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Abstract. The relationship between mean Ellenberg indicator values (IV) per vegetation relevé and environmental parameters measured in the field usually shows a large variation. We tested the hypothesis that this variation is caused by bias dependent on the phytosociological class. For this purpose we collected data containing vegetation relevés and measured soil pH (3631 records) or mean spring groundwater level (MSL, 1600 records). The relevés were assigned to vegetation types by an automated procedure. Regression of the mean indicator values for acidity on soil pH and the mean indicator values for moisture on MSL gave percentages explained variance similar to values that were reported earlier in literature. When the phytosociological class was added as an explanatory factor the explained variance increased considerably. Regression lines per vegetation type were estimated, many of which were significantly different from each other. In most cases the intercepts were different, but in some cases their slopes differed as well. The results show that Ellenberg indicator values for acidity and moisture appear to be biased towards the values that experts expect for the various phytosociological classes. On the basis of the results, we advise to use Ellenberg IVs only for comparison within the same vegetation type.

Question: The use of expert-based indicator values to estimate abiotic conditions from vegetation is widespread. However, recent research has shown that expert judgement may contain considerable bias and thereby introduces a large amount of uncertainty. Could expert based indicator values be replaced by indicator values based on field measurements? Location: Europe. Methods: We developed a method to estimate species response based on measured physical data, and a method to predict abiotic conditions from the vegetation composition using these responses. This method was tested for soil pH. Results: We were able to estimate the pH response of 556 species of the Dutch flora. Ca. 20% of the responses were, at least, bimodal and many responses had a very wide range. The simplest method ('raw mean') yielded the best prediction of pH; the indicator value of a species is the mean of the soil pH values of the sites where it was observed. A list of all rawmean estimates per species is given. The predicted pH of a new site is the mean of the indicator values of the present species. The estimated species responses were validated on independent Dutch and European data sets. Older successional stages seem to be predicted better than younger stages. Conclusions: Our method performed better than the popular Ellenberg indicator system for the Dutch data set, while being just as easy to use, because it only needs a single value per species. We foresee that, when more data become available, our method has the potential to replace the Ellenberg system.

Background In 1994, a "Pan-European Programme for Intensive and Continuous Monitoring of Forest Ecosystems" started to contribute to a better understanding of the impact of air pollution, climate change and natural stress factors on forest ecosystems. The programme today counts approximately 760 permanent observation plots including near 500 plots with data on both air quality and forest ecosystem impacts. Scope This paper first presents impacts of air pollution and climate on forests ecosystems as reported in the literature on the basis of laboratory and field research. Next, results from monitoring studies, both at a European wide scale and related national studies, are presented in terms of trends and geographic variations in nitrogen and sulphur deposition and ozone concentrations and the impacts of those changes in interaction with weather conditions on (i) water and element budgets and nutrient-acidity status, (ii) forest crown condition, (iii) forest growth and carbon sequestration and (iv) species diversity of the ground vegetation. The empirical, field based forest responses to the various drivers are evaluated in view of available knowledge.Conclusions Analyses of large scale monitoring data sets show significant effects of atmospheric deposition on nutrient-acidity status in terms of elevated nitrogen and sulphur or sulphate concentrations in forest foliage and soil solution and related soil acidification in terms of elevated aluminium and/or base cation leaching from the forest ecosystem. Relationships of air pollution with crown condition, however, appear to be weak and limited in time and space, while climatic factors appear to be more important drivers. Regarding forest growth, monitoring results indicate a clear fertilization effect of N deposition on European forests but the field evidence for impacts of ambient ozone exposure on tree growth is less clear.

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