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Aim: Biogeographic regionalization classifies zones in terms of their biotas and contributes to understanding the ecological and historical factors that affect the distribution of species. We use Ecological Niche Modeling (ENM) to complement missing information on species distribution and thus improve the accuracy of biogeographic boundaries. Location: Balsas Depression Floristic Province, Mexico. Methods: Based on parameters documented in herbarium collections and environmental variables, ENM was carried out to determine the most suitable environmental conditions for a species to thrive (i.e., the species' ecological niche). The ENM and spatial analysis were used to obtain the biogeographic regionalization of the seasonally dry tropical forest (SDTF) in the Balsas Depression (BD), Mexico, through spatial analysis. Using the Maxent algorithm, we constructed ecological niche models (ENMs) of 134 flowering plant species distributed preferentially in the SDTF (characteristic species), most of them endemic to the BD. Subsequently, we obtained an incidence matrix based on the information from the 134 ENMs, which was used to analyze the turnover of species in Biodiverse software. The turnover matrix was used for Non‐metric Multidimensional Scaling (NMDS) ordination and clustering analyses. Finally, the environmental predictors most related to species turnover were identified using the relative environmental turnover method. Results: The clustering analysis divided the SDTF in the BD into four floristic districts — two located in its western part and two in the eastern region. The NMDS differentiated, in the first component, two districts in the western region and one in the eastern. Seven environmental variables contributed significantly to explaining the turnover of species in these districts; the most significant were the elevation, pH, and precipitation of the coldest quarter. Main Conclusions: The use of ENM for the regionalization of areas with high species richness allows for a more detailed classification of subregions and the distribution patterns of the species that define their limits. This provides a more solid theoretical basis for the investigation of biogeographic patterns. [ABSTRACT FROM AUTHOR]

Aims: Unravelling the most prevalent causal direction between diversity and function in naturally recovered plant assemblages can greatly improve our understanding of the functional significance of diversity and its applications under the ongoing environmental changes. In this study, we apply a structural equation model framework to unravel the most plausible causal direction in the diversity–productivity relationship in subseral Mediterranean shrub‐dominated communities. Methods: Total shrub cover (as a proxy of productivity when controlled by the time since land use cessation or the last wildfire), the number of species, and the number of functional types based on the dominant life forms (phanerophytes vs. chamaephytes), and the dominant foliar syndromes (deciduous vs. evergreen, needled vs. broad‐leaved), were sampled in 195 circular plots distributed along an elevation gradient ranging from 400 to 1400 m a.s.l. in the Central Iberian Peninsula. We first explored the distribution of functional types along the elevation gradient using a non‐metric multidimensional scaling (NMDS). Secondly, a structural equation model (SEM) framework using mixed‐effects models was defined to unveil the prevalent causal direction between diversity (species and functional types) and productivity at the landscape scale. Results: Model selection using the Fisher's C information criterion supported a causal direction from total shrub cover to diversity in this landscape. Interestingly, the best supported model also supported a positive relationship between species richness and the number of functional types, which in turn is driven by the total shrub cover along the elevation gradient. Conclusions: Our results suggest that more species might not necessarily boost productivity. On the contrary, ongoing warming temperatures and aridity, which are characteristic of low elevations compared to highlands, might significantly reduce the number of species (victim rather than rescuer) through deleterious effects on productivity. [ABSTRACT FROM AUTHOR]

Aims: Wildfires in dry forest ecosystems in western North America are producing fire effects that are more severe than historical estimates, raising concerns about the resilience of these landscapes to contemporary disturbances. Despite increasing fire activity, relatively little is known about the structure and composition of fire refugia — unburned or low‐severity burned patches where trees survived fire — or the degree to which their understory composition differs from fire‐generated early‐seral forests. Locations: Four recent large fires in dry mixed‐conifer forest in eastern Oregon, USA. Methods: We sampled vegetation and environmental factors in 187 plots (100‐m2) in fire refugia (n = 52) and stand‐replacement patches (SRPs) (n = 135). We used non‐metric multidimensional scaling, indicator species analysis, and randomization tests to compare understory plant communities and diversity in fire refugia and SRPs 12–17 years post‐fire. Results: Understory plant communities in fire refugia and SRPs showed strong compositional affinities, but exhibited shifts in reproductive trait prevalence and differences in landscape‐scale species richness. There were no differences in plot‐scale species richness or the occurrence of two prominent invasive annual grasses (Bromus tectorum, Ventenata dubia). The abundance of common obligate seeding species was similar between plot types, but resprouting and seed‐banking species became substantially more abundant in SRPs. Significantly more plant species occurred only in fire refugia, and significantly fewer in SRPs, than expected by chance. Conclusions: Similarities in understory plant communities between fire refugia and early‐seral forest in SRPs provide evidence for the resilience of historically frequent‐fire forest understory communities to contemporary fire effects. However, fire refugia may serve an ecologically important role as patches with relatively intact forest structure, seed sources that contribute to post‐fire forest recovery, and as reservoirs of species and age structure that may be absent from the higher‐severity burned matrix. [ABSTRACT FROM AUTHOR]

Question: Vegetation recovery and succession patterns after fire are not completely explained by the interactions of climate, disturbance, and species pool. Site‐specific factors can substantially change vegetation succession. We hypothesize that on sites exposed to fire and surface permafrost degradation, successional trajectories will produce different species assemblages than typical post‐fire succession. Location: Da Xing'an Mountains, northern China. Methods: Vegetation and environmental data were collected at eight sites of past natural wildfire events. These sites represented different topographical situations, with four sites on slopes (lacking surface permafrost) and four sites in valleys (with surface permafrost). Three plots were established on each site, representing three different fire presence zones (burned, ecotone and unburned areas), giving a total of 24 plots. We used non‐metric multidimensional scaling (NMS) to describe post‐fire vegetation recovery at different sites and multi‐response permutation procedures (MRPP) to test our hypothesis. Results: The variation in dates of last fire was similar between the slope and valley sites. Slope sites that had been burned prior to 2003 had recovered to a composition similar to unburned sites by the time the study was conducted in 2017. However, none of the burned valley sites had fully recovered, even those exposed to fire in 1986, suggesting that the surface permafrost conditions affected the recovery pattern of vegetation. On burned valley sites, shrub species that are tolerant of saturated soils had become dominant and the number of tree saplings and seedlings became significantly lower than on the slope sites. Conclusion: The interaction of fire and topographic site type (through the influence of surface permafrost degradation) was revealed as a primary factor affecting species composition and tree density of post‐fire communities. On valley sites, melting of the surface permafrost after fire caused a failure of tree recruitment and prompted shrub species tolerant of saturated soils to become dominant. [ABSTRACT FROM AUTHOR]

Questions: Past agricultural land use and forest management have shaped and influenced the understorey composition in European forests for centuries. We investigated whether understorey vegetation assemblages are affected by (a) legacies from a historical infield/outland agricultural system (i.e., a system with nutrient‐enriched vs nutrient‐depleted areas), (b) recent management intensity (i.e., thinning/felling activities), and (c) the interaction of recent management and potential legacies. Location: Oak forests in Skåne, south Sweden. Methods: We use three vegetation surveys (1983, 1993/94 and 2014) and notes on management and land‐use history, available for 62 permanent 500 m² plots. We conducted linear mixed effect modelling to detect both main and interactive effects of past land use and recent management on understorey diversity measures and vegetation indicator values for light and fertility. We combined nonmetric multidimensional scaling with permutational multivariate analysis of variance and indicator species analysis to detect compositional differences caused by past land use and/or recent management. Results: Understorey diversity was mainly affected by management activities, but the former infield/outland agricultural system was an important determinant of understorey composition. Understorey composition of former infields reflected higher nutrient availability and lower light availability compared to former outland. Past land use and recent management had interactive effects on light‐related understorey variables: for the less intensively managed plots, the outland plots contained more light‐demanding species than the infield plots, while for the more intensively managed plots, the light‐demanding signature of the understorey was similar for infield and outland plots. Conclusions: Different intensities of past land use as well as recent forest management influenced the composition of the forest understorey, and interactions were present. Therefore, careful consideration of both the long‐term land‐use history and the more recent disturbances due to forest management are necessary when making future predictions of understorey composition and diversity. [ABSTRACT FROM AUTHOR]

Aims: Plant responses to disturbances and environmental variation can manifest in communities as compositional nestedness (i.e., one community is a subset of another) and/or turnover (two communities represent different compositional gradient spaces). Yet, different sampling designs can artificially give an illusion of such compositional differences among two datasets, making it problematic to harmonize them in multi‐species analysis. We test the prediction that sampling differences which increase beta‐diversity components (nestedness and turnover) among two vegetation datasets will decrease their exchangeability. Location: Boreal forests of Tanana River region, interior Alaska, USA. Methods: We develop novel methods for comparing compositional variation among two datasets in nonmetric multidimensional scaling (NMDS) ordination. Resampled NMDS establishes internal sampling variability for each dataset independently, and reciprocal NMDS determines external exchangeability when the two are mutually exchanged. We first compare simulated data with specified beta‐diversity differences, then evaluate two forest inventories based on local vs regional sampling designs in Alaska's boreal forests. Results: As simulated species turnover and nestedness increased, internal sampling variability remained essentially constant, but external exchangeability progressively declined. Species turnover (not nestedness) had the larger negative effect on exchangeability. Among the boreal forest inventories, internal sampling variability was relatively similar, and exchangeability was weakly moderate, but the regional inventory exhibited much better fit to broad‐scale environment. Species turnover (not nestedness) contributed the majority of beta‐diversity differences among the two forest inventories, suggesting that strong environmental gradients were unequally represented. Conclusions: Species turnover alters multivariate outcomes more drastically than species nestedness. Therefore, combining two vegetation datasets may be inadvisable when turnover prevails. Instead, a multi‐scale perspective, with separate but complementary forest inventory analyses, can portray local and regional variation at appropriate scales. Our method is tractable for assessing exchangeability of potentially inconsistent sampling designs, like those that are common in synthesis studies and long‐term ecological monitoring. Combining two community datasets in one ordination can be risky if sampling designs differ. We present "reciprocal NMDS" methods and software to estimate multivariate data exchangeability. From simulations and real vegetation communities of boreal Alaska, poor exchangeability arises when species turnover prevails over nestedness. Long‐term monitoring programs can benefit from evaluating exchangeability when sampling designs change over time. [ABSTRACT FROM AUTHOR]

Question How do canopy disturbance and soil properties structure vascular plant community species composition and resilience to encroachment by exotic species in a tropical montane wet forest? Location Hawai'i Experimental Tropical Forest ( HETF), a tropical montane wet forest, on Mauna Kea, Hawai'i Island, Hawai'i, USA. Methods Previous studies employing airborne Li DAR were used to define three zones across an elevation gradient from 900 to 1500 m. Within each zone, a ~1000-m block transect was selected to cross two different volcanic substrates: one derived from surface lava and one derived from thick ash deposits. Non-metric multidimensional scaling ( NMS) scores of vegetation data were related to independently-derived environmental NMS scores and spatial location with generalized additive models ( GAM). Results Vascular plant species composition in all elevation zones consists of three NMS axes, which are best modelled by one of three possible environmental NMS axes or by location. The first NMS axis of species composition in the lowest elevation zone (40% variance explained ( VE)) is a function of location on volcanic substrates (61% deviance explained ( DE)). The second lowest elevation axis (27% VE) is a function of unexplained spatial heterogeneity (31% DE). The third lowest elevation NMS axis (24% VE) is a function of the spatial mosaic of canopy disturbance (16% DE). In the middle elevation zone, species composition most strongly relates to the interaction between volcanic substrate and the condition of the soil surface for all three NMS axes (41%, 27%, 24% VE; 70%, 16%, 24% DE). The primary axis of species composition in the highest elevation zone (41% VE) corresponds with substrate and soil condition (55% DE) but the second and third axes of species composition (27% and 25% VE) relate to canopy dieback disturbance (36%, 14% DE). Counts of exotic species and 0-2 m height class native tree species respond to the type of volcanic substrate and soil surface condition in all three elevation zones. Lava-derived substrates have a higher incidence of exotic species and less native tree regeneration; whereas ash-derived substrates have higher numbers of native tree species regenerating and many fewer exotic species. Discussion The tropical montane forests on Mauna Kea reflect a native-dominated plant community response to disturbance on both lava- and ash-derived volcanic substrates, and a higher propensity for exotic species to occur on the lava-derived substrate. Native plant communities on ash-derived soils may have higher resilience to exotic invasion than communities on lava-derived substrates. Our results indicate resource managers should explicitly account for variation in soils and substrate type when prioritizing, implementing and monitoring management interventions to foster native plant assemblages and control the spread of exotic and invasive species. [ABSTRACT FROM AUTHOR]

Questions How have the historical frequency and severity of natural disturbances in primary Picea abies forests varied at the forest stand and landscape level during recent centuries? Is there a relationship between physiographic attributes and historical patterns of disturbance severity in this system? Location Primary P. abies forests of the Eastern Carpathian Mountains, Romania; a region thought to hold the largest concentration of primary P. abies forests in Europe's temperate zone. Methods We used dendrochronological methods applied to many plots over a large area (132 plots representing six stands in two landscapes), thereby providing information at both stand and landscape levels. Evidence of past canopy disturbance was derived from two patterns of radial growth: (1) abrupt, sustained increases in growth (releases) and (2) rapid early growth rates (gap recruitment). These methods were augmented with non-metric multidimensional scaling to facilitate the interpretation of factors influencing past disturbance. Results Of the two growth pattern criteria used to assess past disturbance, gap recruitment was the most common, representing 80% of disturbance evidence overall. Disturbance severities varied over the landscape, including stand-replacing events, as well as low- and intermediate-severity disturbances. More than half of the study plots experienced extreme-severity disturbances at the plot level, although they were not always synchronized across stands and landscapes. Plots indicating high-severity disturbances were often spatially clustered (indicating disturbances up to 20 ha), while this tendency was less clear for low- and moderate-severity disturbances. Physiographic attributes such as altitude and land form were only weakly correlated with disturbance severity. Historical documents suggest windstorms as the primary disturbance agent, while the role of bark beetles ( Ips typographus) remains unclear. Conclusions The historical disturbance regime revealed in this multi-scale study is characterized by considerable spatial and temporal heterogeneity, which could be seen among plots within stands, among stands within landscapes and between the two landscapes. When the disturbance regime was evaluated at these larger scales, the entire range of disturbance severity was revealed within this landscape. [ABSTRACT FROM AUTHOR]

Context A historical review of ordination studies is presented with particular reference to the pioneering contributions of the late Prof. I. Noy- Meir and their continuing relevance. Issues (1) Comparisons of ordination methods are often confounded by differences in the methodological algorithm, dissimilarity measure used and the data standardization employed. (2) Artificial data where 'truth' is known offer a means of evaluating ordination approaches but are highly sensitive to the ecological model assumed. (3) Data standardization is frequently used but its influence on ordination is poorly understood and lacks theoretical justification. Review Historically, the above issues have been continually raised since the first use of artificial data by Swan in 1970 to demonstrate the 'horseshoe distortion'. Three distinct conceptual models have been used to generate artificial data, yet no consensus on their suitability has emerged since they were first used in the mid-1970s. Comparative studies had, by the late 1980s, shown that some approaches recovered 'ecological truth' better than others. Differences between comparative studies in conceptual models, nature of the data matrices used, different dissimilarity measures, ordination algorithms and evaluations methods limited acceptance of this conclusion. Data standardization alters the properties of the vegetation data matrix. Yet little is known regarding the influence on ordination results of the collective vegetation properties stand abundance, dominance or species richness, which are altered by standardization. Recent developments Knowledge of the properties of individual dissimilarity measures and ordination algorithms has increased; a few new methods have emerged. Pragmatism of the type 'this method gives me useful answers so I do not need to use a better method' is common. Tests of conceptual models are now occurring based on species distribution modelling. Conclusions A consensus is emerging that non-metric multidimensional scaling and dissimilarity measures such as the Bray- Curtis coefficient should be used in preference to correspondence analysis methods based on the χ2 dissimilarity measure. Absence of a comprehensive model of vegetation composition is limiting ordination as a method of community analysis. Inconsistencies between different ordination methods and ecological models first recognized in the 1970s remain today. [ABSTRACT FROM AUTHOR]

Questions How does spatial scale (extent and grain) influence the relative importance of different environmental factors as determinants of plant community composition? Are there general scale thresholds that mark the transition from primarily edaphic to primarily climatic control of plant communities? Location Global. Methods We surveyed the empirical literature and identified 89 analyses from 63 published studies that analysed vegetation-environment relationships involving at least two categories of predictor variables (edaphic, climatic, topographic, biotic, spatial or disturbance-related). For each analysis, we identified the primary predictor variable (i.e. the variable that explained the most variation in community composition) and the relative effect size of the best predictor variable from each category. We defined 'primacy' as the proportion of times a variable category was primary when it was measured, and analysed primacy and the relative effect size of each category as a function of spatial extent and grain. We also analysed the subset of studies that measured both edaphic and climatic variables to identify spatial extent and grain thresholds for the primacy of these factors. We surveyed the empirical literature and identified 89 analyses from 63 published studies that analysed vegetation-environment relationships involving at least two categories of predictor variables (edaphic, climatic, topographic, biotic, spatial or disturbance-related). For each analysis, we identified the primary predictor variable (i.e. the variable that explained the most variation in community composition) and the relative effect size of the best predictor variable from each category. We defined 'primacy' as the proportion of times a variable category was primary when it was measured, and analysed primacy and the relative effect size of each category as a function of spatial extent and grain. We also analysed the subset of studies that measured both edaphic and climatic variables to identify spatial extent and grain thresholds for the primacy of these factors. Results Edaphic variables had the highest primacy in the overall data set and at fine grain sizes (<200 m2), but there were no strong trends in primacy across studies of varying spatial extent. We detected trends of increasing relative effect size of climatic variables with increasing spatial extent, and decreasing relative effect size of edaphic variables with increasing spatial grain, although these patterns were not statistically significant. Among studies that measured both edaphic and climatic variables, the importance of climate factors relative to edaphic factors increased with increasing spatial extent and grain, with scale thresholds of 1995 km2 for extent and 295 m2 for grain. Conclusions Our study illustrates that vegetation-environment relationships depend on the spatial scale (extent and grain) of observation and provide empirical support for the view that there is a transition from a primarily edaphic influence to a primarily climatic influence on plant community composition with increasing spatial scale. [ABSTRACT FROM AUTHOR]

Question: Does the upward shift of species and accompanied increase in species richness, induced by climate change, lead to homogenization of Alpine summit vegetation? Location: Bernina region of the Swiss Alps. Methods: Based on a data set from previous literature we expand the analysis from species richness to beta-diversity and spatial heterogeneity. Species compositions of mountain summits are compared using a two-component heterogeneity concept including the mean and the variance of Sørensen similarities calculated between the summits. Non-metric multidimensional scaling is applied to explore developments of single summits in detail. Results: Both heterogeneity components (mean dissimilarity and variance) decrease over time, indicating a trend towards more homogeneous vegetation among Alpine summits. However, the development on single summits is not strictly unidirectional. Conclusions: The upward shift of plant species leads to homogenization of alpine summit regions. Thus, increasing alpha-diversity is accompanied by decreasing beta-diversity. Beta-diversity demands higher recognition by scientists as well as nature conservationists as it detects changes which cannot be described using species richness alone. [ABSTRACT FROM AUTHOR]

Objective: Treeless meadows and parks are widespread but poorly understood features of the montane vegetation of the western USA. These communities frequently form reversed treelines where grassy valleys occur below forested slopes above. Our purpose was to assess the environmental correlates of such treelines, as well as patterns in the composition and diversity of grasslands and forest margins in the Valles Caldera National Preserve. Location: Valles Caldera National Preserve (35°50′-36°00′ N, 106°24′-106°37′ W, 2175-3150 m), Jemez Mountains, New Mexico, USA. Methods: We conducted a gradient analysis based on 200 nested quadrats on transects crossing reversed treelines and spanning the compositional heterogeneity of grasslands. We used cluster analysis and non-metric multidimensional scaling to assess relationships between compositional variation and environmental variables. Results: We found strong, highly significant relationships of the vegetation to gradients in slope inclination, soil texture, moisture, nutrient availability, and nighttime minimum temperatures. Reversed treelines are most strongly associated with shifts in the thermal regime, exhibit weaker relationships with soil texture and nutrient content, and show no relationship with gravimetric soil moisture. Gradients in aspect, soil moisture, and annual mean temperature are associated with compositional variation within grasslands and forest margins. Conclusions: Lower nightly minimum temperatures and fewer consecutive frost-free days resulting from cold-air drainage may prevent tree seedling establishment in valley bottoms via photo-inhibition, tissue damage, or frost heaving. Finetextured soils may also impede tree seedling establishment in valley bottoms. These findings lay the groundwork for experimental and physiological tests of these potential causes of these reversed treelines. [ABSTRACT FROM AUTHOR]

Question: To what extent do surrogate approaches to vegetation description provide equivalent data and estimates of the patterns of variability in species composition to that which would be obtained using species-level abundance data? Locations: Picos de Europa in Northern Spain and South Uist, Outer Hebrides, Scotland, UK. Methods: Percentage cover data were collected from 117 plots in montane and sub-alpine grassland and woodland mosaics in the Picos de Europa and 217 quadrats across a gradient from temperate coastal dunes to upland grassland and heath on South Uist. From these data, 14 surrogate datasets were derived using supra-species (genus, family) levels of description, presence-absence, life form, growth form and plant functional types (PFTs; derived from seven easily measurable traits). The descriptive power of each of the 14 surrogate datasets in each area, relative to the original cover abundance dataset, was assessed by 'second stage' analysis, based on Spearman's rank correlation coefficient calculated between pairs of similarity matrices. Results: In both areas, presence-absence data showed the closest similarities to the original cover abundance data, followed by data generalised at supra-species level. PFT, life form, growth form and leaf trait data were less similar. Conclusions: Many situations exist where it may be more efficient or desirable to collect neither species nor abundance data and to use appropriate surrogates. The results demonstrate clearly that the information content of surrogate datasets in our study may be an acceptable substitute. These ideas merit further investigation in a wider range of habitats and contexts. [ABSTRACT FROM AUTHOR]

Question: What are the changes in vegetation structure, soil attributes and mesofauna associated with grazing in mesic grasslands? Location: Southern Campos of the Río de la Plata grasslands, in south-central Uruguay. Methods: We surveyed seven continuously grazed and ungrazed paired plots. Plant and litter cover were recorded on three 5-m interception lines placed parallel to the fence in each plot. We extracted soil fauna from a 10 cm deep composite sample and analysed the oribatids. Soil attributes included bulk density, water content, organic carbon (in particulate and mineral associated organic matter) and nitrogen content and root biomass at different depths. Changes in floristic, Plant Functional Types and mesofauna composition were analysed by Non-metric Multidimensional Scaling. Results: Species number was lower in ungrazed than in grazed plots. Of 105 species in grazed plots only three were exotics. Shrub and litter cover were significantly higher inside the exclosures, while the cover of Cyperaceae-Juncaceae was lower. Grazing treatments differed significantly in plant and oribatid species composition. Grazing exclusion significantly reduced soil bulk density and increased soil water content. Carbon content in particulate organic matter was lower in the upper soil of ungrazed sites, but deeper in the profile, grazing exclosures had 8% more carbon in the mineral associated organic matter. Conclusions: Our results generally agree with previous studies but deviate from the results of previous analyses in (1) the increase of shrub cover in ungrazed sites; (2) the redistribution of the soil organic carbon in the profile and (3) the low invasibility of the prairies regardless of grazing regime. [ABSTRACT FROM AUTHOR]

This article investigates whether the Braun-Blanquet abundance/dominance (AD) scores that commonly appear in phytosociological tables can properly be analysed by conventional multivariate analysis methods such as Principal Components Analysis and Correspondence Analysis. The answer is a definite NO. The source of problems is that the AD values express species performance on a scale, namely the ordinal scale, on which differences are not interpretable. There are several arguments suggesting that no matter which methods have been preferred in contemporary numerical syntaxonomy and why, ordinal data should be treated in an ordinal way. In addition to the inadmissibility of arithmetic operations with the AD scores, these arguments include interpretability of dissimilarities derived from ordinal data, consistency of all steps throughout the analysis and universality of the method which enables simultaneous treatment of various measurement scales. All the ordination methods that are commonly used, for example, Principal Components Analysis and all variants of Correspondence Analysis as well as standard cluster analyses such as Ward's method and group average clustering, are inappropriate when using AD data. Therefore, the application of ordinal clustering and scaling methods to traditional phytosociological data is advocated. Dissimilarities between relevés should be calculated using ordinal measures of resemblance, and ordination and clustering algorithms should also be ordinal in nature. A good ordination example is Nonmetric Multidimensional Scaling (NMDS) as long as it is calculated from an ordinal dissimilarity measure such as the Goodman & Kruskal γ coefficient, and for clustering the new OrdClAn-H and OrdClAn-N methods. [ABSTRACT FROM AUTHOR]

Questions: Are ordinal data appropriately treated by multivariate methods in numerical ecology? If not, what are the most common mistakes? Which dissimilarity coefficients, ordination and classification methods are best suited to ordinal data? Should we worry about such problems at all? Methods: A new classification model family, OrdClAn (Ordinal Cluster Analysis), is suggested for hierarchical and non- hierarchical classifications from ordinal ecological data, e.g. the abundance/dominance scores that are commonly recorded in relevés. During the clustering process, the objects are grouped so as to minimize a measure calculated from the ranks of within-cluster and between-cluster distances or dissimilarities. Results and Conclusions: Evaluation of the various steps of exploratory data analysis of ordinal ecological data shows that consistency of methodology throughout the study is of primary importance. In an optimal situation, each methodological step is order invariant. This property ensures that the results are independent of changes not affecting ordinal relationships, and guarantees that no illusory precision is introduced into the analysis. However, the multivariate procedures that are most commonly applied in numerical ecology do not satisfy these requirements and are therefore not recommended. For example, it is inappropriate to analyse Braun-Blanquet abudance/dominance data by methods assuming that Euclidean distance is meaningful. The solution of all problems is that the dissimilarity coefficient should be compatible with ordinal variables and the subsequent ordination or clustering method should consider only the rank order of dissimilarities. A range of artificial data sets exemplifying different subtypes of ordinal variables, e.g. indicator values or species scores from relevés, illustrate the advocated approach. Detailed analyses of an actual phytosociological data set demonstrate the classification by OrdClAn of relevés and species and the subsequent tabular rearrangement, in a numerical study remaining within the ordinal domain from the first step to the last. [ABSTRACT FROM AUTHOR]

Questions: Does post-fire plant succession in boreal bogs vary microtopographically and are successional patterns re- producible among similar microtopographic features? Does succession preserve microtopography post-fire? Location: Boreal bog peatlands near Sinkhole Lake and Athabasca, Alberta, Canada. Methods: We assessed microtopographic variation in post- fire plant community succession through stratigraphic macrofossil analysis of bog soil cores collected from high (hummock) and low (hollow) positions. We conducted vegetation surveys and collected soil cores from ten hummocks and hollows in each bog. Pre-fire microtopographic status was inferred based on floral composition and compared to current microtopography. Results: Hollow vegetation was more variable than hum- mocks, both in present composition and post-fire succession. The successional trajectory of current hummocks was relatively uniform, showing relatively rapid shifts to Sphagnum fuscum dominance, but varied greatly in hollows. Hollows, although compositionally variable, were typically perpetuated following fire, while hummocks had an approximately equal chance of being perpetuated or becoming hollows. Conclusions: Greater compositional variability at lower microtopographic positions, both spatially and temporally, is most likely due to the ability of hollows to support a wider range of species and greater susceptibility to severe disturbance. Likewise, spatial variability in fire severity appears to be responsible for perpetuation or change in microtopographic status, favouring the creation of hollows over maintenance of hummocks. [ABSTRACT FROM AUTHOR]

Question: What is the nature and relative importance of compositional gradients within- and between fens? Location: Iowa, USA. Methods: 506 0.5 m × 0.5 m quadrats were sampled from 31 fens across a 550 km extent. Presence/absence of all vascular plant taxa, plus the non-vascular genera Sphagnum and Chara, and values for 24 environmental variables were noted. Global Non-Metric Multidimensional Scaling and Monte Carlo tests were used to describe compositional variation and identify significant environmental co-variables. Model-based cluster analysis was used to identify the optimal number of groups supported by the data, while k-means clustering was used to assign each quadrat to a group. The number of occurrences (and frequency) of each species within each group was calculated. Two-dimensional 95% Gaussian confidence intervals, ANOVA, correlation coefficient homogeneity tests, log-linear modelling, and Fisher's exact tests were used to document patterns of compositional change. Results: Two stable axes of variation were identified: the first being most closely correlated with soil pH, Mg, Ca, P, 5, vegetation height, surface and -10 cm soil temperature, site area, perimeter, perimeter/area ratio, growing season, and air temperature, with the second being most correlated to soil moisture, N, disturbance level, % organic matter, hummock height, N-S coordinate, and precipitation. Individual sites harboured between 20-47% of total compositional variation, with 28% of Axis 1 and 55% of Axis 2 scores being contained within-sites. Five compositional regions were identified that differed in the proportion of calciphile and hydrophile species. Compositional groups differed significantly between geologic types. Conclusions: While the principal axis of variation (corresponding to the rich-poor fen gradient) is present largely between sites, the second axis (corresponding to water level) is largely repeated within sites. Documentation and protection of vegetation patterns and species diversity within Iowa fens will thus require consideration of multiple sites across the landscape. [ABSTRACT FROM AUTHOR]

VEGAN adds vegetation analysis functions to the general-purpose statistical program R. Both R and VEGAN can be downloaded for free. VEGAN implements several ordination methods, including Canonical Correspondence Analysis and Non-metric Multidimensional Scaling, vector fitting of environmental variables, randomization tests, and various other analyses of vegetation data. It can be used for large data. Graphical output can be customized using the R language's extensive graphics capabilities. VEGAN is appropriate for routine and research use, if you are willing to learn some R. [ABSTRACT FROM AUTHOR]

A method is described to determine the number of significant dimensions in metric ordination of a sample. The method is probabilistic, based on bootstrap resampling. An iterative algorithm takes bootstrap samples with replacement from the sample. It finds in each bootstrap sample ordination coordinates and computes, after Procrustean adjustments, the correlation between observed and bootstrap ordination scores. It compares this correlation to the same parameter generated in a parallel bootstrapped ordination of randomly permuted data, which uponmany iterations will generate a probability. The method is assessed in principal coordinates analysis of simulated data sets that have varying number of variables and correlation levels, uniform or patterned correlation structure. The results suggest the method is more reliable than other available methods in recovering the true intrinsic dimensionality. Examples with grassland data illustrate utility. [ABSTRACT FROM AUTHOR]