火地塘林区原生森林植被极点排序及分类

本文采用极点排序技术，对火地塘林区主要乔木种群及森林群落进行了排序分析，结果表明影响本林区乔木种群及群落分布格局的两个显著的主导的生态梯度是海拔高度和坡度梯度。以乔木树种构成及其相对优势度作为分类依据，将火地塘林区原生森林植被划分为2个森林类群；5个类型组；10个类型。     

Patterns of diel activity and species richness in young and small fishes of European streams: a review of 20 years of point abundance sampling by electrofishing

Originally developed to assess the relative abundance of ≥1+ fishes in large rivers, point abundance sampling by electrofishing (PASE) was adapted for 0+ fishes in the mid‐1980s. Being both economical and widely applicable, PASE for 0+ fish has become a commonly used sampling approach in Europe, but its use for estimating 0+ fish density and species richness has attracted particular concern because of size and species selectivity. As such, this review is both timely and necessary. It summarizes the development of PASE and evaluates its various applications: studies of 0+ fish community composition, relative abundance and density, species richness (S), population size structure, larval and juvenile growth dynamics, microhabitat use, diel dynamics of species–species and species–microhabitat interactions, and the analysis of data emanating from PASE databases. The use and potential misuse of replicate sampling in estimates of S are examined, with PASE data from various European rivers re‐analysed to assess geographical patterns in 0+ fish S. Comparisons of PASE and other approaches for estimating 0+ fish density and species richness have all demonstrated PASE to be cost‐effective and relatively reliable, but sampling accuracy and precision do decrease as fishes enter the juvenile period of development.     

新疆昭苏县沙尔套山天然草地植物群落数量分类与排序(简报)

运用WinTWINS和CANOCO中的DCA排序对沙尔套山主体山地的植被进行了数量分类和排序,将沙尔套山植被划分为16个群丛,进一步用DCA排序方法进行了排序,DCA排序结果与WinTWINS分类结果具有很好的一致性。     

Land cover,riparian zones and instream habitat influence stream fish assemblages in the eastern Amazon

The Amazon rainforest has experienced rapid land‐use changes over the last few decades, including extensive deforestation that can affect riparian habitats and streams. The aim of this study was to assess responses of stream fish assemblages to deforestation and land cover change in the eastern Amazon. We expected that percentage of forest in the catchment is correlated with local habitat complexity, which in turn determines fish assemblage composition and structure. We sampled 71 streams in areas with different land uses and tested for relationships between stream fish assemblages and local habitat and landscape variables while controlling for the effect of intersite distance. Fish assemblage composition and structure were correlated with forest coverage, but local habitat variables explained more of the variation in both assemblage composition and structure than landscape variables. Intersite distance contributed to variance explained by local habitat and landscape variables, and the percentage of variance explained by the unique contribution of local habitat was approximately equivalent to the shared variance explained by all three factors in the model. In these streams of the eastern Amazon, fish assemblages were most strongly influenced by features of instream and riparian habitats, yet indirect effects of deforestation on fish assemblage composition and structure were observed even though intact riparian zones were present at most sites. Long‐term monitoring of the hydrographic basin, instream habitat and aquatic fauna is needed to test for potential legacy effects and time lags, as well as assess species responses to continuing deforestation and land‐use changes in the Amazon.     

Spatial and temporal variation in fish community structure and diversity in the largest tropical flood‐pulse system of South‐East Asia

The Tonle Sap River and Lake (TSRL) is South‐East Asia's largest tropical flood pulse with a flow‐reversal system that supports one of the world's largest freshwater fisheries. However, among the world's tropical floodplains, the resources of the TSRL have received little ecological research. Here, we described the spatiotemporal TSRL fish diversity and community variation using daily records from 2012 to 2015 on fish abundance from six sites covering the TSRL system. We found that high fish diversity occurred in sites located in the middle of Tonle Sap Lake, and the lowest diversity was observed in the southern section. The spatial abundance distribution patterns displayed a river–lake gradient, with three fish assemblages that were clustered based on their composition similarities and were characterised by 96 indicator species. In the southern section, fish assemblages were characterised by longitudinal migratory fishes; in contrast, in the middle system, fish assemblages were represented by species with combined ecological attributes (i.e. longitudinal and lateral migratory species and floodplain residents). Towards the northern section, fish assemblages were composed of lateral migratory and floodplain resident species. Species richness and abundance peaked at approximately 2–2.5 and 4 months, respectively, after the peak flow in early October, during which Tonle Sap River resumes its normal flow direction (outflow). This suggests that seasonal flood pulses (i.e. rising and falling water levels) play a pivotal role in structuring spatiotemporal variation in the TSRL fish assemblages. Our study has implications for fisheries monitoring and conservation initiatives.     

Genotype by environment effects and selection for drought tolerance in tropical maize. I. Two mode pattern analysis of yield

Ten trials evaluated the performance of several late tropical maize populations (La Posta Sequía, Pool 26 Sequía and Tuxpeño Sequía) selected for tolerance to drought during flowering and grain filling and also for yield potential. Families (S₁ or full-sib) had been selected recurrently for six to eight years on an index of traits. Pattern (clustering and ordination) analysis was used to analyse the relative performance of entries that included cycles of selection for drought tolerance in the populations and non-drought tolerant checks. Mean environment (E) yields ranged from 1.0 to 10.4 t ha^-1. Analysis of variance showed that 97.9% of the total sums of squares was accounted for by E, and that, of the remaining sums of squares the G × E (genotype by environment interaction) was almost 3 times that of the contribution of G alone. Cluster analysis separated the checks, the earlier maturing drought tolerant entries and the later maturing drought tolerant entries. This was verified by principal component (PC) analysis of the G × E matrix. Grouping of the environments (i.e. based on entry performance), resulted in the separation of different types of droughts, and of medium and high yielding well-watered environments. The patterns of discrimination observed indicated that the yield gains under drought would have been unlikely to occur if selection had been done only in well-watered environments. Within each population, selection improved broad adaptation (higher mean yield) to both drought and well-watered environments and cycles of selection ‘jumped’ from non-drought-tolerant to drought-tolerant groups as their specific adaptation to drought environments increased.     

林种结构规划的层次分析方法

本文应用层次分析方法,对林种结构的规划建立了模型,并给出一个应用实例。结果表明该模型对解决林种结构的合理规划是实用可行的。     

黄土高原植物群落生态关系研究

应用TWINSPAN、DCA、CCA、DCCA等数量分析方法，从植物群落与环境的生态关系方面，对黄土高原植物群落类型、结构、生态及分布格局进行了研究。结果表明，将排序和分类结合起来能更好地反映黄土高原植物群落间的生态关系。     

Detecting the spatial component of variation in the weed community at the farm scale with variation partitioning by canonical correspondence analysis

Variation partitioning by canonical correspondence analysis (CCA) was applied to analyse spatial variation in the species composition of a weed community for an area of farmland in southern Finland. The farmland, covering 450 ha, was sampled with a 60 m × 60 m grid. Data on weed species were collected along with the following groups of explanatory variables: spatial variables (the terms of second-order polynomial trend surface regression equation generated on the x and y co-ordinates of sample quadrats: x, y, x², xy, y², x²y and xy²), farmer variables (nine farms), soil variables (four soil types and pH value), crop variables (barley, oats, sugarbeet, potato and turnip rape) and physical variables (area of field, altitude, slope and aspect in four directions). The main variation in species composition along the first and second CCA axes was caused by interplay between farmer and crop variables. Farmer and crop variables explained more of the variation than did soil or physical variables. All the variables were to some extent spatially structured. The spatial variables contributed 54.5% of the total variation, of which pure spatial variation accounted for 12.2%. The highest covariation with spatial variables was detected with farmer (33.7%) and crop variables (25.7%). Variation partitioning by CCA is recommended for studying the relationship between the spatial variation in weed communities and explanatory variables.