超声技术在抑郁症诊疗中的作用研究及应用进展

超声波作为一种机械振动波,兼具波动效应、力学效应和热效应.这3种效应在临床中均有较大应用价值,可用于疾病的成像诊断、辅助给药、调控以及热消融治疗等.超声技术所具有的非侵入性、穿透力强、空间分辨率高等特性,使其在神经系统疾病的诊断和治疗中具有广泛的应用前景.而抑郁症作为一种常见的精神疾病,其诊断和治疗都面临很大的困难.因此,大量学者将超声技术应用于抑郁症诊疗.本文主要从超声成像、超声定点给药、超声调控、超声诱导抑郁几个方面总结近十年来超声技术在抑郁症中的应用,以期为研究抑郁症发病机制及诊疗提供一定的参考和帮助.     

澜沧江流域水生昆虫群落分类多样性和功能多样性海拔格局的空间尺度依赖性

群落分类多样性和功能多样性的海拔格局研究, 是了解生物多样性空间分布现状、揭示多样性维持和变化机制的重要途径。当前对水生昆虫分类多样性和功能多样性沿海拔梯度分布格局, 及其尺度依赖性依旧缺乏深入研究。本文基于2013-2018年在云南澜沧江流域500-3,900 m海拔梯度共149个溪流点位的水生昆虫群落调查数据, 利用线性或二次回归模型探索并比较了局部尺度(点位尺度)和不同区域尺度(100 m、150 m、200 m、250 m海拔段)的分类多样性指数(物种丰富度指数、Simpson多样性指数和物种均匀度指数)和功能多样性指数(树状图功能多样性指数(dbFD)、Rao二次熵指数(RaoQ)和功能均匀度指数(FEve))的海拔格局。结果表明, 在局部尺度, 物种丰富度指数和dbFD指数沿海拔梯度均无显著分布特征, Simpson多样性指数、RaoQ指数、物种均匀度指数和FEve指数沿海拔梯度呈现U型或者单调递减趋势。在区域尺度, 随着区域海拔带宽度的增加, 物种丰富度指数沿海拔呈不显著的单调递减格局, 但dbFD指数沿海拔分布由U型转变为单调递减趋势; Simpson多样性指数和RaoQ指数沿海拔梯度由显著U型趋势转变为无显著分布特征; 物种均匀度指数沿海拔梯度无显著分布特征, 但FEve指数呈显著增加的海拔格局。综上, 群落分类多样性指数和功能多样性指数沿海拔梯度分布存在局部和区域尺度的空间差异, 但区域尺度下二者海拔格局随海拔带宽度的增加存在一定程度的一致性。     

金佛山亚热带常绿阔叶林地表土壤动物群落特征及其影响因素

为探讨小尺度下不同微生境的土壤动物群落特征及其与环境因子之间的关系,于2018年10月在金佛山西坡亚热带常绿阔叶林样带内,对其凋落物层及腐殖质层两类微生境的土壤动物群落进行调查及相应环境因子的测定。此次调查共捕获地表土壤动物12381头,隶属于3门9纲22目。其中优势类群为蜱螨目和长角虫兆目,个体数占比为75.24%;常见类群为原虫兆目、愈腹虫兆目、短角虫兆目、双翅目、鞘翅目和膜翅目,个体数占比为21.23%。同时,土壤动物的密度（M）、Shannon-Wiener多样性指数（H）、Simpson优势度指数（D）及Pielou均匀度指数（E）均表现为腐殖质层极显著高于凋落物层（P<0.01）。根据回归分析及冗余分析结果发现,两类微生境的土壤动物群落特征与环境因子的关系存在一定差异;影响凋落物层土壤动物群落特征的重要环境因子为凋落物的总有机碳、碳氮比、湿度及pH,而影响腐殖质层土壤动物群落特征的重要环境因子为腐殖质的干重、总氮、总磷、湿度、pH及微生物生物量氮。研究表明,常绿阔叶林生态系统的不同微生境间土壤动物多样性特征存在显著差异,小尺度下环境因子对土壤动物群落特征具有重要影响。     

全球气候治理新进展——区域碳排放权分配研究综述

碳排放权作为稀缺的公共资源,其实质是一种新型发展权。科学合理分配有限的碳排放权对实现《巴黎协定》温控目标至关重要。从原则、方法、尺度与方案等维度对碳排放权分配的文献成果进行了系统梳理与归纳。研究表明,国内外学者大多基于公平性和效率性原则探索碳排放权分配;分配方法分为指标法、博弈论法、数据包络分析法和综合法等,各有利弊和适用条件;分配尺度大多涉及国际和区际两个层面,前者由于各国不同的利益诉求较难形成共识性方案,后者主要关注省际分配,更小尺度的研究相对较少。未来碳排放权分配研究趋向于多原则兼顾、多方法联用,涵盖国际、省际、市际及行业、企业等不同尺度。本研究可为制定科学合理的碳排放权分配方案提供理论依据,为我国更为积极有效地参与全球气候治理提供决策参考。     

Occupancy versus colonization–extinction models for projecting population trends at different spatial scales

Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modeling assumptions. Deadwood‐dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales, and they utilize distinct substrates. We tested how the projected large‐scale occupancies of species with differing landscape‐scale occupancies are affected over the coming century by different modeling assumptions. We compared projections based on occupancy models against colonization–extinction models, conducting the modeling at alternative spatial scales and using fine‐ or coarse‐resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization–extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonization–extinction models, with greater difference for the species with lower occupancy, colonization rate, and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modeling scale and resource resolution. We encourage using colonization–extinction models over occupancy models, modeling the process at the finest resource‐unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality, and spatial connectivity.     

Scale‐dependent effects of neighborhood biodiversity on individual tree productivity in a coniferous and broad‐leaved mixed forest in China

The relationship between biodiversity and productivity has stimulated an increasing body of research over the past decades, and this topic still occupies a central place in ecology. While most studies have focused on biomass production in quadrats or plots, few have investigated the scale‐dependent relationship from an individual plant perspective. We present an analysis of the effects of biodiversity (species diversity and functional diversity) on individual tree growth with a data set of 16,060 growth records from a 30‐ha temperate forest plot using spatially explicit individual tree‐based methods. A significant relationship between species diversity and tree growth was found at the individual tree level in our study. The magnitude and direction of biodiversity effects varies with the spatial scale. We found positive effects of species diversity on tree growth at scales exceeding 9 m. Individual tree growth rates increased when there was a greater diversity of species in the neighborhood of the focal tree, which provides evidence of a niche complementarity effect. At small scales (3–5 m), species diversity had negative effects on tree growth, suggesting that competition is more prevalent than complementarity or facilitation in these close neighborhoods. The results also revealed many confounding factors which influence tree growth, such as elevation and available sun light. We conclude that the use of individual tree‐based methods may lead to a better understanding of the biodiversity‐productivity relationship in forest communities.     

Pollen limitation in the endangered Chinese endemic species Sinocalycanthus chinensis

Pollen limitation negatively impacts endangered and endemic plants with small fragmented populations, such as Sinocalycanthus chinensis, an endangered plant endemic to China. In this study, we analyzed the pollen limitation of the S. chinensis Damingshan (DMS) population in 2006, 2009, and 2010, and crossed plants with mates separated by different distances, both within and between populations. The DMS population exhibited strong pollen limitation in fruit set, seed set, and seeds per fruit in 2006, 2009, and 2010. The average accumulated pollen limitation (for fruit set times seeds per fruit) was 0.510 ± 0.180. Progeny crossed with pollen from intermediate neighboring plants within the same population (separated by 30–50 m from pollen recipients) had the lowest fitness. No optimal outcrossing distance was found within the DMS population. Progeny from crosses with the Shunxiwu (SXW) and Daleishan (DLS) populations performed relatively better, while those from crosses with Qingliangfeng (QLF) and Longxushan (LXS) populations performed worse. Compared with average reproductive success, outbreeding depression was found in progeny from crosses with the LXS and QLF populations. Reproductive success from pure self‐pollination indicated S. chinensis is self‐compatible. Geitonogamous selfing increased reproductive success. Based on geitonogamous selfing, the proportion of selfed offspring was relatively high. These results provide basic references for the conservation of this species.     

Meta‐replication,sampling bias,and multi‐scale model selection: A case study on snow leopard (Panthera uncia) in western China

Replicated multiple scale species distribution models (SDMs) have become increasingly important to identify the correct variables determining species distribution and their influences on ecological responses. This study explores multi‐scale habitat relationships of the snow leopard (Panthera uncia) in two study areas on the Qinghai–Tibetan Plateau of western China. Our primary objectives were to evaluate the degree to which snow leopard habitat relationships, expressed by predictors, scales of response, and magnitude of effects, were consistent across study areas or locally landcape‐specific. We coupled univariate scale optimization and the maximum entropy algorithm to produce multivariate SDMs, inferring the relative suitability for the species by ensembling top performing models. We optimized the SDMs based on average omission rate across the top models and ensembles’ overlap with a simulated reference model. Comparison of SDMs in the two study areas highlighted landscape‐specific responses to limiting factors. These were dependent on the effects of the hydrological network, anthropogenic features, topographic complexity, and the heterogeneity of the landcover patch mosaic. Overall, even accounting for specific local differences, we found general landscape attributes associated with snow leopard ecological requirements, consisting of a positive association with uplands and ridges, aggregated low‐contrast landscapes, and large extents of grassy and herbaceous vegetation. As a means to evaluate the performance of two bias correction methods, we explored their effects on three datasets showing a range of bias intensities. The performance of corrections depends on the bias intensity; however, density kernels offered a reliable correction strategy under all circumstances. This study reveals the multi‐scale response of snow leopards to environmental attributes and confirms the role of meta‐replicated study designs for the identification of spatially varying limiting factors. Furthermore, this study makes important contributions to the ongoing discussion about the best approaches for sampling bias correction.     

Genomic Consequences of Long-Term Population Decline in Brown Eared Pheasant

Population genetic theory and empirical evidence indicate that deleterious alleles can be purged in small populations. However, this viewpoint remains controversial. It is unclear whether natural selection is powerful enough to purge deleterious mutations when wild populations continue to decline. Pheasants are terrestrial birds facing a long-term risk of extinction as a result of anthropogenic perturbations and exploitation. Nevertheless, there are scant genomics resources available for conservation management and planning. Here, we analyzed comparative population genomic data for the three extant isolated populations of Brown eared pheasant (Crossoptilon mantchuricum) in China. We showed that C. mantchuricum has low genome-wide diversity and a contracting effective population size because of persistent declines over the past 100,000 years. We compared genome-wide variation in C. mantchuricum with that of its closely related sister species, the Blue eared pheasant (C. auritum) for which the conservation concern is low. There were detrimental genetic consequences across all C. mantchuricum genomes including extended runs of homozygous sequences, slow rates of linkage disequilibrium decay, excessive loss-of-function mutations, and loss of adaptive genetic diversity at the major histocompatibility complex region. To the best of our knowledge, this study is the first to perform a comprehensive conservation genomic analysis on this threatened pheasant species. Moreover, we demonstrated that natural selection may not suffice to purge deleterious mutations in wild populations undergoing long-term decline. The findings of this study could facilitate conservation planning for threatened species and help recover their population size.