A morphological classification of plants,with special reference to the New Zealand alpine flora

Abstract. A plant is a complex of integrated systems (leaves, leaf groups, stems, roots, inflorescences), coexisting side by side or superimposed on each other to produce the life form (orphysiognomy) of the individual. The classic Raunkiaer classification based fundamentally on one character (apex position) is insufficient for the purpose of a functional classification. Five keys are given to determine the categories of:

• 1) the plant silhouette or general shape resulting from a combination of other systems, with 11 categories proposed;
• 2) the leaf group, with 14 categories;
• 3) the stem, with 27 categories;
• 4) the root, with 5 categories; and
• 5) the inflorescence, with 3 categories.

Each plant can be named according to the category or model of each of the five different systems that they most resemble, or by using only the name(s) of systems which are more conspicuous than others. Characters are selected primarily for their influence on form and secondarily on size. This scheme allows for detailed studies of a flora in terms of morphological characteristics (alone or in systems), expressed as frequency of occurrence of each character in the flora. Characters can be analysed separately (e.g. entire margined leaves), as a combination of characters (e.g. leaf groups) or as a combination of systems (e.g. rosettes without stems). Thus correlations between environmental variables and plants canbe made with more precision than in previous classification schemes. The classification also serves as the framework for including additional morphological data and incorporating new models. The New Zealand alpine flora is used as a test case and to exemplify the classification.     

广州地区19个引进龙眼品种果实品质的评价与分类

对广州地区引进的19个龙眼(Dimocarps longan)品种的果实品质进行了评价与分类研究。结果表明：在表观性状方面,除品种间肉质、果形差异较大外,其它性状差异不大,部分性状之间具有一定的关联性;小果或薄皮的品种一般可溶性固形物含量较高,薄皮、厚肉或横扁的品种一般可食率较高。运用分层聚类的方法,依据各品质指标将品种划分为3类; 运用基于主成分分析的因子分析法,将8个品质指标用3个主成分来表示(累计贡献率达88.27%);确定简化后的品质评价指标为单果质量、果形指数、可食率和肉厚率,并依据因子得分和简化指标对19个品种进行聚类,两种聚类结果基本一致。     

Static and Dynamic Facial Images Cue Similar Attractiveness Judgements

Approaches to the study of human mate preferences commonly involve judgements of facial photographs and assume that these judgements provide a reasonable reflection of how individuals would be perceived in real encounters. However, three recent studies have each reported non‐significant correlations between judgements using photos (static images) and those using videos (dynamic images). These results have led previous authors to conclude that static and dynamic faces are judged according to different evaluative standards and that this may call into question the validity of findings from experiments using static images. However, the extent of the discrepancy in judgements between image formats remains unknown, and may be influenced by different experimental designs. Here, we tested the effects of several experimental design factors on the strength of correlations between image presentation formats. Using both male and female targets, we compared observed static–dynamic judgement correlations when (1) judgements were made by the same or different raters, or (2) by raters of the same‐ or opposite‐sex to the targets, and (3) when dynamic stimuli were collected under different contextual scenarios. For (1) and (2), we also measured correlations when order of presentation of static and dynamic stimuli was alternated. Our results suggest that each design feature has independent effects on the strength of static–dynamic correlations. Correlations were stronger when static and dynamic stimuli were rated by the same raters. They were weakest for judgements of males by females, when based on seeing photos before videos. This interaction with sex is consistent with previous studies, indicating that females are especially responsive to male dynamic cues. However, in contrast to previous findings and in all cases, static–dynamic correlations were strongly and significantly positive, indicating that judgments based on static images provide an accurate representation of someone’s attractiveness during prolonged encounters.     

THE GENETIC BASIS OF A COMPLEX FUNCTIONAL SYSTEM

The relationship between form and function can have profound effects on evolutionary dynamics and such effects may differ for simple versus complex systems. In particular, functions produced by multiple structural configurations (many‐to‐one mapping, MTOM) may dampen constituent trade‐offs and promote diversification. Unfortunately, we lack information about the genetic architecture of MTOM functional systems. The skulls of teleost fishes contain both simple (lower jaw levers) as well as more complex (jaws modeled as 4‐bar linkages) functional systems within the same craniofacial unit. We examined the mapping of form to function and the genetic basis of these systems by identifying quantitative trait loci (QTL) in hybrids of two Lake Malawi cichlid species. Hybrid individuals exhibited novelty (transgressive segregation) in morphological components and function of the simple and complex jaw systems. Functional novelty was proportional to the prevalence of extreme morphologies in the simple levers; by contrast, recombination of parental morphologies produced transgression in the MTOM 4‐bar linkage. We found multiple loci of moderate effect and epistasis controlling jaw phenotypes in both the simple and complex systems, with less phenotypic variance explained by QTL for the 4‐bar. Genetic linkage between components of the simple and complex systems partly explains phenotypic correlations and may constrain functional evolution.     

Multivariate Approach for Studying Interactions between Environmental Variables and Microbial Communities

To understand the role of human microbiota in health and disease, we need to study effects of environmental and other epidemiological variables on the composition of microbial communities. The composition of a microbial community may depend on multiple factors simultaneously. Therefore we need multivariate methods for detecting, analyzing and visualizing the interactions between environmental variables and microbial communities. We provide two different approaches for multivariate analysis of these complex combined datasets: (i) We select variables that correlate with overall microbiota composition and microbiota members that correlate with the metadata using canonical correlation analysis, determine independency of the observed correlations in a multivariate regression analysis, and visualize the effect size and direction of the observed correlations using heatmaps; (ii) We select variables and microbiota members using univariate or bivariate regression analysis, followed by multivariate regression analysis, and visualize the effect size and direction of the observed correlations using heatmaps. We illustrate the results of both approaches using a dataset containing respiratory microbiota composition and accompanying metadata. The two different approaches provide slightly different results; with approach (i) using canonical correlation analysis to select determinants and microbiota members detecting fewer and stronger correlations only and approach (ii) using univariate or bivariate analyses to select determinants and microbiota members detecting a similar but broader pattern of correlations. The proposed approaches both detect and visualize independent correlations between multiple environmental variables and members of the microbial community. Depending on the size of the datasets and the hypothesis tested one can select the method of preference.     

Lateral Preferences as Possible Phenotypic Predictors of the Reserves of the Cardiovascular System and the Features of Sensorimotor Integration in Climbers

The lateral preferences of the hands, the reserves of the cardiovascular system and the features of sensorimotor integration in mountain climbers as possible predictors of adaptation to extreme factors of the external environment have been investigated. The subjects were 15 climbers of high class (men aged 25.5–62.8 years). We used the following methods: reflexometric technique ReBFB (complex sensorimotor reaction in the model of go/no-go, computer simulation according to Chernikov); the assessment of lateral preferences using the standard samples; the orthostatic test (with the recording of the heart rate and evaluation of adaptive reserves based on the indices of mathematical analysis of the cardiac rhythm in the transition period according to a technique by Riftin). Sensorimotor integration was performed under normal conditions and under normobaric hypoxia. All indicators were correlated with the age and proficiency of the climbers. We observed no statistically significant correlations between age and the reserves of the cardiovascular system in the group of climbers. Reflexometry in normoxic conditions showed an improvement in the orientation of subjects in the sensory flow as compared with the initial level. The sensorimotor integration (as a response of sensorimotor responses) was more stable during hypoxia as compared with the same indices in normoxia. Noticeable correlation was observed between the results of the humeral test and the reserves of the cardiovascular system defined by orthostatic hypotension: the reserves were higher in the subjects with a higher level of left-hand preference. The regulation of the autonomic nervous system is correlated with left-handedness, which results in more effective adaptation to the high altitude in left-handers. The parameter of handedness can be used as a phenotypic predictor of the level of the cardiovascular system reserves in climbers. It is suggested that the factor of hypoxia with small exposure has a stimulating effect on sensorimotor integration in climbers.     

Topological Strata of Weighted Complex Networks

The statistical mechanical approach to complex networks is the dominant paradigm in describing natural and societal complex systems. The study of network properties, and their implications on dynamical processes, mostly focus on locally defined quantities of nodes and edges, such as node degrees, edge weights and –more recently– correlations between neighboring nodes. However, statistical methods quickly become cumbersome when dealing with many-body properties and do not capture the precise mesoscopic structure of complex networks. Here we introduce a novel method, based on persistent homology, to detect particular non-local structures, akin to weighted holes within the link-weight network fabric, which are invisible to existing methods. Their properties divide weighted networks in two broad classes: one is characterized by small hierarchically nested holes, while the second displays larger and longer living inhomogeneities. These classes cannot be reduced to known local or quasilocal network properties, because of the intrinsic non-locality of homological properties, and thus yield a new classification built on high order coordination patterns. Our results show that topology can provide novel insights relevant for many-body interactions in social and spatial networks. Moreover, this new method creates the first bridge between network theory and algebraic topology, which will allow to import the toolset of algebraic methods to complex systems.     

Spatial and Space-Time Correlations in Systems of Subpopulations with Genetic Drift and Migration

The geographic distribution of genetic variation is an important theoretical and experimental component of population genetics. Previous characterizations of genetic structure of populations have used measures of spatial variance and spatial correlations. Yet a full understanding of the causes and consequences of spatial structure requires complete characterization of the underlying space-time system. This paper examines important interactions between processes and spatial structure in systems of subpopulations with migration and drift, by analyzing correlations of gene frequencies over space and time. We develop methods for studying important features of the complete set of space-time correlations of gene frequencies for the first time in population genetics. These methods also provide a new alternative for studying the purely spatial correlations and the variance, for models with general spatial dimensionalities and migration patterns. These results are obtained by employing theorems, previously unused in population genetics, for space-time autoregressive (STAR) stochastic spatial time series. We include results on systems with subpopulation interactions that have time delay lags (temporal orders) greater than one. We use the space-time correlation structure to develop novel estimators for migration rates that are based on space-time data (samples collected over space and time) rather than on purely spatial data, for real systems. We examine the space-time and spatial correlations for some specific stepping stone migration models. One focus is on the effects of anisotropic migration rates. Partial space-time correlation coefficients can be used for identifying migration patterns. Using STAR models, the spatial, space-time, and partial space-time correlations together provide a framework with an unprecedented level of detail for characterizing, predicting and contrasting space-time theoretical distributions of gene frequencies, and for identifying features such as the pattern of migration and estimating migration rates in experimental studies of genetic variation over space and time.     

How structure determines correlations in neuronal networks

Networks are becoming a ubiquitous metaphor for the understanding of complex biological systems, spanning the range between molecular signalling pathways, neural networks in the brain, and interacting species in a food web. In many models, we face an intricate interplay between the topology of the network and the dynamics of the system, which is generally very hard to disentangle. A dynamical feature that has been subject of intense research in various fields are correlations between the noisy activity of nodes in a network. We consider a class of systems, where discrete signals are sent along the links of the network. Such systems are of particular relevance in neuroscience, because they provide models for networks of neurons that use action potentials for communication. We study correlations in dynamic networks with arbitrary topology, assuming linear pulse coupling. With our novel approach, we are able to understand in detail how specific structural motifs affect pairwise correlations. Based on a power series decomposition of the covariance matrix, we describe the conditions under which very indirect interactions will have a pronounced effect on correlations and population dynamics. In random networks, we find that indirect interactions may lead to a broad distribution of activation levels with low average but highly variable correlations. This phenomenon is even more pronounced in networks with distance dependent connectivity. In contrast, networks with highly connected hubs or patchy connections often exhibit strong average correlations. Our results are particularly relevant in view of new experimental techniques that enable the parallel recording of spiking activity from a large number of neurons, an appropriate interpretation of which is hampered by the currently limited understanding of structure-dynamics relations in complex networks.     

Motivation and Benefits of Complex Systems Approaches in Ecology

Studies of complex systems in other disciplines provide models and analytical strategies for understanding ecosystems and landscapes. The emphasis is on invariant properties, particularly processes that create scaling relations over wide ranges of scale, both in time and space. Translations between levels of ecological organization may be accomplished by succinct characterizations of processes that operate at fine scales, followed by renormalization group analysis to reveal patterns at broad scales. The self-organized patterns found in simple ecosystem, landscape, and forest-fire models may be explained as feedback between the system state and control parameters. Critical phenomena and phase transitions are expected in open, dissipative systems where long-range correlations defy predictions based on average population densities, a concept that becomes irrelevant as nonstationary conditions prevail. Thus, complexity theory for open systems relates to the ecology of self-entailing ecosystems that function as their own environments and thereby create constraints through emergence. Received: 14 April 1998; accepted 26 May 1998     

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.     

Mycobacterium avium Complex in Day Care Hot Water Systems,and Persistence of Live Cells and DNA in Hot Water Pipes

The Mycobacterium avium complex (MAC) is a group of opportunistic human pathogens that may thrive in engineered water systems. MAC has been shown to occur in drinking water supplies based on surface water, but less is known about the occurrence and persistence of live cells and DNA in public hot water systems based on groundwater. In this study, we examined the occurrence of MAC in hot water systems of public day care centers and determined the persistence of live and dead M. avium cells and naked DNA in model systems with the modern plumbing material cross-linked polyethylene (PEX). The occurrence of MAC and co-occurrence of Legionella spp. and Legionella pneumophila were determined using cultivation and qPCR. Co-occurrences of MAC and Legionella were detected in water and/or biofilms in all hot water systems at temperatures between 40 and 54 °C. Moderate correlations were observed between abundance of culturable MAC and that of MAC genome copies, and between MAC and total eubacterial genome copies. No quantitative relationship was observed between occurrence of Legionella and that of MAC. Persistence in hot water of live and dead M. avium cells and naked DNA was studied using PEX laboratory model systems at 44 °C. Naked DNA and DNA in dead M. avium cells persisted for weeks. Live M. avium increased tenfold in water and biofilms on PEX. The results suggest that water and biofilms in groundwater-based hot water systems can constitute reservoirs of MAC, and that amplifiable naked DNA is relatively short-lived, whereas PEX plumbing material supports persistence and proliferation of M. avium.     

Relationship between the protein surface hydrophobicity and its partitioning behaviour in aqueous two-phase systems of polyethyleneglycol-dextran

In order to develop possible correlations to predict partioning behaviour of proteins, five mammalian albumins (goat, bovine, equine, human and pig ones) with similar physico-chemical properties (molecular mass and isoelectrical point) were chosen. Evaluation of the relationship between hydrophobicity and partitioning coefficient (Kr) in polyethylenglycol-dextran (PEG-DxT500) systems formed by polyethyleneglycols of different molecular mass (3350, 6000 and 10,000) was investigated by estimating relative surface hydrophobicity (So) with a fluorescent probe, 1 anilino-8-naphthalene sulfonate. No relationship between Kr and So was found for systems formed by PEG3350, while aqueous two-phase systems with PEG6000 and PEG10,000 gave better correlations. The results obtained may be explained on the basis of an increase in the interaction between the latter PEGs and the protein due to their higher hydrophobic character which increases as the PEG molecular mass does so. In this way, systems with PEGs of higher molecular mass give the highest resolution to exploit hydrophobicity in partitioning.     

An evaluation of Poisson-Boltzmann electrostatic free energy calculations through comparison with experimental mutagenesis data

For systems involving highly and oppositely charged proteins, electrostatic forces dominate association and contribute to biomolecular complex stability. Using experimental or theoretical alanine-scanning mutagenesis, it is possible to elucidate the contribution of individual ionizable amino acids to protein association. We evaluated our electrostatic free energy calculations by comparing calculated and experimental data for alanine mutants of five protein complexes. We calculated Poisson-Boltzmann electrostatic free energies based on a thermodynamic cycle, which incorporates association in a reference (Coulombic) and solvated (solution) state, as well as solvation effects. We observe that Coulombic and solvation free energy values correlate with experimental data in highly and oppositely charged systems, but not in systems comprised of similarly charged proteins. We also observe that correlation between solution and experimental free energies is dependent on dielectric coefficient selection for the protein interior. Free energy correlations improve as protein dielectric coefficient increases, suggesting that the protein interior experiences moderate dielectric screening, despite being shielded from solvent. We propose that higher dielectric coefficients may be necessary to more accurately predict protein-protein association. Additionally, our data suggest that Coulombic potential calculations alone may be sufficient to predict relative binding of protein mutants.     

Simple and accurate correlation of experimental redox potentials and DFT-calculated HOMO/LUMO energies of polycyclic aromatic hydrocarbons

The ability to accurately predict the oxidation and reduction potentials of molecules is very useful in various fields and applications. Quantum mechanical calculations can be used to access this information, yet sometimes the usefulness of these calculations can be limited because of the computational requirements for large systems. Methodologies that yield strong linear correlations between calculations and experimental data have been reported, however the balance between accuracy and computational cost is always a major issue. In this work, linear correlations (with an R² value of up to 0.9990) between DFT-calculated HOMO/LUMO energies and 70 redox potentials from a series of 51 polycyclic aromatic hydrocarbons (obtained from the literature) are presented. The results are compared to previously reported linear correlations that were obtained with a more expensive computational methodology based on a Born-Haber thermodynamic cycle. It is shown in this article that similar or better correlations can be obtained with a simple and cheaper calculation.