Ecology and Evolution最新文献

With the exception of a few groups of birds, such as large raptors and colonial seabirds, direct counts of nests cannot be conducted over very large areas for most of the abundant and widely distributed species, and thus indirect methods are used to estimate their relative abundances and population sizes. However, many species of the Family Hirundinidae (swallows and martins) build their mud nests in discrete, predictable and accessible sites, which are reused across years. Therefore, the direct count of active nests could constitute a reliable method for estimating breeding population sizes and their changes at large spatial and temporal scales. We illustrate the feasibility of this monitoring approach through a single year survey of >2700 nests of three coexisting Old-World species, the barn swallow (Hirundo rustica), the red-rumped swallow (Cecropis daurica), and the crag martin (Ptyonoprogne rupestris), distributed across Portugal and Spain. Our results revealed changes in the use of nesting substrates and increases in interspecific nest usurpation rates over recent decades. While 56% of the nests of C. daurica were located in rocks five decades ago, almost 100% are nowadays located in anthropogenic substrates such as bridges, road culverts, and abandoned buildings, which could have favored the range expansion of this species. Nest occupation rates were surprisingly low (12% in C. daurica, 21% in H. rustica, and 37% in P. rupestris), and the proportion of abandoned nesting sites was very high (65% in C. daurica, 50% in H. rustica, and 27% in P. rupestris). Abandonment rates reflect the population decline reported for H. rustica. Notably, the usurpation of nests of C. daurica by house sparrows Passer domesticus, which is the main cause of breeding failure, has increased from 2.4% in 1976–1979 to 34.7% of the nests nowadays. The long-term monitoring of nests may constitute a reliable and affordable method, with the help of citizen science, for assessing changes in breeding population sizes and conservation threats of these and other mud-nest building hirundines worldwide.

Gut microbiome of animals is affected by external environmental factors and can assist them in adapting to changing environments effectively. Consequently, elucidating the gut microbes of animals under different environmental conditions can provide a comprehensive understanding of the mechanisms of their adaptations to environmental change, with a particular focus on animals in extreme environments. In this study, we compared the structural and functional differences of the gut microbiome of grazing yaks between the summer and winter seasons through metagenomic sequencing and bioinformatics analysis. The results indicated that the composition and function of microbes changed significantly. The study demonstrated an increase in the relative abundance of Actinobacteria and a higher ratio of Firmicutes to Bacteroidetes (F/B) in winter, this process facilitated the adaptation of yaks to the consumption of low-nutrient forages in the winter. Furthermore, the network structure exhibited greater complexity in the winter. Forage nutrition exhibited a significant seasonal variation, with a notable impact on the gut microbiota. The metagenomic analysis revealed an increase in the abundance of enzymes related to amino acid metabolism, axillary activity, and mucin degradation in the winter. In conclusion, this study demonstrated that the gut microbiome of grazing yaks exhibits several adaptive characteristics that facilitate better nutrient accessibility and acid the host in acclimating to the harsh winter conditions. Furthermore, our study offers novel insights into the mechanisms of highland animal adaptation to external environments from the perspective of the gut microbiome.

Wolves (Canis lupus) exhibit contrasted activity patterns along their distribution range. The shift from diurnal to nocturnal habits within and among populations appears to be primarily driven by localized levels of human activity, with ambivalent responses toward such disturbance reported among populations. Yet, the drivers and the underlying individual variability of temporal avoidance patterns toward human remains unexplored. We equipped 26 wolves with GPS–GSM collars, obtaining 54,721 locations. We used step lengths, turning angles, and accelerometer data from recorded locations to infer activity through hidden Markov models (Conners, M. G., T. Michelot, E. I. Heywood, et al. 2021. “Hidden Markov Models Identify Major Movement Modes in Accelerometer and Magnetometer Data From Four Albatross Species.” Movement Ecology 9, no. 1: 1–16.). We further explored the probability of activity as a function of a set of proxies of anthropogenic disturbance at different spatial scales and its interaction with different periods of the day by fitting population-level and individual-based hidden Markov models. Wolves were predominantly active during dusk and night, yet variations in activity emerged among individuals across day periods. We did not find clear population-level effects of anthropogenic disturbance predictors, as these were masked by a wide range of individual-specific responses, which varied from positive to negative, with inter-individual variability in responses changing according to different predictors and periods of the day. Our results suggest a non-uniform strategy of wolves in adapting their behavior to human-dominated environments, further underscoring the role of vegetation patches acting as functional refuge cover for buffering the effects of anthropogenic disturbance and boosting the persistence of the species in human-dominated landscapes. This study, for the first time, reveals the individual variability in wolf responses to human disturbance. By fitting hidden Markov models to data from GPS–GSM collars deployed on 26 wolves, we found significant variation between individuals in their responses to different levels of anthropogenic pressure and across different times of day, highlighting a non-uniform strategy for coping with perturbations in human-dominated landscapes. Our findings underscore the diverse behavioral adjustments employed by wolves to persist in these environments and highlight the critical importance of vegetation patches serving as refuge cover.

Managing feral water buffalo in the Northern Territory is a formidable challenge. As an introduced species, buffalo are associated with a myriad of biosecurity, economic, cultural and environmental issues ranging from overgrazing, decreased water quality, disease vectors to the destruction of cultural assets. Nevertheless, the buffalo are also a harvestable resource that can support economic development of the region. To mitigate some of the biosecurity, economic, cultural and environmental risks they pose and manage buffalo effectively, we need a detailed understanding of their spatial and behavioural ecology. However, several factors make understanding how best to manage the dense populations of wild individuals challenging as buffalo inhabit remote areas with limited infrastructure and accessibility and their large size and often aggressive nature can make them difficult to observe in otherwise inaccessible areas. GPS tracking allows for high-frequency data collection and surveillance of individual buffalo. Here, we investigated how the different seasonal periods of a Northern Territory floodplain area shaped patterns of habitat use for 17 buffalo tracked over 16 months. We found in the dry season, buffalo space use is restricted, and the size of home ranges are significantly smaller than in the wet season. During the wet season, buffalo expand their home range area as well as their social encounter area with other buffalo. These differences in their space use and social patterns suggest that increased disease surveillance may be needed for the wet season when buffalo are more likely to share space and interact. During the dry season, however, buffalo movement is more predictable and restricted, suggesting greater optimisation opportunities for buffalo management. Results from these models can be used by land holders, Traditional Owners and wildlife managers to make evidence-based decisions to improve buffalo management with respect to disease risk, sustainable harvest and damage to environmental and cultural assets.

Measuring the outcome of practical interventions and actions helps to inform conservation management objectives and assess progress towards objectives and targets. Measuring success also informs future management by identifying actions that are effective and those that are not. Scrub vegetation is an important habitat type in terrestrial ecosystems, providing important shelter and food resources for biodiversity and livestock. Much of practical land management in the UK involves the monitoring and management of scrub, and current drone-based methods of scrub collection requires expensive equipment or complex methods. A 2021 paper determined a cheap and simple way to determine scrub levels, and this could potentially be used to map temporal changes, as well as identify directional change in scrub. This study looks at whether the method outlined in the 2021 study could be used to measure temporal and directional changes in scrub cover on two nature reserves in the UK: Daneway Banks in Gloucestershire and Flat Holm Island in the Severn Estuary. Scrub levels at Daneway Banks increased from 14.63% in 2015 to 16.52% in 2017, before decreasing to 14.89% in 2021 due to managed cutting and clearing. Scrub cover at Flatholm Island decreased from 10.18% in 2019 to 8.71% in 2021. The exact locations of scrub growth and loss for each site was also calculated and mapped. This approach was found to be a viable way of measuring temporal and directional change in scrub levels. The data can also be used to reframe changes in scrub levels as a shift towards vegetation succession or reduction, to better visualise how changes in scrub levels affect overall site management goals, and is a cheaper, more accessible alternative to current methods of measuring temporal vegetation changes.

Ceracris nigricornis Walker is an insect of the Acrididae, which can harm bamboo, rice, corn, sorghum and other crops, and can cause serious economic losses. In this study, based on 234 occurrence sites of C. nigricornis obtained from the Global Biodiversity Information Facility and literature, and data of three future climate scenarios presented by CMIP6, two niche models (GARP, MaxEnt) were used to predict the suitable area of C. nigricornis in China. The result shows that the main environmental factors affecting the distribution of C. nigricornis are min temperature of coldest month (bio6), mean temperature of coldest quarter (bio11), precipitation of driest month (bio14) and precipitation of wettest quarter (bio16). From the result of MaxEnt model, it can be seen that the suitable area of C. nigricornis in China is 128.91 × 10⁴ km² under current scenario. It will decrease by 3.19% in the 2050s and then increase by 12.04% in the 2090s under the SSP1-2.6 scenario, increase by 5.79% in the 2050s and then decrease by 7.53% in the 2090s under the SSP2-4.5 scenario, and increase by 33.03% in 2050s and then decrease by 23.31% in the 2090s under SSP5-8.5 scenario. From the result of GARP model, it can be seen that the suitable area of C. nigricornis in China is 166.09 × 10⁴ km² under current scenario. It will increase by 8.41% in 2050s and then continue to increase by 6.11% in 2090s under SSP1-2.6 scenario, increase by 23.84% in the 2050s and then decrease by 0.88% in the 2090s under the SSP2-4.5 scenario, and increase by 34.37% in 2050s and then decrease by 1.75% in 2090s under SSP5-8.5 scenario. The boundaries of suitable areas will expand to the north and southwest of China under future climate change scenarios, specially in Sichuan, Chongqing and Yunnan. Local forestry authorities should strengthen the monitoring of bamboo forests to prevent the damage caused by the introduction of C. nigricornis.

The processes of developmental stability, canalization, and phenotypic plasticity have ecological and evolutionary significance, and been studied extensively, but mostly separately and thus the relationships between them are not straightforward. Our objective was to better integrate these processes in the context of temporally heterogeneous environments. We did this by investigating the effects of early experience with temporal heterogeneity in water availability on associations between developmental stability, canalization, and phenotypic plasticity. We subjected eight plant species to a first round of alternating inundation and drought vs. constantly moderate water treatments (heterogeneous experience) and a second round of water conditions (to test plasticity). We measured fluctuating asymmetry (FA) in leaf size, intra- and inter-individual variation (CV_intra and CV_inter), and plasticity (PI) in traits and analyzed correlations between these variables across all species. Results showed little correlations between FA, CV_intra and PI, several positive correlations between FA and CV_inter in more stressful conditions, especially in as well as positive correlations between CV_inter and PI initially and negative correlations between them later. These suggested the complexity of these relationships, which can depend on whether plasticity occurs. Greater inter-individual variation will more likely cooperate with plasticity before or during plastic response, whereas higher canalization may reflect phenotypic convergence. Both higher FA and CV_intra can reflect faster growth, while CV_intra may also reflect plant growth stage, and the two mechanisms should cooperate in response to environmental challenges. The complexity of these relationships suggests plants deal with environmental variation in elaborate and integrative ways which can be affected by many factors.

Cueva del Castillo, R., Sanabria-Urbán, S., Mariño-Pérez, R., & Song, H. (2024). Annual temperature, body size, and sexual size dimorphism in the evolution of pyrgomorphidae. Ecology and Evolution, 14, e70188. https://doi.org/10.1002/ece3.70188

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Species distribution models (SDMs) are widely used to project how species distributions may vary over time, particularly in response climate change. Although the fit of such models to current distributions is regularly enumerated, SDMs are rarely tested across longer time spans to gauge their actual performance under environmental change. Here, we utilise paleozoological presence/absence records to independently assess the predictive accuracy of SDMs through time. To illustrate the approach, we focused on modelling the Holocene distribution of the hartebeest, Alcelaphus buselaphus, a widespread savannah-adapted African antelope. We applied various modelling algorithms to three occurrence datasets, including a point dataset from online repositories and two range maps representing current and ‘natural’ (i.e. hypothetical assuming no human impact) distributions. We compared conventional model evaluation metrics which assess fit to current distributions (i.e. True Skill Statistic, TSS_c, and Area Under the Curve, AUC_c) to analogous ‘paleometrics’ for past distributions (i.e. TSS_p, AUC_p, and in addition Boyce_p, F2-score_p and Sorensen_p). Our findings reveal only a weak correlation between the ranking of conventional metrics and paleometrics, suggesting that the models most effectively capturing present-day distributions may not be the most reliable to hindcast historical distributions, and that the choice of input data and modelling algorithm both significantly influences environmental suitability predictions and SDM performance. We thus advocate assessment of model performance using paleometrics, particularly those capturing the correct prediction of presences, such as F2-score_p or Sorensen_p, due to the potential unreliability of absence data in paleozoological records. By integrating archaeological and paleontological records into the assessment of alternative models' ability to project shifts in species distributions over time, we are likely to enhance our understanding of environmental constraints on species distributions.

Fatty acids (FAs) are vital biomolecules crucial for determining food quality for higher trophic levels. To investigate FA transfer and turnover time in predators, we conducted a diet switch experiment using jellyfish polyps. These polyps were fed food sources including Artemia sinica nauplii and FA-manipulated copepod Pseudodiaptomus annandalei, maintained on distinct algal diets with varied FA compositions. Our findings reveal that copepods may have a strong potential to synthesize long-chain polyunsaturated FA to maintain biochemical homeostasis when consuming low-quality food. Consequently, the species-specific fatty acid composition within plankton, combined with effects of seasonal environmental fluctuations and climate change, leads to changes in the FA composition of foundational food web components. These alterations create a complex “nutrient black box” effect as they propagate up trophic levels. Our study shows that jellyfish polyps fail to accumulate EPA and DHA but display high levels of ARA compared to their zooplankton and phytoplankton food sources, suggesting a potential association with dietary EPA and DHA through an unidentified pathway. Certain FA components indicate variations in the turnover time when polyps undergo a dietary shift. Understanding the trajectory of FA metabolism across the “phytoplankton–zooplankton” interface, along with its turnover time, provides crucial insights for modeling diet estimation of components within food webs.