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Frontiers in Ecology and Evolution
Number of Followers: 50  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2296-701X
Published by Frontiers Media Homepage  [96 journals]
  • Adaptive slope reliability analysis method based on sliced inverse
           regression dimensionality reduction

    • Authors: Zheng Zhou, Hai-Bin Xiong, Wen-Xia Wu, Yi-Jian Yang, Xu-Hai Yang
      Abstract: The response surface model has been widely used in slope reliability analysis owing to its efficiency. However, this method still has certain limitations, especially the curse of high dimensionality when considering the spatial variability of geotechnical parameters. The slice inverse regression dimensionality reduction method is efficient to obtaining the dimensionality-reduction variables from the original soil parameters space, before constructing the response surface. However, the dimensionality reduction process may cause accuracy deficiency due to the loss of variable information. An adaptive slope reliability analysis method is proposed to quantify and correct information loss and errors. Additionally, the slope failure probability based on the response surface in the dimensionality reduction space is modified to an unbiased one based on the finite model in the original space. In this study, two soil slopes considering spatial variability are taken as examples. The results illustrate that this method can effectively reduce the loss of accuracy in the dimensionality reduction process, while obtaining unbiased finite-element-based failure probability effectually. The method addresses the limitation whereby the accuracy of the dimensionality reduction process depends on the sample size and the number of dimensionality-reduction variables. Simultaneously, the proposed method significantly improves the computational efficiency of the sliced inverse regression method and realizes a reasonable dimensionality reduction effect, thereby improving the application of the response surface in practical slope reliability high-dimensional issues.
      PubDate: 2023-09-22T00:00:00Z
       
  • Regional differences and evolution trends of China’s industrial
           green transformation

    • Authors: Chunyan Liu, Jun Xu, Jun Zhao
      Abstract: Green and low-carbon development is the direction of the current technological revolution and industrial transformation, while China is still in the historical stage of deep industrialization and has yet to completely break away from the high-input, high-consumption, and high-emission development method, and is still facing serious challenges in terms of improving the efficiency of resource utilization and reducing pollution emissions. To effectively promote China’s industrial green transformation, it is necessary to accurately grasp its development connotations and scientifically realize the measurement of industrial green transformation. Therefore, this paper measures the efficiency of China’s industrial green transformation, based on the directional distance function and the Global Malmquist-Luenberger (GML) index, to portray its distribution dynamics, regional differences and further identify its growth drivers. The results found that the overall efficiency of China’s industrial green transformation has been steadily increasing, and that the regional pattern is characterized by northwestern, northeastern, central, eastern and southwestern regions, in that order. The Markov chain estimates show that industrial green transformation efficiency is most likely to remain in its original state, with probabilities of 88.31%, 63.54%, 42.86%, and 75.61% for low, medium-low, medium-high, and high levels respectively, but also has a jump shift characteristic, with a certain possibility of falling back from the high-efficiency state to the low state. Dagum Gini coefficient estimation results show that differences between groups in the five major regions are the main source of the widening differences in the overall industrial green transformation, with the contribution remaining at around 60%. Further research suggests that economic growth, technological progress, foreign trade, and foreign direct investment (FDI) may lead to a widening of the efficiency gap in industrial green transformation, while the industrial structure and outward foreign direct investment (OFDI) help to reduce spatial differences to some extent. Based on the above conclusions, this paper proposes some countermeasures to promote the overall improvement and coordinated development of China’s industrial green transformation.
      PubDate: 2023-09-22T00:00:00Z
       
  • Environmental and spatial factors play different roles in phytoplankton
           community assembly in different hydrological seasons in Lake Wuchang,
           China

    • Authors: Zihao Meng, Kang Chen, Feifei Hu, Lu Liu, Deguo Yang, Xuemei Li
      Abstract: Lake phytoplankton communities are affected by environmental and spatial factors. We studied the relative importance of environmental and spatial factors on the phytoplankton community assembly in Lake Wuchang across three hydrological seasons, which were divided into dry (December to March), normal (April to June, October to November) and wet seasons (July to September) based on the water level and depth. Spatial and temporal patterns of environmental factors and phytoplankton community composition and diversity were studied using Kruskal–Wallis test, Wilcoxon test and NMDS. CCA, Mantel and partial Mantel tests, and PLS-PM were used to investigate the effects of environmental and spatial factors on phytoplankton community characteristics. Results showed that phytoplankton assemblages at the eight study sites were composed of totally 244 species belonging to 9 phyla, which changed from Bacillariophyta and Chlorophyta to Cyanophyta across the whole hydrological period. There was significantly higher abundance and biomass in the normal and wet seasons than that in the dry season. Phytoplankton alpha diversity exhibited uniform temporal distribution patterns with higher values in the dry season than in the normal and wet seasons. The Mantel and partial Mantel tests revealed that environmental (physicochemical conditions of lake water) and spatial factors (geographic distances among sites) jointly affected the phytoplankton community structure and beta diversity across the hydrological seasons, while spatial factors were more important in the wet season. Partial least squares path models showed that spatial factors exhibited a significant positive correlation with the phytoplankton diversity with the path coefficients of 0.53 and 0.71 in the normal and wet seasons, respectively. Phytoplankton composition had significant correlation with on phytoplankton diversity with the path coefficient of −0.75 and 0.61 in the normal and wet seasons, respectively. Our findings revealed that both environmental and spatial factors affected the phytoplankton community assembly in Lake Wuchang. Environmental factors played a more important role in the dry season, while spatial factors were more important in the wet season. With the exception of the abiotic factors (environmental and spatial), the impacts of biotic factors on phytoplankton community cannot be ignored. Therefore, it is also necessary to strengthen further research on the top-down control over phytoplankton communities in Lake Wuchang.
      PubDate: 2023-09-22T00:00:00Z
       
  • A survey of blow fly (Diptera: Calliphoridae) populations in Phoenix,
           Arizona

    • Authors: Andrew W. Meeds, Travis W. Rusch, Danielle L. Falcone, Lauren M. Weidner
      Abstract: Utilizing insects in legal investigations as a tool for estimating forensically important timelines (e.g., minimum post-mortem interval (min-PMI)) is becoming more commonly used and accepted throughout the world. In the United States much of the climate is temperate, however, the Sonoran Desert is an arid location with extreme heat and irregular rainfall. Work on forensically relevant insects in this region is severely understudied. This study surveyed the populations of forensically important blow flies (Diptera: Calliphoridae) in Phoenix, Arizona for one year using traps baited with four different food sources. Nine species across four genera were collected with Lucilia sericata, Calliphora latifrons, and Lucilia mexicana accounting for 98.6% of total blow flies captured in the baited traps. Abundance drastically changed throughout the year, ranging from 500+ flies to 0 flies captured in a month, with species abundance correlating with temperature and humidity. These results reveal that environmental conditions (i.e., maximum temperature and relative humidity) may limit blow fly activity or seasonally remove (or make inactive) entire local populations, thus affecting their ability to colonize remains and produce an accurate min-PMI.
      PubDate: 2023-09-21T00:00:00Z
       
  • Genetic connectivity constrained by natural barriers in a key agricultural
           pest: insights from mitochondrial DNA analysis

    • Authors: Jinyu Li, Yi Mao, Kai Li, Wei Chen, Linyang Sun, Bang Zhang
      Abstract: In the context of anthropogenic global change, the study of landscape effects on species movement has garnered increasing attention. Landscape genetics offer indirect yet attractive means to capture species dispersal events across generations and their interaction with landscapes. However, landscape genetic patterns tend to exhibit significant variations across taxa and rely on the molecular makers adopted. Here, we investigated how landscapes influence population connectivity of an important tea pest, Empoasca onukii, using mitochondrial DNA sequences of 1,518 individuals from 57 locations in mainland China and offshore islands. We analyzed the inter-population genetic divergence and integrated multiple models to explicitly quantify their association with geographic distance, environmental heterogeneity, and landscape barriers. Analyses revealed a reduction in gene flow on islands, along the Yangtze River, and across mountainous regions of Western China. Models explicitly detected the predominant contributions of topographic complexity to population divergence and evidenced that mountains may serve as effective dispersal barriers for E. onukii. These results suggest that the limited gene exchange resulting from low population connectivity among mountains might generate the observed patterns of mitochondrial genetic variations, which contrasts the climate-related pattern previously observed on microsatellites. The findings enhance our comprehension of the evolutionary and epidemic dynamics of E. onukii, and highlight the demand of considering species-specific traits when studying population landscape genetic patterns. Moreover, the study emphasizes the necessity of employing multiple molecular markers to comprehensively elucidate landscape effects on population connectivity across diverse species for valuable insights into biodiversity conservation, pest control, and other management decisions.
      PubDate: 2023-09-21T00:00:00Z
       
  • Ecological vulnerability assessment of coral islands and reefs in the
           South China Sea based on remote sensing and reanalysis data

    • Authors: Yuan Ma, Changbo Jiang, Shanshan Li, Yizhuang Liu, Xiaofeng Wen, Yuannan Long, Shuai Yuan, Yuantai Kang, Yongjie Wang, Ruixuan Wu
      Abstract: Coral reefs are ecosystems that are highly vulnerable to external environmental impacts, including changes associated with ocean acidification and global warming. Assessing the vulnerability of coral reef growth environments over large areas of the sea is a difficult and complex process, as it is influenced by many variables. There are few studies on environmental vulnerability assessment of coral islands and reefs in the South China Sea. It is therefore particularly important to understand the environmental sensitivity of corals and how coral communities respond to changes in climate-related environmental variables. In this study, indicators were selected mainly from natural environmental factors that hinder the development of coral reefs. The sea surface temperature (SST), sea surface salinity (SSS), wind velocity (WV) and direction, sea level height (SL), ocean currents (OC), and chlorophyll concentration (Chl) of coral reefs in South China Sea Island were integrated to calculate the coral reef environmental vulnerability region. In a GIS environment, Spatial Principal Component Analysis (SPCA) was used to develop sensitivity models and evaluate the ecological vulnerability of coral reefs. Based on the Environmental vulnerability indicator (EVI) values, the study area was classified as 5 grades of ecological vulnerability: Potential (0.000–0.577), Light (0.577–0.780), Medium (0.780–0.886), Heavy (0.886–0.993) and Very Heavy (0.993–1.131). Sensitivity models identified regional gradients of environmental stress and found that some coral reefs in western Malaysia and southwestern Philippines have higher vulnerability. Meanwhile, the study found that the reefs of Paracel Islands and Macclesfield Bank areas of medium vulnerability. Future use of high-precision data from long time series will allow better estimates of site-specific vulnerability and allow for the precise establishment of marine protected areas so that the ecological diversity of coral reefs can be sustained.
      PubDate: 2023-09-21T00:00:00Z
       
  • Habitat quality assessment and multi-scenario prediction of the
           Gansu-Qinghai section of the Yellow River Basin based on the FLUS-InVEST
           model

    • Authors: Jie Yang, Baopeng Xie, Degang Zhang, Erastus Mak-Mensah, Tingting Pei
      Abstract: Research on the impact of land use change on regional habitat quality, in various future scenarios, can effectively aid planning and decision-making for sustainable development at a regional level. The study conducted its research in the Gansu-Qinghai Yellow River section and used ArcGIS and a land use transfer matrix to analyze the spatiotemporal pattern of land use and land cover changes. The study assessed the changes in habitat quality in the Gansu-Qinghai Yellow River region between 1990 and 2020, using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, by evaluating the gains and losses. Simultaneously, 15 elements of the natural economy were chosen and examined for their temporal and spatial impact on habitat quality using the random forest model and spatially weighted regression model. To forecast land use changes in the Gansu-Qinghai Yellow River section for 2030, the Future Land Use Simulation Model (FLUS) model was utilized and a series of four scenarios (cultivated land protection scenario, ecological protection scenario, natural development scenario, and rapid development scenario) were employed. The research results indicate that over 70% of the Gansu-Qinghai Yellow River is occupied by grasslands, and only a small portion of the area, about 0.22%, is developed for construction purposes. The quality of the habitat in the Gansu-Qinghai Yellow River had a minor drop between 1990 and 2020, followed by an improvement. Habitat quality changes are primarily attributed to improvements, with variations across different areas, i.e., enhanced in the east and reduced in the central and western parts. The habitat quality of the Gansu-Qinghai Yellow River has improved in all four scenarios compared to 2020, as evidenced by the decrease in low-value habitats and increase in high-value areas. The ecological protection scenario has the highest average habitat quality value. These research results can be used to support policy development and ecological restoration initiatives in the Gansu-Qinghai Yellow River.
      PubDate: 2023-09-21T00:00:00Z
       
  • Research on the application and promotion of the carbon neutral concept
           based on the attention mechanism in football under the end-to-end
           architecture|Introduction|Methods|Results|Discussion

    • Authors: Mingda Hou, Xilin Mu, Shuyong Liu
      Abstract: IntroductionIn light of escalating concerns regarding global warming and environmental pollution, the pursuit of carbon neutrality has emerged as a pivotal strategy to address climate change on a global scale. As society becomes increasingly conscious of its ecological impact, various sectors, including sports, are urged to embrace environmental responsibility. This study seeks to explore the integration of a carbon neutral framework utilizing artificial intelligence's attention mechanism within the realm of football, with the aim of contributing to football's adoption of carbon neutrality.MethodsThe study commences by introducing an end-to-end architectural framework capable of unifying and optimizing all facets of football to realize a comprehensive carbon-neutral objective. This architecture serves as a consolidated platform for enhancing carbon emission reduction within football pedagogical activities, fostering synergy among diverse constituents while concurrently assessing the equilibrium between carbon reduction and pedagogical effectiveness. Subsequently, attention mechanisms are leveraged to heighten the efficacy and comprehensibility of carbon-neutral strategies. The application of attention mechanisms enables the model to autonomously focus on attributes or regions closely associated with carbon neutrality objectives, thereby facilitating precision and efficacy in recommending carbon neutral strategies. By employing attention mechanisms in football, a more thorough understanding of carbon emissions' dynamics is attained, allowing for the identification of pivotal emission contributors and tailored suggestions for emission mitigation. Furthermore, the Long Short-Term Memory (LSTM) method is employed to analyze football time-series data. Given football's intricate sequence of actions, the LSTM technique adeptly captures long-term dependencies, offering improved analysis and optimization of carbon emissions during football activities.ResultsThe integrated end-to-end architectural framework offers a holistic approach to carbon-neutral football strategies. Attention mechanisms effectively enhance the focus and interpretation of carbon-neutral strategies, contributing to precise and impactful recommendations. Employing LSTM for time-series analysis aids in comprehending carbon emission dynamics, enabling the identification of efficacious carbon neutral strategies. The study underscores the potential of AI-driven attention mechanisms and LSTM in fostering carbon neutrality within football.DiscussionThe study's findings underscore the viability of integrating AI-driven methodologies, specifically attention mechanisms and LSTM, to promote carbon neutrality within the football domain. The end-to-end architecture serves as a foundational platform for comprehensive carbon emission reduction, offering potential for broader application in other sectors. The combination of attention mechanisms and LSTM engenders deeper insights into carbon emissions' intricate temporal dynamics, informing the development of targeted strategies for emission mitigation. The study's outcomes provide theoretical underpinnings for advancing sustainable football practices and inspire the broader adoption of carbon neutrality principles across diverse domains.
      PubDate: 2023-09-20T00:00:00Z
       
  • Monitoring marine pollution for carbon neutrality through a deep learning
           method with multi-source data
           fusion|Introduction|Methods|Results|Discussion

    • Authors: Bin Wang, Lijuan Hua, Huan Mei, Yanyan Kang, Ning Zhao
      Abstract: IntroductionMarine pollution can have a significant impact on the blue carbon, which finally affect the ocean’s ability to sequester carbon and contribute to achieving carbon neutrality. Marine pollution is a complex problem that requires a great deal of time and effort to measure. Existing machine learning algorithms cannot effectively solve the detection time problem and provide limited accuracy. Moreover, marine pollution can come from a variety of sources. However, most of the existing research focused on a single ocean indicator to analyze marine pollution. In this study, two indicators, marine organisms and debris, are used to create a more complete picture of the extent and impact of pollution in the ocean.MethodsTo effectively recognize different marine objects in the complex marine environment, we propose an integrated data fusion approach where deep convolutional neural networks (CNNs) are combined to conduct underwater object recognition. Through this multi-source data fusion approach, the accuracy of object recognition is significantly improved. After feature extraction, four machine and deep learning classifiers’ performances are used to train on features extracted with deep CNNs.ResultsThe results show that VGG-16 achieves better performance than other feature extractors when detecting marine organisms. When detecting marine debris, AlexNet outperforms other deep CNNs. The results also show that the LSTM classifier with VGG-16 for detecting marine organisms outperforms other deep learning models.DiscussionFor detecting marine debris, the best performance was observed with the AlexNet extractor, which obtained the best classification result with an LSTM. This information can be used to develop policies and practices aimed at reducing pollution and protecting marine environments for future generations.
      PubDate: 2023-09-19T00:00:00Z
       
  • Comparing two strategies of counter-defense against plant toxins: a
           modeling study on plant–herbivore
           interactions|Introduction|Methods|Results and discussion

    • Authors: Suman Chakraborty, Jonathan Gershenzon, Stefan Schuster
      Abstract: IntroductionVarious herbivorous insects prefer toxic plants as their hosts, although this may appear paradoxical. They have evolved specific adaptations (called counter-defenses) against the toxins. For example, the two-component chemical defense system of plants of the Brassicaceae family against herbivores consists of glucosinolates (GLSs) and the activating enzyme myrosinase. GLS hydrolysis by myrosinase leads to isothiocyanates (ITCs), which are toxic and deterrent to many insect herbivores. Two different types of counter-defenses can be distinguished: a preemptive counter-defense that prevents the GLSs from being hydrolyzed to ITCs due to metabolic redirection and direct counter-defense, where the ITCs are formed but then metabolized to non-toxic conjugates. In general, preemptive counter-defense is only a possibility if the plant stores a precursor of the toxin, which is activated upon attack. Preemptive counter-defense is believed to be more efficient due to the lower exposure to ITCs, but this has not been satisfactorily demonstrated experimentally.MethodsHere, we derive on theoretical grounds the conditions under which preemptive counter-defense reduces exposure to ITCs compared to direct counter-defense by studying the dynamics of GLS defense and counter-defense with two separate ordinary differential equation models. We model how herbivory transfers the GLSs to the insect gut with the leaf material. Thereafter, we describe the insects’ exposure to toxins by deriving the dynamics of ITCs in the gut during feeding with the two types of counter-defenses.Results and discussionBy calculating the area under the curve (AUC) of the ITC concentrations, we show, based on empirical data, that herbivores with a preemptive detoxification system are usually less exposed to ITCs. In addition, our models explain how the decline in the level of ITCs is achieved by both counter-defenses, which helps to understand the overall mechanisms and benefits of these techniques. Our results may also apply to plant defenses by inactive toxin precursors other than GLSs as well as to insects that sequester such precursors for their own defense.
      PubDate: 2023-09-19T00:00:00Z
       
  • Aging trajectories are trait- and sex-specific in the long-lived Alpine
           swift

    • Authors: Héloïse Moullec, Sophie Reichert, Pierre Bize
      Abstract: Senescence is defined as the general deterioration of the organism (i.e. physiology, morphology, reproduction), and is associated with increasing mortality and decreasing fertility with age. Although senescence has now been widely reported in wild animals, little is known on whether senescence affects all traits, whether this process is synchronized across traits, and whether males and females are affected in the same way. Using an individual-based monitoring of 20+ years in free-living population of Alpine swifts (Tachymarptis melba), we investigated age-dependent variation between sexes and between six biometric traits, 4 reproductive traits, and 1 measure of parasite burden. We accounted for selective disappearance and terminal effects in our analyses. Our results provide general support for age-dependent variation at adulthood in 8 out of the 11 traits investigated. Most traits showed a variation with 2 thresholds, with first a strong improvement until 4 to 12 years of age (e.g., increased fork length, decreased parasite load, or earlier laying date) followed by a plateau and a decline at older ages. The age of the second threshold showed sex specific asynchrony, with an earlier threshold in males than in females for tail length, parasite burden and laying date, as well as moderate asynchrony across traits. Rates of senescence differed between sexes, with stronger senescence of the tail in females than in males and with evidence of reproductive senescence in females but not in males. We also found evidence of terminal investment in males with respect to brood size at hatching and terminal decline with increased asymmetry of the fork and decreased body mass. We found evidence of selective appearance with males with longer fork and little fork asymmetry starting to reproduce earlier in life, and females that start to reproduce earlier tending to higher reproductive success. Finally, we found selective disappearance of males with longer tails and marginal effect of selective disappearance of females with lower body mass. We discuss how natural or sexual selection may have led to these trait- and sex-specific patterns of aging in this long-lived bird.
      PubDate: 2023-09-19T00:00:00Z
       
  • Geography, climate and shifts in host plants distribution explain the
           genomic variation in the cactus moth

    • Authors: Daniel Poveda-Martínez, Víctor Noguerales, Stephen D. Hight, Guillermo Logarzo, Brent C. Emerson, Laura Varone, Esteban Hasson
      Abstract: Landscape heterogeneity and the host plant use are factors suggested to play determinant roles in shaping the evolutionary history of herbivorous insects. However, the role of the reconfiguration of host plants distributions linked to Quaternary climate oscillations as drivers of contemporary population genetic structure is still poorly understood. Here, we formally examine the relative contribution of such factors on intraspecific diversification using the South American cactus moth, Cactoblastis cactorum, an herbivore insect specialized in the use of cacti as host plants. We assessed genomic variation using genome-wide SNPs and mitochondrial data in populations sampled across a broad geographical gradient where moths feed on different cactus species. We integrated demographic simulations and ecological niche modeling into a landscape genomics framework, to test alternative hypotheses of past and current population connectivity for both C. cactorum and its host plants. Regions exhibiting higher genomic diversity were evaluated for congruence with areas where suitable climatic conditions remained stable through time. Our results revealed that past spatial configuration of suitable habitat conditions and shifts of host plants distributions are the factors that better explain the intraspecific diversification. Genomic data also supported the hypothesis that areas of long-term habitat stability served as refugia for C. cactorum, enabling the maintenance of high levels of genetic diversity over time. Overall, our study highlights the importance of integrating inter-specific interactions and their spatio-temporal dynamics to better understand the relative importance of abiotic and biotic factors driving the diversification processes in herbivorous insects with broad geographical and restricted host ranges.
      PubDate: 2023-09-19T00:00:00Z
       
  • Corrigendum: Editorial: Neuroethology of the colonial mind: ecological and
           evolutionary context of social brains

    • Authors: J. Frances Kamhi, Mathieu Lihoreau, Sara Arganda
      PubDate: 2023-09-19T00:00:00Z
       
  • Editorial: Microbial volatiles and communication

    • Authors: Dani Lucas-Barbosa, Niels O. Verhulst, Viviane Cordovez
      PubDate: 2023-09-19T00:00:00Z
       
  • Analytical analysis for horizontal displacement of pile anchor support
           structure considering prestress

    • Authors: Yong-qiang Ling, Lei Song, Jian Hao, Xiao-lin Cao, Xiao-hui Yang
      Abstract: The pile-anchor supporting structure is widely used in foundation pit engineering, it is particularly necessary for calculating lateral displacement of the pile-anchor supporting structure. The soil stress state is transformed by the additional stress caused by the prestress, thus the lateral displacement can be decreased own to pile-anchor supporting structure bearing active earth pressure had changed. Prestress as a concentrated force is decomposed into the horizontal component and vertical component, calculating the additional stress caused by the prestress and getting the formula of active earth pressure of considering the additional stress, setting up calculation model of the pile-anchor supporting structure. For typical examples of foundation pit engineering, the parameters are substituted into a program written based on derived formulas, and the elastic deformation superposition method is used to calculate the horizontal displacement of the pile anchor support structure. The comparison and verification is carried out by Finite element analysis. The influence of cohesion and friction angle on pile displacement, bending moment, and shear force has been studied. This study found that cohesion and friction angle have a significant impact on the displacement of pile anchor support structures.
      PubDate: 2023-09-18T00:00:00Z
       
  • Y chromosome evidence confirms northeast Asian origin of Xinjiang Kazakhs
           and genetic influence from 18th century expansion of Kerey
           clan|Abstract|Methods|Results and discussion

    • Authors: Bangyan Wang, Jiayu Liang, Edward Allen, Xin Chang, Zixi Jiang, Yao Yu, Meisen Shi, Shaoqing Wen
      Abstract: AbstractThe Kazakhs of Xinjiang province are characterized by their nomadic lifestyle and patrilineal clan system. However, compared to Central Asian Kazakhs, a lack of Y chromosomal high-resolution analysis has hindered our understanding of the paternal history of modern Xinjiang Kazakhs.MethodsIn this study, we present the analysis of 110 Y-SNP data from 209 Altay Kazakhs and 201 Ili Kazakhs in Xinjiang, along with their previously reported 24 Y-STR loci data.Results and discussionWe found that the Y chromosome haplogroups exhibit greater diversity in Altay Kazakhs compared to Kazakhs in Kazakhstan, Russia, and other regions of China. Y-SNP-based PCA plots reveal that both the Altay and Ili Kazakhs are situated between the Turkic, Mongolia, and Tibeto-Burman clusters. The dominant haplogroup C2a1a3-F1918, which originated in northeast Asia during the Neolithic Age, accounts for nearly half of the Altay and Ili Kazakhs. The Y lineage network of C2a1a3-F1918 contained two subclusters. Approximately 60.6% of the Altay Kazakhs belong to the DYS448-23 subcluster, indicating their Kerey-Abakh ancestry. On the other hand, around three-quarters of the Ili Kazakhs belong to the DYS448-22 subcluster, suggesting their Kerey-Ashmaily heritage. Notably, the TMRCA ages of the DYS448-23 subcluster were calculated to be 289.4 ± 202.65 years, which aligns with the historical immigration of the Kerey clan back to the Altay Mountains after the defeat of the Dzungar by the Qing dynasty in the mid-18th century.
      PubDate: 2023-09-18T00:00:00Z
       
  • Spatial−temporal variation of ecological environment quality and driving
           factors from 2000 to 2020 in Wuliangsu Lake Basin, Northern China

    • Authors: Caixia Li, Guoqi Chai, Zhiyuan Li, Xiang Jia, Lingting Lei, Long Chen, Yunfan Li, Yunfeng Cao, Ruoning Zhu, Xiaoli Mei, Xiaoli Zhang
      Abstract: Due to global climate change and the intensification of human activities, the ecological function of Wuliangsu Lake Basin has been seriously degraded. Obtaining accurate spatial–temporal dynamics of regional ecological environment quality is essential for the evaluation of ecological management and restoration effects. This study assessed the trend changes and drivers of the Remote Sensing Ecological Index (RSEI) in the Wuliangsu Lake Basin from 2000−2020. Firstly, the trend analysis method and hurst index were used to analyze the temporal and spatial variation of RSEI. Then the main factors of RSEI variation were analyzed using meteorological data, integrated nighttime lighting data, and population density data. Overall, the RSEI shows an increasing trend from the west to the east with a rate of 0.0034 year−1 over the last 21 years. The area change of RSEI was 54.22%, 63.80% and 52.43% for 2000−2006, 2007−2013 and 2014−2020, respectively, which indicates that most areas have a stable ecological environment. However, the overall Future Improvement Trend (FIT) area of RSEI is 42.21%, mainly in Dengkou area, Urad Qianqi and central area. This indicates that the RSEI remains stable locally and shows an overall improving trend. The results of the correlation analysis showed that the areas influenced by meteorological and human factors were highly coincident, mainly in Dengkou and northern Linhe areas and Urad Qianqi. Considering the lagging effect of ecological engineering, the sustainable development status of RSEI in the western and eastern regions will maintain an improving trend in the future. Our study confirms the complex relationship between RSEI and meteorological and human activities, which is crucial for the scientific management of watershed ecosystems under the influence of anthropogenic factors.
      PubDate: 2023-09-18T00:00:00Z
       
  • Phylogenetically independent behavior mediating geographic distributions
           suggests habitat is a strong driver of phenotype in crangonyctid amphipods
           

    • Authors: McLean L. D. Worsham, Parvathi Nair, J. Randy Gibson, David Rodriguez, Benjamin F. Schwartz, Weston H. Nowlin
      Abstract: It is unclear if geographic distributions of animals are behaviorally mediated or simply maintained by ecologically-driven deleterious effects on fitness. Furthermore, it is not well known how behaviors that may affect geographic distributions and responses to environmental stressors evolve. To explore this, we examined behavioral and physiological reactions to light in six species of amphipods in the family Crangonyctidae collected from a variety of subterranean and epigean habitats. Stark differences between epigean and subterranean habitats occupied by different crangonyctid species allowed this clade to serve as an appropriate model system for studying the link between habitat and phenotype. We sampled habitats in or adjacent to the Edwards Aquifer in central Texas and collected two epigean and four stygobiontic species. We examined respiratory and behavioral responses to light in all study species. We found that similarities in behavioral and physiological responses to light between species were only weakly correlated with genetic relatedness but were correlated with habitat type. However, the breadth of variation in phenotype was found to be correlated with phylogenetic relationships, suggesting that population level trait evolution likely involves interactions between standing population level variation and strength of selection. Our findings suggest that natural selection via environmental conditions may outweigh history of common ancestry when predicting phenotypic similarities among species, and that behavioral and physiological phenotypes may mediate the evolution of biogeographic distributions.
      PubDate: 2023-09-18T00:00:00Z
       
  • Impact of fintech and environmental regulation on green innovation:
           inspiration from prefecture-level cities in China

    • Authors: Lin Ni, Yalu Yu, Huwei Wen
      Abstract: Environmental regulations may promote regional ecological evolution, but they also increase the need for financing green innovation activities. This study uses panel data from prefecture-level cities in China to examine the impact of fintech and environmental regulation on regional green innovation in the digital economy era. Empirical evidence shows that fintech significantly promotes regional green innovation, and fintech has a positive interaction effect with environmental regulation. While the evidence generally supports the role of environmental regulations in promoting green innovation, the evidence is insignificant in some models. The synergistic effect of fintech and environmental regulation on utility model green innovation is significant, but not on invention type green innovation. Climate policy, as a carbon regulatory policy, does not directly lead to green innovation, but it significantly collaborates with fintech to promote green innovation. The effects of fintech and environmental regulation on green innovation also have heterogeneity effects between resource-based and non-resource-based cities, and non-resource-based cities have a greater effect on achieving green innovation through fintech and environmental regulation. Our findings contribute to optimizing the coordination system between financial and environmental policies, thereby driving regional green innovation development with fintech in the digital age.
      PubDate: 2023-09-18T00:00:00Z
       
  • Editorial: Aquatic insect ecology in a changing world

    • Authors: Alexander B. Orfinger, David C. Houghton, Jason L. Robinson
      PubDate: 2023-09-18T00:00:00Z
       
 
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