生态恢复方式对喀斯特生境苔藓植物物种组成的影响

为探究生态恢复方式对苔藓植物的影响,研究了自然弃耕和退耕还林等生态恢复方式对重庆市中梁山喀斯特地区不同生境类型下苔藓植物物种组成特征的影响。结果表明,研究区有苔藓植物15科26属41种,其中藓类39种,苔类2种,美灰藓(Eurohypnum leptothollum)为主要优势物种;研究区石生藓类植物占比较大,生活型以平铺型和丛集型为主,各生境物种多样性及相似性指数整体偏低,但相比弃耕杂草地、灌木林和经济型林地,竹林和马尾松林中苔藓植物具有更高的物种多样性;冗余分析表明,郁闭度和光照强度是影响苔藓植物分布的关键环境因子,乔木林为苔藓植物的生长提供了更适宜的生境。因此,相比于自然恢复和经济性林地等恢复方式,退耕还林是喀斯特退化生境更为理想的生态恢复方式。     

上海市树附生苔藓植物生态位

生态位理论在植被生态研究中有着重要的应用价值,引入生态位理论对树附生苔藓植物进行了研究。在上海市市区和郊区主要公园、部分街道及校园,包括崇明岛等地区,共设立18个样点,调查发现43种树附生苔藓植物,其中藓类植物39种,苔类植物4种。根据盖度值计算了43种树附生苔藓植物的生态位宽度。结果表明,树附生苔藓植物种数(N)与生态位宽度(B)符合公式N=0.3423e-0.0369B,r=0.9347,大部分的树附生植物生态位宽度很窄,67.44%种类的生态位宽度小于0.1。本文计算了43种树附生苔藓植物的生态位重叠值,应用主分量分析法和最小生成树法对它们进行分类。将43种树附生苔藓植物分成3个生态类群,它们与生境关系显著。因此,在苔藓植物保护中应特别注意对树附生苔藓植物及其生境的保护。     

森林林下植被生物量收获的样方选择和模型

在控制误差内寻求样方的最小面积和最少样方数量是植被生态学野外研究的重要问题。在综合考虑取样的边界效应和时间、劳力消耗的基础上,研究了在控制误差内测定森林林下植被生物量时应选择的最佳样方大小和数量,并找出最佳的自变量拟合了估算林下植被生物量的预测方程。结果表明,利用Wiegert的方法测定研究区林下植被生物量取样方案,得出0．25m。的小样方为最佳取样面积。但小样方受边界效应的影响很大,会产生过高的生物量估计。通过分析了边界效应的影响和生物量相对平均值的变化,得出2m×1m是本研究的最佳样方面积,而10个2m×1m的样方能把标准误差控制在生物量平均值的10％以内。灌木生物量回归方程所选取的3个自变量D^2H、CH和P日中,CH与灌木生物量的相关性和以CH为自变量的线性回归方程的拟合度较其他2个变量好。而以PH为自变量的灌木生物量预测方程在实际操作中能提高研究的简便性和效率。以PH为自变量的林下草本层单位面积生物量的预测方程分别为Wv=11．65＋4．25（PH）和wD=24．23＋6．85（PH）。     

苔藓植物对森林生态界面指示作用的研究

对长白山长白松林林缘、暗针叶林林缘以及笃斯越桔灌丛落叶松林间3个生态过渡带上苔藓植物分布特点的研究表明,苔藓植物盖度与多样性指数可以作为判别林缘生态界面客观性的指标,这些指标均能以y=b·a^x进行拟合。通过生态界面系统信息量公式计算了这些指标在生态界面上的信息量,并讨论它们的生态学意义。     

茅台上游河谷地区苔藓植物生态学研究

对贵州茅台镇茅台上游河谷地区的苔藓植物生态学进行了研究。结果表明,该地区有苔藓植物30科53属116种;生态类型有石生、土生、沙生、树附生、腐木生和水生等6种;PCA排序分析表明,在大气候相同的环境下,苔藓植物生态分布格局差异大,主要受微环境的影响。淡色同叶藓、拟阔叶小石藓、毛口藓、齿边缩叶藓、褶叶青藓和拟脆枝曲柄藓为该地区的优势苔藓植物,其生物量为32.80~225.00 g m-2,饱和吸水量为23519.90~269999.96 g m-2。这说明,苔藓植物在该地区的生态修复过程中,以其特有的生态功能在水土保持和涵养水源、物质循环、土壤性质改善和更新等方面起到十分重要的作用。     

浙江金华市郊地面苔藓植物生态位研究

在金华市郊不同生境设立30个样点。调查发现共有67种地面苔藓植物。计测了其中的54个主要种类的生态位重叠值和宽度,以生态位重叠值为指标,应用最小生成树法和主坐标排序法对它们进行分类。结果发现,金华市郊的地面生苔藓植物可被分成3个生态类群,苔藓植物种数(N)与生态位宽度(B)符合:N=27.304e 11.425B(R2=0.9915),大部分的地面生苔藓植物生态位宽度很窄。     

苔藓植物的化学生态学

苔藓植物是植物界中的一大类群,其竞争力非常有限,常生长在维管束植物无法生存的环境中。苔藓植物合成的许多次生代谢产物具有调节高等植物生长、抑制微生物、昆虫拒食、抗紫外线辐射以及抗干旱能力,在对抗生态环境中的生物胁迫以及非生物胁迫中发挥重要的作用。     

石漠化程度对苔藓植物多样性及其结皮土壤化学性质的影响

以研究区域不同石漠化等级为代表,分析苔藓多样性特征及其结皮土壤化学性质变化规律,探索其对石漠化进程的响应机制。结果显示:(1)苔藓物种多样性:含苔藓14科29属84种,其中苔类2科2属2种;(2)多样性指数表现为:重度石漠化阶段中度石漠化轻度石漠化极重度石漠化无石漠化;其均匀度为:中度石漠化阶段轻度石漠化重度石漠化极重度石漠化无石漠化;(3)随着石漠化程度加剧,苔藓群落组成中混合群落比重下降而纯群落比重上升;群落生活型则呈现交织型递减而丛集型递增的规律。(4)结皮土壤中全氮、全磷和微生物量碳随石漠化加剧均都呈递减趋势。(5)通过Partial RDA分析发现密枝青藓(Brachythecium amnicolum)、褶叶藓(Palamocladium nilgheriense)和美灰藓(Eurohypnum leptothallum)等可用于石漠化生态修复。石漠化程度对苔藓多样性影响不显著,但对其群落特征和生活型影响显著。因此可以结合苔藓群落和生活型特征监测石漠化,同时也可使用苔藓作为先锋植物引进用于石漠化早期修复。     

安徽石台县与青阳县苔藓植物多样性

生物多样性保护优先区域代表了生物多样性富集区、典型生态系统与关键物种分布区, 对于生物多样性保护具有重要意义, 但优先区域内自然保护地覆盖率通常较低, 存在很大的保护空缺。苔藓植物作为生物多样性的一个重要组成部分, 在生态系统中发挥着重要作用, 但由于个体细小、分类鉴定困难等, 使得其多样性保护成为整个生物多样性保护中较为薄弱的一环。为了了解我国生物多样性保护优先区域苔藓植物多样性及受保护情况, 本文以黄山-怀玉山生物多样性保护优先区域内的石台县和青阳县为例, 通过系统的样线法调查优先区域内自然保护地内、外的苔藓植物多样性, 比较了其物种组成特点及相似性。结果表明, 该区域共有苔藓植物64科140属344种, 包括苔类植物27科40属106种、藓类植物37科100属238种, 其中有5种为濒危物种。自然保护地内有60科120属270种, 保护地外有46科90属185种, 保护地内、外苔藓植物科、属、种的Jaccard相似性系数分别为0.66、0.50和0.32, 表明自然保护地内、外物种组成差异很大。与石台县和青阳县苔藓植物历史数据相比, 本研究新增苔藓植物14科64属273种, 其中包括安徽省新记录2科9属96种, 而且有18种仅分布于自然保护地外。根据对该区域物种累积曲线及外推估计分析, 当采集足够充分时, 基于标本数的物种多样性预测值为485种, 基于样线数的预测值为563种, 说明石台县和青阳县的苔藓植物多样性仍存在被低估的可能。本研究结果一方面表明了自然保护地之外的苔藓植物在保护中有重要价值, 另一方面也反映了苔藓植物的野外就地保护存在空缺。建议在我国其他生物多样性保护优先区域开展类似的调查和研究, 以期为今后对苔藓植物的分布规律及保护研究提供翔实的基础数据。     

长白山主要生态系统苔藓植物的生物多样性研究

长白山地区共有苔藓植物65科179属437种,32个变种和亚种。其中,石生和岩面薄土生种类(saxicolous bryophyte)最丰富,其次为腐木生种类(saprophytic bryophyte)和树生种类(epiphytic bryophyte),再次为土生种类(soil and humus bryophyte)。沼泽地、水体等生境中的种类(peat, marsh and water bryophyte) 相对较少。地面生苔藓植物的物种丰富度以暗针叶林(dark conifer forest)最高,而多样性以落叶松－沼泽地(Larix olgensis-bogs)和暗针叶林为最高;腐木生苔藓植物的物种丰富度和多样性均以暗针叶林为最高,树附生苔藓植物的物种丰富度和多样性以暗针叶林以及红松阔叶混交林(Pinus koraiensis broad-leaved mixed forest) 与暗针叶林间的过渡林为最高。定性分析表明,海拔高度、林冠层郁闭度和林内湿度、土壤酸度、含水量、林下倒木的丰富程度等可能是影响本地区苔藓植物多样性的重要环境因子。     

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence–absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size ( n  < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.     

Influence of macroinvertebrate sample size on bioassessment of streams

In order to standardise biological assessment of surface waters in Europe, a standardised method for sampling, sorting and identification of benthic macroinvertebrates in running waters was developed during the AQEM project. The AQEM method has proved to be relatively time-consuming. Hence, this study explored the consequences of a reduction in sample size on costs and bioassessment results. Macroinvertebrate samples were collected from six different streams: four streams located in the Netherlands and two in Slovakia. In each stream 20 sampling units were collected with a pond net (25×25 cm), over a length of approximately 25 cm per sampling unit, from one or two habitats dominantly present. With the collected data, the effect of increasing sample size on variability and accuracy was examined for six metrics and a multimetric index developed for the assessment of Dutch slow running streams. By collecting samples from separate habitats it was possible to examine whether the coefficient of variation (CV; measure of variability) and the mean relative deviation from the “reference” sample (MRD; measure of accuracy) for different metrics depended only on sample size, or also on the type of habitat sampled. Time spent on sample processing (sorting and identification) was recorded for samples from the Dutch streams to assess the implications of changes in sample size on the costs of sample processing. Accuracy of metric results increased and variability decreased with increasing sample size. Accuracy and variability varied depending on the habitat and the metric, hence sample size should be based on the specific habitats present in a stream and the metric(s) used for bioassessment. The AQEM sampling method prescribes a multihabitat sample of 5 m. Our results suggest that a sample size of less than 5 m is adequate to attain a CV and MRD of ≤ 10% for the metrics ASPT (Average Score per Taxon), Saprobic Index and type Aka+Lit+Psa (%) (the percentage of individuals with a preference for the akal, littoral and psammal). The metrics number of taxa, number of individuals and EPT-taxa (%) required a multihabitat sample size of more than 5 m to attain a CV and MRD of ≤ 10%. For the metrics number of individuals and number of taxa a multihabitat sample size of 5 m is not even adequate to attain a CV and MRD of ≤ 20%. Accuracy of the multimetric index for Dutch slow running streams can be increased from ≤ 20 to ≤ 10% with an increase in labour time of 2 h. Considering this low increase in costs and the possible implications of incorrect assessment results it is recommended to strive for this ≤ 10% accuracy. To achieve an accuracy of ≤ 10% a multihabitat sample of the four habitats studied in the Netherlands would require a sample size of 2.5 m and a labour time of 26 h (excluding identification of Oligochaeta and Diptera) or 38 h (including identification of Oligochaeta and Diptera). Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users.     

7个林木大小多样性指数表达能力比较

林木大小多样性直接反映森林生态系统的健康与稳定, 客观恰当地表达大小多样性对于评价天然林或人工林的经济、生态、社会价值及其经营效果至关重要。本研究选用7个林木大小多样性指数, 其中4个与距离无关(Simpson大小多样性指数D_N、Shannon大小多样性指数H_N、断面积Gini系数GC和直径变异系数CV_d), 3个与距离有关(Simpson大小分化度指数D_T、Shannon大小分化度指数H_T和大小分化度均值指数$\bar{T}$), 通过6组模拟林分和4块实测林分比较分析了它们的表达能力。结果表明: 不考虑极端情况(极端情况为对比林分林木大小混交不同但林木直径构成完全相同), GC、CV_d、$\bar{T}$、D_T和H_T能客观恰当地表达不同径级分布林分的林木大小多样性差异, 其中CV_d区分能力最强, GC次之。若考虑极端情况, 只有$\bar{T}$、D_T和H_T能区分出不同大小混交程度林分的林木大小多样性差异。本研究认为CV_d和GC因计算简单, 易于实际应用, 在营林活动中可作为分析林木大小多样性的首选指数; $\bar{T}$因能识别不同大小混交程度林分的空间差异, 即对林分更新变化敏感, 适用于动态分析林分的结构特征。     

重庆主城区地面苔藓植物群落特征及其与环境的关系

通过对重庆主城区44个样地的地面苔藓植物进行样方调查,应用物种多样性指数和典范对应分析(CCA),研究了该地区苔藓植物种类组成、物种多样性和群落与环境因子的关系.结果表明： 石生群落共有苔藓植物25科43属86种;土生群落共有苔藓植物22科28属46种.相比公园、风景区和缙云山国家级自然保护区,大学校园的石生和土生苔藓植物物种多样性水平较高.双向指示种分析结果将石生群落划分为3种类型,土生群落划分为2种类型.典范对应分析显示,林冠郁闭度是影响公园和大学校园内石生苔藓植物的主要环境因子;海拔、相对湿度和人为干扰程度是影响自然保护区和旅游景区内石生苔藓植物的主要环境因子.土壤〖JP2〗pH值、人为干扰程度和林冠郁闭度是影响公园和大学校园土生苔藓植物的主要环境因子;海拔、相对湿度和土壤含水量是影响自然保护区和旅游景区内土生苔藓植物的主要因子.     

淀山湖鱼类生物多样性调查样本量的优化设计

样本量大小影响估算鱼类种群动态和鱼类群落特征的准确性和精确度.本文以淀山湖渔业资源调查为例,研究估算淀山湖鱼类群落特征所需的样本量大小.2010年7月—2011年6月研究期间每月进行一次淀山湖渔业资源调查,共捕获14科45种鱼类.利用重采样方法,估算淀山湖渔业资源调查最优调查频次和最佳站点数.结果表明: 在淀山湖渔业资源调查中,站点数和调查频次呈负相关关系;保持95%的探测率探测90%的物种,每年调查11和12次相应需要设置21和19个站点.Shannon多样性指数随着每次调查站点数的增多而变大,增长到一定程度之后逐渐趋于稳定.淀山湖鱼类群落的物种多样性调查最佳站点数为21.本文的研究方法和结果可以为其他类似研究提供借鉴.     

初始投标值数量和样本容量对双边界二分式CVM的影响

双边界二分式条件价值评估法是当前广泛应用于评估生态环境和自然资源价值的陈述偏好法。为了研究双边界二分式CVM中,不同分布中初始投标值数量及样本容量对WTP的影响,应用蒙特卡洛模拟和支付意愿函数模型相结合的方法,用概率分位数设计投标值,分别选择数据来源不同的Weibull分布和对数Logistic分布,动态模拟不同初始投标值数量和样本容量对WTP期望值产生的影响。模拟结果表明,对不同的WTP概率分布,初始投标值数量和样本容量对WTP的影响趋势是一致的,当初始投标值数量和样本容量分别大于5和500时,初始投标值数量和样本容量的增加,对WTP估计值的影响程度越来越小。研究结果表明,在二分式CVM研究中,当以WTP期望为代表值时,其初始投标值数量和样本容量至少为5和500。研究结论为二分式CVM问卷设计中投标值数量及样本容量的设定提供参考依据。     

An efficient sample size adaptation strategy with adjustment of randomization ratio

In clinical trials, sample size reestimation is a useful strategy for mitigating the risk of uncertainty in design assumptions and ensuring sufficient power for the final analysis. In particular, sample size reestimation based on unblinded interim effect size can often lead to sample size increase, and statistical adjustment is usually needed for the final analysis to ensure that type I error rate is appropriately controlled. In current literature, sample size reestimation and corresponding type I error control are discussed in the context of maintaining the original randomization ratio across treatment groups, which we refer to as “proportional increase.” In practice, not all studies are designed based on an optimal randomization ratio due to practical reasons. In such cases, when sample size is to be increased, it is more efficient to allocate the additional subjects such that the randomization ratio is brought closer to an optimal ratio. In this research, we propose an adaptive randomization ratio change when sample size increase is warranted. We refer to this strategy as “nonproportional increase,” as the number of subjects increased in each treatment group is no longer proportional to the original randomization ratio. The proposed method boosts power not only through the increase of the sample size, but also via efficient allocation of the additional subjects. The control of type I error rate is shown analytically. Simulations are performed to illustrate the theoretical results.     

Blinded sample size recalculation in multiple composite population designs with normal data and baseline adjustments

The increasing interest in subpopulation analysis has led to the development of various new trial designs and analysis methods in the fields of personalized medicine and targeted therapies. In this paper, subpopulations are defined in terms of an accumulation of disjoint population subsets and will therefore be called composite populations. The proposed trial design is applicable to any set of composite populations, considering normally distributed endpoints and random baseline covariates. Treatment effects for composite populations are tested by combining p-values, calculated on the subset levels, using the inverse normal combination function to generate test statistics for those composite populations while the closed testing procedure accounts for multiple testing. Critical boundaries for intersection hypothesis tests are derived using multivariate normal distributions, reflecting the joint distribution of composite population test statistics given no treatment effect exists. For sample size calculation and sample size, recalculation multivariate normal distributions are derived which describe the joint distribution of composite population test statistics under an assumed alternative hypothesis. Simulations demonstrate the absence of any practical relevant inflation of the type I error rate. The target power after sample size recalculation is typically met or close to being met.     

Local community size mediates ecological drift and competition in metacommunities

The outcome of competitive interactions is likely to be influenced by both competitive dominance (i.e. niche-based dynamics) and ecological drift (i.e. neutral dynamics governed by demographic stochasticity). However, spatial models of competition rarely consider the joint operation of these two processes. We develop a model based on the original competition-colonization trade-off model that incorporates niche and neutral processes and several realistic facets of ecological dynamics: it allows local competition (i.e. competition within a patch) to occur within communities of a finite size, it allows competitors to vary in the degree of competitive asymmetry, and it includes the role of local migration (i.e. propagule pressure). The model highlights the role of community size, i.e. the number of competitors in the local community, in mediating the relative importance of stochastic and deterministic forces. In metacommunities where local communities are small, ecological drift is substantial enough that strong competitors become effectively neutral, creating abrupt changes in the outcome of competition not predicted by the standard competition-colonization trade-off. Importantly, the model illustrates that, even when other aspects of species interactions (e.g. migration ability, competitive ability) are unchanged, local community size can alter the dynamics of metacommunity persistence. Our work demonstrates that activities which reduce the size of local communities, such as habitat destruction and degradation, effectively compound the extinction debt.