Principal components analysis as a tool for the optimization of experimental conditions

Principal Components Analysis is used to display the variation in a data set consisting of the free amino-acid patterns in serum from dogs as a function of fasting time. Inhomogeneities found in the data set resulted in an optimization of the experimental conditions. Moreover important observations concerning sampling time and biological variability could be made.     

A comparison of reciprocal averaging and non-centred principal components analysis

Non-centred Principal Components Analysis (NPCA) ordinates sites and species simultaneously, and can be solved either by direct iteration or by eigenvector calculation. The weight of sites and species in the analysis is proportional to their overall abundance. Because of this, the method is not susceptible to distortion by rare species, as is the case with Reciprocal Averaging (RA). Detrending techniques can also be applied to this method to eliminate arch effects.When NPCA was tried with field data, it produced ordination axes that were significantly associated to independently measured environmental variables. In contrast, RA failed to produce axes related to environmental factors, even after the main rare species had been eliminated from the analysis.Abbreviations NPCA Non-centred Principal Components Analysis - RA Reciprocal Averaging     

TECHNIQUES FOR STUDYING THE SPATIO-TEMPORAL DISTRIBUTION OF ANIMAL VOCALIZATIONS IN TROPICAL WET FORESTS

ABSTRACT

An array of four microphones was set up in two rain forest locations in Costa Rica, and 12–14 hours of sound were recorded over a 24-hour period at each location. Using this acoustical location system, the distribution of animal signaling in time, space and frequency could be assessed. This study demonstrates the feasibility of localizing some animals acoustically even under difficult field conditions in a highly reverberant and noisy environment. Primates seem to be particularly easy to track using this method, while birds seem more problematical. We also advocate the use of long-term indiscriminate acoustical sampling of all vocalizers, in order to give information about the synecology of animal communication. Long-term spectral analysis and data reduction by Principal Components Analysis provide tools for comparing acoustical samples over time and space.     

Influence of ionic strength and conductivity on benthic diatom communities in a tropical river (Monjolinho), S?o Carlos-SP, Brazil

Benthic diatoms are important indicators of ecological conditions in lotic systems. The objective of this study was to elucidate the confounding effects of eutrophication, organic pollution and ionic strength and conductivity on benthic diatom communities. Benthic diatoms and water quality sampling was done at 10 sites during summer base flow period (2008 and 2009). Detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) were used to determine environmental gradients along which species vary with respect to ionic strength and conductivity and other environmental variables. Using variance partitioning, we assessed the individual importance of a set of environmental variables (eutrophication and organic pollution) versus ionic strength and conductivity on diatom community structure. The effects of ionic strength and conductivity and organic pollution, eutrophication and other environmental variables were integrated into overall resultant benthic diatom communities. Through partial CCA, we partitioned the variance in diatom data between two sets of exploratory variables, i.e. ionic strength and conductivity (26.9%); other variables, particularly eutrophication and organic pollution (23.0%); shared variance (11.3%) and unexplained variance (38.8%). Due to the interaction of the effects of ionic strength and conductivity and other variables in this study, laboratory experiments must be performed to confirm the observed effects of ionic strength and conductivity.     

Vegetation-environment relationships on a species-rich coastal mountain range in the fynbos biome (South Africa)

The species-rich fynbos of the southern Langeberg Mountains, South Africa was studied along three transects (a) to evaluate the compatibility of a floristic classification of the southern Langeberg vegetation with a fynbos biome-wide structural classification of mountain vegetation, (b) to describe the environmental gradients to which the vegetation responds and (c) to investigate the relationship between the vegetation and the abiotic environmental variables which determine the pattern of distribution of the fynbos communities on the southern Langeberg.Principal Components Analysis (PCA) was used to determine correlations between environmental variables independent of vegetation data. Similarities between the 46 communities (determined by floristics) from the three transects were determined using cluster analysis and grouped into 14 higher-level units. Detrended Correspondence Analysis (DCA) was then used for indirect gradient analysis after which Canonical Correspondence Analysis (CCA) was used in a direct gradient analysis of the vegetation with the environmental variables.Compatibility between the floristic and structural classification of the vegetation was analysed. The PCA principal gradient was defined as one from sites with high rock cover, shallow soils and north aspects to those with low rock cover, deeper soils and south aspects. The second gradient is most strongly positively correlated with percentage organic carbon and most strongly negatively correlated with soil clay content. In contrast to the PCA, the DCA showed that the principal gradient is a precipitation gradient, with the response of the vegetation dominated by the change from wet to dry conditions and from low to high winter incoming radiation. The CCA showed that the variation in the mountain habitats to which the vegetation responds can be predicted from a combination of a few environmental variables. The principal gradient was one of change from high to low mean annual precipitation with an opposite change in winter incoming radiation. The second gradient was described by percentage surface rock cover and soil clay content. A simple model using the environmental factors selected in the CCA was proposed for predicting the distribution of floristically determined community groups in the fynbos vegetation of the Langeberg and the southern Cape coastal mountains in general.     

Parallel Analysis: a method for determining significant principal components

Abstract. Numerous ecological studies use Principal Components Analysis (PCA) for exploratory analysis and data reduction. Determination of the number of components to retain is the most crucial problem confronting the researcher when using PCA. An incorrect choice may lead to the underextraction of components, but commonly results in overextraction. Of several methods proposed to determine the significance of principal components, Parallel Analysis (PA) has proven consistently accurate in determining the threshold for significant components, variable loadings, and analytical statistics when decomposing a correlation matrix. In this procedure, eigenvalues from a data set prior to rotation are compared with those from a matrix of random values of the same dimensionality (p variables and n samples). PCA eigenvalues from the data greater than PA eigenvalues from the corresponding random data can be retained. All components with eigenvalues below this threshold value should be considered spurious. We illustrate Parallel Analysis on an environmental data set. We reviewed all articles utilizing PCA or Factor Analysis (FA) from 1987 to 1993 from Ecology, Ecological Monographs, Journal of Vegetation Science and Journal of Ecology. Analyses were first separated into those PCA which decomposed a correlation matrix and those PCA which decomposed a covariance matrix. Parallel Analysis (PA) was applied for each PCA/FA found in the literature. Of 39 analy ses (in 22 articles), 29 (74.4 %) considered no threshold rule, presumably retaining interpretable components. According to the PA results, 26 (66.7 %) overextracted components. This overextraction may have resulted in potentially misleading interpretation of spurious components. It is suggested that the routine use of PA in multivariate ordination will increase confidence in the results and reduce the subjective interpretation of supposedly objective methods.     

Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID) and Artificial Neural Network Models (ANNs)

There are a large number of tomato cultivars with a wide range of morphological, chemical, nutritional and sensorial characteristics. Many factors are known to affect the nutrient content of tomato cultivars. A complete understanding of the effect of these factors would require an exhaustive experimental design, multidisciplinary scientific approach and a suitable statistical method. Some multivariate analytical techniques such as Principal Component Analysis (PCA) or Factor Analysis (FA) have been widely applied in order to search for patterns in the behaviour and reduce the dimensionality of a data set by a new set of uncorrelated latent variables. However, in some cases it is not useful to replace the original variables with these latent variables. In this study, Automatic Interaction Detection (AID) algorithm and Artificial Neural Network (ANN) models were applied as alternative to the PCA, AF and other multivariate analytical techniques in order to identify the relevant phytochemical constituents for characterization and authentication of tomatoes. To prove the feasibility of AID algorithm and ANN models to achieve the purpose of this study, both methods were applied on a data set with twenty five chemical parameters analysed on 167 tomato samples from Tenerife (Spain). Each tomato sample was defined by three factors: cultivar, agricultural practice and harvest date. General Linear Model linked to AID (GLM-AID) tree-structured was organized into 3 levels according to the number of factors. p-Coumaric acid was the compound the allowed to distinguish the tomato samples according to the day of harvest. More than one chemical parameter was necessary to distinguish among different agricultural practices and among the tomato cultivars. Several ANN models, with 25 and 10 input variables, for the prediction of cultivar, agricultural practice and harvest date, were developed. Finally, the models with 10 input variables were chosen with fit’s goodness between 44 and 100%. The lowest fits were for the cultivar classification, this low percentage suggests that other kind of chemical parameter should be used to identify tomato cultivars.     

Comparison of ordinations and classifications of vegetation data

The methodology of comparing the results of multivariate community studies (resemblance matrices, ordinations, hierarchical and nonhierarchical classifications) is reviewed from two viewpoints: basic strategy and measure employed. The basic strategy is determined by 7 choices concerning the type of results, consensus methods or resemblance measures, hypothesis testing or exploratory analysis, lack or presence of reference basis, data set congruence or algorithmic effects, number of factors responsible for differences among results, and the number of properties considered in the comparison. Included is a brief summary of methods applicable to vegetation studies. Examples from a grassland survey demonstrate the utility of comparisons in evaluating the effects of plot size, data type, standardization, taxonomic level and number of species on classifications and ordinations.Abbreviations OUC = Operational Unit of Comparison - PCA = Principal Components Analysis - PCoA = Principal Coordinates Analysis - SSA = Incremental Sum of Squares Agglomeration     

Distance decay of similarity,effects of environmental noise and ecological heterogeneity among species in the spatio‐temporal dynamics of a dispersal‐limited community

The joint spatial and temporal fluctuations in community structure may be due to dispersal, variation in environmental conditions, ecological heterogeneity among species and demographic stochasticity. These factors are not mutually exclusive, and their relative contribution towards shaping species abundance distributions and in causing species fluctuations have been hard to disentangle. To better understand community dynamics when the exchange of individuals between localities is very low, we studied the dynamics of the freshwater zooplankton communities in 17 lakes located in independent catchment areas, sampled at end of summer from 2002 to 2008 in Norway. We analysed the joint spatial and temporal fluctuations in the community structure by fitting the two‐dimensional Poisson lognormal model under a two‐stage sampling scheme. We partitioned the variance of the distribution of log abundance for a random species at a random time and location into components of demographic stochasticity, ecological heterogeneity among species, and independent environmental noise components for the different species. Non‐neutral mechanisms such as ecological heterogeneity among species (20%) and spatiotemporal variation in the environment (75%) explained the majority of the variance in log abundances. Overdispersion relative to Poisson sampling and demographic stochasticity had a small contribution to the variance (5%). Among a set of environmental variables, lake acidity was the environmental variable that was most strongly related to decay of community similarity in space and time.     

The Relationship between Economic Status,Knowledge on Dengue,Risk Perceptions and Practices

The reemergence of dengue as an important public health problem reflects the difficulties in sustaining vertically organized, effective, control programs and the need for community-based strategies for Aedes aegypti control that result in behavioral change. We aimed to disentangle the relationships between underlying determinants of dengue related practices. We conducted a cross-sectional study in 780 households in La Lisa, Havana, Cuba. A questionnaire and an observation guide were administrated to collect information on variables related to economic status, knowledge on dengue, risk perception and practices associated with Aedes aegypti breading sites. To test a conceptual model that hypothesized direct relationships among all these constructs, we first used Exploratory Factor Analysis with Principal Component Analysis to establish the relationship between observed variables and the underlying latent variables. Subsequently, we tested whether the observed data supported the conceptual model through Confirmatory Factor Analysis. Exploratory Factor Analysis indicated that the items measured could be reduced into five factors with an eigenvalue >1.0: Knowledge on dengue, Intradomiciliar risk practices, Peridomiciliar risk practices, Risk perception and Economic status. The proportion of the total variance in the data explained by these five factors was 74.3%. The Confirmatory Factor Analysis model differed from our hypothesized conceptual model. Only Knowledge on dengue had a significant, direct, positive, effect on Practices. There was also a direct association of Economic status with Knowledge on dengue, but not with Risk perception and Practices. Clarifying the relationship between direct and indirect determinants of dengue related practices contributes to a better understanding of the potential effect of Information Education and Communication on practices and on the reduction of Aedes aegypti breeding sites and provides inputs for designing a community based strategy for dengue control.     

Gross morphometry of young Geochelone sulcata (Testudines: Testudinidae) in Costa Rica

The African Spur tortoise, Geochelone sulcata, has been introduced to Costa Rica. A total of 31 tortoises were measured for 26 gross morphometry parameters. All individuals measured were inmature, aged from 5 to 34 months, and were born in captivity in La Garita de Alajuela, Costa Rica. Mean straight carapace length was 83.1 mm, mean straight plastron length was 68.3 mm and mean maximum height was 46.2 mm. All the measurements were correlated, except tail length and cloacal distance. Weight had the highest positive allometry coefficient. All the variables were joined in two Principal Components; tail length and cloacal distance in Factor 2 and the rest of them in Factor 1. Lack of correlation among tail measures and the other variables as well as their inclusion in a different Factor could be related with an incipient development of sexual dimorphism characters.     

Gulf of fos (France): Main hydrological features (1976–1978)

Surrounded by a heavily industrialized area, subject to natural fresh water dilution (Etang de Berre, Rhône river), the Gulf of Fos is an unbalanced neritic zone. Its distrophic character is accentuated by numerous continental discharges; furthermore, the climatic instability which characterizes this region (irregular periods of winds, fluvial risings) reinforces the changing ecological conditions in the gulf waters. The present paper shows the major ecological conditions in that neritic area, and the main events occured during the 1976–1978 period, through and extensive sampling network. The principal regulating features are thus described by the mean of a mathematical data processing (Principal Components Analysis).     

The Physical and Chemical Limnology of 24 Ponds and One Lake from Isachsen,Ellef Ringnes Island,Canadian High Arctic

The limnology of freshwaters surrounding Isachsen, Ellef Ringnes Island, Nunavut was examined to determine the baseline physical and chemical limnological conditions present in the region. Sites were found to be circumneutral to slightly acidic, and were oligotrophic. Concentrations of most measured chemical variables were highly variable, with broad ranges that greatly exceeded those found in previous surveys conducted in the High Arctic. Ratios of nitrogen to phosphorus suggest that nitrogen may be the limiting nutrient for algal growth at the majority of sites. Principal Components Analysis (PCA) indicated that the major controls on water chemistry variability between sites were conductivity and related variables, and nutrients, explaining 36.5% and 26.5% of the variation in the dataset, respec‐tively.     

Principal component analysis: Development of a multivariate index for assessing eutrophication according to the European water framework directive

The discriminating power of eutrophication assessment schemes is often affected by the intercorrelation between cause (nutrient concentrations) and response (phytoplankton biomass and diversity) variables. Principal component analysis, a multivariate data reduction technique producing new sets of uncorrelated variables, was applied on nitrate, nitrite, ammonia, phosphate and chlorophyll α concentrations from coastal waters in the Aegean Sea, Eastern Mediterranean, and the first principal component was derived and evaluated as a eutrophication index on an independent dataset. The index, a linear combination of the five variables with almost equal weights, was found efficient in discriminating levels of eutrophication and critical thresholds characterizing oligotrophy, mesotrophy and eutrophication were set. The applicability of these thresholds for the implementation of the European Water Framework Directive was also examined thereof a five-level water quality classification scheme was developed.     

Tracing alpha, beta, and gamma diversity responses to environmental change in boreal lakes

Boreal lakes undergo broad-scale environmental change over time, but biodiversity responses to these changes, particularly at macroecological scales, are not well known. We studied long-term trends (1992–2009) of environmental variables and assessed α, β, and γ diversity responses of phytoplankton and littoral invertebrates to these changes. Diversity was assessed based on taxon richness (“richness”) and the exponentiated Shannon entropy (“diversity”). Almost all environmental variables underwent significant monotonic change over time, indicating mainly decreasing acidification, water clarity and nutrient concentrations in the lakes. These variables explained about 54 and 38 % of variance in regression models of invertebrates and phytoplankton, respectively. Despite this, most diversity-related variables fluctuated around a long-term mean. Only α and γ richness and diversity of invertebrates increased monotonically through time, and these patterns correlated significantly with local and regional abundances. Results suggest that biodiversity in boreal lakes is currently stable, with no evidence of regional biotic homogenization or local diversity loss. Results also show that richness trends between phytoplankton and invertebrates were widely uncorrelated, and the same was found for diversity trends. Also, within each taxonomic group, temporal patterns of richness and diversity were largely uncorrelated with each other. From an applied perspective, this suggest that long-term trends of biodiversity in boreal lakes at a macroecological scale cannot be accurately assessed without multiple lines of evidence, i.e. through the use of multiple taxa and diversity-related variables in the analyses.     

Personality and conditioning: factors of classical CR acquisition and extinction and their relationship to personality types

A number of psychophysiological, cognitive and personality measures, and classical appetitive and aversive SR acquisition and extinction rates were taken from a sample of 25 male undergraduate volunteers. Principal Components Analysis of the data revealed general acquisition and extinction factors which were indexed by the psychophysiological variables. Regression analyses showed additionally that Eysenck's E-I dimension predicts both acquisition and extinction rates, and that imagery may be an important mediational variable in CR acquisition.     

Patterns of life history variation in the Funariales,Polytrichales and Pottiales

Abstract

A combination of Principal Component and Cluster Analyses is used to test for recurring suites of life history variation among 357 species of the Funariales, Polytrichales, and Pottiales. About 85% of among-species covariation in life expectancy, spore size and number, and sexuality is summarized by three Principal Components. Cluster Analyses, using species scores on these three derived variables, identify six groups of species based on similar grades of covariation in life history traits. These groups also differ significantly in water relations, gametophyte size, modes of spore dispersal, and prevalence of asexual reproductive propagules, and apparently are ecologically coherent, at least with regard to spatio-temporal scales of habitat availability and heterogeneity.

A number of differences emerge in comparisons of Principal Component Analyses performed separately for each of seven families. In particular, the distribution of overall variance among successive components varies greatly, suggesting that the number of biologically independent axes of life history specialization differs among families. Likewise, differences in loadings of the life history variables on Principal Components indicate that their patterns of covariation change as a function of familial membership.

In the Pottiales, the likelihood of producing sporophytes decreases with increasing life expectancy, and also shows a negative association with the production of asexual propagules. The likelihood of producing asexual propagules is higher among dioicous species and those not known with gametangia than among monoicous species, and is also positively associated with life expectancy. Alternative historical and ecological explanations are offered to account for these patterns of association.

These results support the idea that recurring suites of life history traits occur among moss species, and the patterns of life history variation appear to be associated with particular sets of environmental circumstances. The influence of phylogenetic history on life history variation is also strong. Until explicitly phylogenetic approaches can be employed, the extent to which observed patterns are adaptive rather than historically contingent must remain unresolved.     

Bird and mammal species composition in distinct geographic regions and their relationships with environmental factors across multiple spatial scales

Global patters of species distributions and their underlying mechanisms are a major question in ecology, and the need for multi‐scale analyses has been recognized. Previous studies recognized climate, topography, habitat heterogeneity and disturbance as important variables affecting such patterns. Here we report on analyses of species composition – environment relationships among different taxonomic groups in two continents, and the components of such relationships, in the contiguous USA and Australia. We used partial Canonical Correspondence Analysis of occurrence records of mammals and breeding birds from the Global Biodiversity Information Facility, to quantify relationships between species composition and environmental variables in remote geographic regions at multiple spatial scales, with extents ranging from 10⁵ to 10⁷ km² and sampling grids from 10 to 10,000 km². We evaluated the concept that two elements contribute to the impact of environmental variables on composition: the strength of species' affinity to an environmental variable, and the amount of variance in the variable. To disentangle these two elements, we analyzed correlations between resulting trends and the amount of variance contained in different environmental variables to isolate the mechanisms behind the observed relationships. We found that climate and land use‐land cover are responsible for most explained variance in species composition, regardless of scale, taxonomic group and geographic region. However, the amount of variance in species composition attributed to land use / land cover (LULC) was closely related to the amount of intrinsic variability in LULC in the USA, but not in Australia, while the effect of climate on species composition was negatively correlated to the variability found in the climatic variables. The low variance in climate, compared to LULC, suggests that species in both taxonomic groups have strong affinity to climate, thus it has a strong effect on species distribution and community composition, while the opposite is true for LULC.     

Cyanobacteria blooms cannot be controlled by Effective Microorganisms (EM<Superscript>®</Superscript>) from mud- or Bokashi-balls

The aim of the present contribution is to assess whether the abundance of mollusk species in the Southern Pampas (Argentina), an environmentally homogeneous region, reflect the local conditions of water bodies. In order to test this hypothesis, a comprehensive study was conducted in 30 sites regularly distributed across the region. At each site, the abundance of mollusk species was determined, and a series of physico-chemical measurements taken. Principal Component Analysis (PCA) and Cluster Analysis (CA) were used for the ordination of sampling sites based on the measured environmental variables. In addition, Canonical Correspondence Analysis (CCA) was conducted to explore the relationships between environmental variables and mollusk abundances. Mollusk species were represented by the gastropods Biomphalaria peregrina, Chilina parchappii, Heleobia parchappii, Physa acuta, Pomacea canaliculata, Stenophysa marmorata, Uncancylus concentricus and the bivalve Musculium argentinum. Although aquatic vegetation cover, conductivity, and substrate were among the main parameters influencing mollusk distribution, their effect was insufficient to explain the spatial distribution pattern of the species in a regional scale. It is because the Southern Pampas is a very homogeneous area, and the ranges of these environmental conditions are within the range of ecological tolerance of most of the species represented. Yet, some species resulted good indicators of environmental conditions at local (microhabitat) scale, i.e., particular microhabitats that occur in different water bodies as well. In fact, even distributed in many different water bodies along the Southern Pampas C. parchappii is always linked to lotic environments, and U. concentricus is exclusively restricted to hard substrata. On the other hand, H. parchappii is the only species represented in mesohaline waters and P. acuta appeared to be a good indicator of pollution in the area.     

Do dung beetles show interrelated evolutionary trends in wing morphology,flight biomechanics and habitat preference?

In flying organisms, wing shape and biomechanical properties are recognized as key traits related to dispersal, foraging behavior, sexual selection and habitat preferences. To determine if differences in dung beetle wing shape and flight biomechanics are consistent with habitat preferences in a phylogenetic context, we examined how wing morphology varied in a set of 18 Mozambique forest and grassland dung beetle (Scarabaeinae) species, representing nine genera and six tribes. Geometric morphometric measurements were taken of entire wings, as well as two additional shape characters comprising the RA4 and CuA to J regions of veins. Ordination (Principal Components Analysis and Canonical Variate Analysis) of landmark data revealed three different trends in wing shape related to expansion or contraction in external wing margins. These trends were consistent with published dung beetle phylogenies and a phylogenetic reconstruction of ancestral morphological changes using parsimony analysis of wing landmark configurations. Analysis of variance showed that the Procrustes distances between wing shapes were significantly correlated to species identity (~?48% of variance), wing size (~?27%), habitat (~?11%) and two of the three, tested, biomechanical variables (wing loading, wing aspect ratio: ~?1%). However, while a phylogenetic generalized least squares analysis confirmed a strongly significant phylogenetic signal for wing shape, it found no significant effect of any other variable. Therefore, wing shape evolution in dung beetles appears to have been phylogenetically constrained and habitat may constitute only a weak selective pressure for changes in wing shape.