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This version available http://nora.nerc.ac.uk/8737/ NERC has developed NORA to enable users to access research outputs wholly or partially funded by NERC. Copyright and other rights for material on this site are retained by the authors and/or other rights owners. Users should read the terms and conditions of use of this material at http://nora.nerc.ac.uk/policies.html#access This document is the author's final manuscript version of the journal article, incorporating any revisions agreed during the peer review process. Some differences between this and the publisher's version remain. You are advised to consult the publisher's version if you wish to cite from this article. www.esajournals.orgContact CEH NORA team at noraceh@ceh.ac.ukThe NERC and CEH trade marks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. Field observations and experimental data of effects of nitrogen (N) deposition on plant species 2 diversity have been used to derive empirical critical N loads for various ecosystems. The great 3 advantage of such as approach is the inclusion of field evidence, but there are also restrictions, 4 such as the absence of explicit criteria regarding significant effects on the vegetation, and the 5 impossibility to predict future impacts when N deposition changes. Model approaches can account 6 for this. In this paper, we review the possibilities of static and dynamic multi-species models in 7 combination with dynamic soil -vegetation models to (i) predict plant species composition as a 8 function of atmospheric N deposition and (ii) calculate critical N loads in relation to a prescribed 9 protection level of the species composition. The similarities between the models are presented, but 10 also several important differences, including the use of different indicators for N and acidity and 11 the prediction of individual plant species versus plant communities. A summary of the strengths 12 and weaknesses of the various models, including their validation status, is given. Furthermore, 13 examples are given of critical load calculations with the model chains and their comparison with 14 empirical critical N loads. We show that linked biogeochemistry-biodiversity models for N have 15 potential for applications to support European policy to reduce N input, but the definition of 16 damage thresholds for terrestrial biodiversity represents a major challenge. There is a also a clear 17 need for further testing and validation of the models against long-term monitoring or long-term 18 experimental datasets and against large-scale survey data. This requires a focused data collection in 19Europe, combing vegetation descriptions with variables affecting the species diversity, such as soil 20 acidity, nutrient status and water availability. Finally, there is a need for adaptation and upscaling of 21 the models beyond the regions for which dose-response relationships have been parameterised, to 22 make them ...

The growth habit of the rosette plant Plantago lanceolata is highly variable, and many vegetative and reproductive traits co‐vary. At one end of the range plants have relatively few but long and erect leaves, form few daughter rosettes, and produce a limited number of large spikes, with relatively heavy seeds. Plants at the other end of the range have the opposite characteristics. This suite of characters was shown to correlate with the height of the vegetation in mid‐summer. The causes for this association between different traits were investigated in different experiments, with the following results: Plants from two contrasting habitats both react strongly to light intensity and the red to far‐red (R/FR) ratio of the ambient light. Light intensity mainly affected plant size, whereas light quality affected the growth habit. Populations differ in their mean response rather than in the level of plasticity (i.e., slope of the reaction norms). Experiments show that genetic factors (population effects), R/FR ratio, and hormone treatments (GA or CCC) have similar effects on morphology, and are largely additive and interchangeable. Ten different populations were grown in a common garden, so that the genetic (clonal) correlation within populations, and their bivariate phenotypic means could be compared. Trait combinations which deviated in the same direction (both higher of both lower than the mean over all populations) on average had positive clonal correlations within populations, whereas combinations which deviated in opposite directions had negative correlations. Artificial selection on leaf length, performed under a high or a low R/FR ratio showed clear responses to selection, with heritabilities around 0.4. Correlated responses were found in many other traits, and genetic correlations were similar to the trait associations for the means of different natural populations. Correlated responses to selection depended on environmental circumstances. Under a high R/FR ratio (sun) evidence for a size/number trade‐off was found for leaf length and leaf number. Under a low R/FR ratio, however, a trade‐off between leaf length and leaf quality was found. In conclusion, the trait associations that are so characteristic for the growth habit in Plantago lanceolata are probably due to differences in hormone levels or activities. Genes and environmental factors affect growth habit in similar ways, by tapping into this regulatory mechanism. In the field, selection can lead to concerted changes in the mean of different traits, but changes in plasticity will be slow.

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In gynodioecious species, male steriles co-occur with hermaphrodites. Usually, the male sterile trait is maternally inherited, hence it is called Cytoplasmic Male Sterility (CMS). Nuclear loci restore male fertility in combination with their 'own' specific cytoplasmic types. In theory, two fitness components are important for the maintenance of this breeding system: a fitness advantage of the male steriles, and costs of restoration. The costs of restoration are alleged negative pleiotropic effects of restorer alleles.In this study the effects of different CMS types on plant performance and the cost of restoration were assessed in two experiments with Plantago lanceolata L. Biomass production differed significantly between the CMS types studied. In order to assess the costs of restoration, hermaphrodites with or without restorer alleles for a CMS type other than its own were compared. The studied restorer alleles caused a reduction in weight per seed, but the number of seeds produced was unaffected. The estimated cost of restoration measured as reduction of seed biomass was 13% for restorer alleles for CMSI. However, in the second experiment no pleiotropic effects of restorer alleles were detected, either because the assumptions for the experimental set-up were not valid or the costs of restoration may not always be expressed.

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Plants from a sun and shade population were grown in two environments differing in the ratio of red to far-red light (R/FR ratio). A low R/FR ratio, simulating vegetation shade, promoted the formation of long, upright-growing leaves and allocation towards shoot growth, whereas a high R/FR ratio had the opposite effects. The increase in plant height under the low R/FR ratio was accompanied by a reduction in the number of leaves. Population differences in growth form resembled the differences between plants grown in different light environments: plants from the shade population had rosettes with long erect leaves, whereas plants from the sun population formed prostrate rosettes with short leaves. Plants from the shade population were more responsive to the R/FR ratio than plants from the sun population: the increases in leaf length, plant height, and leaf area ratio under a low R/FR ratio were larger in the shade population. However, differences in plasticity were small compared to the population difference in growth form itself. We argue that plants do not respond optimally to shading and that developmental constraints might have limited the evolution of an optimal response.

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