Erik Aude

Cryptogam communities on decaying deciduous wood – does tree species diversity matter?

Abstract.Bryophyte and fungal communities were investigated on fallen trees representing seven deciduous tree species in a mixed near natural nemoral forest. Bryophytes were represented by 41 taxa, including several very frequent species. Of the 296 fungal species, most were recorded with very low frequency and the share of high frequent species was much lower than among the bryophytes. Species turnover was bigger in the fungal communities, compared to the bryophyte communities, and related to a higher extent to measured differences in environmental conditions. Tree species diversity was found to be an important factor for fungal species composition, while only small differences in bryophyte species composition were found between the different tree species. On the other hand bryophyte species richness showed distinct relations to tree species and microclimatic variables, a tendency which was not evident for fungal diversity. It is concluded that the two organism groups to some extent differ in their conservation demands. Thus, conservation of wood-inhabiting bryophytes requires prioritising of large, coherent forest stands in which a stable humid microclimate and a reasonable supply of dead wood is secured. Successful conservation of fungi requires that substantial amounts of dead wood are left for natural decay in a variety of natural forest environments representing different tree species, so that heterogeneity in dead wood types is secured.

Vegetation diversity of conventional and organic hedgerows in Denmark

Abstract Many attempts have been made to reduce the impact of modern conventional farming on the environment and semi-natural ecosystems. One of them is organic farming, known primarily for the absence of pesticides and artificial fertilisers. The objective of this study was to study and test the differences in the spontaneous vegetation of comparable hedgerows in the same area situated within organic and conventional farming systems. The hedge bottom vegetation was surveyed during August 2001 in 13 hedgerows of each farming system. Farming type had not changed on either side of the hedgerows for the lifetime of the hedges (10–14 years). Sampling was associated with a set of 16 measured environmental variables. In the two farming systems hedgerows were comparable in terms of landscape, age, soil type, nutrient status and width. A mixed analysis of variance (ANOVA) found no significant difference in measured soil and radiation variables between farming types. Farming types only differed in the use of pesticides. Significant differences between farming types in plant species diversity at alpha, beta and gamma levels were found. More species that are normal in semi-natural habitats were found on organic farms. There was an overlap in species composition between farming type, but a slightly higher species turnover on conventional farms. The ordination axes were highly correlated with calibrated Ellenberg values of fertility, light and soil moisture. Soil fertility and farming type were important factors to explain variation in species composition. Organic farming had a significantly reduced impact on hedge bottom vegetation compared to conventional farming. Higher extinction due to pesticide drift and immigration rates may be responsible for the significantly higher species diversity and different species composition in hedges on organic farms. The differences in species diversity and plant types are briefly discussed.

Influence of management on the species composition of epiphytic cryptogams in Danish Fagus forests

. The purpose of this study is to evaluate and to quantify the influence of management on the epiphytic species composition in Danish Fagus sylvatica forests. Trunks were chosen at random within selected blocks in both managed and unmanaged Fagus stands.117 trunks in 43 sample plots in three forests were investigated. Cover was estimated for 72 lichens, 29 bryophytes and two fungi on vertical trunks 0.3 -2 m above ground. 18 explanatory variables were recorded and arranged in three groups: eight management-related variables, six micro-climatic- and soil variables, and four geographical- and geological variables. Canonical Correspondence Analysis was used to test and to quantify the explaining power of the three groups of variables applying the variation partitioning approach. Detrended Correspondence Analysis was used to evaluate whether important gradients were ignored. It was concluded that the traditional ‘shelterwood uniform system’ used in Fagus forests has a marked influence on the epiphytic species composition. Thus, management-related variables explained more than one third of the total variation explained, which equals 10.9% of the total variation. Microclimatic and soil variables explained 9.0%, and geographical and geological variables explained 6.0%. The following three recommendations are suggested to reduce the significant influence of management on the epiphytic species composition. First, it should be attempted to ensure a continuous occurrence of some big trees per ha to be left for natural death and decomposition. Second, regular thinning is necessary, especially in the first part of rotation. Third, a multi-layered forest, where wind and desiccation effects are minimized, is recommended.

Developing a classifier for the Habitats Directive grassland types in Denmark using species lists for prediction

Abstract This paper describes the use of supervised methods for the classification of vegetation. The difference between supervised classification and clustering is outlined, with reference to their current use in vegetation science. In the paper we describe the classification of Danish grasslands according to the Habitats Directive of the European Union, and demonstrate how a supervised classification can be used to achieve a standardized and statistical interpretation within a local flora. We thereby offer a statistical solution to the legal problem of protection of certain selected habitat types. The Habitats Directive protects three types of Danish grassland habitats, whereas two remaining types fall outside protection. A classification model is developed, using available Danish grassland data, for the discrimination of these five types based on their species composition. This new Habitats Directive classification is compared to a previously published unsupervised classification of Danish grassland vegetation. An indicator species analysis is used to find significant indicator species for the three protected habitat types in Denmark, and these are compared to the characteristic species mentioned in the interpretation manual of the Habitats Directive. Eventually, we discuss the pros and cons of supervised and unsupervised classification and conclude that supervised methods deserve more attention in vegetation science. Abbreviations: DCA = Detrended Correspondence Analysis; CCA = Canonical Correspondence Analysis; CVA = Canonical Variates Analysis; HD = Habitats Directive; TWINSPAN = Two-way indicator species analysis. Nomenclature: Tutin et al. (1964–1993).

PREDICTION OF HABITAT QUALITY USING ORDINATION AND NEURAL NETWORKS

The development of an automatic classification model for prediction of con- servation value is described. The classifier combines ordination and neural network (NN). The classifier was trained to predict the probability of a sample being of potential conser- vation interest. The neural network was trained on a priori classified data and used sample scores derived from ordination for prediction. The complexity of the NN classifier and the selection of the optimal ordination method were guided by cross-validation of a series of candidate models. The conservation value of a test data set was predicted by the NN classifier, and this classification was evaluated in terms of species richness, nativeness, rarity, and P diversity. Finally, we evaluated the capability of the approach to handle new samples not included in the ordination. These samples were derived from habitats of threatened vascular plants, and they were all successfully predicted to be valuable. It is shown that the combination of ordination and neural networks successfully repro- duces the a priori classification. It is further demonstrated on a test data set which the classifier discriminates with respect to traditional measures of conservation interest such as rarity, nativeness, and diversity. The developed method may be seen as a promising approach to assessment of biological integrity at the scale of plant communities, and further opportunities for its application are suggested.

Changing Course of Secondary Succession in Abandoned Sandy Fields

The vegetation of abandoned arable fields on dry sandy soils was investigated in 1986 and again in 2000. Comparison of the two data sets by ordination, calibration based on indicator values, and statistical modelling revealed that the vegetation in 2000 differed significantly from the vegetation in 1986. Part of this difference could be explained by field age, but significant difference remained after correction for age. The analysis showed that species indicating nutrient-rich and acidic conditions were more abundant in the 2000 samples than expected from the age of the fields. Possible causes for the observed differences are discussed, and the role of airborne nitrogen deposition and landscape changes is emphasised. Changing course of successional processes may place serious constraints on future habitat restoration.

Dataset on species incidence, species richness and forest characteristics in a Danish protected area

The data presented in this article are related to the research article entitled “Restoring hydrology and old-growth structures in a former production forest: Modelling the long-term effects on biodiversity” (A. Mazziotta, J. Heilmann-Clausen, H. H.Bruun, Ö. Fritz, E. Aude, A.P. Tøttrup) [1]. This article describes how the changes induced by restoration actions in forest hydrology and structure alter the biodiversity value of a Danish forest reserve. The field dataset is made publicly available to enable critical or extended analyses.