Temporal fluctuations and experimental effects in desert plant communities

In the Chihuahuan Desert of the southwestern United States we monitored responses of both winter and summer annual plant communities to natural environmental variation and to experimental removal of seed-eating rodents and ants for 13 years. Analyses of data on population densities of the species by principal component analysis (PCA) followed by repeated measures analysis of variance (rmANOVA) on PCA scores showed that: (1) composition of both winter and summer annual communities varied substantially from year to year, presumably in response to interannual climatic variation, and (2) community composition of winter annuals was also significantly affected by the experimental manipulations of seed-eating animals, but the composition of the summer annual community showed no significant response to these experimental treatments. Canonical discriminant analysis (CDA) was then applied to the data for winter annuals to more clearly identify the responses to the different classes of experimental manipulations. This analysis showed that removing rodents or ants or both taxa caused distinctive changes in species composition. There was a tendency for large-seeded species to increase on rodent removal plots and to decrease on ant removal plots, and for small-seeded species to change in the opposite direction. In the winter annual community there was a significant time x treatment interaction: certain combinations of species that responded differently to removal of granivores also showed opposite fluctuations in response to long-term climatic variation. The large year-to-year variation in the summer annual community was closely and positively correlated across all experimental treatments. The use of multivariate analysis in conjunction with long-term monitoring and experimental manipulation shows how biotic interactions interact with variation in abiotic conditions to affect community dynamics.     

Climatic limits for the present distribution of beech (Fagus L.) species in the world

Aim Beech (Fagus L., Fagaceae) species are representative trees of temperate deciduous broadleaf forests in the Northern Hemisphere. We focus on the distributional limits of beech species, in particular on identifying climatic factors associated with their present range limits. Location Beech species occur in East Asia, Europe and West Asia, and North America. We collated information on both the southern and northern range limits and the lower and upper elevational limits for beech species in each region. Methods In total, 292 lower/southern limit and 310 upper/northern limit sites with available climatic data for all 11 extant beech species were collected by reviewing the literature, and 13 climatic variables were estimated for each site from climate normals at nearby stations. We used principal components analysis (PCA) to detect climatic variables most strongly associated with the distribution of beech species and to compare the climatic spaces for the different beech species. Results Statistics for thermal and moisture climatic conditions at the lower/southern and upper/northern limits of all world beech species are presented. The first two PCA components accounted for 70% and 68% of the overall variance in lower/southern and upper/northern range limits, respectively. The first PCA axis represented a thermal gradient, and the second a moisture gradient associated with the world‐wide distribution pattern of beech species. Among thermal variables, growing season warmth was most important for beech distribution, but winter low temperature (coldness and mean temperature for the coldest month) and climatic continentality were also coupled with beech occurrence. The moisture gradient, indicated by precipitation and moisture indices, showed regional differences. American beech had the widest thermal range, Japanese beeches the most narrow; European beeches occurred in the driest climate, Japanese beeches the most humid. Climatic spaces for Chinese beech species were between those of American and European species. Main conclusions The distributional limits of beech species were primarily associated with thermal factors, but moisture regime also played a role. There were some regional differences in the climatic correlates of distribution. The growing season temperature regime was most important in explaining distribution of Chinese beeches, whilst their northward distribution was mainly limited by shortage of precipitation. In Japan, distribution limits of beech species were correlated with summer temperature, but the local dominance of beech was likely to be dependent on snowfall and winter low temperature. High summer temperature was probably a limiting factor for southward extension of American beech, while growing season warmth seemed critical for its northward distribution. Although the present distribution of beech species corresponded well to the contemporary climate in most areas, climatic factors could not account for some distributions, e. g., that of F. mexicana compared to its close relative F. grandifolia. It is likely that historical factors play a secondary role in determining the present distribution of beech species. The lack of F. grandifolia on the island of Newfoundland, Canada, may be due to inadequate growing season warmth. Similarly, the northerly distribution of beech in Britain has not reached its potential limit, perhaps due to insufficient time since deglaciation to expand its range.     

Climate and vegetation at the Eurosiberian-Mediterranean boundary in the Iberian Peninsula

Abstract. The Northern Iberian Peninsula is dominated by various types of vegetation from deciduous oak and ash to evergreen oak woodlands. A recent vegetation map of Spain portrays vegetation series which are characterized in terms of their phytogeographic region or bioclimatic (altitudinal) belt. The aim of this paper is to determine whether the areas comprised by both phytogeographic regions (Eurosiberian and Mediterranean) in the study area, as established from the phytogeographic characterization of the vegetation, can be discriminated by climatic variables using multivariate methods, and to compare these with other conventional approaches. In addition, bioclimatic (altitudinal) belts and the main vegetation types were tested for discrimination by climatic variables. Conventional climatic criteria as well as discriminant and principal component analysis were applied to climatic data from 205 meteorological stations for which vegetation information had been taken from the vegetation map. Conventional criteria are good predictors of the phytogeographic division (Mediterranean and Eurosiberian regions) in the study area. Results were improved by multiple discriminant analysis based on climatic data of the dry period of the year (June to September). Both regions in the study area can be predicted with over 95 % accuracy. Using the same multivariate procedure and temperature data the bioclimatic (altitudinal) belts of the study area can be predicted with over 90 % accuracy. The main vegetation groups of the study area can also be predicted with over 80 % accuracy. Ordination analysis supported the results of the discriminant analysis. Empirical models have been generated to predict the phytogeographic- and belt character of any station in the area. The significance of the various periods of the year for discriminating regions and belts is evaluated. The responsiveness to climatic events during the year may be region specific. This study confirms the strong relationship between climate and vegetation in the Northern Iberian Peninsula, particularly regarding the Eurosiberian-Mediterranean boundary.     

Climatic responses of Pinus pseudostrobus and Abies religiosa in the Monarch Butterfly Biosphere Reserve,Central Mexico

Understanding the effects of climate on the growth of trees is important to project the response of forests to climate change. Dendrochronological analysis offers a “proxy” source for the effects of climatic variation on tree growth at different spatial and temporal scales. To examine influences of temperature and precipitation on radial growth of Pinus pseudostrobus and Abies religiosa, this study combines measurements of radial growth patterns of forest trees in the Monarch Butterfly Biosphere Reserve (MBBR) in central Mexico with temperature and precipitation variables from instrumental records. Dendrochronological samples were collected as cross sections and increment cores by using a chainsaw and increment borers, respectively. Total ring-width chronologies were developed for each site. Principal component analyses (PCA) were used to identify common temperature, precipitation and tree growth variation patterns. Correlation and response function analyses between chronologies and records of temperature and precipitation were used to evaluate the relation of climate variables on tree growth. The months during which tree growth was most strongly affected by precipitation were January, February and October from the previous year; only the temperature of September from the previous year affected the tree growth. In some chronologies, May’s average monthly maximum temperature was negatively correlated with tree growth. PCA and a comparison of PCA factor scores of climatic variables and chronologies showed no significant differences between northern, central or southern portions of the MBBR. Apparently, tree growth in the MBBR is reduced in years of low January–May precipitation combined with high summer (September of the previous year) temperatures, a scenario which is likely to occur as a consequence of global climate change.     

Identifying Snake Species Threatened by Economic Exploitation and International Trade in China

It is important to identify endangered species from thousands of species and take conservation measures in time. Many researchers have reported declines and overexploitation of snake species, but it is difficult to identify the species requiring emergency concern. We tried to identify the snake species threatened by economic exploitation in mainland China through the following procedure: First, we identified 16 snake species in significant international trade through analyzing trade records; second, we chose 10 variables representing biological characteristics and economics factors. The values of these variables for each species were evaluated from 0 (minimum risk) to 3 (high risk). Three snake species protected by CITES (Convention on International Trade in Endangered Species of Wild Fauna and Flora) were also assessed. We then got the priority rank of these species by calculating their average scores. We found that among the species in significant international trade, except those CITES-listed ones, four snake species were at extremely high risk, while all other snake species in significant trade were endangered or vulnerable. Principal component analysis (PCA) was used to classify the species into four groups according to their different biological and economic characteristics. This study provides a possible way to identify endangered species and to rank their conservation priority. The results of this paper can also be used as a priority sequence for taking conservation action, especially trade control measures.     

Establishing climatic constraints shaping the distribution of alien plant species along the elevation gradient in the Alps

In this work, we analyse the role of climatic constraints in shaping the distribution of alien plant species along the elevation gradient in the European Alps. Alien species occurrence was recorded in 278 plots located beside rivers, from 100 to 2,100 m a.s.l. Climate variables were calculated from the data recorded by 145 meteorological stations and interpolated by a multiple regression approach. Both richness and occurrence of aliens were modelled. In particular, relationships between the occurrence of alien plants and (1) elevation or (2) the climatic variables, were tested by applying generalised linear models and generalised linear mixed models; the model parameters obtained were used to estimate upper elevation limits of alien occurrence and their related climate values. Sixty-eight alien species were encountered, the majority (71%) invasive in Italy and worldwide. A steep decrease in alien species richness with elevation was found, with the probability of alien species occurrence decreasing by half for each 100 m increase in elevation. Minimal adequate models based on (1) non-transformed climatic variables and (2) derived PCA values, confirmed that occurrence of alien plant species along the elevation gradient was positively related to the minimum temperature, the mean temperature and the heat sum for the spring season, rather than to the incidence of absolute minimum temperature and frost days, as usually assumed. Although further experimental analyses are needed, these results support the hypothesis that, referring to climate factors, elevation limits along rivers are mainly established by low spring temperatures which operate at the level of population viability rather than plant survival.     

Estimating plant responses to climate by direct gradient analysis and geographic distribution analysis

We characterised the climatic behaviour of 53 woody species in terms of the climatic factors that play the main role in controlling species distribution in the study area. Floristic and climatic data were obtained from 150 stands in sites under climatic control (i.e. eu-climatopes). The sampling strategy used allowed a reliable match between floristic and climatic observations. Different methods of frequency analysis and goodness-of-fit tests were used to identify associations between species occurrence and climatic characteristics. The species' responses were summarised by statistics describing ecological preferences and amplitudes, and species were grouped accordingly. A Gaussian response model was fitted to the abundance data along the main climatic gradients for selected species and response surfaces were derived by spatial analysis for a set of indicator species. Frequency analysis methods detected 42 indicator taxa for the Baudiere's Qe drought index, and lower numbers, 34 and 22, respectively, for the mean minimum coldest-month temperature and the daily temperature range in the coldest month. Goodness-of-fit tests revealed a lower number of ecological profiles with statistically significant deviations from equidistribution. We discuss the relative performance of the different methods and suggest that the combined use of statistical tests and frequency analyses may improve estimation of the environmental requirements of species. We also recommend using the species' responses to key environmental factors as reliable criteria in the definition of plant functional types. This revised version was published online in August 2006 with corrections to the Cover Date.     

Spatial distribution of sand fly species (Psychodidae: Phlebtominae), ecological niche,and climatic regionalization in zoonotic foci of cutaneous leishmaniasis,southwest of Iran

Cutaneous leishmaniasis (CL) is a complex vector‐borne disease caused by Leishmania parasites that are transmitted by the bite of several species of infected female phlebotomine sand flies. Monthly factor analysis of climatic variables indicated fundamental variables. Principal component‐based regionalization was used for recognition of climatic zones using a clustering integrated method that identified five climatic zones based on factor analysis. To investigate spatial distribution of the sand fly species, the kriging method was used as an advanced geostatistical procedure in the ArcGIS modeling system that is beneficial to design measurement plans and to predict the transmission cycle in various regions of Khuzestan province, southwest of Iran. However, more than an 80% probability of P. papatasi was observed in rainy and temperate bio‐climatic zones with a high potential of CL transmission. Finding P. sergenti revealed the probability of transmission and distribution patterns of a non‐native vector of CL in related zones. These findings could be used as models indicating climatic zones and environmental variables connected to sand fly presence and vector distribution. Furthermore, this information is appropriate for future research efforts into the ecology of Phlebotomine sand flies and for the prevention of CL vector transmission as a public health priority.     

Defining phytoclimatic units in Galicia,Spain, by means of multivariate methods

Abstract. Floristic and climate data from 150 plots in 25 sites in Galicia, Spain, were analysed to test the hypothesis that climate is the major factor governing the distribution of woody plant species. TWINSPAN classification, Detrended Correspondence Analysis and Canonical Correspondence Analysis were applied in successive stages of the data analysis to describe vegetational variation in relation to climatic gradients. Six groups of species were defined, two clearly oceanic (Maritime and Cool Maritime), one mediterranean maritime, and three mediterranean (Cold Mediterranean, Cool Mediterranean and Temperate Mediterranean). An aridity gradient was revealed as the primary factor regulating the distribution of the species considered. This main gradient reflects the transition between the Eurosiberian and Mediterranean bio-geographic regions. The gradient can be characterized by means of the Vernet bioclimatic index. A value ≥ 4 for this index can be taken to define the mediterranean zone in our study area. The mean minimum temperature in the coldest month was the second most influential climatic variable. Partial ordination analysis revealed that the residual variation was insignificant and that the observed variation in vegetation can be fully accounted for by climatic variables.     

Butterfly species richness in the north-west Mediterranean Basin: the role of natural and human-induced factors

Aim We developed a model enabling us to evaluate the contribution of both natural and human‐related factors to butterfly species richness in Catalonia, a Mediterranean area that harbours one of the most diverse butterfly faunas in Europe. Location The study was carried out in Catalonia (north‐east Iberian Peninsula), a region of 31,930 km² lying between the Pyrenees, the Ebro depression and the Mediterranean sea. Methods Data from the Catalan Butterfly Monitoring Scheme were used to assess butterfly species richness from 55 transects spread all over the region. Three groups of environmental variables likely to affect the presence of butterfly species were calculated, above all from geographic information system data: (1) climatology and topography, (2) vegetation structure and (3) human disturbance. Because climatic and topographic variables are expected to be strongly correlated, we first performed a principal component analysis (PCA) to create a summarizing factor that would account for most of the variance within this set of variables. Subsequently, a backward stepwise multiple regression was performed in order to assess the effects of environmental factors on butterfly species richness. Results A total of 131 species were detected in the monitoring transects, representing 75.7% of the butterfly fauna known from Catalonia. Mean species richness per transect and per year was 41.4, although values varied greatly among sites (range: 14–76.8). The final regression model explained more than 80% of the total variance, which indicated a strong association between butterfly species richness and the studied environmental factors. The model revealed the very important contribution of climatic and topographic variables, which were combined into a single factor in the PCA. In contrast to what has been found in other, more northerly countries, species richness was negatively correlated with temperature and positively correlated with rainfall, except for extreme cold and wet conditions. This may be a consequence of the predictably adverse effects of the Mediterranean summer drought on herbivorous insects, and the fact that the limits of distribution of many butterflies correlate well with climatic variables. Human disturbance (defined as the proportion of urban and agricultural landscape cover in buffer areas of 5 km around the transect sites) was the second most important predictor for species richness. We found that a significant decrease in species numbers was associated with an increase in human pressure, a finding that indicates that not only building development, but also modern‐day agricultural practices are detrimental to the conservation of Mediterranean butterflies. Surprisingly, vegetation variables had an almost negligible effect on butterfly species richness. Main conclusions Our findings strongly indicate that the current motors of global change will have a negative effect on Mediterranean butterfly assemblages. First, changes in land‐use are transforming and fragmenting the landscape into an inhospitable and less permeable matrix for butterflies. Secondly, the negative correlation between species richness and temperature will lead to a predictable loss of diversity over the coming years, as predicted in the most plausible scenarios of climate change. Considering the high butterfly richness characterizing the Mediterranean Basin, this future trend will pose a serious threat to biodiversity.     

Mechanisms of hydrazine toxicity in rat liver investigated by proteomics and multivariate data analysis

A proteomics approach combined with multivariate data analysis was used to examine the hepatotoxic effect of hydrazine in 30 male Sprague Dawley rats, assigned to four treatment groups and two control groups. Liver samples from the individual animals were resolved by two-dimensional differential gel electrophoresis (2-D DIGE) and protein patterns from the 2-D gels were analyzed by principal component analysis (PCA) and partial least squares regression (PLSR). The PCA plot was able to describe the variation in the protein expression related to dose and time, by separation or clustering of different animal groups. PLSR followed by variable selection (Jack-knifing) was used to select proteins that varied significantly in relation to the dose related response of the hydrazine treatment. The 10 up-regulated and 10 down-regulated proteins with highest rank in the PLSR model were identified by mass spectrometry. Hydrazine treatment induced altered expression of proteins related to lipid metabolism, Ca(2+) homeostasis, thyroid hormone pathways and stress response. Several of the identified proteins have not previously been implicated in hydrazine toxicity and may thus be regarded as new potential biomarkers of induced liver toxicity.     

Comparison of multivariate methods for the analysis of genetic resources and adaptation in Phytolacca dodecandra using RAPD

The extent of genetic differentiation among 17 Ethiopian populations (249 individuals) of Phytolacca dodecandra (Endod) sampled along altitudinal gradients that varied from 1600 to 3000 m was investigated using random amplified polymorphic DNA (RAPD). The populations were classified into three altitude groups: lowland (1600–2100 m), central-highland (2101–2500 m) and highland (2500–3000 m). Seventy polymorphic loci scored from 12 RAPD primers, singly or in combination with ecogeographical variables (altitude, longitude, latitude, temperature and rainfall), were used for principal component, discriminant, correlation, and stepwise multiple regression analyses. Principal component analysis (PCA) clearly differentiated lowland and the central-highland populations from those of the highlands independent of their geographical regions. Canonical discriminant analysis separated the lowland plants from those of the highlands with the central-highland plants being intermediate. Classificatory discriminant analysis corrected classification of 92.8% of the 249 plants into their respective three altitude groups. Multiple regression analysis identified a strong association between some RAPDs and altitude, temperature and rainfall, while the variation in most RAPDs was explained by combinations of the different ecogeographical variables. It is hypothesised that the different altitude groups may be (1) chemical and/or physiological ecotypes produced as a result of complex interactions of altitude with climatic and/or edaphic factors, or (2) different in ploidy levels. The significant correlations obtained between population means from some RAPDs and altitude and temperature as well as the strong association of some RAPDs with the ecogeographical variables in the multiple regression analysis suggest that part of the RAPD polymorphism could be adaptive, and responsive to environmental selection. Received: 15 December 1999 / Accepted: 12 February 2000     

Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France

Aim  To estimate the relative importance of climate and soil nutritional variables for predicting the distribution of Acer campestre (L.) in French forests.
Location  France.
Methods  We used presence/absence information for A. campestre in 3286 forest plots scattered all over France, coupled with climatic and edaphic data. More than 150 climatic variables (temperature, precipitation, solar radiation, evapotranspiration, water balance) were obtained using a digital elevation model (DEM) and a geographical information system (GIS). Six direct soil variables (pH, C/N ratio, base saturation rate, concentrations of calcium, magnesium and potassium) were available from EcoPlant, a phytoecological data base for French forests. Using a forward stepwise logistic regression technique, we derived two distinct predictive models for A. campestre ; the first with climatic variables alone and the second with both climatic and edaphic variables.
Results  The distribution of A. campestre was poorly modelled when including only climatic variables. The inclusion of edaphic variables significantly improved the quality of predictions for this species, allowing prediction of patches of presence/absence within the study region.
Main conclusion  Soil nutritional variables may improve the performance of fine-scale (grain) plant species distribution models.     

Elevational patterns of species richness and endemism for some important taxa in the Hengduan Mountains, southwestern China

We describe the elevational patterns of species richness and endemism of some important taxa in the Hengduan Mountains, southwest China. Species richness data came from publications, an online database, herbaria and field work. Species richness was estimated by rarefaction and interpolation. The Hengduan Mountains region was divided into a southern and northern subregion, and all species were assigned to four groups based on their distributional range within this region. The conditional autoregressive model (CAR) was used to relate species richness and explanatory variables. The elevational patterns of total, endemic and non-endemic species richness, at subregion and entire region scales, presented to be unimodal and peaked at similar elevations. Area size was strongly related with species richness, and was more powerful in explaining variation in species richness in the northern subregion than in the southern subregion. A single climatic variable (mean annual rainfall, potential evapotranspiration or moisture index) showed a weak relationship with the elevational pattern of species richness. Area and climatic variables together explained more than 67% of the variation in non-endemic richness, 53% in total richness, and 50% in endemic richness. There were three patterns of endemism at the generic level with increasing elevation: namely endemism increased, decreased, or peaked at middle elevations. All selected taxa have experienced rapid speciation and evolution within this region, which plays an important role in the uniform elevational patterns of total, endemic and non-endemic richness, and in the multiform elevational patterns of endemism. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Where and why? Bees,snail shells and climate: Distribution of Rhodanthidium (Hymenoptera: Megachilidae) in the Iberian Peninsula

Species distribution patterns are widely studied through species distribution models (SDMs), focusing mostly on climatic variables. Joint species distribution models (JSDMs) allow inferring if other factors (biotic interactions, shared phylogenetic history or other unmeasured variables) can also have an influence on species distribution. We identified current distributional areas and optimal suitability areas of three species of the solitary snail‐shell bee Rhodanthidium (Hymenoptera: Megachilidae), and their host gastropod species in the Iberian Peninsula. We undertook SDMs using Maxent software, based on presence points and climatic variables. We also undertook JSDMs for the bees and the snails to infer if co‐occurrence could be a result of biotic interactions. We found that the three bee species: (1) use at least five different species of Mediterranean snails; (2) use empty shells not only for nesting but also for sheltering when there is adverse weather and during the night; (3) have their most suitable areas in the eastern and southern Iberian Peninsula, mostly on limestone areas; and (4) have their optimal range under Mediterranean climatic values for the studied variables. There is positive co‐occurrence of Rhodanthidium with the gastropod species, especially with the snail Sphincterochila candidissima. The contribution of the environmental component to the co‐occurrence is less than that of the residual component in those cases, suggesting that: (i) the use of biotic resources (between Rhodanthidium and the gastropod species); (ii) shared phylogenetic history (between R. septemdentatum and R. sticticum); or (iii) unmeasured variables are largely responsible for co‐occurrence.     

Insights from the clustering of microarray data associated with the heart disease

Heart failure (HF) is the major of cause of mortality and morbidity in the developed world. Gene expression profiles of animal model of heart failure have been used in number of studies to understand human cardiac disease. In this study, statistical methods of analysing microarray data on cardiac tissues from dogs with pacing induced HF were used to identify differentially expressed genes between normal and two abnormal tissues. The unsupervised techniques principal component analysis (PCA) and cluster analysis were explored to distinguish between three different groups of 12 arrays and to separate the genes which are up regulated in different conditions among 23912 genes in heart failure canines'' microarray data. It was found that out of 23912 genes, 1802 genes were differentially expressed in the three groups at 5% level of significance and 496 genes were differentially expressed at 1% level of significance using one way analysis of variance (ANOVA). The genes clustered using PCA and clustering analysis were explored in the paper to understand HF and a small number of differentially expressed genes related to HF were identified.     

Principal component analysis for clustering gene expression data

MOTIVATION: There is a great need to develop analytical methodology to analyze and to exploit the information contained in gene expression data. Because of the large number of genes and the complexity of biological networks, clustering is a useful exploratory technique for analysis of gene expression data. Other classical techniques, such as principal component analysis (PCA), have also been applied to analyze gene expression data. Using different data analysis techniques and different clustering algorithms to analyze the same data set can lead to very different conclusions. Our goal is to study the effectiveness of principal components (PCs) in capturing cluster structure. Specifically, using both real and synthetic gene expression data sets, we compared the quality of clusters obtained from the original data to the quality of clusters obtained after projecting onto subsets of the principal component axes. RESULTS: Our empirical study showed that clustering with the PCs instead of the original variables does not necessarily improve, and often degrades, cluster quality. In particular, the first few PCs (which contain most of the variation in the data) do not necessarily capture most of the cluster structure. We also showed that clustering with PCs has different impact on different algorithms and different similarity metrics. Overall, we would not recommend PCA before clustering except in special circumstances.     

Multivariate analysis of climatic patterns of the Meditrranean basin

Climatic data from 444 weather-recording stations in the Mediterranean basin are examined by cluster analysis and principal component analysis. The application of numerical clustering distinguished several groups of climatic stations clearly interpretable in geographic and climatic terms. The hierarchical structure of the dendrograms could be used to identify at different scales uniform climatic regions. The complementary application of principal component analysis produced an ordination of climatic types, which clearly showed the main trends of variation in the precipitation and temperature patterns.     

CONTROL OF VEGETATION ON CONTRASTING SUBSTRATES: HERB PATTERNS ON SERPENTINE AND SANDSTONE

Binary discriminant analysis (BDA) reveals relationships between species distributions and environmental variables. In this study, BDA was applied to transects on serpentine and sandstone in the Wenatchee Mountains, Washington. Species presence and states of ten habitat variables were recorded in each quadrat. Species response patterns significantly different from a random expectation suggested that distributions are controlled by soil moisture far more strongly on serpentine than they are on sandstone, where light and its correlates are more important. Environmental patterns were explored with direct principal components analysis (PCA) of standardized environmental variables and indirectly by PCA of the significant D-values. The latter is biased towards variables to which species respond strongly. The results emphasize the environmental and floristic contrasts between substrates. On serpentine, direct PCA indicates that effective moisture, soil fertility, and insolation control the first three axes, while on sandstone, insolation, fertility, and effective moisture control the first three axes, respectively. The PCA of D-values (Q-mode) is similarly interpreted: moisture is strongly correlated with the first component on the serpentine transect, while insolation and fertility are correlated with the first component on sandstone. Species ordinations also result from Q-mode analysis. They reflect species responses to the identified gradients and indicate mutual species-environment interactions. These analyses conform to the hypothesis that mineral conditions of serpentine select against intolerant species and that survivors respond primarily to moisture conditions that are a result of low productivity, attributable to adverse nutrient conditions. On sandstone, the moisture gradient is less pronounced, and direct canopy effects that create variable light conditions predominate. BDA is a useful tool in ecological survey and pattern analysis. Species responses to environmental factors may be estimated quickly and directly. This method will help to focus subsequent research, improve experimental design, and generate explicit and testable hypotheses about species-habitat interactions.