Integrative zoology最新文献

High altitudes are challenging for the animals that inhabit these environments. The Xizang plateau frog (Nanorana parkeri), endemic to the Qinghai-Tibet Plateau and distributed between 2800 and 5100 m, represents an ideal model for studying high-altitude adaptations. Here, we compared environmental differences between high- (4600 m) and low-altitude (3400 m) habitats, characterized the physiological traits of high-altitude frogs, and integrated metabolomic and proteomic data to elucidate adaptive mechanisms to extreme environments. High-altitude habitats exhibited significantly lower water temperatures and dissolved oxygen levels. High-altitude frogs showed a 31%-37% reduction in resting metabolic rate, decreased concentrations of metabolites (glucose and β-hydroxybutyric acid), and 18%-56% lower activities of critical metabolic enzymes. This coordinated metabolic depression is indicative of an energy conservation strategy for surviving at high altitudes. Interestingly, hepatic glycogen (3.1-fold increase) and pyruvate accumulated in high-altitude frogs, suggesting enhanced energy storage and potential antioxidant utilization. Metabolomic profiling further revealed a remodeling of glycerophospholipid, indicating adaptive membrane stabilization. Proteomics analysis identified altered expression of proteins involved in stress response, energy metabolism, and translation, including chaperones (DNAJB6 and DNAJC22) and glutathione peroxidase (GPX4), which may be potential biomarkers for evaluating high-altitude adaptation in ectothermic vertebrates. Collectively, these findings demonstrate that N. parkeri survives in high-altitude environments through a synergistic strategy of metabolic remodeling and protein expression adjustment to optimize energy efficiency and enhance cellular protection. This study provides new insights into the mechanisms by which ectothermic vertebrates adapt to extreme environments.

Sexual dimorphism is classically attributed to sexual selection, yet natural selection via sex-specific ecological pressures is equally important. We investigated this interplay by testing how camouflage and thermoregulation shape sexual color dimorphism across four Diploderma lizards with a comparative framework capturing diverse ecologies. Using spectrometry and image analysis, we documented pronounced sexual color dimorphism in dorsal patterns. Females prioritized background matching, while males favored high-contrast surface disruption, except in Diploderma slowinskii where monomorphic strategies suggested habitat-specific adaptations. Male stripes critical for disruption significantly reduced solar heat gain, imposing a physiological cost absent in females. This sex-specific optimization, males sacrificing thermoregulation for camouflage efficacy and females favoring crypsis, demonstrates how divergent natural selection pressures drive sexual color dimorphism evolution. Our findings enhance the understanding of animal coloration beyond the sexual selection paradigm, positioning ecological trade-off as a fundamental mechanism shaping sexual color dimorphism.

Birds play a critical role in maintaining ecological balance and serve as key indicators of biodiversity. Observing bird behavior in natural environments poses significant challenges. However, identifying bird songs through sensor technology provides a non-invasive and environmentally friendly method for monitoring avian diversity. Nevertheless, bird songs in natural environments are often obscured by substantial noise, and supervised learning-based recognition methods depend on extensive manual data annotation. To address these challenges, we propose Contrastive Residual Masked AutoEncoder-BirdNET (CResMAE-BirdNET), a specialized network for bird song recognition capable of autonomously extracting features from vast amounts of unlabeled acoustic data, thereby significantly enhancing recognition performance. First, to mitigate environmental noise and enhance model robustness, we apply four audio enhancement techniques and introduce a time-frequency self-calibration fusion module (TFSC) that integrates spectral ripple features. Next, CResMAE-BirdNET combines contrastive learning with a masked autoencoder framework, integrating residual attention in the encoder and a residual multi-layer perceptron in the decoder, enhancing the ability to capture the relationship between local and global features for superior feature representation. Finally, extensive experiments on our self-built 40-class dataset (Bird40Song) and the public dataset (Birdsdata) validate the effectiveness of the proposed method, achieving recognition accuracies of 99.35% and 98.43%, along with F1-scores of 99.34% and 98.28%, respectively. The results highlight significant advancements in bird song recognition, demonstrating the potential of CResMAE-BirdNET to support large-scale ecological monitoring and biodiversity research. Code available at: https://github.com/xzq-okkkkkkk/CResMAE-BirdNET.

The chorotype, a group of species with similar distributions, provides critical insights into biogeographical patterns. Despite recent advances in taxonomic discovery and revision, one-third of terrestrial vertebrates in China remain unclassified into established chorotypes, hindering understanding of the zoogeographical patterns in China. Here, we updated chorotype classifications and renewed the zoogeographical regions for terrestrial vertebrates in China based on distribution data for 3059 species (638 mammals, 1298 birds, 563 reptiles, and 560 amphibians). We constructed a presence‒absence matrix using 1° × 1° grid cells and assigned species chorotypes to a predefined chorotype framework. Based on the proportions of species chorotypes within each grid cell, we constructed a dissimilarity matrix and used hierarchical clustering to delineate zoogeographical regions of terrestrial vertebrates in China. Discriminant analysis achieved high cross-validation accuracy for chorotype assignment across taxa. Among the 1040 newly updated species, Southern China and Himalaya‒Hengduan Mountains chorotypes played dominant roles, and most of them were reptiles and amphibians. Cluster analysis identified eight zoogeographical regions: North China, Northeast China, the Qiangtang Plateau, Northwest China, South China, Chinese Taiwan Island, the Yungui Plateau, and the Himalaya‒Hengduan Mountains. Despite the broad transition zones in eastern China with mixed chorotypes, the Qinling‒Huaihe Line emerged as the Palearctic‒Oriental boundary. Our study provides the first quantitative update of chorotypes for terrestrial vertebrate species in China, validated through the Grade of Membership model, and renews the zoogeographical regions. Mapping geographical patterns of chorotype proportion is promising for exploring biotic transition zones and offers a reliable framework for delineating biogeographical regions.

Lankesterella Labbe, 1899 is a genus of blood parasites found in reptiles, amphibians, and birds that has been poorly understood. In birds, it was originally classified as Hepatozoon Miller, 1908 or Atoxoplasma Garnham, 1905, but recent studies have revealed the diversity, prevalence, and host specificity of Lankesterella using integrative approaches, particularly the 18S rDNA gene. The introduction of new diagnostic protocols focusing on mitochondrial genes requires assessing the comparability of different diagnostic methods. This study aims to compare microscopy and molecular detection methods for Lankesterella spp. infections in wild birds, while also exploring the phylogenetic relationships inferred from different genetic markers. A total of 99 samples from nine passerine species were analyzed in a double-blind study using microscopy and PCR protocols targeting 18S rDNA, CytB, and COI. The overall Lankesterella sp. prevalence was 33%, with 17% detected by microscopy and 23% by molecular methods. In our study, the highest prevalences were found in European robins Erithacus rubecula (8.08%) and wrens Troglodytes troglodytes (9.09%). CytB detected the highest number of infections among the three used protocols, followed by COI, whereas 18S rDNA yielded the lowest detection rate. Only four samples were positive for all three genes and by microscopy. CytB and microscopy combined detected the highest number of infections, despite the low correspondence. Phylogenetic analysis confirmed high host specificity, with the best phylogenetic tree resolutions seen in COI and CytB. The study emphasizes the importance of using multiple methods, especially CytB and microscopy, to determine infection prevalence.

Avian haemosporidian parasites, such as Haemoproteus, Leucocytozoon, and Plasmodium are transmitted by blood-sucking insects and can negatively affect their host. These parasites have specific life cycles that allow them to survive and spread efficiently through their vectors. However, the research on vectors and their feeding preferences are scarce. Therefore, in this study, we investigated haemosporidian parasite vectors and their feeding preferences in insects collected at birds of prey nests. To catch the vectors, UV-light traps were hung at the nests of birds of prey between June and July 2020 and 2021. Parous and nulliparous biting midge females were separated. Parous females were dissected for salivary gland preparations, and their remnants were stored in 96% EtOH for PCR-based analysis. We screened parous females for the presence of parasites amplifying a fragment of the cytochrome b gene of haemosporidian parasites using specific primers (Plas1F/HaemNR3 and 3760F/HaemJR4). To identify the feeding preference, we analyzed 73 engorged biting midge females using vertebrate specific primers L14841/H15149. In total, we dissected and analyzed 1262 parous biting midges (Culicoides spp.) and three blackfly (Simulium spp.) females. We found that Simulium vernum is a natural vector of Leucocytozoon sp. and identified Haemoproteus spp. sporozoites in Culicoides kibunensis, Culicoides pictipennis, and Culicoides segnis. DNA of three birds and two mammals was detected in engorged biting midges. In conclusion, our study provides valuable insights into the identification of natural vectors of avian haemosporidian parasites and their feeding preferences, contributing to a better understanding of the ecological dynamics that influence parasite transmission.

Animals need inhibitory control to achieve goals when taking a detour, requiring self-regulation, decision-making, and spatial awareness to suppress direct approaches and find alternative routes. In amphibians, particularly salamanders, there is a considerable lack of information regarding inhibitory control. We examined this cognitive trait in two species of salamanders, Hynobius yiwuensis and Salamandrella tridactyla, across larval and post-metamorphic stages using a detour task where they had to navigate around a transparent barrier to reach food. Results indicate significant differences in detour behavior and inhibitory control across life-history stages and between species. While larvae of H. yiwuensis performed significantly better than the metamorphs in solving the task, metamorphs of S. tridactyla outperformed their larvae, with 100% of individuals successfully reaching the food. Task success, that is, reaching the food around the barrier, increased over trials, and individuals demonstrating greater persistence and lower latency were significantly more likely to succeed. Metamorphs exhibited significantly lower latency than larvae, indicating faster decision-making overall. However, this effect varied across species as H. yiwuensis metamorphs did not show reduced latency. Pecking and reverse (retreating from the barrier, reorienting, and approaching from a different direction), used as indicators of errors, decreased over successive trials, which could be interpreted as evidence of learning. Individuals of H. yiwuensis displayed significantly higher instances of committing errors compared to S. tridactyla. As individuals were lab-reared from eggs, the difference in cognitive abilities across species and developmental stages may reflect underlying genetic differences shaped by their distinct ecological adaptations and evolutionary trajectories.

Amphibians are experiencing significant declines due to habitat destruction, climate change, and the emergence of infectious diseases, such as chytridiomycosis. Despite their historical use as research models, standardized amphibian models are currently scarce. The Neotropics, particularly Colombia, host a remarkable diversity of amphibians, with approximately 876 species recorded. While hemoparasites are frequently reported in these species, their life cycles remain poorly characterized due to chronic infections and reliance on invertebrate vectors. This study identifies Rhinella horribilis (Wiegmann, 1833) as a promising animal model for pathogen research. These toads are widespread in the Neotropics; in fact, other members of this genus, such as Rhinella marina (Linnaeus, 1758), are invasive in some regions. They host a diverse range of blood and ectoparasites yet face minimal conservation concerns. We aimed to standardize the ex situ husbandry of R. horribilis under conditions that differed from its native habitat, successfully maintaining them for a period of 2 years. We describe optimal care protocols and present a case study monitoring trypanosome presence. Our findings support R. horribilis as a valuable model for studying amphibian pathogens. Their manageable size, non-lethal blood collection, broad distribution, and natural susceptibility to infections make them ideal for long-term research in physiology, ethology, microbiology, and parasitology. This model could facilitate studies on Batrachochytrium dendrobatidis (Bd) and blood parasites, advancing conservation efforts for endangered species.

Vector density plays a critical role in the transmission dynamics of vector-borne diseases and thus in their health and evolutionary effects. Despite extensive research on pathogens, controlled experimental studies on vector density effects remain limited. This study investigates the relationship between vector density and transmission using the model system of feral pigeon Columba livia, hippoboscid fly Pseudolynchia canariensis, and the haemosporidian blood parasite Haemoproteus columbae. Five experimental groups of pigeons were exposed to increasing numbers of infected louse flies (0-4 per bird) to quantify the resulting infection prevalence, transmission speed, and effects on host health and behavior. Over 50 days, infection prevalence correlated positively with vector density. Higher vector exposure linearly accelerated infection onset and increased prevalence. By day 80, all groups had reached 100% infection. With increasing vector densities, breathing rate decreased. Body temperature slightly increased in infected birds over time. These findings demonstrate the importance of vector density in shaping disease transmission and show how low vector densities limit parasite spread. The transmission power laws in similar systems may strongly depend on the morphology and life-history peculiarities of vector taxa. The pigeon-louse fly system offers a comfortable model system for experimental research on vector-borne disease ecology. The current study presents an experimental epidemiology template for quantifying the role of vector numbers and behavior in shaping transmission dynamics, parasite population structure, host-parasite co-evolution, and its health consequences.

Biodiversity monitoring is a crucial component of conservation, providing essential information on species occurrence, population dynamics, community composition, and ecosystem structure. Recently, to enhance wildlife protection, passive acoustic monitoring (PAM) technology has been developed based on animal sound characteristics and has become an important tool for wildlife monitoring. The vast amount of data generated by PAM has been transformed by the "big data" revolution, and research methods that integrate artificial intelligence (AI) with efficient and powerful machine learning models are rapidly advancing. The primary challenge is to isolate the vocalization data of target species from this massive dataset and to determine whether the developed methods can be applied to other species. In this study, we focused on the acoustic signals of a critically endangered white-headed langur, a primate species endemic to China. Unlike traditional methods that transform sound frequencies into spectrogram images, our approach uses a Deep Audio Detection Network (DeepADN) that directly converts audio into acoustic features, which are then fed into a convolutional neural network for accurate detection of white-headed langur calls, even in noisy environments. Our method optimized detection performance, achieving a recall rate of 98.22% and reducing manual review workload by 87.07%. Furthermore, DeepADN demonstrated cross-species applicability by successfully detecting François' langur calls, highlighting its potential for broader conservation monitoring efforts.