<abstract>Distribution modelling - research with the purpose of modelling the distribution of observable objects of a specific type - has become established as an independent branch of ecological science, with strong proliferation of approaches and methods in recent years. Since it was first made available to distribution modellers in 2004, the maximum entropy modelling method (MaxEnt) has established itself as a state-of-the-art method for distribution modelling. Default options and settings in the user-friendly Maxent software has become established as a standard practice for distribution modelling by MaxEnt.A mini-review of 87 recent publications in which MaxEnt was used with empirical data to model distributions showed that the ‘standard MaxEnt practice’ is followed by a large majority of users and questioned by few. However, the review also provides indications that MaxEnt models obtained by the standard practice are sometimes overfitted to the data used to parameterise the model; examples of cases in which simpler MaxEnt models with predictive performance do exist. Results of the review motivate strongly for a better understanding of the ecological implications of the maximum entropy principle, as a basis for choosing MaxEnt options and settings.This paper provides a thorough explanation of MaxEnt for ecologists, ending with a set of suggestions for improvements to the current practice of distribution modelling by MaxEnt. The explanation for MaxEnt given in the paper differs from previous explanations by being based on the maximum likelihood principle and by being based upon a gradient analytic perspective on distribution modelling. Four new findings are particularly emphasised: (1) that a strict maximum likelihood explanation of MaxEnt is possible, which places MaxEnt among regression methods in the widest sense; (2) that the true degrees of freedom for the residuals of a Max- Ent null model is N - n, the difference between the number of background and the number of presence observations used in the modelling; (3) that likelihood-ratio and F-ratio tests can be used to compare nested MaxEnt models; and (4) that subset selection methods are likely to be preferential to shrinkage methods for model selection in MaxEnt. Methods for internal model performance assessment, model comparison, and interpretation of MaxEnt model predictions (MaxEnt output), are described and discussed. Two simulated data sets are used to explore and illustrate important issues relating to MaxEnt methodology.Arguments for development of a generally applicable ‘consensus MaxEnt practice’ for spatial prediction modelling are given, and elements of such a practice discussed. Five main additions or amendments to the ʻstandard MaxEnt practiceʼ are suggested: (1) flexible, interactive tools to assist deriving of variables from raw explanatory variables; (2) interactive tools to allow the user freely to combine model selection methods, methods and approaches for internal model performance assessment, and model improvement criteria, into a data-driven modelling procedure, (3) integration of independent presence/absence data into the modelling process, for external model performance assessment, for model calibration, and for model evaluation; (4) new output formats, notably a probability-ratio output format which directly expresses the ʻrelative suitability of one place vs. anotherʼ for the modelled target; and (5) development of options for discriminative use of MaxEnt, i.e., use of with presence/absence data. The most important research needs are considered to be: (1) comparative studies of strategies for construction of parsimonious sets of derived variables for use in MaxEnt modelling; and (2) comparative tests on independent presence/absence data of the predictive performance of MaxEnt models obtained with different model selection strategies, different approaches for internal model performance assessment, and different model improvement criteria. </abstract>

A strict maximum likelihood explanation of MaxEnt, and some implications for distribution modelling

<abstract><title style='display:none'>Abstract</title>Species distribution modeling (SDM) can be useful for many applied purposes, e.g., mapping and monitoring of rare and endangered species. Sparse presence data are a recurrent, major obstacle to precise modeling of species distributions. Thus, knowing the minimum number of presences required to obtain reliable distribution models is of fundamental importance for applied use of SDM. This study uses a novel approach to assess the critical sample size (CSS) sufficient for an accurate prediction of species distributions with Maximum Entropy Modeling (MaxEnt). Large presence datasets for thirty insect species, ranging from generalists to specialists regarding their responses to main bioclimatic gradients, were used to produce reference distribution models. Models based on replicated subsamples of different size drawn randomly from the full dataset were compared to the reference model using the index of vector similarity distribution models. Models based on replicated subsamples of different size drawn randomly from the full dataset were compared to the reference model using the index of vector similarity (<italic>IVS</italic>). Two thresholds for <italic>IVS</italic> were determined based on comparison of nine reference models to random null models. The threshold values correspond to 0.95 and 0.99 probability that a model outperforms a random null model in terms of similarity to the reference dataset. For 90% of the species, clearly nonrandom models were obtained with less than 10 presence observations, and for 97% of the species with less than 15 presence observations. We conclude that the number of presence observations required to produce nonrandom models is generally low and, accordingly, that even sparse datasets may be useful for distribution modelling.</abstract>

How much is enough? Influence of number of presence observations on the performance of species distribution models

<abstract><title style='display:none'>Abstract</title>An up-to-date bibliography of botanical literature related to the Canary Islands is presented, listing 2.738 titles covering all disciplines of botany. Titles dealing with phytochemical or agricultural aspects may, however, be incomplete.</abstract>

Botanical bibliography of the Canary Islands

<abstract><title style='display:none'>Abstract</title>After massive proliferation over the last decade, distribution modelling (DM) – research with
the purpose of modelling the distribution of observable objects of a specific type – has grown
into an independent branch of ecological science. There is consensus that this new discipline
needs a stronger theoretical foundation. I describe DM as an inductive scientific process with
12 steps, organised into three composite steps: ecological model, data model, and statistical
model. Step 8, modelling of the overall ecological response, places DM unambiguously among
gradient analysis techniques and motivates for a gradient analytic (GA) perspective on DM. DM
terminology is reviewed and revised accordingly.
Three fundamental insights of the GA perspective are described: (1) that external ‘factors’
do not influence the species one by one, but act on the species in concert; (2) that a few major
complex-gradients normally account for most of the variation in species composition that can
be explained environmentally; and (3) that species occur within a restricted interval along
each major complex-gradient. These insights are developed into a theoretical platform for DM.
General patterns of species performance variation along environmental complex-gradients and
the structuring processes responsible for these patterns are reviewed. Three categories of ecoclines,
i.e., gradients of variation in species composition and the environment, are recognised:
regional ecoclines, local ecoclines, and condition or impact ecoclines. Causes and implications
of the unimodal shape of species’ responses to environmental complex-gradients are reviewed.
Structuring processes are divided into three categories: limited physiological tolerance, interspecific
interactions, and demographic processes. Relationships between categories of ecoclines,
the processes responsible for variation in species performance along them, and the spatial and
temporal scale intervals in which variation is large, are reviewed.
The GA perspective forms the basis for discussions of important steps in the DM process.
Initially, the controversial concepts of the habitat and the niche are reviewed and their role in
the ecological model (Step 1) discussed. I conclude that neither of these concepts are necessary,
nor useful, for DM. As an alternative to conceptual models based upon the niche concept, I
propose a new conceptual modelling framework for DM, the HED framework, which is rooted in
the gradient analytic perspective. I show how this new framework can be used, in initial phases
of a DM study to formulate a meta-model for factors that influence distributions, and in the
analytic phase to guide important choices of methods and options and to assist interpretation
of modelling results. Important data model issues are: collection of data for the modelled target
and preparation of raw response variables (Steps 2 and 6); collection of explanatory data (Step 3); conceptualisation of the study area (Step 4); collection of data for calibration and evaluation
(Step 9); and transformation of explanatory variables to derived variables subjected to DM (Step
5,ii). Important statistical model issues are: statistical model formulation, i.e. choice of method
(Step 7,i) and model specification (Step 7,ii); model selection and internal assessment of model
performance (Steps 8,i and 8,ii); and model evaluation (Step 10). Two points are emphasised:
(1) that modelling purpose should inform choice of methods and options; and (2) the importance
of an independently collected presence/absence data set, which can be used to calibrate,
evaluate and iteratively improve models.
Finally I list seven challenges of particular importance for progress in DM: (1) that more
knowledge of patterns of natural variation is needed; (2) that a better mechanistic understanding
of causes of patterns of natural variation is needed; (3) that the availability of relevant rasterised
explanatory variables needs to be improved; (4) that more studies of patterns at local
and micro spatial scales, in addition to multiple-scale studies using DM methods, are needed;
(5) that evaluation by independent data should be established as a standard in DM; (6) that
further insights into statistical modelling methods and their options, with particular reference
to appropriateness for different types of data and DM purposes, are needed; and (7) that DM
methods should be incorporated in studies with a broader scope. I conclude that there are
considerable potentials for improvement of DM methods and practice. Increased return from
DM in terms of contributions that improve our understanding of patterns of natural variation
and their causes, should be expected.</abstract>

A gradient analytic perspective on distribution modelling

<abstract>
<title style='display:none'>Abstract</title>
An up-to-date checklist of the vascular plants of Macaronesia (the Azores, the Madeira archipelago, the Salvage Islands, the Canary Island, and the Cape Verde Islands) is given. 3,106 species belonging to 1,062 genera are listed, as are also a number of intraspecific taxa down to variety level. 20 new nomenclatural combinations are made within the genera <italic>Atalanthus, Lavandula, Pericallis, Satureja,</italic> and <italic>Sinapidendron.</italic> A second section lists ea. 2,300 synonyms and their presumed identity.
</abstract>

Flora of Macaronesia. Checklist of vascular plants. 4. revised edition

<abstract>
<title style='display:none'>Abstract</title>
Forty mosses and twenty-six hepatics are reported for the first time from Fuerteventura, and fifteen mosses and nine hepatics are reported for the first time from Lanzarote, among them <italic>Gigaspermum mouretii</italic> Corb. which is new to Macaronesia. All taxa recorded so far are listed and their distribution outlined. Distribution maps are given for some of the more common species. The zonation of bryophytes is considered, and a survey of their phytogeographical affinities is given. some ecological factors are discussed, and it is suggested that the bryophyte flora of these two islands is primarily restricted by climatic factors.
</abstract>

Distribution of bryophytes on Fuerteventura and Lanzarote, the Canary Islands.

<abstract>
<title style='display:none'>Abstract</title>
A multitude of landscape characterisation and mapping methods exist, but few methods take into account that landscapes properties vary in a gradual, continuous manner along multiple directions of variation. In this study, we used gradient analytic methods, rooted in ecological continuum theory, to analyse landscape variation throughout Norway. The aim is to explain differences in landscape properties in the simplest possible way, by identifying ‘complex landscape gradients’ (CLGs), i.e. composite gradients of co-occurring landscape elements and properties. We collected data by stratified sampling of 100 test areas (20×20 km), in which we delineated a total of 3966 observation units (landscape polygons 4–30 km²) based on geo-morphological criteria. For each observation unit, 85 landscape variables were recorded. We identified patterns of variation in landscape element composition by parallel use of two multivariate statistical methods, detrended correspondence analysis (DCA) and global nonmetric multidimensional scaling (GNMDS).
The analyses revealed that the most important properties explaining differences in total landscape elements composition was location of the landscape relative to the coastline and coarse-scale landform variation. Most landscape elements had distinct optima within specific segments along broad-scale complex-gradients in landscape properties. A tentative landscape-type hierarchy was built by an iterative procedure by which the amount of compositional turnover in landscape-element composition between adjacent types was standardised. Six ‘major landscape types’ were identified based on geomorphological criteria. Within each major type, we identified a unique set of 2–5 important CLGs, representing geo-ecological, bio-ecological, and land use-related landscape variation. Minor landscape types were obtained by combining segments along two or more CLGs.
The study shows that geological diversity, biological diversity and human land-use are tightly intertwined at the landscape level of ecological complexity, and that predominantly abiotic processes control and constrain both biotic processes and human land use.
</abstract>

Gradient analysis of landscape variation in Norway

Vegetation ecology: theory, methods and applications with reference to Fennoscandia

Evolution in higher plants: patterns and processes

<abstract>
<title style='display:none'>Abstract</title>
The vegetation of shell-beds is studied in an island on the coast of Skagerak, SE Norway. Within this restricted area 125 sample plots, 1 m2 each, were distributed by a restricted random procedure. Frequency in subplots and percentage cover were used for estimation of species abundance. A set of 33 environmental variables was obtained from each sample plot. Ecological gradients corresponding to the main vegetational gradients are identified by means of DCA ordination results correlated with environmental data. DCA ordination results are further interpreted by the use of an earlier classification of the vegetation and by application of Grime’s strategy concept. The following complex gradients were recognized: ( 1) the primary successional gradient, influenced by variables dependent on site age, e.g. elevation, distance from the sea, and rate of decomposition of mollusc shells, (2) the secondary successional gradient, from open meadow vegetation via open shrub vegetation to dense shrub vegetation, highly correlated with variables independent of site age, e.g intensity of grazing, (3) the nutrient availability gradient, and (4) the soil moisture gradient. Interpretation of relations between coenoclines and environmental variables was performed by Kendall rank correlation and relationships among ecological variables analysed by PCA ordination. Direct gradient analysis by <italic>rh-DCCA</italic> is used as a supplement to DCA. The ratio between the <italic>rh-</italic>DCCA eigenvalue of the first ordination axis and the corresponding eigenvalue of the first residual (unconstrained) axis is used to quantify the importance of each environmental variable. The performed multivariate analyses show that the successional pathways on shell-bed shores are dependent on the grazing pressure. The relative importance of the following structuring processes is discussed: (1) interspecific interaction (competition, coexistence and facilitation), (2) destabilizing factors (disturbance and fluctuations), (3) stress, and (4) chance. Ordination and association analyses shows that <italic>Juniperus communis</italic> is the most important structuring species in the material. Grazing is necessary to reduce overgrowth by junipers and to maintain a high species diversity.
The field data are used for inspection of the performance of different rescaling and detrending options, available with DCA ordination. Non-linear rescaling appears to be less influenced by deviant sample plots as compared to linear rescaling, and the S.D. units of the axes produced by non-linear rescaling are considered better interpretable in terms of a unimodal model of species responses to ecological gradients. Available options for detrending by polynomials are shown to be inferior to the detrending by segments option, as polynomial detrending may impose a polynomial distortion on the point configuration in the ordination space.
</abstract>

Vegetation patterns and structuring processes in coastal shell-beds at Akerøya, Hvaler, SE Norway.

<abstract>
<title style='display:none'>Abstract</title>
A complete and up-to-date checklist of the vascular plants of Macaronesia (the Azores, the Madeira archipelago, the Salvage Islands, the Canary Islands, and the Cape Verde Islands) is given. 3.125 species belonging to 1.041 genera are listed, as are also a number of intraspecific taxa down to variety level. New combinations are proposed within the genera <italic>Cheilanthes, Pericallis</italic> and <italic>Pulicaria.</italic> A second section lists 2.250 synonyms and their presumed identity.
</abstract>

Flora of Macaronesia. Checklist of vascular plants. 3. revised edition.

<abstract>
<title style='display:none'>Abstract</title>
Vegetational and ecological monitoring of boreal forests in Norway was initiated in 1988, as a part of the programme “Countrywide monitoring of forest health” at Norwegian Institute of Land Invetory (NIJOS). Ten reference areas for monitoring will be established and analysed within five years; two new areas each year. Each of the monitoring areas is planned to be reanalysed every fifth year. In each monitoring area 10 macro sample plots, 50 m2 each, are selected. Within each macro sample plot <italic>5</italic> meso sample plots, 1 m2 each, are randomly placed and the vegetation is analysed by using frequency in subplots as measure of species abundance. Within each meso sample plot one micro sample plot (two in the first established monitoring area), 0.0625 m2 each, is analysed by the same method. In connection with each meso sample plot several environmental variables are recorded. In each ma cro sample plot several tree variables and variables describing the terrain are recorded. The variables are used for environmental interpretation as well as for monitoring, since known relations between vegetation and environmental gradients form the basis of vegetational and ecological monitoring. Any future changes in vegetation, soil and the health of trees have to be interpreted in relation to the analysis of vegetation-environment relationships in order to identify changes due to air pollution or climatic changes.
The data from the first established monitoring area, Rausj0marka in Akershus county, are subjected to analysis in this paper. The most important vegetational and environmental gradients in the area are discussed, as well as the field methodology and the methods for data analysis to be used in integrated monitoring. The advantages of integrated monitoring of vegetation, soil and trees on the same sample plots are emphasized, including advantages for surveying and monitoring of species (bioindicators).
</abstract>

Vegetational and ecological monitoring of boreal forests in Norway. I. Rausjømarka in Akershus county, SE Norway.

<abstract>
<title style='display:none'>Abstract</title>
128 species in 45 genera of sorediate and isidiate, crustose, corticolous lichens are recorded from Norway. Accounts of their morphology, chemistry, and substratum preferences are presented, and a discussion of their distribution in Norway is supported by maps for a number of taxa. With few exceptions, the taxa can be distinguished on thallus characters alone. Several taxa, especially those with brown or blue-pigmented soralia, have soredia with a distinct cortex. New species are: <italic>Buellia arborea</italic> Coppins &amp; Tønsb. (from Norway and Scotland), <italic>Fuscidea arboricola</italic> Coppins &amp; Tønsb. (from Norway, Sweden, and Scotland), <italic>F. pusilla</italic> Tønsb. (from Norway, Sweden, and Scotland), <italic>Lecanora flavoleprosa</italic> Tønsb. (from Norway and Austria), <italic>L. flavopunctata</italic> Tønsb. (from Norway and Sweden), <italic>L. norvegica</italic> Tønsb. (from Norway), <italic>Lecidea gyrophorica</italic> Tønsb. (syn. <italic>L. epizanthoidiza</italic> auct., non Nyl.), <italic>L. praetermissa</italic> Tønsb. (from Norway and Sweden), <italic>L. subcinnabarina</italic> Tønsb. (from Norway), <italic>L. vacciniicola</italic> Tønsb. (from Norway, Sweden, and Spain), <italic>Lecidella subviridis</italic> Tønsb. (from Norway and Sweden), <italic>Lepraria elobata</italic> Tønsb. (from Norway), <italic>L. jackii</italic> Tønsb. (from Norway), <italic>L. obtusatica</italic> Tønsb. (from Norway), <italic>L. umbricola</italic> Tønsb. (from Norway, England, and Scotland), <italic>Micarea coppinsii</italic> Tønsb. (from Norway and Scotland), <italic>Rinodinaflavosoralifera</italic> Tønsb. (from Norway), <italic>R. disjuncta</italic> Sheard &amp; Tønsb. (from Norway and the pacific coast of U.S.A. and Canada), and <italic>Schaereria corticola</italic> Muhr &amp; Tønsb. (from Norway, Sweden and Scotland). <italic>Ochrolechia androgyna</italic> s. lat. is shown to comprise at least four distinct species.
New combinations are: <italic>Cliostomum leprosum</italic> (Räsänen) Holien &amp; Tønsb., <italic>Lepraria rigidula</italic> (B. de Lesd.) Tønsb., <italic>Mycoblastus caesius</italic> (Coppins &amp; P. James) Tønsb., <italic>Placynthiella dasaea</italic> (Stirton) Tønsb., and <italic>Ropalospora viridis</italic> (Tønsb.) Tønsb. <italic>Lecidea turgidula</italic> var. <italic>pulveracea</italic> Fr. is raised to specific level with the new name <italic>Lecidea leprarioides</italic> Tønsb. <italic>Mycoblastus sterilis</italic> Coppins &amp; P. James is reduced to synonymy with <italic>M. fucatus</italic> Stirton.
<italic>Pertusaria borealis</italic> is new to Europe. <italic>Halecania viridescens, Lecanora farinaria, Lepraria caesioalba</italic> Laundon ined., <italic>L. eburnea</italic> Laundon ined., <italic>Megalospora tuberculosa, Opegrapha multipuncta,</italic> and <italic>Scoliciosporum gallurae</italic> are new to Scandinavia. <italic>Mycoblastus caesius, Lecidella elaeochroma</italic> “f. <italic>soralifera”, L. flavosorediata, Micarea granulans</italic> (saxicolous, not treated), <italic>Opegrapha sorediifera,</italic> and <italic>Rinodina degeliana</italic> are new to Norway.
In some cases, Poelt’s species pair concept can be applied to this group of lichens. Additional secondary substances, not occurring in the primary species, sometimes occur in the soralia of the secondary species. In this case, presence of the additional substance cannot be regarded as an independent taxonomic character, and the species pair concept is still useful. However, morphologically indistinguishable specimens with different chemistry may represent different secondary species.
The term consoredia is introduced to denote diaspores composed of aggregated soredia.
</abstract>

The sorediate and isidiate, corticolous, crustose lichens in Norway

<abstract>
<title style='display:none'>Abstract</title>
Swamp forests dominated by <italic>Picea abies</italic> contribute strongly to the total plant species richness in boreal forests. The variation in species composition and environmental conditions in swamp forests and the relationships of swamp forests to mires and upland forest, have, however, remained insufficiently known. From a preliminary survey of 57 spruce swamp forests, eleven localities were selected to represent the variation in the study area with respect to size and nutrient status, and altitude and position in the landscape. Physiographic and hydrotopographic descriptions were made. A total of 150 1-m2 plots were distributed on the localities by a restricted random procedure. In each plot, the abundance of all vascular plants, bryophytes and macrolichens was recorded as frequency in 16 subplots, 53 variables (topographic and geographic, tree influence, water-table, water chemical and physical, and soil chemical and physical) were measured. The gradient ( coenocline) structure of vegetation was found by parallel DCA and LNMDS ordinations, interpreted ecologically by analysis of correlations and geostatistical patterns. The two main coenoclines were the same for the full species composition and for vascular plant and cryptogams considered separately. The first gradient was related to soil acidity and nutrient concentrations: plots segregated into relatively poor (and intermediate) and richer swamp forests. Nitrogen availability is considered a decisive factor for species’ responses to this gradient. The second gradient was related to depth to the water table and mesotopographic relief of the swamp-forest surface, varying mostly on fine (0.75-1.5 m) scales. Vascular plants segregate along this gradient due to a trade-off between tolerances to waterlogging and drought, bryophyte are influenced by a complex set of factors. Two minor vegetation gradients were also found; one related to microtopography (extending from flat, lawn-like areas dominated by large bryophytes to more strongly sloping sites dominated by small mosses and hepatics; ‘pocket species’) and one weakly related to the annual water-table amplitude. Relatively strong coenoclines were found that separated entire swamp forests but were uncorrelated with measured variables. These occurred because all swamp forests, notably the richer, had a strong element of uniqueness in species composition, probably because species are recruited from a large species pool during thousands of years. Swamp forest is proposed as a broad term for all peatlands with trees, including mire margin, from which it is essentially indistinguishable. Similarities with, and differences from, open mire and forest on mineral soil are discussed. Some unique features of swamp forests are pointed out. A classification of swamp forests into eight site-types by division of the two main gradients is proposed. Descriptions are provided for the six site-types encountered in the study area. All intact richer swamp forests and a representative selection of poor swamp forests should be protected if maintenance of the biological diversity of (coniferous) forests in general, and swamp forests in particular, is aimed at.
</abstract>

Vegetation-environment relationships of boreal spruce swamp forests in Østmarka Nature Reserve, SE Norway

<abstract>
<title style='display:none'>Abstract</title>
The understory vegetation (vascular plants, bryophytes and lichens) in an area dominated by boreal coniferous forests is subjected to detailed ecological analysis. Two hundred meso sample plots (1 m2) are used as basis for vegetation sampling, and provided with measurements of 33 environmental variables. Species abundance is recorded as frequency in 16 subplots. Parallel DCA and 2-dimensional LNMDS ordinations of meso sample plots were largely identical, both provided two coenocline axes interpretable in ecological terms. The first axis is interpreted as the response to a broad-scale topographical complex-gradient, made up of two independent complex-gradients; (1) a topography-soil depth complex-gradient in the pine forest (running from lichen-rich pine forests to submesic <italic>Vaccinium myrtillus-dominated</italic> spruce forests), and (2) a complex-gradient in soil nutrient status in the spruce forest. The second axis, mainly affecting the species composition of the bottom layer, is interpreted as a fine-scale paludification gradient. The causes of variation along these gradients are discussed: Desiccation tolerance is considered to act directly on the physiology of vascular plant species, setting their limits towards xeric sites. Similarly, cryptogams with optima in the more mesic sites are considered to be excluded from drier sites by physiological tolerance. Limits of cryptogams towards more mesic sites are, however, considered to be set by competitive ability (growth rates) in accordance with the competitive hierarchy theory. N availability is assumed to be the most important factor for differentiation of vascular plants along the nutrient gradient, while bryophytes are expected to respond to a complex of factors, including structural properties of the humus layer. Increasing N accumulation in the humus towards xeric sites may indicate oversaturation due to deposition of airborne NO3- or NH&gt;4+. Fine-scale paludification, mainly of a soligenous type, occurred in sloping terrain with shallow soil. The cryptogams apparently make up a competitive hierarchy also along the paludification gradient. No other coenoclines could be identified by analysis of 0.0625 m2 micro sample plots, most probably because the response of vegetation to micro-scale environmental gradients (probably most important: the variation in microtopography) not essentially different from the meso-scale gradients, and because the importance of random processes increase towards finer scales. Structuring processes are discussed with reference to the observed patterns. The lack of a closed bottom layer in almost all sample plots is considered a strong indication of high importance of fine-scale disturbance and density-independent mortality in the investigated system, while interspecific competition is of lower importance. The methodology in vegetation ecological studies is discussed with particular reference to monitoring. The potential of an integrated concept using permanent plots, parallel investigation of vegetation and environmental parameters, and gradient analysis, is stressed. Several suggestions for future studies, based on this integrated approach, are made.
</abstract>

Vegetation-environment relationships of boreal coniferous forests in the Solhomfjell area, Gjerstad, S Norway

<abstract>
<title style='display:none'>Abstract</title>
Vegetational and environmental monitoring of boreal spruce forest was initiated in 1988, as a part of the programme “Contrywide Monitoring of Forest Health” at the Norwegian Institute of Land Inventory (NIJOS). As a basis for monitoring, relationships between trees, understory vegetation and environmental conditions (vertical relationships) were analysed for each of ten reference areas. The reference areas were selected to span regional gradients, in climatic conditions and deposition of airborne pollutants, in old-growth, so-called “bilberry-dominated”, “small-fem” and “low-herb”, also paludified, spruce forests south of the Polar Circle. Fifty 1-m2 meso sample plots, randomly chosen within ten 50-m2 macro sample plots in each reference area, were subjected to vegetation analysis, using frequency in subplots as species abundance measure. Environmental (including soil chemical) and tree parameters were recorded for meso as well as macro sample plots.
The main vegetational gradients were found by parallel use of DCA and LNMDS ordination methods and subjected to environmental interpretation, mainly by means of non-parametric correlation analyses. DCA and LNMDS in most cases revealed the same main gradients in vegetation, but outliers were more frequent in LNMDS ordinations, due to higher vulnerability of this method to plots with deviating number of species. A complex-gradient in nutrient conditions, with pH and the concentration of nitrogen as the most constantly contributing variables, but with considerable between-area variation with respect to important cations, was evident in nine reference areas. Soil moisture varied along the second vegetational gradient in most areas. In the three most humid reference areas, the Ca concentration was related to variation in soil moisture and gradients from below to between trees, while unrelated or inversely related to the same vegetational gradient as pH. Species abundances were plotted on plot positions in DCA ordinations in order to summarize the species· responses to environmental variation in each area.
Variation in vegetation in the total data set (500 meso sample plots) was partitioned onto two sets of explantory variables (environmental and climatic/geographical) by use of CCA, in order to find the relative importance of environmental and climatic/geographical variation. The fraction of variation exclusively explained by environmental variables was about 1 7%, while only 5% of the variation was explained exclusively by climatic variables. The variation shared by both sets of variables was about 8%.
The main vegetational gradients and environmental/climatic/geographical complex-gradients in the total data set were found by DCA and subsequent interpretation of axes. The main complex-gradients found by separate analyses of data from each reference area, were reflected along the DCA axes in total ordinations, but differences between areas with respect to positions along both environmental and climatic/geographical gradients were also evident.
Meso plot occurrences of selected species were plotted in a DCA ordination of the total data set, with variation exclusively due to climatic/geographical variables removed, in order to express regional similarities and differences in the species· responses to the environment. The different patterns of species· distributions in the DCA ordination were discussed in the light of their use as indicators of specified environmental conditions.
</abstract>

Vegetation-environment relationships of boreal spruce forests in ten monitoring reference areas in Norway

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The Journal of Natural History Museum and University of Oslo

 Contains monographs in plant taxonomy, phytogeography, plant ecology, plant morphology, evolutionary botany. Archiving  Sciendo archives the...

 Contains monographs in plant taxonomy, phytogeography, plant ecology, plant morphology, evolutionary botany. Archiving...

AHEAD OF PRINT

Volume 40 (2022): Issue 1 (December 2022)

Volume 39 (2019): Issue 1 (January 2019)

Volume 38 (2018): Issue 1 (October 2018)

Volume 37 (2014): Issue 1 (April 2014) Multiple parallel ordinations: the importance of choice of ordination method and weighting of species abundance data, Editor: Vegar Bakkestuen

Volume 36 (2013): Issue 1 (April 2013) A strict maximum likelihood explanation of MaxEnt, and some implications for distribution modelling, Editor: Vegar Bakkestuen

Volume 35 (2012): Issue 1 (December 2012) A gradient analytic perspective on distribution modelling, Editor: Vegar Bakkestuen

Volume 34 (2010): Issue 1 (April 2010) Vegetation composition, gradients and environment relationships of birch forest in six reference areas in Norway,
Editor: R. H. Økland

Volume 33 (2009): Issue 1 (December 2009) The lichen flora of Svalbard, Editor: R. H. Økland

Volume 32 (2008): Issue 1 (November 2008) Gradients analyses of forests ground vegetation and its relationships to environmental variables in five subtropical forest areas, S and SW China,
Editors: K. Høiland and R. H. Økland