connections to biological phenomena. Here, we articulate specific hypotheses regarding the relationship between avian vocal activity and phenological events, and present a flexible, reproducible methodological pipeline for quantifying avian vocal phenology from PAM data. We applied our pipeline to 18,568 h of audio from 185 recording sites across Olympic National Park, USA. We processed acoustic data through an AI species classifier (BirdNET), then filtered the output using species-specific precision thresholds established through expert review to minimize false positives. For 25 species representing diverse migratory strategies across two elevational strata, we used hierarchical generalized additive models (HGAMs) to estimate daily probabilities of vocal activity from which we extracted standardized “phenometrics” describing the timing, duration, and shape of vocal activity curves. PAM-derived patterns of phenometrics broadly supported expectations, showing promise for future expansion of these methods. Resident species generally exhibited earlier and longer vocal periods than migratory species, and birds at mid-elevations showed delayed and shortened vocal phenology relative to lower elevations. Many species displayed bimodal vocal patterns, with secondary peaks 30–50 days after initial peaks. These generalizable patterns of vocal phenology likely cue transitions in various stages of the avian breeding cycle. Late-season vocal activity, especially in irruptive and resident species, highlighted the method's capacity to capture ecological transitions beyond the breeding season, but robust inferences require further ground-truthing. This study advances the use of PAM for phenological research, offering outputs that can inform long-term monitoring and detect phenological shifts in response to environmental change. We make recommendations for methodological and technological advancement, and highlight the need for studies that integrate PAM data and field-based observation to further strengthen the links between observed phenometrics and confirmed biological states of vocal organisms.

The Qinghai-Tibet Plateau (QTP) is a global biodiversity hotspot where Quaternary climatic oscillations profoundly shaped the evolution of endemic alpine flora. Understanding how genetic diversity and structure in these species responded to past climate change is crucial for deciphering regional evolutionary mechanisms. Using chloroplast and nuclear genome data of 958 samples from 48 populations, we evaluated the genetic diversity and population structure of Primula sikkimensis. We then investigated the lineage differentiation and dynamics of species by combining an Approximate Bayesian Computation procedure and species distribution modeling. Our study indicates that P. sikkimensis maintained separate glacial refugia in the Hengduan Mountains and eastern Himalayas during the Last Glacial Maximum (LGM). Our results suggest that postglacial range expansions onto the inner QTP plateau were accompanied by gene flow arising from both intraspecific secondary contact between previously isolated populations and interspecific hybridization events, which collectively enhanced genetic diversity and adaptive capacity in plateau populations. Our findings underscore the critical role of postglacial population dynamics and gene flow in shaping genetic diversity and adaptive potential of alpine endemics like P. sikkimensis, highlighting evolutionary responses to Quaternary climate change on the QTP.

The Pacific nudibranch Hermissenda crassicornis (sensu lato) is a well-known model organism in neuroscience. This species was recently split into three pseudocryptic species based on differences in genetics, morphology, and behavior. We used ddRADSeq data from 33 individuals (2354 loci) and coalescent isolation-with-migration models alongside forward simulations to estimate and evaluate the demographic history of the clade. We inferred (1) a novel phylogenetic tree topology with the North American species as sisters, (2) relatively old divergence times (0.55 and 1.29 mya), (3) a much larger population size in the southern species H. opalescens, and (4) no recent or current gene flow between the sympatric species H. crassicornis and H. opalescens. Then we examined behavioral differences between sympatric H. crassicornis and H. opalescens to characterize possible mechanisms promoting their reproductive isolation. Mating experiments showed that both H. crassicornis and H. opalescens display assortative mating, consistent with the existence of a prezygotic reproductive barrier. Our results support the splitting of H. crassicornis (sensu lato) and reinforce the need to reassess previous studies that used the species complex as a model organism.