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District Tor Ghar is phytosocilogically unexplored region in the western Himalaya. Present study was conducted in district Tor Ghar during the summers of 2012 and 2013 to study floristic diversity of herbaceous flora in the region. The district Tor Ghar is located on 34° 32′ - 34° 50′ N, and 72° 48′ - 72°58′ E. A total of 229 herb species belonging to 168 genera and 66 families were identified. Herbaceous vegetation was sampled from 1 × 1 m quadrats. For vegetation classification into plant communities, presence, absence (1,0) data on 229 herbaceous species and 64 locations were analyzed in PCORD version 5 via Cluster and Two Way Cluster Analyses. Six plant communities were established. Plant abundance data were treated in CANOCO version 4.5 to measure the ecological gradient of plant species and communities of the region. Detrended Correspondence Analysis (DCA) a type of indirect gradient analysis reconfirmed the results of Cluster and Two way Cluster Analysis. Moreover the study furnishes useful information for improvement, protection and management of present vegetation status for future generation. A comprehensive conservation measure with practical implementation is utmost necessary for conservation of rapidly depleting plant resources of the area.

In the present study, the temporal and spatial paleoecology of the Lower Silurian Rytteråker Formation in the Oslo region, is explored through multivariate gradient analysis of a novel dataset of stratigraphically collected acetate peels from two localities in the Oslo Region, as well as ordination-based reanalysis of two previously published datasets. By applying up to four different ecological ordination methods in parallel in a comparative, integrated approach – on both raw and abundance-scale weighted data, a single robust high-level faunal and environmental gradient associated with ordination axis one was identified in both the newly sampled and historical datasets. In both the novel acetate peel dataset and the historical dataset of bedding plane point-count data, the gradient appeared to be primarily structured by the abundances of pentamerid brachiopods, and secondarily by overall fossil diversity and richness. In-sample environmental proxy variables from the datasets, as well as newly gathered supplementary data in the form of elemental XRF measurements, magnetic susceptibility readings, brachiopod shell orientation measurements and field observations, seem to indicate storm frequency and/or high energy deposition as the most significant complex environmental variable structuring all three primary gradients. As such, the gradients are likely reflective both of real ecological change affecting species distribution, as well as a biases regarding preservation and taphonomy. As such, the results from this study partially challenge previous interpretations of the fauna of the Rytteråker Formation as being primarily controlled by depositional depth. Although depth would in some cases also be correlated with benthic storm frequency, the prospect of a barrier patch reef/shoal-lagoonal system in the area does not make this connection a necessity. It also provides a strong case for the multiple parallel ordination approach as a useful tool for discerning ecologically interpretable gradients both from new and historic datasets. However, as indicated disparities in diversity and richness, the novel acetate peel study design applied here seems to be more appropriate for discerning faunal gradients in localities that are generally more fossil rich (i.e. higher depositional energy), while larger-scale macrofossil surveys akin to some of the historical datasets, might be more appropriate for energetically quieter depositional environments. The link between periodic wave turbulence and faunal change also implies some interesting possible parallels between the underlying environmental factors influencing Paleozoic and modern benthic soft-substrate ecosystem gradients, which could provide a basis for future studies.

Aim: while we understand broad climate drivers of insect distributions throughout the Arctic, less is known about the role of spatial processes in determining these relationships. As such, there is a need to understand how spatial controls may influence our interpretations of chironomid environment relationships. Here, we evaluated whether the distribution of chironomids followed spatial gradients, or were primarily controlled by environmental factors.Location: Eastern Canadian Arctic, Greenland, Iceland.Taxon: non-biting midges (Chironomidae)Methods: we examined chironomid assemblages from 239 lakes in the western North Atlantic Arctic region (specifically from the Arctic Archipelago of Canada, two parts of west Greenland (the southwest and central west), and northwest Iceland). We used a combination of unconstrained ordination (Self Organizing Maps); a simple method with only one data matrix (community data), and constrained ordination (Redundancy Analysis); a canonical ordination with two data sets where we extracted structure of community related to environmental data. These methods allowed us to model chironomid assemblages across a large bioregional dimension and identify specific differences between regions that were defined by common taxa represented across all regions in high frequencies, as well as rare taxa distinctive to each region found in low frequencies. We then evaluated the relative importance of spatial processes versus local environmental factors. Results: we find that environmental controls explained the largest amount of variation in chironomid assemblages within each region, and that spatial controls are only significant when crossing between regions. Broad-scale biogeographic effects on chironomid distributions are reflected by the distinct differences between chironomid assemblages of Iceland, central-west Greenland, and eastern Canada, defined by the presence of certain common and low-frequency, rare taxa for each region. Environmental gradients, especially temperature, defined species distributions within each region, whereas spatial processes combine with environmental gradients in determining what mix of species characterizes each broad and geographically distinct island region in our study.Main conclusions: we outline that while biogeographic context is important for defining interpretations of environmental controls on species distributions, the primary control on distributions within regions is environmental. These influences are fundamentally important to know for reconstructing past environmental change and better understanding historical distributions of these insect indicators.

This study focuses on comparing the driving ecological factors and community diversity of fen vegetation from the plain part of the South Ural region with those of the mountain fen vegetation, previously described by us (Ivchenko and Znamenskiy Russian Journal of Ecology 47:453–459, 2016), by means of vegetation data clustering and gradient analysis. The indicator values by several authors (H Ellenberg, E Landolt, LG Ramensky, DN Tsyganov) and WorldClim bioclimatic variables were used to determine the ecological meaning of the gradients. We found that the main gradient for both plain and mountain fen vegetation is the “poor-rich fen” gradient, which depends on local substrate chemical composition. The second gradient is associated with moisture, which tends to increase consistently both from mountains towards plains and across plains from peneplain towards West Siberian Lowland. The moisture gradient proved to be unrelated to precipitation, which increase linearly from plains towards mountains. The community diversity in the mountain part is higher than in the plain part. The fen vegetation of plains and mountains overlap in ordination space but a half of the types described for mountain fen vegetation do not occur on plains, while two types of plain fen vegetation from the West Siberian Lowland are absent on mountains.

Complex processes related to biotic and abiotic forces can impose limitations to assembly and composition of plant communities. Quantifying the effects of these constraints on plant functional traits across environmental gradients, and among communities, remains challenging. We define ecological constraint (C-i) as the combined, limiting effect of biotic interactions and environmental filtering on trait expression (i.e., the mean value and range of functional traits). Here, we propose a set of novel parameters to quantify this constraint by extending the trait-gradient analysis (TGA) methodology. The key parameter is ecological constraint, which is dimensionless and can be measured at various scales, for example, on population and community levels. It facilitates comparing the effects of ecological constraints on trait expressions across environmental gradients, as well as within and among communities. We illustrate the implementation of the proposed parameters using the bark thickness of 14 woody species along an aridity gradient on granite outcrops in southwestern Australia. We found a positive correlation between increasing environmental stress and strength of ecological constraint on bark thickness expression. Also, plants from more stressful habitats (shrublands on shallow soils and in sun-exposed locations) displayed higher ecological constraint for bark thickness than plants in more benign habitats (woodlands on deep soils and in sheltered locations). The relative ease of calculation and dimensionless nature of C-i allow it to be readily implemented at various scales and make it widely applicable. It therefore has the potential to advance the mechanistic understanding of the ecological processes shaping trait expression. Some future applications of the new parameters could be investigating the patterns of ecological constraints (1) among communities from different regions, (2) on different traits across similar environmental gradients, and (3) for the same trait across different gradient types. Refereed/Peer-reviewed

Summary Recent advances employing generalized linear models in ecology have led ecological statisticians to argue strongly for the need to re-evaluate or re-invent commonly used multivariate analyses in ecology to explicitly address the mean–variance ratios of the underlying species data. This paper re-evaluates previous work on the importance of aligning distance- or dissimilarity-based methods with the mean–variance ratios of underlying data and extends the analyses to additional simulated data designed to test the specific assertions of model-based advocates with respect to ordination analysis. Similar analyses are conducted on an observed community dataset where the observed species abundances exhibit a quadratic variance-to-mean ratio. The results emphasize two general points with respect to (i) the sensitivity of ordination to species abundance distributions and (ii) the inherently hierarchical nature of community analysis. Previously observed problematic results are shown to result from extremely high between-community variability in sample unit abundance, and are independent of the underlying species mean–variance ratios. Results for simulated data as well as for observed coral reef community data show similar results. Multivariate analyses of the newly simulated data from two communities along a simulated gradient show excellent results despite the underlying species negative binomial distributions and putatively problematic mean–variance ratios. Problems identified in previously observed results reflect a misunderstanding of the hierarchical nature of ecological communities. Mechanisms operating at the individual species level can manifest at the community level as a different ecological (and statistical) phenomenon. Specifically, uncorrelated or divergent changes in species abundances within communities lead inevitably to dispersion effects at the community level. The hierarchical nature of the analysis is independent of the specifics of the species mean–variance ratios, and would obtain whether species abundances are distributed with uniform, normal, or negative-binomial distributions. The results presented here demonstrate that suitable ordination of the data accurately represents the ecological response at the community level. However, paired ordinations on non-standardized and standardized data can elucidate the underlying species-level changes in abundance as the mechanism driving the change in community dispersion.

In mountainous areas, the landscape spatial pattern is affected by topography and human activities. To better understand topographic influences on the vegetation structure in the landscape mosaic and interpret the ecological implications of spatial patterns, the relationships between topographic features and landscape pattern indices (LPIs) should be addressed. The objective of this study is to address the effects of topography on LPIs (both planimetric and surface LPIs) by integrating spatial analysis and gradient analysis. To fulfill these objectives, two different mountain research sites located in the Lancang River watershed were chosen, both planimetric and surface landscape metrics were used to quantify natural category (NC) and anthropogenic category (AC) patterns, and the redundancy ordination gradient method was used to address the relationship between LPIs (planimetric and surface metrics) of NC and AC patterns and topographic attributes. The results suggest that topographic attributes play a prominent role in structuring the landscape mosaic. Elevation is a key factor for NC and AC patch patterns in the study area. The results indicate that the fragmentation and isolation of NC patterns increase as elevation decreases. In contrast, the fragmentation and isolation of AC patterns decrease as elevation decreases.

Based on gradient analysis and indicator values, spring water chemistry and temperature and the dynamics of water level were shown to be the main ecological factors of plant cover differentiation in spring fens. Six groups of plant communities were identified by ordination along the axes of these factors, with each group being characterized by a certain suite of indicator species.

Alpine deserts are noteworthy habitats in temperate high mountain systems such as the Caucasus. Botanically this biome is well studied, yet little is known about its vegetation patterns in quantitative terms, whilst the role of soil pH in species distributions is particularly unexplored. Here we describe and quantitatively analyse vegetation patterns and soil pH in an alpine desert along elevation range (3000–4000 m a.s.l.) on two contrasting slope aspects (N versus S) of Mt. Kazbegi, the Central Greater Caucasus, Georgia. We sampled vegetation with standardized stratified-random design and collected soil samples for measuring pH; the collected data were analyzed using multivariate ordination methods. Overall, 63 species were recorded and, as expected, strong dependence of species distribution on elevation and between slopes was observed. However, we also found that soil pH increased monotonically and more steeply on N than on S slope, and many relatively abundant species changed their preference to slope aspect from N to S in parallel with the increasing difference in soil pH between N and S slopes. Our results suggest that the observed shift in slope preference from N to S, at least in part, can be explained by the differences in soil pH gradient between N and S slopes.

Habitat degradation associated with resource development is a major ecological concern, particularly in Canada’s boreal zone where limited information on biodiversity is available. Habitat degradation can lead to reductions in biodiversity and ecosystem function, especially when drivers of variability and diversity patterns have not been identified for a region of interest. In this study, the distribution of diatom genera in the Peace–Athabasca Delta in northeastern Alberta was examined in relation to seasonal, geographic, and alkalinity gradients. Grab samples of six abiotic variables (total dissolved nitrogen, total dissolved phosphorus, dissolved iron, turbidity, pH, and specific conductance (SPC)) were taken from 12 remote wetlands over three sampling periods, and regressed against an ordination of diatom community composition to identify key environmental drivers of diatom community variation. Indirect gradient analysis identified two major gradients among sites. First, separation of sites among sampling periods showed successional seasonal changes in diatom community composition. Second, separation of sites from the Peace sub-delta and Birch sub-delta showed a gradient of geographic separation. Direct gradient analysis failed to explain the underlying drivers of these two gradients, but did show that alkalinity is a key driver of diatom community composition in the Embarras sub-delta, and that these sites could be particularly vulnerable to community changes associated with acidification.

We examine the influence of multiple environmental factors on quantitative reconstructions of past climate that are based on conventional transfer function approaches using subfossil midge remains preserved in lake sediments. Chironomid assemblages from the uppermost sediments of 366 lakes spanning northern North America were compared to environmental parameters using direct gradient analysis. While temperature expectedly explained the largest amount of variation in the chironomid assemblages, dissolved organic carbon (DOC) and total Kjeldahl nitrogen (TKN) accounted for significant amounts of the remaining variance. By constraining chironomid assemblages to mean-July air temperature (JulyT), we found a cluster of 70 lakes that were orthogonal to the primary temperature gradient in ordination. These lakes tended to be cold with higher DOC and TKN concentrations, yet had chironomid assemblages that were similar to the assemblages found in less productive, warmer lakes. In order to examine how secondary gradients affected paleotemperature reconstructions, three chironomid-based transfer function models were generated: a full dataset model (all 366 lakes), a reduced temperature-constrained model (296 lakes), and a reduced secondary-constrained model (70 lakes). Application of these models to four previously published Holocene paleotemperature reconstructions were used to distinguish the influence of temperature versus secondary-gradient effects. While unproductive Arctic lake paleotemperature reconstructions were found to be robust, reconstructions for two lakes in the boreal-tundra ecotone suggest secondary gradients influenced parts of their records. We recommend that passive core trajectory analysis upon our expansive surface-sediment calibration set provides a means to assess the veracity of paleotemperature reconstructions and potential influence of secondary gradients.

The ground beetle fauna of the area of Cape Emine was studied. Over the period 2010 – 2012 adult carabid beetles were collected. The investigation was carried out at 13 sampling sites and pitfall traps were used. During the study altogether 12618 specimens were captured. Mathematical processing of the data by gradient analysis with methods for classification and ordination of the communities was performed. Analysis of distribution of the zoogeographical categories and life forms was done. The primary role of the humidity and vegetation as ecological factors affecting the distribution of the communities of ground beetles was proven.

Previous studies have shown that the floristic composition of northern peatlands provides important information regarding ecosystem processes and their responses to environmental change. Remote sensing is the most expeditious method of obtaining floristic information at landscape and regional scales, but the spatial complexity of many northern peatlands and the spectral similarity of a number of peatland vegetation species is such that the success of traditional methods of vegetation classification is often limited. Here, we assessed whether ordination and regression analyses may be a useful alternative method for mapping peatland plant communities from remote sensing data. We used isometric feature mapping (Isomap) to describe the community structure of the peatland vegetation and related the identified continuous floristic gradients to hyperspectral imagery (AISA Eagle) using partial least squares regression (PLSR). We performed the same analysis at two hierarchical levels of species aggregation in order to map continuous gradients in the composition of both species and plant functional types (PFTs), the latter of which is the most widely used level of aggregation in northern ecosystems. Isomap was able to transfer 82% and more than 96% of the observed ground-based observations to the ordination space for plots characterised by species and PFT; respectively. The modelled floristic gradients showed good agreement with ground-based species and PFT observations although the strength of the agreement was proportional to the amount of floristic variation explained by each ordination axis (r2val = 0.74, 0.45 and 0.30 for the first three ordination axes and r2val = 0.68 and 0.66 for the first two ordination axes; for species and PFT floristic gradients respectively). We also found that how a PFT is defined has an important influence on the success with which it can be mapped. The resultant mapped floristic gradients enabled visualisation of homogeneous vegetation stands, heterogeneous mixtures of different key species and PFTs, and the presence of continuous and abrupt floristic transitions, without the need for unique spectral signatures or the collection of data characterising ancillary environmental variables.

Differences in species composition across ecological communities are the result of multiple interacting mechanisms. Gradient analysis has been perhaps the most widely used statistical framework in describing how ecological communities vary in space, and aiding in determining the causes underlying these patterns. Direct gradient analysis allows the use of predictors such as environmental factors and spatial descriptors to directly estimate their contributions in explaining common and independent patterns of species distributions. In recent years, ecologists have started to explore how evolutionary history is associated with community patterns given the observation that species that share a common phylogenetic history tend also to have similar niches. Although ecological phylogenetics is among the fastest-growing fields in ecology, gradient analysis has not yet been fully integrated in this field. In this paper, we show and adapt the versatility of gradient analysis in describing and interpreting patterns of ecological communities based on their patterns of phylogenetic structure. Describing phylogenetic patterns across communities presents additional challenges regarding statistical inference in contrast to classic direct gradient analysis that are described and tackled here. We investigate the performance of our phylogenetic gradient analysis frameworks using simulations and provide a detailed example using a grassland community dataset.

The monitoring of ecosystems alterations has become a crucial task in order to develop valuable habitats for rare and threatened species. The information extracted from hyperspectral remote sensing data enables the generation of highly spatially resolved analyses of such species’ habitats. In our study we combine information from a species ordination with hyperspectral reflectance signatures to predict occurrence probabilities for Natura 2000 habitat types and their conservation status. We examine how accurate habitat types and habitat threat, expressed by pressure indicators, can be described in an ordination space using spatial correlation functions from the geostatistic approach. We modeled habitat quality assessment parameters using floristic gradients derived by non-metric multidimensional scaling on the basis of 58 field plots. In the resulting ordination space, the variance structure of habitat types and pressure indicators could be explained by 69% up to 95% with fitted variogram models with a correlation to terrestrial mapping of >0.8. Models could be used to predict habitat type probability, habitat transition, and pressure indicators continuously over the whole ordination space. Finally, partial least squares regression (PLSR) was used to relate spectral information from AISA DUAL imagery to floristic pattern and related habitat quality. In general, spectral transferability is supported by strong correlation to ordination axes scores (R$^{2}$ = 0.79–0.85), whereas second axis of dry heaths (R$^{2}$ = 0.13) and first axis for pioneer grasslands (R$^{2}$ = 0.49) are more difficult to describe.

The Valle di Manche (VdM) section (Calabria, Southern Italy) offers the opportunity to investigate the ostracod turnover along a continuous shelf succession straddling the Early-Middle Pleistocene boundary, and compare it against other paleoenvironmental (i.e., mollusks) and paleoclimatic (Uvigerina peregrina δ18O) records. High-resolution (ca. 1 sample/m) ostracod fauna quantitative data, coupled with gradient analysis (Detrended Correspondence Analysis and non-Metric Multi-Dimensional Scaling), document a strong relationship between changes in faunal composition and lithofacies vertical stacking patterns. The comparison between the mollusk- and ostracod-derived ordination data demonstrates that the meio- and macro-faunal turnover is guided by a common complex gradient: bathymetry. The integrated ostracod-mollusk gradient analysis also provides a trend in water depths along the section, highlighting to what extent such multivariate approach can improve the paleoenvironmental and sequence stratigraphic interpretation of ancient shallow marine successions. When plotted stratigraphically, ordination major axis sample scores reveal two increasing-decreasing patterns in water depth that fit well with the T-R cycles previously identified. Paleobathymetric estimates combined with the vertical distribution of key ostracod groups (i.e., epiphytic taxa on sandy substrates vs. deep-sea mud related taxa) allow refining depositional trends, stratal stacking patterns and position of previously not well resolved sequence stratigraphic surfaces within each T-R cycle (e.g., Transgressive Surface-TS). Indeed, two rapid increases in water depth values mark the TSs that separate shallowing-upward, progradational (RST) from deepening upward, retrogradational (TST) stratal stacking patterns of shelf deposits. The TSs, which underline fine-grained successions dominated by deep-sea mud-lover taxa, are invariably constrained to the inception of interglacials Marine Isotope Stages (MIS) 21 and 19, identified within the VdM section by benthic foraminifera δ18O values. Within both the VdM T-R cycles, the deepest conditions (ca. 140 m of water depth) are invariably identified within the Neopycnodonte unit, slightly above the lightest δ18O intervals. The overlying decreasing bathymetric trend, coupled with shifts in ostracod ecological groups, allows to identify in the bryozoans lithofacies the stillstand+falling of the relative sea-level, also tracked by a progressively heavier δ18O record. More stable paleobathymetric conditions (around 40–45 m of water depth) characterize the overlying silt-sand deposits dominated by epiphytic species and showing the heaviest δ18O values.

The freshwater populations of native fish species (Ns) have reached critical levels in many parts of the world due to combined habitat deterioration by human interventions and exotic fish species (Es) invasions. These alarming conditions require combined and well-designed interventions for restoring environmental quality and restricting Es invasion. The aim of the study is to propose a method to design spatially explicit priorities of intervention for the recovery of Ns populations in highly impacted freshwater systems by exotic multi-species invasion and water quality (WQ) degradation. WQ and Es are used as Ns descriptors, which require intervention. The method uses gradient analysis (ordination method of Canonical Correspondence Analysis) for assessing the weights of Ns descriptors' effects, which are further used to develop weighted severity indices; the severity index of WQ ( Swq ) and Es invasion ( Se ), respectively. Swq and Se are further merged to one combined total severity index St . The proposed method provides a) a ranking of the sites, based on the values of S t , which denotes the priority for combined intervention in space and can be visualized in maps, b) a ranking of the most important Ns descriptors for each site to perform site-specific interventions, and c) Es rankings based on their potential threat on Ns for species-specific interventions. WQ, Es and Ns data from 208 sampling sites located in the Emilia-Romagna Region (Northern Italy) were used as a case study for the presentation of the proposed method. The application of the method showed that the north and northwestern lowland areas of Emilia-Romagna region presented the higher priority for intervention since the Ns of these areas are the most impacted from combined Es invasions and WQ degradation. Specific Es belonging to cyprinids, which are mostly responsible for the decline of aquatic vegetation and the increase of water turbidity, and a top Es predator (Wels catfish) were mostly present in these areas. Additionally, the most important WQ stressors of Ns were found to be COD, BOD and temperature that are all connected to oxygen depletion. The aforementioned conditions in the areas described by high priority for intervention can be used as a basis for the development of specific Ns conservation practices targeting the containment of the most harmful Es, the restoration of aquatic vegetation and the improvement of oxygen conditions.

This chapter shows how direct and indirect gradient analysis can be handled in the ade4 package, with a special emphasis on three direct ordination methods: Coinertia Analysis, Redundancy Analysis and Canonical Correspondence Analysis.

Understanding how habitat structures species assemblages in a community is one of the main goals of community ecology. To relate community patterns to particular factors defining habitat conditions, ecologists often use canonical ordinations such as canonical redundancy analysis (RDA). It is a common practice to use dissimilarity coefficients to perform canonical ordinations through distance-based RDA (db-RDA) or transformation-based RDA (tb-RDA). Dissimilarity coefficients are measures of resemblance where the information about species communities is condensed into a symmetric square matrix of dissimilarities among sites. In this study, we compared 16 of the most commonly used dissimilarity coefficients to evaluate if the species-abundance distribution (SAD) of a community can be used to select an appropriate coefficient. Of these, 11 are designed to be used primarily with abundance data, although they can also be used with presence–absence data, whereas five can only be applied to presence–absence data....

Aims Many past practices in afforestation and forest management were instrumented for addressing the issues of tree species selection, planting regimes and development of overstory structure, but neglected understory vegetation. Our objective was to determine the controlling factors of herb-layer plant distribution and the importance of topography in determining local-scale spatial patterns of herbaceous plants. Methods The occurrence and distribution of herb-layer plants were investigated on 26 plots in the Xiaoshegou catchment of Lingkong Mountain, Shanxi Province, China. Community types were classified using two-way indicator species analysis (TWINSPAN) and the relationship between the distribution and abundance of herb-layer species and environmental gradients was analyzed using the canonical correspondence analysis (CCA) ordination method. Forward selection and Monte Carlo permutation test were used to select the factors important in determining the herb-layer plant distribution. Partial CCA (PCCA) was also performed to partition the variance that was explainable by categorical habitat and biotic factors studied. Important findings The 26 survey plots were classified into six groups characterized by the dominant overstory tree species. The results of CCA ordination reflected the relationship between herb-layer community structure and selective environmental variables. The classification of 26 plots in CCA ordination was consistent with the result of TWINSPAN. Forward selection and Monte Carlo test suggested that stand type, soil nutrients and slope position were the most important factors determining understory plant distribution. PCCA revealed that habitat and biotic factors together explained 42.9% of variance in the distribution of understory herbaceous plants. Habitat factors alone explained 31.8% of the variance, biotic factors alone explained 7.8% of the variance and interactionbetween habitat and biotic factors explained 3.2% of the variance. The partitioning of variance using the PCCA helped with identifying the important habitat factors regulating understory herbaceous plant distribution at the study site. However, the fact that more than half of the variance was unaccounted for by the factors studied suggests that other factors we did not measure could also play a role in determining the occurrence and distribution of herbaceous plants on the forest floor, e.g., human activities and random events. Our study demonstrates the importance of both topography and overstory tree species in determining the occurrence and distribution of herb-layer plant species in temperate forest of mountainous areas.

The biological reason for a species' presence under given environmental conditions is that the species possesses traits that make establishment and survival, usually also reproduction, possible under these conditions. Biological traits analysis (BTA), when coupled with environmental variables, can provide information regarding which traits are to be expected for a given environmental state. As such, BTA provides complementary information to multivariate analysis of community data based on species composition. In this study, BTA was conducted on a data set of sediment macrofauna collected from a temperate fjord system and related to a wide range of environmental variables. The biological traits were analysed in a multiple parallel ordination framework, which can enhance the reliability of the extracted gradient structure and evaluate the importance of weight given to abundance. Two traitclines, gradients in functional attributes of the species, were found in the study area. The first traitcline was related to bottom currents and sediment constituents while the second traitcline was related to current strength and particle deposition on the bottom. Together with a companion study of gradients in species composition (coenoclines), this study of functional features (traitclines) illustrates that the species composition may consist of taxonomically different, but functionally similar species, giving rise to strong gradients in species composition but weak gradients in trait category composition when subjected to ordination analyses.

The present study classified global Ecosystem Functional Types (EFTs) derived from seasonal vegetation dynamics of the GIMMS3g NDVI time-series. Rotated Principal Component Analysis (PCA) was run on the derived phenological and productivity variables, which selected the Standing Biomass (approximation of Net Primary Productivity), the Cyclic Fraction (seasonal vegetation productivity), the Permanent Fraction (permanent surface vegetation), the Maximum Day (day of maximum vegetation development) and the Season Length (length of vegetation growing season) variables, describing 98% of the variation in global ecosystems. EFTs were created based on Isodata classification of the spatial patterns of the Principal Components and were interpreted via gradient analysis using the selected remote sensing variables and climatic constraints (radiation, temperature, and water) of vegetation growth. The association of the EFTs with existing climate and land cover classifications was demonstrated via Detrended Correspondence Analysis (DCA). The ordination indicated good description of the global environmental gradient by the EFTs, supporting the understanding of phenological and productivity dynamics of global ecosystems. Climatic constraints of vegetation growth explained 50% of variation in the phenological data along the EFTs showing that part of the variation in the global phenological gradient is not climate related but is unique to the Earth Observation derived variables. DCA demonstrated good correspondence of the EFTs to global climate and also to land use classification. The results show the great potential of Earth Observation derived parameters for the quantification of ecosystem functional dynamics and for providing reference status information for future assessments of ecosystem changes.

Transformation processes in countries like Kyrgyzstan often lead to intensifi cation or extensifi cation of grazing on mountain pastures. In order to reveal the impact of livestock grazing on vegetation patterns, we examined traits of dominant and frequent species in four previously classifi ed plant communities. In particular we analysed trait-environment relationships using multivariate RLQ analysis and univariate fourth-corner statistics in order to identify most relevant environmental gradients. Functional Response Groups (FRG’s) of plant taxa were derived from clustered RLQ ordination space, and were subsequently analysed for their proportionality in previously identifi ed plant communities. Plant height, growth form, lateral spread, fl owering time and life cycle showed a high degree of correlation with grazing. RLQ analysis revealed a high differentiation of plant trait values along a grazing gradient on the fi rst RLQ axis. FRG’s matched three of four vegetation types by constancy and fi delity values (phi) well. Thus, trait-based analyses were successfully used to identify functionally similar groups of species with regard to different regimes of grazing pressure.

Biodiversity is declining on a global scale and the limited resources available for conservation efforts and research need to be used efficiently. Fungi are a megadiverse taxonomic group where lack of knowledge impedes sufficient conservation focus. Inventories of fungi require a high level of expertise and are difficult and expensive due to seasonal variation and fluctuation in sporocarp formation. Lidar offers objective, fine-resolution and potentially cheap and broad scale data for representing vegetation structure and has proven useful for prediction of the diversity of plant and animal species. In this study, we used lidar-derived variables as explanatory variables in models of fungal species richness and controlling gradients of species composition, represented by three ordination axes derived from multidimensional scaling. The fungal data comprised a data set of 1527 species recorded in three inventories of 121 sites covering all major terrestrial habitat types across Denmark. We compared the performance of lidar-derived explanatory variables with two field inventory-based sets of variables: 1) lists of vascular plants and 2) recordings of soil, microclimate and vegetation structure. Lidar-derived variables performed best in predicting fungal richness and the first ordination axis, interpreted as a gradient from low and open herb-dominated communities over closed swards and scrubs to closed-canopy forests (cross validated r 2 of 0.50 and 0.81, respectively). The number of red-listed species and the second ordination axis were poorly predicted by lidar, and the third ordination axis was equally well detected by the three explanatory sets of variables (cross validated r 2 of 0.38). From a fungal conservation perspective, it is promising that lidar-based variables hold information suitable for detecting major gradients in fungal richness and composition.

Seasonal ponds are common throughout forested regions of the north central United States. These wetlands typically flood due to snow-melt and spring precipitation, then dry by mid-summer. Periodic drying produces unique fishless habitats with robust populations of aquatic invertebrates. A basin’s physical/chemical features, the absence of vertebrate predation, and especially the duration of seasonal flooding, have long been viewed as the major structuring influences on these communities, but previous studies have shown only limited effects of environmental variables on pond invertebrates. Applying ordination methods to data from weekly collections of invertebrates during 2008–2009, we tested influences of site-level environmental gradients on the presence and relative abundance of aquatic invertebrate communities in 16 seasonal ponds in a forested region of north central Minnesota, USA. We assessed invertebrate community patterns in relation to pond size and depth, soil nutrients, canopy closure, hydroperiod, and predominant groundwater function (recharge, discharge, or flow-through). Patterns in pond invertebrate community composition were consistently related to pond depth, overhead canopy closure, and hydroperiod. Site-level hydrologic function showed weak relationships to seasonal patterns of invertebrate abundance. Although physical features of ponds had only modest influence on presence and abundance of invertebrates, weekly sampling improved models relating environmental variables to pond invertebrates.

Although ecological stability has been widely studied in the fossil record, it has seldom been analyzed in trilobite dominated communities. We test stability in these communities from the Upper Cambrian–Lower Ordovician of the Cordillera Oriental, Northwestern Argentina. The studied interval spans approximately 5 ma. and for this analysis it was divided in four smaller scale informal intervals of approximately 1.5 to 2 ma. Sampling covers a wide geographic area of ~ 7000 km2 in each time bin. In order to analyze ecological stability, we tested for patterns predicted from the hypothesis of coordinated stasis and habitat tracking. For the analysis of coordinated stasis we studied taxonomic turnover. Migrations and evolutionary turnovers based on the regional and global occurrence of taxa were assessed. Results indicate important rates of immigration and emigration, highlighting the relevance of migration in the assembly of the meta-community. The percentage of carryovers and holdovers was variable between intervals and did not show a bimodal pattern, contradicting the coordinated stasis model. In addition, an ordination analysis performed with correspondence analysis suggests that each interval has an idiosyncratic genus composition. In order to test the model of habitat tracking, an analysis of the stability of biotic gradients and the environmental fidelity of stenotopic taxa was conducted. We carried out a Mantel test to analyze the recurrence of taxa present in different intervals. The results showed that taxa are grouped differently in every interval, indicating instability of biotic gradients. We also performed a gradient analysis for each interval and compared intervals with each other using a Procrustes analysis. Results of this analysis indicate that taxa respond individualistically to environmental changes. Moreover, high Procrustes errors are present in rare taxa. Because rarity is largely related to niche breadth, this result suggests that many stenotopic taxa had little environmental fidelity. Overall, this study suggests that migration appears to be of great importance in the composition of local and regional communities, and that the biotic gradients formed in each interval had a distinct composition and structure. Such compositional and ecological instability do not show convincing evidence to support coordinated stasis. Finally, the concept of individualistic habitat tracking is more clearly understood in light of metacommunity processes such as dispersal and habitat preferences, rather than as a process by itself. Fil: Balseiro, Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigaciones en Ciencias de la Tierra. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Centro de Investigaciones en Ciencias de la Tierra; Argentina Fil: Waisfeld, Beatriz Graciela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigaciones en Ciencias de la Tierra. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Centro de Investigaciones en Ciencias de la Tierra; Argentina