基于种群、功能群对比分析洞庭湖浮游植物群落驱动因素及水质评价

浮游植物是水生态系统中最重要的组成部分,因其对水环境变化敏感而常被用于指示水环境状态,但其对环境的响应受分类方法的影响.为了解洞庭湖浮游植物种群(门、属)和功能群(FG)两种分类法对环境的驱动响应特征和适用性,于2019年3～12月分水期对该湖共进行了4次采样,比较分析了浮游植物种群和功能群的分布特征及其与环境因子的响应关系,并对比了TLI指数、 Shannon-Wiener指数、Q指数等评价方法在洞庭湖的适用性.结果表明,洞庭湖共检出浮游植物6门61属,可划分为23个功能群和9个优势功能群,功能群演替趋势为P/MP/D(3月)■月)■月)■(12月).层次分割结果表明,洞庭湖浮游植物的种群分布与变化受环境因子的驱动大于空间驱动;影响浮游植物种群和功能群的主要环境因子为水温(WT)、高锰酸盐指数、溶解氧(DO)、电导率(Cond)、水位(WL)和总磷(TP),环境因子对两者的独立解释性排序相差不大.RDA分析表明,浮游植物功能群对环境因子的响应要优于浮游植物种群.综合对比分析发现,利用Q指数进行水质评价在洞庭湖水体有较好的适用性.     

长柄石杉居群遗传多样性和遗传结构的AFLP分析

石杉科植物因所含石杉碱甲(Huperzine A)对中老年痴呆等具有良好疗效,近年来倍受关注.利用AFLP分子标记对武夷山脉广布种长柄石杉[Huperzia serrata(Thunb.ex Murray)Trev.var.longipetiolata(Spring)H.M.Chang]7个居群112株个体进行遗传多样性和居群遗传结构分析.选用多态性高、分辨力强的8对选择性扩增引物组合共获得675个位点,其中多态位点比例为69.38%.居群内观测等位基因数(Na)为1.633,有效等位基因数(Ne)1.493;Nei’s基因多样性指数(He)与Shannon多态性信息指数(I)的平均值分别为0.272和0.392,多样性最高为地处武夷山脉中段的泰宁居群和建宁居群,最低为山脉北段的光泽居群.居群总基因多样性(Ht)为0.327 3,居群内基因多样性(Hs)为0.272 2,居群间的遗传分化系数(Gst)为0.168 1,表明居群内变异是长柄石杉遗传多样性的主要来源.由Gst估计,武夷山脉长柄石杉自然居群的基因流(Nm)为2.474 0.邻接树分析表明居群间遗传亲缘关系与地理位置相关.武夷山脉长柄石杉较高的遗传多样性和基因流水平表明其仍然具有相当的适应(生存)能力和进化潜力,这可能与其生物学(异交水平)、生态学特性及武夷山脉相对良好的生境条件有关.     

太湖和巢湖夏季蓝藻水华期间产毒微囊藻和非产毒微囊藻种群丰度的空间分布

应用荧光定量PCR技术对蓝藻水华暴发期间太湖和巢湖水体中产毒微囊藻和总微囊藻种群丰度的空间分布进行了研究.分别以微囊藻毒素合成基因基因家族成员mcyD和小核糖体16S rDNA序列构建定量PCR标准曲线,研究产毒微囊藻和总微囊藻种群丰度.结果表明:太湖和巢湖微囊藻种群由产毒微囊藻和非产毒微囊藻组成;蓝藻水华暴发期间,微囊藻种群组成及其丰度分布具有明显的空间差异性:太湖产毒微囊藻种群丰度为9.89×104～4.51×106 copies mL-1,产毒微囊藻占总微囊藻种群的比例为20.5%～38.1%;巢湖产毒微囊藻种群丰度为4.12×104～5.44×106 copies mL-1,其占总微囊藻种群的比例为8.4%～96.6%.总的来说,富营养化严重的湖区总微囊藻和产毒微囊藻种群丰度较高,产毒微囊藻占总微囊藻种群的比例也较高.图7表3参29     

Large-sample-size assessment of socioeconomic predictors of community-level resource management occurrence

Community-level resource management efforts are cornerstones in ensuring sustainable use of natural resources. Yet, understanding how community characteristics influence management practices remains contested. With a sample size of ≥725 communities, we assessed the effects of key community (i.e., socioeconomic) characteristics (human population size and density, market integration, and modernization) on the probability of occurrence of fisheries management practices, including gear, species, and spatial restrictions. The study was based in Solomon Islands, a Pacific Island country with a population that is highly dependent on coastal fisheries. People primarily dwell in small communities adjacent to the coastline dispersed across 6 island provinces and numerous smaller islands. We used nationally collected data in binomial logistic regression models to examine the likelihood of management occurrence, given socioeconomic context of communities. In contrast to prevailing views, we identified a positive and statistically significant association between both human population size and market integration and all 3 management practices. Human population density, however, had a statistically significant negative association and modernization a varied and limited association with occurrence of all management practices. Our method offers a way to remotely predict the occurrence of resource management practices based on key socioeconomic characteristics. It could be used to improve understanding of why some communities conduct natural resource management activities when statistical patterns suggest they are not likely to and thus improve understanding of how some communities of people beat the odds despite limited market access and high population density.     

A stochastic model for estimating sustainable limits to wildlife mortality in a changing world

Human-caused mortality of wildlife is a pervasive threat to biodiversity. Assessing the population-level impact of fisheries bycatch and other human-caused mortality of wildlife has typically relied upon deterministic methods. However, population declines are often accelerated by stochastic factors that are not accounted for in such conventional methods. Building on the widely applied potential biological removal (PBR) equation, we devised a new population modeling approach for estimating sustainable limits to human-caused mortality and applied it in a case study of bottlenose dolphins affected by capture in an Australian demersal otter trawl fishery. Our approach, termed sustainable anthropogenic mortality in stochastic environments (SAMSE), incorporates environmental and demographic stochasticity, including the dependency of offspring on their mothers. The SAMSE limit is the maximum number of individuals that can be removed without causing negative stochastic population growth. We calculated a PBR of 16.2 dolphins per year based on the best abundance estimate available. In contrast, the SAMSE model indicated that only 2.3–8.0 dolphins could be removed annually without causing a population decline in a stochastic environment. These results suggest that reported bycatch rates are unsustainable in the long term, unless reproductive rates are consistently higher than average. The difference between the deterministic PBR calculation and the SAMSE limits showed that deterministic approaches may underestimate the true impact of human-caused mortality of wildlife. This highlights the importance of integrating stochasticity when evaluating the impact of bycatch or other human-caused mortality on wildlife, such as hunting, lethal control measures, and wind turbine collisions. Although population viability analysis (PVA) has been used to evaluate the impact of human-caused mortality, SAMSE represents a novel PVA framework that incorporates stochasticity for estimating acceptable levels of human-caused mortality. It offers a broadly applicable, stochastic addition to the demographic toolbox to evaluate the impact of human-caused mortality on wildlife.     

土地资源的多级网格数据结构建立与应用研究

传统的基于行政区的土地统计数据不能完全表现区域内部土地利用的空间分异特征,以武汉市为实验区,对基于网格的统计信息算法STING(Statistical Information Grid-based method)进行扩展,以景观多样性指数为定量化指标对实验区进行四叉树划分生成不均匀多级网格,建立一种拟合了行政区划界线的不均匀的多级网格结构来存储、管理和分析土地数据。并以此多级网格数据结构为平台计算和生成实验区人口密度空间分异渲染图,初步抽取了人口分布与土地利用之间的关系。实验表明,基于多级网格的统计方法能更好地表达土地利用及其相关数据的空间分异性,利于对土地资源数据的进一步挖掘以抽取所需知识。     

Sensitivity Analyses of Spatial Population Viability Analysis Models for Species at Risk and Habitat Conservation Planning

Abstract:  Population viability analysis (PVA) is an effective framework for modeling species- and habitat-recovery efforts, but uncertainty in parameter estimates and model structure can lead to unreliable predictions. Integrating complex and often uncertain information into spatial PVA models requires that comprehensive sensitivity analyses be applied to explore the influence of spatial and nonspatial parameters on model predictions. We reviewed 87 analyses of spatial demographic PVA models of plants and animals to identify common approaches to sensitivity analysis in recent publications. In contrast to best practices recommended in the broader modeling community, sensitivity analyses of spatial PVAs were typically ad hoc, inconsistent, and difficult to compare. Most studies applied local approaches to sensitivity analyses, but few varied multiple parameters simultaneously. A lack of standards for sensitivity analysis and reporting in spatial PVAs has the potential to compromise the ability to learn collectively from PVA results, accurately interpret results in cases where model relationships include nonlinearities and interactions, prioritize monitoring and management actions, and ensure conservation-planning decisions are robust to uncertainties in spatial and nonspatial parameters. Our review underscores the need to develop tools for global sensitivity analysis and apply these to spatial PVA.     

Conservation Threats Due to Human-Caused Increases in Fire Frequency in Mediterranean-Climate Ecosystems

Periodic wildfire is an important natural process in Mediterranean-climate ecosystems, but increasing fire recurrence threatens the fragile ecology of these regions. Because most fires are human-caused, we investigated how human population patterns affect fire frequency. Prior research in California suggests the relationship between population density and fire frequency is not linear. There are few human ignitions in areas with low population density, so fire frequency is low. As population density increases, human ignitions and fire frequency also increase, but beyond a density threshold, the relationship becomes negative as fuels become sparser and fire suppression resources are concentrated. We tested whether this hypothesis also applies to the other Mediterranean-climate ecosystems of the world. We used global satellite databases of population, fire activity, and land cover to evaluate the spatial relationship between humans and fire in the world's five Mediterranean-climate ecosystems. Both the mean and median population densities were consistently and substantially higher in areas with than without fire, but fire again peaked at intermediate population densities, which suggests that the spatial relationship is complex and nonlinear. Some land-cover types burned more frequently than expected, but no systematic differences were observed across the five regions. The consistent association between higher population densities and fire suggests that regardless of differences between land-cover types, natural fire regimes, or overall population, the presence of people in Mediterranean-climate regions strongly affects the frequency of fires; thus, population growth in areas now sparsely settled presents a conservation concern. Considering the sensitivity of plant species to repeated burning and the global conservation significance of Mediterranean-climate ecosystems, conservation planning needs to consider the human influence on fire frequency. Fine-scale spatial analysis of relationships between people and fire may help identify areas where increases in fire frequency will threaten ecologically valuable areas.     

Changes in the Carabid Fauna (Coleoptera, Carabidae) of Meadow Steppes during the Past Decades

Basic trends in the structural dynamics of the meadow-steppe carabid fauna over the period from 1970 to 1997 have been analyzed. Data on changes in the abundance and composition of dominant species are reported. Transformation of carabidocenoses is mainly accounted for by an increased humidity of the climate and the related mesophytization of forest–steppe ecosystems.     

Phenes of Woody Plants: Identification,Scaling, and Use in Population Studies (An Example of Pinus sylvestrisL.)

The methods of identification and scaling of phenes of forest plants are described. The phene identification consists of five stages. Specific features of studies at each stage are shown using identification of the phenes of seed color, cone color, and seed scale structure in Scotch pine (Pinus sylvestrisL.) as examples. The method of phene scaling is based on the comparison of phene frequencies in a bog and in adjacent upland populations of pine. At the boundary between the bog and dry land, the frequencies of population-level phenes change, whereas those of superpopulation-level phenes remain unchanged.