ABSTRACT High‐density SNP arrays are increasingly used in ecological and evolutionary studies, yet their application in wild species remains challenging. In this study, we evaluated the performance of the Affymetrix Axiom Mouse HD array, originally developed for Mus musculus, in two wild small mammals, Apodemus flavicollis and Apodemus sylvaticus, with particular focus on genetic diversity and population connectivity across seven sampling sites within a fragmented landscape. A total of 96 individuals (43 A. flavicollis and 53 A. sylvaticus) were genotyped using a 616K SNP array. After quality control filtering for missingness and minor allele frequency, more than 160,000 high‐quality autosomal SNPs were retained for each species. Despite being designed for a different species, the array effectively discriminated between A. flavicollis and A. sylvaticus, with principal component analysis clearly separating the two species. Levels of genetic diversity were comparable across sites, with mean observed heterozygosity around 0.33 and consistently negative FIS values, indicating a slight excess of heterozygotes. Population structure analyses revealed extremely weak spatial genetic differentiation. ADMIXTURE supported a single genetic cluster (K = 1) within each species, while analysis of molecular variance attributed more than 99% of genetic variation to within‐individual components. Pairwise relationship analyses showed that related individuals were not confined to single sites but occurred across sampling locations, supporting ongoing gene flow even across the fragmented landscape. No significant isolation‐by‐distance pattern was detected. Overall, our results indicate high population connectivity and limited spatial genetic structuring in both species across the study area, consistent with the documented dispersal capacity of these species at the spatial scale investigated. Moreover, this study demonstrates that high‐density SNP arrays can provide powerful genomic tools for investigating dispersal dynamics and population structure in closely related wildlife species under habitat fragmentation, where subtle genetic patterns may otherwise remain undetected.
ABSTRACT The pyrophilous beetle Melanophila acuminata is a decomposer of freshly burned wood, playing a critical role in nutrient cycling within forest ecosystems. To investigate the impact of climate change on the global distribution of M. acuminata, this study employed MaxEnt modeling in conjunction with 22 environmental variables under current and future conditions (2050s and 2070s) to conduct a comparative analysis of its suitable habitats. After rational screening, a total of 795 global occurrence records and 10 selected key environmental variables were incorporated into the MaxEnt model, which demonstrated excellent predictive accuracy (AUC ≥ 0.919). The results indicate that the mean temperature of the coldest quarter (Bio11) and the precipitation of the driest month (Bio14) are the primary factors limiting the distribution of M. acuminata. Under current climate conditions, its high‐suitability areas are concentrated in Northern Europe and the border region between the United States and Canada. Under the high‐emission scenario (SSP5‐8.5) in the 2070s, the high‐suitability area is projected to contract by nearly 36%, with the centroid shifting northwestward to higher elevation and an increase in habitat fragmentation. This projected contraction and fragmentation of suitable habitats may pose particular challenges for M. acuminata, given its known reliance on habitat connectivity for locating fire sites via its specialized infrared sensory system (Schmitz and Bousack 2012). However, direct validation of this mechanistic link requires further empirical investigation. Based on the predicted suitable habitats of M. acuminata in 2050s and 2070s, future conservation efforts should focus on high‐suitability areas in Northern Europe and Canada.
ABSTRACT Archaea, a pivotal domain in the global biosphere, serve as indispensable mediators in biogeochemical turnover of mangrove wetlands. Nonetheless, high‐resolution vertical changes of archaeal communities, function, co‐occurrence patterns, and assembly mechanisms as well as their driving factors are poorly described in the mangrove sediments. Herein, through high‐throughput analysis of archaeal communities across seven depth intervals (0–90 cm) within 8 sediment cores collected in the Zhanjiang mangrove wetlands, we provide the vertical profiles of archaeal community composition and function, co‐occurrence networks, and assembly mechanisms along the sediment depth. Our results show that archaeal abundance declined with sediment depths, while higher archaeal diversity was observed in the mangrove deep sediments. Thermoplasmatota was more abundant in surface mangrove sediments, whereas Thermoproteota (Bathyarchaeia) was remarkably enriched in deep sediments. Metabolically, surface archaeal communities are characterized by carbohydrate, amino acid, cofactor and vitamin metabolism, whereas glycan biosynthesis, xenobiotics biodegradation, and nucleotide metabolism serve as the predominant functions in deep archaeal communities. The surface network displayed greater complexity and stability than the deep counterpart, with Thermoproteota functioning as keystone taxa across all three networks. Further, stochastic processes govern archaeal community assembly in all sediment layers. Finally, sediment depth, temperature, moisture, TP, clay content, and salinity were identified as key drivers shaping archaeal communities. These findings expand our knowledge regarding the vertical distribution characteristics and key driving factors of mangrove archaea, while also underscoring their ecological importance in deep mangrove sediment habitats.
ABSTRACT Grassland ecosystems provide substantial social and cultural value but are vulnerable to climate change and human activities. Large‐scale evidence on how climate and disturbance jointly affect above‐ground biomass (AGB), species richness, and their relationship remains limited. We conducted a meta‐analysis by compiling and standardizing plot‐level observations from 226 studies of Chinese grasslands. The final database contained 1192 records from 378 sites surveyed between 1982 and 2019, with matched climatic variables (mean annual temperature, annual precipitation, and radiation) and disturbance categories (grazing, mowing, and fencing). Random‐forest models identified disturbance, precipitation, and radiation as the strongest predictors of AGB, whereas temperature was the strongest predictor of species richness. AGB was higher under mowing and fencing than under grazing and declined with increasing grazing intensity; it also increased with local precipitation. Species richness was highest under mowing, followed by fencing and grazing, and was greatest under wetter conditions and moderate temperatures. Across the national dataset, AGB and species richness were linearly and positively related overall, although several plant formations showed a unimodal pattern. Heavy grazing weakened the linear relationship, whereas moderate grazing strengthened it. Our study provides a scientific basis for the management of grassland ecosystems under the influence of climate change and human activities.
Benthic biofilm microbial communities play a critical role in riverine primary production, nutrient cycling, and organic matter decomposition, yet their responses to hydrological alterations due to small hydropower plants (SHPs) remain poorly understood, particularly with respect to seasonal dynamics. This study conducted a one-year monitoring survey across four river sections (upstream, reservoir, dewatered reach, and downstream) in the Oujiang River Basin, Zhejiang Province, China, covering all four seasons. The results showed that the reservoir section exhibited distinct bacterial composition, while the dewatered reach harbored the highest diversity, broader niche breadth, and was governed by stochastic assembly processes. Seasonally, deterministic processes dominated in summer, whereas stochastic processes prevailed in winter. Predicted functional profiling suggested that the SHP may exert a regulatory role in carbon and nutrient metabolism, with pronounced functional differences observed in summer. This study indicates that SHPs reshape microbial assembly and predicted function by altering hydrological regimes. As an observational case study based on a single representative facility, these findings should be interpreted as hypothesis-generating rather than conclusive; however, they provide key ecological insights and a methodological reference for future impact assessments of similar diversion-type SHPs in subtropical river systems.
Birds have a unique physiology, and their gut microbiota is regulated by ecological factors such as diet and migratory strategies. However, our understanding of how these factors drive the assembly and changes in the gut microbiota in birds is limited. We performed 16S rRNA sequencing of 61 bird cloacae samples. The results showed significant differences in the composition of the gut microbiota among birds with different ecological types (p < 0.05), and each taxonomic group (omnivory, carnivory, herbivory; migratory, or resident) had its core and unique ASVs (Amplicon Sequence Variants). Diet significantly altered the composition of the birds' gut microbiota, while migration strategy had a small but significant effect (p < 0.05). The dispersion in migratory birds was similar to that in resident birds, suggesting that migration does not increase the individual variability of bird gut microbiota. Overall, our findings reveal the associations between the avian gut microbiota and their diet or migration behavior.
Understanding species interactions is integral to understanding ecosystem function and predicting how disturbances may affect the services provided to society. Analysis of trophic interactions, however, requires a significant investment of time and resources. Using a simple predator-prey pairing of a semi-sessile rotifer and motile algae, the Predator-Prey Encounter Detection (PrED) model aims to streamline and semi-automate video analysis of species interactions using computer vision and machine learning techniques. Based on Ultralytics YOLOv5 architecture with an implementation of SORT tracking, the PrED model can estimate algal density and generate a "potential encounter" log with timestamps to allow researchers to skip through a video. After the model validation and testing steps, the PrED model achieved over 90% precision and recall scores. By reducing the time it takes to analyze a species interaction video, the PrED model will save researchers time and act as an efficient tool to study plankton dynamics.
High-throughput sequencing has transformed biomonitoring by enabling scalable molecular inventories, but most programs still emphasize taxa lists. In this Perspective, Biomonitoring 3.0 is proposed as a framework that builds on molecular inventories to monitor ecological dynamics, interactions, and biological responses through time. Environmental RNA is presented as a complementary source of information because, in some settings, it can provide more temporally local evidence of recent biological activity and responses than DNA alone. An inference ladder is introduced to grade interaction evidence from co-detection and statistical associations to interaction-explicit links, coupled signal-response dynamics and, where feasible, ecosystem-level consequences. Field designs are outlined that use repeated time-series sampling and paired sampling of potential signal sources and recipients to improve temporal interpretation and strengthen attribution. Minimum reporting elements are also recommended to support transparent comparison, validation, and cross-study synthesis. The "3.0" designation therefore refers to a change in the primary monitoring objective: from documenting community membership alone to evaluating ecological dynamics and feedbacks relevant to ecosystem condition and management. We conclude with a practical agenda for developing environmental nucleic-acid measurements into decision-relevant indicators of interactions and change.
ABSTRACT In oviparous species, females shape offspring phenotype during early development by varying the resources they deposit in the egg prior to laying. Yolk androgen levels, for example, vary within and among females and their deposition is influenced by maternal state, as well as environmental conditions, including the social environment. By providing artificial breeding sites, such as rooftops, urbanisation has created novel breeding contexts for Herring gulls, which, however, differ from a traditional ground‐breeding context in several ecological characteristics that may influence yolk androgen deposition. Here, we compared yolk testosterone concentrations in the last‐laid egg of rooftop‐ and ground‐breeding Herring gulls across two breeding seasons and tested whether variation was associated with social environment (approximated by nest density) or maternal quality differences (reflected by egg volume, laying date of the last egg and diet composition). Rooftop‐breeding pairs showed higher yolk testosterone concentrations than ground‐breeding pairs in 2023, while no difference was observed in 2024. Ground‐breeding pairs also exhibited significant interannual variation, whereas rooftop pairs did not. Neither nest density nor any proxy of maternal quality explained variation in yolk testosterone levels. These results indicate that yolk testosterone allocation in Herring gulls is variable but not consistently explained by breeding context, social environment or maternal state.
ABSTRACT Ecotones are transition zones that integrate environmental gradients and play an important role in biodiversity conservation; however, within the context of South Korea, their ecological functions and spatial characteristics remain insufficiently quantified at the national scale. Scientific evidence is needed to support their inclusion in protected area planning. In this study, we quantified the spatial distribution and ecological characteristics of ecotone zones (EZs) across vegetation–climate zones in the temperate forests of South Korea and examined their associated biodiversity patterns and species turnover. Entropy‐based spatial classification was conducted to delineate the EZs. Environmental and compositional differences among zones were tested using ANOVA and multivariate ordination (CCA, MRPP), while species turnover and community‐assembly processes were examined through zeta‐diversity–based model comparisons (RMSE, AIC). The EZs exhibited mixed characteristics of multiple vegetation–climate zones, showing intermediate environmental conditions and transitional species composition consistent with a buffering role. EZs showed high species richness (607.8 ± 9.6 species per grid) that did not differ significantly from the Northern Temperate Zone (NTZ) (p = 0.069), and CCA explained the compositional gradient, with the first two axes accounting for 86.5% of the constrained variance (CCA1 = 57.2%, CCA2 = 29.3%). MRPP results indicated the greatest compositional overlap between EZ and the Central Temperate Zone (A = 0.0317), the lowest agreement value among all pairwise comparisons. The zeta‐diversity analysis revealed unimodal patterns with intermediate turnover and partial stability dominated by stochastic processes. These patterns indicate that EZs are transition zones associated with high species richness and intermediate turnover. Overall, our findings suggest that EZs may warrant consideration in protected‐area prioritization and provide a quantitative basis for identifying them at the national scale.
ABSTRACT The Mongolian Plateau, a typical arid and semi‐arid zone in Eurasia, is characterized by highly heterogeneous and fragmented wetland habitats. Phragmites australis, a common wetland species in this region, exhibits remarkable adaptability. Unraveling the coordination between phylogenetic history and local environmental filtering is crucial for elucidating its adaptive mechanisms. Integrating landscape genomics and trait‐based phylogenetic analyses, we analyzed transcriptome‐wide SNPs, multidimensional functional traits, and environmental variables across 90 individuals from 30 natural P. australis populations. This study aims to reveal the genetic and phenotypic variation patterns underlying population genetic structure and trait variation, specifically distinguishing the roles of geographic isolation, environmental filtering, and phylogenetic history. Results reveal a significant drainage‐dependent pattern in genetic structure. Populations in hydrologically connected basins show extensive admixture, whereas those in isolated endorheic basins form distinct lineages. While geographic isolation underpins genetic differentiation, environmental filtering independently explains ~33.84% of the genetic variation, driven primarily by moisture heterogeneity (precipitation seasonality and soil moisture). Crucially, we observed differentiated evolutionary trajectories across functional traits. Structural traits (e.g., plant height, leaf thickness) are phylogenetically conserved; in contrast, physiological traits (e.g., water use efficiency) are decoupled from phylogeny, showing patterns consistent with high plasticity regulated by local environments. This evolutionary decoupling strategy enables P. australis to flexibly adapt to heterogeneous habitats while maintaining structural stability. This study uncovers the synergistic mechanisms by which geographic isolation and environmental filtering jointly shape the genetic patterns of this cosmopolitan species at a regional scale, clarifies that its evolutionary responses may depend heavily on the differentiated plasticity of trait types, and provides valuable regional insights into how widespread wetland species adapt to heterogeneous environments under global change.
ABSTRACT Studying historical dynamics and compositional changes of ecotones is essential for improving predictions of their responses to anthropogenic global change. However, the small size and geographic isolation of marginal ecotonal stands require retrospective analyses at the local scale. Here, we combine soil macrofossil charcoal analysis (SMCA), a lake‐sediment pollen record, and contemporary forest inventories to reconstruct past dynamics and assess contemporary trajectories of forest stands located at the northern boundary of the boreal‐temperate ecotone (BTE) in the Rimouski hinterland (Lower St. Lawrence region, Canada). Radiocarbon‐dated soil charcoal particles and regional pollen data reveal a delayed local establishment of thermophilous species, such as white pine (Pinus strobus), toward the end of the Holocene Climatic Optimum. This lagged expansion of temperate taxa coupled with a decline of boreal conifers led to the development of thermophilous assemblages that persisted into the early Neoglacial despite climatic cooling. Borealization of the landscape did not begin until the late Neoglacial (⁓1500 cal year BP), coinciding with shifts in the fire regime and the arrival of the eastern white cedar (Thuja occidentalis). At the stand‐scale, comparisons among charcoal assemblages in buried and surface soil layers with dead and living trees reveal an unprecedented proliferation by trembling aspen, as well as a recent establishment of jack pine likely reflecting anthropogenic disturbances associated with European settlement. However, current size‐class distribution suggests that these recent changes are likely to be transient in the absence of recurrent disturbances. Although predictive modeling remains necessary to forecast future forest trajectories under climate change, our results underscore the value of multi‐proxy reconstructions for disentangling vegetation responses to interacting climate and disturbance drivers.
ABSTRACT The supraglacial environment represents a unique habitat that harbors overlooked biodiversity, which is increasingly threatened by climate warming but remains underexplored. This study aims to investigate bacterial and fungal distribution patterns on five debris‐covered glaciers from two typical mountain ranges dominated by a monsoon climate (Mt. Gongga and Mt. Gangrigabu). High‐throughput amplicon sequencing of the bacterial 16S rRNA gene (V3–V4 region) and the fungal ITS region was performed using the Illumina MiSeq platform. Despite harsh and nitrogen‐limited conditions, the supraglacial debris across two mountain ranges supported phylogenetically diverse microbial taxa. Dominant bacterial families included Sphingomonadaceae, Chitinophagaceae, and Comamonadaceae, while dominant fungal families included Thelephoraceae, Mortierellaceae, and Inocybaceae, highlighting the establishment of specialized microbial assemblages in oligotrophic glacier surface environments. Compared with Mt. Gongga, supraglacial debris from Mt. Gangrigabu exhibited significantly lower bacterial alpha diversity, likely driven by environmental filtering associated with higher pH and total carbon content. In contrast, fungal alpha diversity showed limited regional variation. Notably, we observed a significant “distance decay” pattern in both bacterial and fungal communities, which illustrated a decline in taxonomic similarity with increasing geographic distance across glaciers, particularly pronounced in bacterial communities (R = −0.70, p < 0.001). Microbial community composition exhibited stronger glacier‐specific differentiation, heterogeneous environmental selection emerged as the dominant ecological process shaping microbial turnover across isolated glaciers, with pH and carbon content playing dominant roles in shaping microbial community variation. Our cross‐range comparison reveals that deterministic environmental filtering among geographically isolated glaciers governs the spatial turnover in supraglacial microbial communities, providing new insights into the ecological mechanisms governing microbial biogeographic patterns in rapidly changing cryospheric ecosystems across the southeastern Tibetan Plateau.
ABSTRACT The study of functional trait variation is increasingly used to understand macrophyte adaptation, as traits reflect organismal performance under different ecosystem conditions. Phenotypic expression results from the interplay of genetic and environmental factors: genetics provides the molecular basis for heritable traits and constrains potential phenotypes, while the environment acts as a selective and modulatory force. However, the genetic insight into traits has rarely been addressed in freshwater macrophyte studies. This review examines the different ways in which the DNA of macrophytes interplays with the environment and contributes to the variation in their functional traits, outlining main approaches, gaps, and future challenges. Only 21 studies explicitly combined genetics with functional traits and environment in the last fifteen years. The most common approach was the use of common garden experiments to explore acclimation and adaptation in a few model species. Current studies mainly focus on morphological and growth traits that best describe macrophytes' economic strategies, with limited attention to other trait categories, while the genetic and DNA traits studied are more variable. Across studies, environmental factors generally explained a larger proportion of functional trait variation, highlighting the dominant role of phenotypic plasticity for macrophyte acclimatation, whereas genetic contribution increased under experimentally manipulated conditions. Genome size and epigenetic variation influenced phenotypic plasticity; however, the effect was different and inconsistent on traits and depended on phylogenetic relationships and geographical environment variation. In field studies of natural populations, life history traits and hydrology had a strong effect on the geographic distribution of genetic diversity and the response to selection, as well as on our ability to distinguish selection from genetic drift. Future research should enhance molecular analyses, adopt multifactorial and long‐term experimental designs, develop conceptual frameworks to address the relationships between genomics, environment and functional traits and integrate emerging tools to capture macrophyte adaptation better.
ABSTRACT The increasing global habitat fragmentation has led to a marked decline in landscape connectivity, posing a severe threat to biodiversity. However, our understanding of how landscape connectivity influences biodiversity, particularly for plant diversity, remains notably limited. Taking the meadow of Poyang Lake as a case and comprehensively considering the ecological processes of water level change and species dispersal, this study firstly applied the landscape pattern metrics and the graph‐theoretic connectivity metrics to measure the dynamics of meadow structural connectivity and functional connectivity after identifying the spatial distribution of meadow at different water levels. Then, the effects of meadow connectivity on plant diversity and its scale effects were revealed through the linear regression model (LRM), and the redundancy analysis (RDA) was used to explore the contrasted explanatory of meadow structural connectivity and functional connectivity to plant diversity patterns. The results showed that: (1) Meadow was inundated and divided by water and its shrinkage coexisted with fragmentation when the water level rose. While meadow emerged and spliced and its expansion co‐occurred with cohesion when the water level fell. (2) When the water level increased, the shape of patch simplified, the area of patch shrank, the density of patch reduced, the aggregation of patch decreased and the meadow structural connectivity decreased progressively. Meanwhile, the number of components rose, the possibility of connectivity decreased and the meadow functional connectivity reduced dramatically. (3) Higher meadow connectivity not only led to greater plant species richness (α diversity) at the landscape scale but also increased plant community similarity (i.e., low β diversity) at the patch scale. Functional connectivity explains plant diversity patterns better than structural connectivity. This thesis proposes a new perspective of landscape connectivity for biodiversity conservation and landscape pattern optimization in lake areas.
ABSTRACT Accurate species identification is essential for effective management of threatened species, especially those with overlapping distributions and similar morphologies. Skate (Order Rajiformes) exhibit a highly conserved superficial morphology, which has resulted in a long history of taxonomic confusion and misidentification within this group. The flapper skate (Dipturus intermedius) and common blue skate (D. batis) are prime examples of this challenge; both species inhabit the Northeast Atlantic and share a complicated, intertwined taxonomic history. Given their overlapping distributions, precise species identification is necessary to ensure targeted management actions. Despite the availability of reliable morphological keys for larger specimens, identification of juveniles remains challenging because many diagnostic features are underdeveloped or obscured by damage. This study aimed to identify additional traits for differentiating juvenile (< 100 cm) flapper and common blue skate by employing morphological approaches validated through molecular techniques. The analysis focused on identifying distinct features that remain detectable in damaged specimens, ensuring the method's practical applicability in field conditions. We identified four robust features that can be used to differentiate juveniles of the two species: ventral coloration, disc shape, anterior disc margin shape and rostrum shape. The findings presented here enhance data accuracy for juvenile flapper and common blue skates, support targeted conservation actions, and contribute to the effective management and long‐term recovery of these threatened species.
Anthropogenic disturbances to forests have reduced densities of tree cavities and potentially led to declines in the abundance of cavity-dependent mammals. Artificial cavities (nest boxes, carved and drilled cavities) may be used to restore habitat quality that may otherwise take many decades to recover naturally. We investigated whether artificial cavities could support populations of two species of Australian cavity-dependent mammals, the brush-tailed phascogale (Phascogale tapoatafa, 200 g) and the inland sugar glider (Petaurus notatus, 110 g). This is the first detailed study of non-flying mammals that has attempted to do this. We censused animals twice per year over 6 years in 164 nest boxes arranged in 74 clusters through a 600-ha forest block deficient in tree cavities. We addressed four key questions: (1) were nest boxes used by a large number of individuals of the target species, (2) was use sustained over multiple years, (3) were nest boxes used for breeding and (4) what proportion of the local population might be supported by the nest boxes? We detected up to 58 adult phascogales and 232 adult sugar gliders in our boxes. Use was sustained over time with a mean probability of occupancy per cluster per year of 0.66 in the phascogale and 0.89 in the sugar glider. Differences in life history influenced how breeding was assessed. We detected breeding in 98% of female phascogales and at 68% of sites with sugar gliders. We estimated the total number of adults of each species that might occupy our study area based on their known spatial requirements. Our nest boxes potentially supported up to 61% of the adult female phascogales and 72% of the adult sugar gliders in the study area. Provision of shelter and breeding sites for such large segments of populations could be highly beneficial to manage populations of cavity-dependent mammals.
No systematic comparison of DNA extraction strategies exists for minute Vertiginidae (shell height < 3 mm), a group posing a dual analytical challenge: extremely low tissue input and co-purified PCR-inhibitory mucus. For legally protected species, an additional requirement to preserve the shell voucher further constrains available protocols. Using Vertigo antivertigo as the model species, we compared six approaches applied to specimens preserved in 96% ethanol (n = 10 per method): two HotSHOT alkaline-lysis protocols (destructive and non-destructive shell-preserving variants), a modified CTAB protocol supplemented with PVP-40 and DTT, and three commercial silica-column kits (GeneJET Genomic, DNeasy Blood & Tissue, QIAamp DNA Micro). DNA yields were quantified by QuantiFluor fluorometry, and PCR performance was subsequently assessed across four loci (COI barcode, COI mini-barcode, ITS1, ITS2). DNeasy Blood & Tissue produced the highest fluorometric concentrations; QIAamp DNA Micro and CTAB + PVP-40 gave intermediate values. The shell-preserving HotSHOT variant yielded lower concentrations but improved A260/230 ratios. BSA and trehalose supplementation increased PCR success in inhibition-prone HotSHOT extracts from 70% to 100%. ITS1 Sanger sequencing of three Vertigo species listed in Annex II of the EU Habitats Directive, all extracted with the shell-preserving protocol, confirmed species-level identification (99.8%-100% BLASTn identity; mean Phred Q > 51). The shell-preserving non-destructive HotSHOT protocol yields sequenceable DNA from protected Vertiginidae while retaining the morphological voucher, making it the preferred option for conservation-genetic monitoring. The practical decision framework documented here-integrating voucher preservation, amplification robustness and per-sample cost-has broad applicability to other minute terrestrial gastropods processed in large-scale biodiversity surveys.
Habitat fragmentation is widely expected to reduce population connectivity and increase genetic differentiation, although the strength of these effects depends on species-specific traits such as dispersal ability. Here, we investigated the population genetic structure of the cosmopolitan butterfly, Pieris rapae L. (Lepidoptera: Pieridae), across western Germany using genome-wide single-nucleotide polymorphism (SNP) data. To analyze the effects of landscape structure on genetic connectivity, we applied a paired study design comprising four landscape pairs, each consisting of a highly intensified, modern agricultural landscape and a more heterogeneous, traditional landscape. Our results revealed no evidence of genetic differentiation. Pairwise FST values were close to zero; we detected no isolation by distance, and clustering analyses supported a single genetic population. No meaningful associations between genetic variation and environmental variables were detected, with landscape effects explaining less than 0.4% of genomic variation. Consequently, we found no evidence for stronger genetic structuring in modern compared to more connected traditional landscapes. Our results suggest that extensive habitat fragmentation does not necessarily translate into reduced genetic connectivity in highly mobile, generalist species. In P. rapae , high dispersal ability and ecological generalism appear to buffer against the genetic consequences of landscape modification, resulting in panmictic population structure even across strongly contrasting agricultural landscapes.
ABSTRACT In order to ensure the effective conservation of the critically endangered European hamster (Cricetus cricetus), there is a necessity for the implementation of targeted conservation measures and reliable monitoring methods. This study explores the potential of employing Deep Learning (DL) to assist with camera trap monitoring for the purpose of tracking hamster activity. To this end, an object detection model (YOLO) was trained to efficiently analyze large volumes of video data from summer 2023 with high reliability. The model achieved a weighted average F1‐score of 0.93 and an accuracy of 0.93 for the detection of European hamsters, effectively differentiating them from other species. A comparison between DL‐based and human evaluations confirmed that DL can reliably depict hamster activity patterns. The findings of this study suggest that European hamsters exhibit peak activity levels at dusk, with the highest peak in activity occurring around sunset. In contrast, activity levels were lowest around midday. Autocorrelation analysis revealed a biphasic activity pattern, with a secondary peak occurring approximately before sunrise. This study underscores the potential of employing DL for long‐term conservation efforts and its applicability in assessing the success of reintroduction programs.
