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Most Central African rainforests are characterized by a remarkable abundance of light‐demanding canopy species: long‐lived pioneers (LLP) and non‐pioneer light demanders (NPLD). A popular explanation is that these forests are still recovering from intense slash‐and‐burn farming activities, which abruptly ended in the 19th century. This “human disturbance” hypothesis has never been tested against spatial distribution patterns of these light demanders. Here, we focus on the 28 most abundant LLP and NPLD from 250 one‐ha plots distributed along eight parallel transects (~50 km) in the Yangambi forest. Four species of short‐lived pioneers (SLP) and a single abundant shade‐tolerant species (Gilbertiodendron dewevrei) were used as reference because they are known to be strongly aggregated in recently disturbed patches (SLP) or along watercourses (G. dewevrei). Results show that SLP species are strongly aggregated with clear spatial autocorrelation of their diameter. This confirms that they colonized the patch following a one‐time disturbance event. In contrast, LLP and NPLD species have random or weakly aggregated distribution, mostly without spatial autocorrelation of their diameter. This does not unambiguously confirm the “human disturbance” hypothesis. Alternatively, their abundance might be explained by their deciduousness, which gave them a competitive advantage during long‐term drying of the late Holocene. Additionally, a canonical correspondence analysis showed that the observed LLP and NPLD distributions are not explained by environmental variables, strongly contrasting with the results for the reference species G. dewevrei, which is clearly aggregated along watercourses. We conclude that the abundance of LLP and NPLD species in Yangambi cannot be unambiguously attributed to past human disturbances or environmental variables. An alternative explanation is that present‐day forest composition is a result of adaptation to late‐Holocene drying. However, results are inconclusive and additional data are needed to confirm this alternative hypothesis., The objective of this paper was to contribute to the elucidation of the light‐demanding species persistence puzzle in the Congo Basin rainforest canopy. Three hypotheses have been tested, which suggest: (H1) legacy of past disturbances, (H2) legacy of adaptation to a drier climate, and (H3) consequence of heterogeneity of the environment. Our results clearly support H1 for the species of short‐lived pioneer guild and do not unambiguously support a single hypothesis for the long‐lived pioneer and non‐pioneer light‐demanding guilds, although they seem to favor H2.

The Rwenzori region in Uganda, a global biodiversity hotspot, is currently undergoing exponential economic and population growth, which puts continuous stress on its freshwater ecosystems. In Sub-Saharan Africa, biomonitoring campaigns using region-specific biotic indices is limited, particularly in Uganda. In this research, we present the Rwenzori Score (RS), a new macroinvertebrate-based biotic index developed to specifically assess the aquatic health of Rwenzori streams and rivers. We collected and measured both biological and physicochemical variables and identified 34,202 macroinvertebrates, belonging to 64 different taxa. The RS was developed in two steps. First, using canonical ordination, we identified chemical variables that correlated significantly with gradients in macroinvertebrate assemblage distribution and diversity. Second, based on selected variables and weighted averages, we determined specific family indicator values and assigned pollution tolerance values (varying from 1: tolerant, to 10: sensitive) to a family. Finally, we established four water quality classes: poor, fair, good, and excellent. The RS is highly correlated with the Average Score Per Taxon System (p &lt, 0.05), a well-known and widely used biotic index. The RS has 5 unique taxa that are not included in other regional indices. In this regard, the development of the RS is a beneficial tool for tailor-made biomonitoring that can contribute to the sustainable development of the Rwenzori stream and river basins.

In this paper, we reflect on a number of aspects of ordination methods: how should absences be treated in ordination and how do model-based methods, including Gaussian ordination and methods using generalized linear models, relate to the usual least-squares (eigenvector) methods based on (log-) transformed data. We defend detrended correspondence analysis by theoretical arguments and by reanalyzing data that previously gave bad results. We show by examples that constrained ordination can yield more informative views on effects of interest compared to unconstrained ordination (where such effects can be invisible) and show how constrained axes can be interpreted. Constrained ordination uses an ANOVA/regression approach to enable the user to focus on particular aspects of species community data, in particular the effects of qualitative and quantitative environmental variables. We close with an analysis examining the interaction effects between two factors, and we demonstrate how principal response curves can help in their visualisation. Example data and Canoco 5 projects are provided as Supplementary Material.

Patterns of epilithic diatom species distribution in relation to environmental variables from 12 sampling sites on the main stream and some of its tributaries in the Nilufer Stream Basin were determined using multivariate statistical techniques. The stream basin has been heavily influenced by anthropogenic effects. The upper part of the basin that is distant from pollution sources mostly has a spring water quality, while the lower part where the stream flows through the urban area and receives domestic and industrial wastewater has a quite low quality. Ordination techniques using both diatom taxa and 21 environmental variables revealed non-to slightly polluted upper basin sites and highly polluted lower basin sites along the stream. The results showed that the stream catchment is polluted gradually from upstream to downstream and that most of the downstream sites have very low water quality especially in summer months. A total of 134 epilithic diatom taxa belonging to 50 genera were recorded for 12 sample sites. Partial CCA results indicated that water temperature (T), discharge (Q), and total phosphorus (TP) were the most important variables affecting the distribution of diatom species. Unpolluted or slightly polluted upper basin sites were dominated by Achnanthidium minutissimum, Cocconeis placentula var. euglypta, Gomphonema olivaceum, and Navicula tripunctata. Highly polluted lower basin sites were characterized by high levels of organic and inorganic matters and low dissolved oxygen (DO) values. Species widespread in the highly polluted lower basin sites such as Nitzschia umbonata, Nitzschia amphibia, Nitzschia capitellata, Nitzschia palea, Nitzschia paleacea, Luticola mutica, and Stephanodiscus niagarae were mostly related to pollution indicator variables such as ammonium nitrogen (NH4(+)-N), sodium (Na+), total phosphorus (TP), and total organic matter (TOM).

This article describes a multidisciplinary approach to assessing potential vegetation types. The relation between vegetation distribution as derived from field survey and habitat characteristics in the Yellow River Delta (YRD) was analyzed using detrended canonical correspondence analysis (DCCA). The three-dimensional groundwater numerical simulation model MODFLOW yielded an accurate distribution of the shallow groundwater table within the study area. Groundwater table and soil salinity appeared to have the largest influence on the distribution patterns of specific indicator species. The quantitative relationships between species presence and environmental factors were further explored using logistic regression, allowing for the prediction of potential species distribution in relation to fluctuations in groundwater depth and soil salinity. Based on this, potential distribution maps for specific plant species and their communities were generated using ArcGIS. The potential vegetation map was compared to the actual vegetation map (interpreted from SPOT imagery), which leads to a discussion of the main factors responsible for fragmentation and degradation of the local vegetation system

Phytoplankton communities are structured by factors acting over temporal and spatial scales. Identifying which factors are driving spatial patterns in aquatic communities is the central aim of ecology. In this study, data sets of phytoplankton communities and environmental data of two Portuguese reservoirs types (lowland ‘‘riverine reservoirs’’ and higher altitude ‘‘artificial lake reservoirs’’) were used to determine the importance of environmental variables at different spatial (geographical, regional and local) and time scales (seasons, years) on the community structure. In all the data sets, the multivariate ordination technique Canonical Correspondence Analysis (CCA) showed that regional and local scales explained the majority (9–18% and 13–19%, respectively) of the taxa variance. However, for ‘‘riverine reservoirs’’, time variables were more important, explaining 27% of the variability in phytoplankton assemblages. Variance partitioning was used to assess the individual importance of the three spatial scales and time for the community structure of the two reservoir types. The majority of among-site variability (5.9–21.4%) was accounted for by time variables, with local, regional, and geographical scale variables accounting for 3.3– 5.6%, 3.7–4.5% and 2.6–2.9%, respectively. The effects of different spatial scales on phytoplankton communities were clearly interrelated; thus, implying that phytoplankton assemblages are capable of detecting stress from catchment to site scales.

Constrained ordination methods aims at finding an environmental gradient along which the species abundances are maximally separated. The species response functions, which describe the expected abundance as a function of the environmental score, are according to the ecological fundamental niche theory only meaningful if they are bell-shaped. Many classical model-based ordination methods, however, use quadratic regression models without imposing the bell-shape and thus allowing for meaningless U-shaped response functions. The analysis output (e.g. a biplot) may therefore be potentially misleading and the conclusions are prone to errors. In this paper we present a log-likelihood ratio criterion with a penalisation term to enforce more bell-shaped response shapes. We report the results of a simulation study and apply our method to metagenomics data from microbial ecology.

Correspondence analysis on an aggregated lexical table is a typical practice in textual analysis in which a contextual categorical variable is used to aggregate documents, depending on the categories to which they belong. This work generalises this approach and considers several quantitative, categorical or mixed contextual variables. The result is a new method that we have called `correspondence analysis on a generalised aggregated lexical table'. A favoured application derives from surveys by questionnaire, including both open-ended and closed questions. The free-text answers are encoded into a respondents $$\times $$× words frequency table called a lexical table. The closed questions, either quantitative or categorical, form the contextual variables. The primary objective is to establish a typology of the variables and a typology of the words from their mutual relationships as grasped from jointly analysing the textual and contextual tables. Validation tests are offered, particularly in the form of confidence ellipses. The comprehensive and numerous properties of the method, similar to correspondence analysis properties, are detailed. Promising results are obtained as indicated by an application to a marketing survey conducted among 1,000 respondents.

A long-standing observation in community ecology is that the scaling of species richness, as exemplified by species-area curves, differs on local and regional scales. This decoupling of scales may be largely due to sampling processes ( the increasing constraint imposed by sampling fewer individuals at fine scales), as distinct from ecological processes, such as environmental heterogeneity, that operate across scales. Removal of the sampling constraint from fine-scale richness estimates should yield species-area curves that behave like those of the regions in which they are embedded, but an effective method for this removal has not been available. We suggest an approach that incorporates the manner in which small areas accumulate species over time as a way to remove the signature of sampling processes from fine-scale species-area curves. We report for three species-rich grasslands from two continents how local plant species richness is distributed through time at multiple, nested spatial scales, and we ask whether sampling-corrected curves reflect the spatial scaling of richness of each larger floristic province. Our analysis suggests that fine-scale values of richness are highly constrained by sampling processes, but once these constraints are removed, the spatial scaling of species richness is consistent from the scale of individuals to that of an entire province.

Despite recent modelling approaches integrating the effects of niche-based processes and dispersal-based processes on local plant species composition, their relative importance is still not clear. We test whether the predictability of local species composition from environmental conditions is influenced by dispersal traits. We analyzed a large database with co-occurrence data, using ordination techniques (DCA and CCA) to identify the major environmental determinants of species composition. The percentage of explained variance in occurrence was quantified for individual species with CCA. Effects of life-history traits on the predictability of occurrence patterns were tested by means of regression analysis, using a generalized linear models approach. The results reveal close correlations between species composition and environmental conditions, implying that the predictability of the set of species that might occur in a given environmental setting ("habitat species pool") is high. The habitat species pool, however, reflects the potential species composition, and not the actual local situation. At the level of individual species, a large proportion (>90%) of the variation in occurrence remained unexplained. Predictability of species occurrence patterns was increased by a greater capacity for long-distance dispersal, greater adult longevity and the capacity to build a persistent seed bank. The results indicate that the predictability of species composition from environmental conditions is reduced by a few orders of magnitude by dispersal limitation and that poor dispersers are underrepresented.

A new ordination method, called co-correspondence analysis, is developed to relate two types of communities (e.g., a plant community and an animal community) sampled at a common set of sites in a direct way. The method improves the simple, indirect approach of applying correspondence analysis (reciprocal averaging) to the separate species data sets and correlating the resulting ordination axes. Co-correspondence analysis maximizes the weighted covariance between weighted averaged species scores of one community and weighted averaged species scores of the other community. It thus attempts to identify the patterns that are common to both communities. Both a symmetric descriptive and an asymmetric predictive form are developed. The symmetric form relates to co-inertia analysis and the asymmetric, predictive form to partial least-squares regression. In two examples the predictive power of co-correspondence analysis is compared with that of canonical correspondence analyses on syntaxonomic and environmental data. In the first example, carabid beetles in roadside verges are shown to be more closely related to plant species composition than to vegetation structure (biomass, height, roughness, among others), and, in the second example, bryophytes in spring meadows are shown to be more closely related to the species composition of the vascular plants than to the measured water chemistry.

Floodplains of large rivers are among the most dynamic and diverse, yet most threatened ecosystems on earth. For a solid underpinning of river conservation and rehabilitation measures, it is critical to unravel the influences of the multiple stressors affecting floodplain ecosystems. Using canonical correspondence analysis with variance partitioning, we disentangled and ranked the influences of three floodplain ecosystem stressors (land use, flooding and soil contamination) on terrestrial plant and soil-dwelling arthropod assemblages in a floodplain area along the river Rhine in The Netherlands. We included five biotic assemblages: plant species (73 taxa), ground beetle species (57 taxa), ground beetle genera (29 taxa), beetle families (32 taxa) and arthropod groups at taxonomic levels from family to class (10 taxa). Plant and arthropod assemblages were primarily related to land use, which explained 19–30% of the variation in taxonomic composition. For plant species composition, flooding characteristics were nearly as important as land use. Soil metal contamination constituted a subordinate explanatory factor for the plant assemblages only (3% of variation explained). We conclude that the taxonomic composition of terrestrial plant and arthropod assemblages in our study area is related to land use and flooding rather than soil metal contamination.

his contribution presents a review of the development of the study of vegetation dynamics since 1979, in the framework of a jubilee meeting on progress in the study of vegetation. However, an exhaustive review is both impossible and unnecessary. It is impossible within the few pages available because of the vast literature published, and it is unnecessary because there are several review papers and textbooks available. To start with the year 1979 itself, two important papers appeared (White 1979; Huston 1979), and a symposium on advances in vegetation science was held in Nijmegen (Van der Maarel 1980a,b). Further publications consulted for this paper include Pickett & White (1985), Pickett et al. (1987), Gray et al. (1987), Burrows (1990), Van Andel et al. (1993), Glenn-Lewin et al. (1992) and Agnew et al. (1993). In 1979 a similar special meeting was held (Werger 1979), where I contributed with a review-like paper on numerical methods in vegetation science. Since this important aspect of vegetation science was not covered at this jubilee meeting, some developments of this branch have been included here, mainly so far as they apply to vegetation dynamics. Since I am involved in one particular branch of vegetation dynamics, i.e. gap dynamics, extra attention will be paid to recent work in Uppsala, perhaps at the expense of other new developments.

Question: Is it possible to translate vegetation maps into reliable thematic maps of site conditions? Method: This paper presents a new method, called Iteratio, by which a coherent spatial overview of specific environmental conditions can be obtained from a comprehensive vegetation survey of a specific area. Iteratio is a database application which calculates environmental indicator values for vegetation samples (releves) on the basis of known indicator values of a limited number of plant species. The outcome is then linked to a digitalized vegetation map (map of plant communities) which results in a spatial overview of site conditions. Iteratio requires the indicator values of a minimum of 10–20% of the species occurring. The species are given a relative weight according to their amplitudes: species with a narrow range are weighted stronger, species with a broad range are weighted weaker. Conclusion: The method presented here enables a coherent assessment of site conditions on the basis of a vegetation survey and the indicator values of a limited number of plant species.

Habitat modification, pollution, overfishing, poaching, competition from nonindigenous species, and diseases have led to the extinction in Europe of many populations of indigenous crayfish. Under the rationale that any programme of reintroduction should be preceded by a thorough understanding of habitat requirements of the species of concern, we studied the microhabitat use of an Austropotamobius pallipes population in Tuscany, central Italy. Microhabitat use was assessed for water depth, current velocity, substrate, percentages of boulders, underwater tree roots, and in-stream vegetation cover. Results show that A. pallipes’ habitat use is size-partitioned. Smaller individuals mostly occupy stream edges in shallow waters with submerged roots, whereas larger individuals use deeper waters, often associated with boulders. Crayfish spatial distribution is restricted mostly to the microhabitats characterised by extensive cover and slow current velocity. The study highlights the importance of habitat heterogeneity and cover elements for the protection of this indigenous species.

There is a growing need to predict ecological responses to long-term habitat change. However, statistical models for marine soft-substratum ecosystems are limited, and consequently there is a need for the development of such models. In order to assess the utility of statistical modelling approaches for predicting likely changes in species distributions under varying environmental conditions, we tested the utility of logistic modelling and classification approaches. We successfully developed models relating the presence/absence of common intertidal macrofauna to changing environmental variables such as sediment characteristics, depth/elevation, tidal currents and wind-wave (i.e. wind-generated wave activity) disturbance. The final model for each species contained between 1 and 6 variables, where the percentage correctly predicted was moderate to high, ranging from 59 to 97%. We were also able to identify relationships between higher level variables such as estuary type, basin morphometry and catchment-draining processes in driving macrobenthic community composition; however, we were unable to fully test the utility of the classification approach due to differences in the scale at which the macrobenthic data was collected and the scale of the higher level physical variables. These models were developed and tested using data that covered a range of environmental conditions in 5 estuaries in New Zealand. Such broad-scale statistical models play a critical role in our understanding of the likely effects of large-scale habitat change. However, a greater understanding of the fine-scale mechanistic controls on species distributions such as life-history characteristics, density information and biotic interactions would potentially lead to the development of more sensitive models. [KEYWORDS: Logistic regression · Statistical modelling · Classification systems · Benthic macrofauna · Sedimentation · Estuary · Macroecology · New Zealand]

Despite recent modelling approaches integrating the effects of niche-based processes and dispersal-based processes on local plant species composition, their relative importance is still not clear. We test whether the predictability of local species composition from environmental conditions is influenced by dispersal traits. We analyzed a large database with co-occurrence data, using ordination techniques (DCA and CCA) to identify the major environmental determinants of species composition. The percentage of explained variance in occurrence was quantified for individual species with CCA. Effects of life-history traits on the predictability of occurrence patterns were tested by means of regression analysis, using a generalized linear models approach. The results reveal close correlations between species composition and environmental conditions, implying that the predictability of the set of species that might occur in a given environmental setting ("habitat species pool") is high. The habitat species pool, however, reflects the potential species composition, and not the actual local situation. At the level of individual species, a large proportion (>90%) of the variation in occurrence remained unexplained. Predictability of species occurrence patterns was increased by a greater capacity for long-distance dispersal, greater adult longevity and the capacity to build a persistent seed bank. The results indicate that the predictability of species composition from environmental conditions is reduced by a few orders of magnitude by dispersal limitation and that poor dispersers are underrepresented.

Few macrobenthic studies have dealt simultaneously with the two major gradients in estuarine benthic habitats: the salinity gradient along the estuary (longitudinal) and the gradients from high intertidal to deep subtidal sites (vertical gradient). In this broad-scale study, a large data set (3112 samples) of the Schelde estuary allowed a thorough analysis of these gradients, and to relate macrobenthic species distributions and community structure to salinity, depth, current velocities and sediment characteristics. Univariate analyses clearly revealed distinct gradients in diversity, abundance, and biomass along the vertical and longitudinal gradients. In general, highest diversity and biomass were observed in the intertidal, polyhaline zone and decreased with decreasing salinity. Abundance did not show clear trends and varied between spring and autumn. In all regions, very low values for all measures were observed in the subtidal depth strata. Abundance in all regions was dominated by both surface deposit feeders and sub-surface deposit feeders. In contrast, the biomass of the different feeding guilds showed clear gradients in the intertidal zone. Suspension feeders dominated in the polyhaline zone and showed a significant decrease with decreasing salinity. Surface deposit feeders and sub-surface deposit feeders showed significantly higher biomass values in the polyhaline zone as compared with the mesohaline zone. Omnivores showed an opposite trend. Multivariate analyses showed a strong relationship between the macrobenthic assemblages and the predominant environmental gradients in the Schelde estuary. The most important environmental factor was depth, which reflected also the hydrodynamic conditions (current velocities). A second gradient was related to salinity and confirms the observations from the univariate analyses. Additionally, sediment characteristics (mud content) explained a significant part of the macrobenthic community structure not yet explained by the two other main gradients. The different assemblages are further described in terms of indicator species and abiotic characteristics. The results showed that at a large, estuarine scale a considerable fraction of the variation in abundance and biomass of the benthic macrofauna correlated very well with environmental factors (depth, salinity, tidal current velocity, sediment composition). (C) 2003 Elsevier Science B.V. All rights reserved.

We investigated the within-site distribution of Enchytraeidae, Collembola, Oribatida, Mesostigmata and Prostigmata relative to varying water level and substrate quality on pine mire sites forming a drainage succession continuum. Collembolans were most intolerant of wetness, favoring drier locations at all stages of the drainage succession. In general, the effect of water level variation on the within-site distribution of the soil fauna was strongest when the site was at an early stage of either progressive or regressive water level change. When the average water level was below 20 cm, it no longer had a significant effect on the distribution of mites, but still affected that of Enchytraeidae and Collembola. Boron was positively correlated with faunal density in several cases, and thus may be the growth limiting nutrient affecting substrate quality for decomposers in these sites. The overall changes in the soil mesofauna in drained peatlands depicted here show that these peatland forests are converging ecologically on upland forests where decomposition in general is much faster than in pristine peatlands. The change caused by restoration shows how labile these ecosystems are also with respect to the mesofaunal community.

This contribution presents a review of the development of the study of vegetation dynamics since 1979, in the framework of a jubilee meeting on progress in the study of vegetation. However, an exhaustive review is both impossible and unnecessary. It is impossible within the few pages available because of the vast literature published, and it is unnecessary because there are several review papers and textbooks available. To start with the year 1979 itself, two important papers appeared (White 1979; Huston 1979), and a symposium on advances in vegetation science was held in Nijmegen (Van der Maarel 1980a,b). Further publications consulted for this paper include Pickett & White (1985), Pickett et al. (1987), Gray et al. (1987), Burrows (1990), Van Andel et al. (1993), Glenn-Lewin et al. (1992) and Agnew et al. (1993). In 1979 a similar special meeting was held (Werger 1979), where I contributed with a review-like paper on numerical methods in vegetation science. Since this important aspect of vegetation science was not covered at this jubilee meeting, some developments of this branch have been included here, mainly so far as they apply to vegetation dynamics. Since I am involved in one particular branch of vegetation dynamics, i.e. gap dynamics, extra attention will be paid to recent work in Uppsala, perhaps at the expense of other new developments.

Short-term field experiments are often used to predict and evaluate long-term management effects. Based on a mowing experiment in two calcareous fens near Lake Neuchatel, Switzerland, we investigated whether shea-term treatment effects (i.e. during the first four years) were confirmed by longterm results (13 - 14 yr). Plots were mown in summer or in winter or left unmown. The main long-term trends in overall species composition (based on percentage cover estimates) were already observable in the first four years: mown and unmown plots diverged, whereas summer-cut and winter-cut plots remained similar. At the individual species level, however, short-term and long-term treatment effects differed considerably: many species whose abundance seemed affected by treatments during the first four years showed no response in the long term, and vice versa. These discrepancies were similar when based on cover estimates or on counts of shoots. Species responses did actually depend on the time scale considered. Short-term and long-term treatment effects on species richness were similar (i.e. a decrease in unmown plots), although only long-term effects were significant. Treatment effects on the above-ground biomass varied considerably, and short-term trends (lower biomass in unmown plots) differed from long-term trends (higher biomass in unmown plots). Our sites showed little overall change in species composition during the period investigated, and treatment effects were low compared with other similar experiments. if study sites are less stable or treatment effects more drastic, a short-term evaluation is expected to be even less reliable. Knowledge on species dynamics at a site may help to choose the adequate spatial and temporal scale of investigation, and thus increase the efficiency of management experiments.