Ecological vegetation maps

On ecological vegetation maps, the distribution of vegetation is related to one or more features of the environment. Tolerance, competition, map scales and the environment are discussed with regard to their bearing on the geographical distribution of phytocenoses and their portrayal on maps. There are two types of ecological vegetation maps: those relating the vegetation to one environmental quality, and those with two or more such qualities. The interpretation of ecological vegetation maps is relatively simple when plant communities are related to a single quality of the biotope and difficult but usually more useful when related to several qualities. Perfection is not possible but can be approached asymptotically.     

Brazilian vegetation on maps

The development and current status of mapping the vegetation of Brazil is discussed. This includes the manner of portraying the vegetation on maps, especially with regard to physiognomy and structure, the floristic composition and ecological relations. A slow beginning has given way to a rapid though uneven development. Recent government efforts tend to correct this.     

RAxML and FastTree: comparing two methods for large-scale maximum likelihood phylogeny estimation

Statistical methods for phylogeny estimation, especially maximum likelihood (ML), offer high accuracy with excellent theoretical properties. However, RAxML, the current leading method for large-scale ML estimation, can require weeks or longer when used on datasets with thousands of molecular sequences. Faster methods for ML estimation, among them FastTree, have also been developed, but their relative performance to RAxML is not yet fully understood. In this study, we explore the performance with respect to ML score, running time, and topological accuracy, of FastTree and RAxML on thousands of alignments (based on both simulated and biological nucleotide datasets) with up to 27,634 sequences. We find that when RAxML and FastTree are constrained to the same running time, FastTree produces topologically much more accurate trees in almost all cases. We also find that when RAxML is allowed to run to completion, it provides an advantage over FastTree in terms of the ML score, but does not produce substantially more accurate tree topologies. Interestingly, the relative accuracy of trees computed using FastTree and RAxML depends in part on the accuracy of the sequence alignment and dataset size, so that FastTree can be more accurate than RAxML on large datasets with relatively inaccurate alignments. Finally, the running times of RAxML and FastTree are dramatically different, so that when run to completion, RAxML can take several orders of magnitude longer than FastTree to complete. Thus, our study shows that very large phylogenies can be estimated very quickly using FastTree, with little (and in some cases no) degradation in tree accuracy, as compared to RAxML.     

基于RS和GIS的毛乌素沙地植被盖度定量估测

选取毛乌素沙地东北部的伊金霍洛旗为研究区域,以少量野外定位调查数据与其对应的遥感信息和GIS信息为基础,利用岭估计分析方法,对植被盖度估测模型及其影响因子进行系统研究.结果表明,植被盖度除受NDVI影响外,还与其他遥感信息紧密相关,岭估计方法明显地改善了最小二乘估计的缺陷,克服了变量间由于存在复共线性关系对求解待定参数所造成的不利影响,提高了估测精度.建立了以像元为单位的植被盖度估测模型,其模型检验精度达98.7%.此外,还建立了区域性植被盖度地理信息系统,实现了研究区域内任意一点(像元)或任意土地单元植被盖度的查询、更新及自动制图.     

Assessment of two biomass estimation methods for aquatic vegetation growing on the Amazon Floodplain

Studies of macrophyte productivity in the Amazon region are limited by accessibility and costs; hence, they may suffer from reduced sample size and representation. The present study compares a phenometric (indirect) method and a subsampling (direct) method in terms of accuracy and applicability to estimation of aquatic macrophyte biomass in the Amazon. The results show that phenometric models were not as effective as selective subsampling for the estimation of macrophyte biomass under the studied conditions. Phenometric models performed more acceptably for predicting emergent biomass, and less for submerged and total biomass (r² = 0.77, p < 0.05, RMSE = 200-600 g/m² dry mass). Improvements in r² by using species-specific phenometric models were mostly not significant. Phenotypic variation across the studied region was large enough to preclude the generalization of phenometric relationships into accurate numeric models, while the direct subsampling method was able to account for this variation (RMSE < 500 g/m² dry mass). Subsampling also allowed a significant reduction on the physical effort of biomass sampling, which directly translated into wider and more complete sampling. We suggest that direct subsampling presents the best trade-off between accuracy and coverage for macrophyte biomass measurement in the Amazon floodplain.     

Estimating selection by comparing synonymous and substitutional changes

A higher ratio of substitutional to synonymous changes in between-species than in within-species comparisons has been taken as evidence for positive selection changing amino acids. A model is presented in which a difference of this kind arises as a result of purely neutral mutations, provided that the species compared are sufficiently different to approach a steady state between forward and backward mutation. In Neissseria, substitutions are twice as frequent, relative to synonymous changes, in between-species comparisons: it is shown that the data are consistent with the neutral model. The argument does not invalidate evidence for positive selection, for example in Drosophila, when the species compared are fairly similar.     

Quantitative estimation of gibberellic acid by paper chromatography

Метод для количественного определения от gibberellic кислоты в процессе брожения средства массовой информации, с использованием бумаги по убыванию хроматографии в butylacetate воды описана. Образца корректируется, чтобы рН 2.5-3.0, добыто с н-бутанола, и 0,05 мл. органического слоя пятнами на Хроматографический бумагу. После equilibration от Атмосфера в банке, chromatogram Разработана в butylacetate насыщенных с водой, за 7 часов, и растворитель разрешено покинуть капельного нижней части листа. Обнаружение осуществляется путем опрыскивания с 3% раствор серной кислоты в метаноле и после сушки бумаги, пятна с синий u.v. флуоресценции наблюдается. Определенный артикль площадь пятна оценивается с помощью калибровочной кривой, заговор с ценностей, стандартов, соответствующих 20, 60 и 120 μ g. gibberellic кислоты. Погрешность оценки составляет ± 10-15% когда оценки выполняются тщательно. Низкий предел чувствительности 5 μg.     

Soil and vegetation in two Danish fens following changes in water regime

Over a six year period, lowering of the water table throughout the year in two Danish eutrophic fens led to an increase in bulk density and a decrease in pH, exchangeable base cations, total P, available P, and available Mn. The vascular plant flora and ecological characteristics of the vegetation (weighted Moisture-value, Drainage Index, Nitrogen-value and Reaction-value, and proportion of fen species, of different growth forms, and of different seed dispersal types) changed in accordance with changes in water regime towards more dry conditions, changes of edaphic variables towards more acid and oligotrophic conditions, and increased probability of establishment of plants on patches without vegetation.
Additional two years with reestablishment of the original winter water table in one of the fens led to a further decrease in total P and available P. Most of the non-fen species, which had established in the period with low water table throughout the year, were significantly weakened. However, after a period of two years with reestablished winter water table the vegetation was still different from the original vegetation. Methods to state the statistical significance of changes in frequency of species and ecological characteristics of the vegetation have been worked out.     

USLE/RUSLE模型中植被覆盖管理因子的遥感定量估算研究进展

通用土壤流失方程（USLE）及其后续修正方程（RUSLE）是区域土壤侵蚀风险评估和水土保持规划的有效工具.植被覆盖管理因子作为USLE和RUSLE的重要参数之一,其合理估算对土壤侵蚀的准确预测尤为重要.基于野外实地调查和测量的传统估算法费时、费力且费用高,无法满足宏观尺度上植被覆盖管理因子的快速提取.近年来,遥感技术的发展为大尺度植被覆盖管理因子获取提供了丰富的数据和方法.本文基于国内外相关研究成果,综述了植被覆盖管理因子遥感定量估算方法的研究进展,评述了各类方法的优劣,以期为进一步开展大尺度植被覆盖管理因子的定量估算及拓展现有研究思路提供借鉴.     

Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space

• 1 Advances in dynamic ecosystem modelling have made a number of different approaches to vegetation dynamics possible. Here we compare two models representing contrasting degrees of abstraction of the processes governing dynamics in real vegetation.
• 2 Model (a) (GUESS) simulates explicitly growth and competition among individual plants. Differences in crown structure (height, depth, area and LAI) influence relative light uptake by neighbours. Assimilated carbon is allocated individually by each plant to its leaf, fine root and sapwood tissues. Carbon allocation and turnover of sapwood to heartwood in turn govern height and diameter growth.
• 3 Model (b) (LPJ) incorporates a ‘dynamic global vegetation model’ (DGVM) architecture, simulating growth of populations of plant functional types (PFTs) over a grid cell, integrating individual‐level processes over the proportional area (foliar projective cover, FPC) occupied by each PFT. Individual plants are not simulated, but are replaced by explicit parameterizations of their growth and interactions.
• 4 The models are identical in their representation of core physiological and biogeochemical processes. Both also use the same set of PFTs, corresponding to the major woody plant groups in Europe, plus a grass type.
• 5 When applied at a range of locations, broadly spanning climatic variation within Europe, both models successfully predicted PFT composition and succession within modern natural vegetation. However, the individual‐based model performed better in areas where deciduous and evergreen types coincide, and in areas subject to pronounced seasonal water deficits, which would tend to favour grasses over drought‐intolerant trees.
• 6 Differences in model performance could be traced to their treatment of individual‐level processes, in particular light competition and stress‐induced mortality.
• 7 Our results suggest that an explicit individual‐based approach to vegetation dynamics may be an advantage in modelling of ecosystem structure and function at the resolution required for regional‐ to continental‐scale studies.

     

Bayesian and maximum likelihood estimation of genetic maps

There has recently been increased interest in the use of Markov Chain Monte Carlo (MCMC)-based Bayesian methods for estimating genetic maps. The advantage of these methods is that they can deal accurately with missing data and genotyping errors. Here we present an extension of the previous methods that makes the Bayesian method applicable to large data sets. We present an extensive simulation study examining the statistical properties of the method and comparing it with the likelihood method implemented in Mapmaker. We show that the Maximum A Posteriori (MAP) estimator of the genetic distances, corresponding to the maximum likelihood estimator, performs better than estimators based on the posterior expectation. We also show that while the performance is similar between Mapmaker and the MCMC-based method in the absence of genotyping errors, the MCMC-based method has a distinct advantage in the presence of genotyping errors. A similar advantage of the Bayesian method was not observed for missing data. We also re-analyse a recently published set of data from the eggplant and show that the use of the MCMC-based method leads to smaller estimates of genetic distances.     

Quantitative self-organizing maps for clustering electron tomograms

Tomography emerges as a powerful methodology for determining the complex architectures of biological specimens that are better regarded from the structural point of view as singular entities. However, once the structure of a sufficiently large number of singular specimens is solved, quite possibly structural patterns start to emerge. This latter situation is addressed here, where the clustering of a set of 3D reconstructions using a novel quantitative approach is presented. In general terms, we propose a new variant of a self-organizing neural network for the unsupervised classification of 3D reconstructions. The novelty of the algorithm lies in its rigorous mathematical formulation that, starting from a large set of noisy input data, finds a set of "representative" items, organized onto an ordered output map, such that the probability density of this set of representative items resembles at its possible best the probability density of the input data. In this study, we evaluate the feasibility of application of the proposed neural approach to the problem of identifying similar 3D motifs within tomograms of insect flight muscle. Our experimental results prove that this technique is suitable for this type of problem, providing the electron microscopy community with a new tool for exploring large sets of tomogram data to find complex patterns.     

Succession of secondary forests affected by pine wilt disease in western Japan followed on vegetation maps

Abstract. Succession, changes in the distribution pattern of forest vegetation, and Pinus forest survival following pine wilt disease were clarified based on phytosociological analysis and vegetation maps. Survival of Pinus forests was restricted to the early successional stages, which were located on ridges and the upper part of slopes. Subsequent to pine wilt disease, the succession progressed from early to late substages of Pinus forest, mixed deciduous and evergreen Quercus, to evergreen Quercus forest. Succession occurs in abandoned pine forests which apparently are in a bad state and are vulnerable to attacks by pine wilt disease.     

Monitoring changes in spatio-temporal maps of disease

The object of statistical surveillance is to detect a change in a process accurately and quickly as new observations keep adding to the observed part of the process. In this paper we discuss methodological issues in developing a rapid response in a spatial surveillance system. Simple exploratory statistical methods together with more sophisticated methods, based on hierarchical space-time models defined at small area level, are considered.