陕西黄龙山林区褐马鸡春季夜栖地选择

2006年4～6月,在陕西黄龙山林区,对褐马鸡(Crossoptilon mantchuricum)春季夜栖地的选择进行了研究.共记录到22个夜栖地,以夜栖树为中心做一个10 m×10 m样方,测定夜栖地海拔、坡向、坡度、坡位、地貌特征、夜栖树高度和胸径、乔木层盖度、乔木的数量、灌木层盖度、草本盖度、水源距离、人为干扰距离、林缘距离、栖枝高度和栖位上盖度等参数;通过9条样带测定54个随机样方,除栖枝高度和栖位上盖度外,指标相同.结果表明,褐马鸡春季夜栖地多偏向以坡度较大、山坡和山脊、接近水源、远离林边、人为干扰距离较远、乔木盖度和密度较大、栖树胸径较大、灌木层盖度和草本层盖度较小为主要特征的地方.主成分分析表明,前5个特征值的累积贡献率达到72.746%,可以较好地反映褐马鸡春季夜栖地生境特征.根据载荷系数绝对值大小,将褐马鸡春季夜栖地生境选择影响因子分别命名为地形和林下植被因子、气象因子、稳定性因子和水因子.影响褐马鸡夜栖地选择的关键因素是安全、舒适和栖息地转换的方便程度.     

森林生态系统的水源涵养功能及其计量方法

为全面认识与正确评价森林生态系统的水源涵养功能,本文探讨了其概念、表现形式及其计量方法,认为：1）森林的水源涵养功能是一个动态、综合的概念,随着人们对森林水文作用认识的不断深入,其内涵不断丰富扩大,因此森林的水源涵养功能概念存在狭义和广义之分;2）森林的水源涵养功能（广义）有多种表现形式,包括拦蓄降水、调节径流、影响降雨和净化水质等,不过其具体表现形式与研究对象、研究目的以及研究尺度有关;3）目前森林拦蓄降水功能的计量方法主要有土壤蓄水能力法、水量平衡法、年径流量法和多因子回归法等8种,不过这些方法都存在一定的局限性,实际应用中需要综合考虑。     

七姊妹山自然保护区黄杉林群落学特征

黄杉为国家Ⅱ级保护植物,是我国特有的第三纪孑遗的珍贵树种,主要分布在我国亚热带的中山地带。采用Braun-Blanquet的植物社会学调查方法并结合典型样方法对七姊妹山自然保护区的原生黄杉群落进行调查,并对其群落特征进行了分析。结果表明:在2300 m~2的调查样地,共有维管束植物52种,隶属24科38属,群落物种组成主要以杜鹃花科、豆科、五加科、壳斗科等种类为主;群落生活型组成分析显示,该黄杉群落高位芽植物占绝对优势,高位芽植物、地面芽植物占比分别为76.9%、13.5%,地上芽和地下芽植物较少,植物的生活型谱大致呈"L"型;群落重要值分析表明,黄杉重要值为53.6,占较大优势,是群落建群种,乌冈栎、石韦分别是灌木层及草本层的优势种,其重要值分别为24.0、54.8;该黄杉群落物种多样性指数整体较低,除均匀度指数外,优势度指数、多样性指数、丰富度指数总体表现出灌木层乔木层草本层,上坡山脊的规律;种群年龄结构分析表明,七姊妹山自然保护区黄杉种群年龄结构呈"L"型分布,属于增长型种群,在一定时间内,表明黄杉仍为该群落的优势种群,林窗的出现使该黄杉群落保持持续更新。     

Vulnerability to forest loss through altered postfire recovery dynamics in a warming climate in the Klamath Mountains

In the context of ongoing climatic warming, certain landscapes could be near a tipping point where relatively small changes to their fire regimes or their postfire forest recovery dynamics could bring about extensive forest loss, with associated effects on biodiversity and carbon‐cycle feedbacks to climate change. Such concerns are particularly valid in the Klamath Region of northern California and southwestern Oregon, where severe fire initially converts montane conifer forests to systems dominated by broadleaf trees and shrubs. Conifers eventually overtop the competing vegetation, but until they do, these systems could be perpetuated by a cycle of reburning. To assess the vulnerability of conifer forests to increased fire activity and altered forest recovery dynamics in a warmer, drier climate, we characterized vegetation dynamics following severe fire in nine fire years over the last three decades across the climatic aridity gradient of montane conifer forests. Postfire conifer recruitment was limited to a narrow window, with 89% of recruitment in the first 4 years, and height growth tended to decrease as the lag between the fire year and the recruitment year increased. Growth reductions at longer lags were more pronounced at drier sites, where conifers comprised a smaller portion of live woody biomass. An interaction between seed‐source availability and climatic aridity drove substantial variation in the density of regenerating conifers. With increasing climatic water deficit, higher propagule pressure (i.e., smaller patch sizes for high‐severity fire) was needed to support a given conifer seedling density, which implies that projected future increases in aridity could limit postfire regeneration across a growing portion of the landscape. Under a more severe prospective warming scenario, by the end of the century more than half of the area currently capable of supporting montane conifer forest could become subject to minimal conifer regeneration in even moderate‐sized (10s of ha) high‐severity patches.     

Dispersal differences predict population genetic structure in Mormon crickets

Research investigating the geographical context of speciation has primarily focused on abiotic factors such as the role of Pleistocene glacial cycles, or geotectonic events. Few study systems allow a direct comparison of how biological differences, such as dispersal behaviour, affect population genetic structure of organisms that were subdivided during the Pleistocene. Mormon crickets exist in solitary and gregarious 'phases', which broadly correspond with an east-west mtDNA division across the Rocky Mountains. Gregarious individuals form bands that can move up to 2 km daily. This study assessed whether population genetic structure results mainly from deep Pleistocene vicariance or if we can also detect more recent genetic patterns due to phase and dispersal differences superimposed on the older, deeper divisions. We found that separation in refugia was a more important influence on genetic divergence than phase, with the Rockies acting as a barrier that separated Mormon cricket populations into eastern and western refugia during Pleistocene glacial cycles. However, patterns of isolation by distance differ between eastern and western clades for both mitochondrial and nuclear DNA, with greater divergence within the eastern, solitary clade. An mtDNA haplotype mismatch distribution is compatible with historical population expansion in the western clade but not in the eastern clade. A persistent (and possibly sex-biased) difference in dispersal ability has most likely influenced the greater population genetic structure seen in the eastern clade, emphasizing the importance of the interaction of Quaternary climate fluctuations and geography with biotic factors in producing the patterns of genetic subdivision observed today.     

Spatial variation of species diversity across scales in an old-growth temperate forest of China

Species richness and abundance are the two most important diversity variables. Species abundance is additive when aggregated across spatial scale, whereas species richness is non-additive. This study analyzes the effect of spatial scale and site on species abundance and richness in a 25-ha temperate forest plot in the Changbai Mountains, northeastern China. The result shows that species abundance and richness are not only dependent on spatial scales, but also dependent on site. Species abundance responds linearly to changes of spatial scale with no intersection in different sites of the study area. However, although species richness also increases with the increase of spatial scale, there are some intersections for the different sites, suggesting that a species-rich site does not always have a high value if the spatial scale is changed. In all, with respect to additive variables, it is relatively easy to extrapolate them from one spatial scale to another spatial scale, as they and the spatial scale usually form a linear relationship. In contrast, non-additive variables are difficult to extrapolate across spatial scales, because they often respond nonlinearly to spatial scale changes. In order to extrapolate these non-additive variables across spatial scales, it is necessary to estimate the relationships between them and spatial scales. As a result, extrapolation of information among spatial scales may be possible, but very difficult, especially for non-additive variables. Because the 25-ha Changbai plot is very small compared to the extent of the world temperate forests, and the vegetation is a relatively uniform type, more such studies in other ecosystems are needed before theories and generalization about scaling effects can be formulated.     

湖南八面山发现灰冠鹟莺和黑喉山鹪莺

正2015年6月在湖南省桂东县八面山国家级自然保护区(25°54′02″~26°06′59″N,113°37′39″~113°50′08″E,900~2 048 m)发现两种雀形目鸟类,通过查阅文献(郑光美2011,邓学建等2012),确认为湖南首次发现。1灰冠鹟莺Seicercus tephrocephalus2015年6月16日傍晚,在湖南桂东八面山保护区金银铺保护站到主峰之间,海拔1 400 m处的矮林中发现1只小型的莺。该莺体长约11 cm,上体灰绿色而下体黄,黄色的眼圈显著,具黑色的头侧线,顶冠灰色。通过外     

GLM versus CCA spatial modeling of plant species distribution

Despite the variety of statistical methods available for static modeling of plant distribution, few studies directly compare methods on a common data set. In this paper, the predictive power of Generalized Linear Models (GLM) versus Canonical Correspondence Analysis (CCA) models of plant distribution in the Spring Mountains of Nevada, USA, are compared. Results show that GLM models give better predictions than CCA models because a species-specific subset of explanatory variables can be selected in GLM, while in CCA, all species are modeled using the same set of composite environmental variables (axes). Although both techniques can be readily ported to a Geographical Information System (GIS), CCA models are more readily implemented for many species at once. Predictions from both techniques rank the species models in the same order of quality; i.e. a species whose distribution is well modeled by GLM is also well modeled by CCA and vice-versa. In both cases, species for which model predictions have the poorest accuracy are either disturbance or fire related, or species for which too few observations were available to calibrate and evaluate the model. Each technique has its advantages and drawbacks. In general GLM will provide better species specific-models, but CCA will provide a broader overview of multiple species, diversity, and plant communities.