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A. GyalusInstitute of Ecology and Botany, Centre for Ecological Research, ELKH H-2163 Vácrátót, Alkotmány u. 2–4, Hungary

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S. BarabásInstitute of Ecology and Botany, Centre for Ecological Research, ELKH H-2163 Vácrátót, Alkotmány u. 2–4, Hungary

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B. BerkiInstitute of Ecology and Botany, Centre for Ecological Research, ELKH H-2163 Vácrátót, Alkotmány u. 2–4, Hungary

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Z. Botta-DukátInstitute of Ecology and Botany, Centre for Ecological Research, ELKH H-2163 Vácrátót, Alkotmány u. 2–4, Hungary

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M. KabaiInstitute of Ecology and Botany, Centre for Ecological Research, ELKH H-2163 Vácrátót, Alkotmány u. 2–4, Hungary

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A. LengyelInstitute of Ecology and Botany, Centre for Ecological Research, ELKH H-2163 Vácrátót, Alkotmány u. 2–4, Hungary

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B. LhotskyInstitute of Ecology and Botany, Centre for Ecological Research, ELKH H-2163 Vácrátót, Alkotmány u. 2–4, Hungary

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A. CsecseritsInstitute of Ecology and Botany, Centre for Ecological Research, ELKH H-2163 Vácrátót, Alkotmány u. 2–4, Hungary

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New plant trait measurements collected during the field sampling in Pannonian sandy grasslands in Hungary and Serbia are presented. Selected traits include canopy height, leaf area (LA), specific leaf area (SLA) and leaf dry matter content (LDMC). The leaf area measurement procedures of overlapping, 3-dimensional or otherwise difficult-to-measure leaves and shoots are described in details.

Abstract

New plant trait measurements collected during the field sampling in Pannonian sandy grasslands in Hungary and Serbia are presented. Selected traits include canopy height, leaf area (LA), specific leaf area (SLA) and leaf dry matter content (LDMC). The leaf area measurement procedures of overlapping, 3-dimensional or otherwise difficult-to-measure leaves and shoots are described in details.

Plant traits are plant characteristics that play a role in adapting to the biotic and abiotic environment and can be measured at the level of individuals (Violle et al. 2007). The trait-based approach is an efficient tool in a wide range of research, as it is used in agricultural sciences (e.g. Abalos et al. 2019), community ecology (e.g. Schöb et al. 2017), evolutionary biology (e.g. Santangelo et al. 2019), restoration ecology (e.g. Halassy et al. 2019) and the studies dealing with ecosystem services (e.g. Cresswell et al. 2019). However, while trait databases are steadily growing, continuous intraspecific variation is underrepresented (Kattge et al. 2020), and there is evidence that it should be considered in analyses (e.g. Carmona et al. 2019, Read et al. 2017).

Hereby, we publish canopy height, leaf area (LA), specific leaf area (SLA) and leaf dry matter content (LDMC) records measured from 2016 to 2019 in Hungary and Serbia. The dataset can be divided into two categories based on the purpose of collection: (1) Ágasegyháza project: data collected for an ongoing project to explore the role of intraspecific variation within communities, covering the spectrum from sandy grasslands to oligotrophic wet meadows; (2) Traits of Pannonian grassland species: data of species and/or locations underrepresented in the global trait databases, e.g. TRY (Kattge et al. 2020). The Ágasegyháza project involves 93 plots and 217 species from two meadows and sandy grasslands near Ágasegyháza village (Hungary), while the other collection covers 101 species from 15 locations, in Hungary and Serbia.

During the field and the laboratory measurements, we followed the standard protocols of the LEDA database (Kleyer et al. 2008, Knevel et al. 2003) and the suggestions of Cornelissen et al. (2003). We measured the canopy height (i.e. the height of the vegetative part of the plant) of 5 to 30 randomly selected, robust, well-grown individuals of the species per location. To measure the SLA, LA and LDMC, we collected two mature and intact leaves per individual, altogether from at least ten individuals, for laboratory measurements. In the case of leafless plants (Ephedra distachya, Equisetum ramosissimum) or plants where the photosynthetic activity of the stem is comparable to that of the leaves (Corispermum leptopterum, Eleocharis uniglumis), a young shoot was collected. The fresh weight of the whole leaves (in most cases, including petiole and rachis; for details, see Appendix 3) were measured after 12-hour-long rehydration. Then we scanned the leaves at 400 DPI and calculated their projected area from the raster image using Lafore analysing software (free software by Veiko Lehsten (s.d.), University of Oldenburg). In the case of rolled-up leaves (e.g. Festuca pseudovina) or shoots (e.g. Equisetum ramosissimum) we calculated the upper half of the circumference by multiplying the projected area by pi / 2. In case of Poa pratensis and Stipa capillata, where some leaves were folded in half, we multiplied their area by 2. In case of Fumana procumbens, where the leaf shape is approximately half-cylinder, projected areas were multiplied by pi / 4 + 0.5. In the case of Syrenia cana, where the leaf shape is closest to a triangular prism, projected areas were multiplied by 1.5.

In the case of Achillea asplenifolia and Achillea collina – which have a complex, tile-like leaf structure, impossible to project into 2-dimensional space without overlaps –, we approximated real leaf area by calibration. From both species, we selected three different sized leaves, and first scanned and calculated the projected area in the usual way. Then, we severed the leaflets of each leaf from their rachis by forceps, and scanned them again without overlaps to get the whole area of the disassembled leaves. We fitted a function with the intact leaf measures on the x-axis and their disassembled measures on the y-axis; the best fitting model was the linear function with zero intercept. After that, we estimated the real leaf area of the other individuals with this linear equation. We found only a negligible difference between intact and teared up measures in the case of Achillea asplenifolia; probably because their leaflets are sparsely placed, preventing overlap. Thus we used the linear equation method only at A. collina.

After the scanning process, leaves were dried in oven at 60°C for 72 hours, and then we measured their dry mass. For calculating SLA, the one-sided area of the fresh leaves (LA) was divided by their oven-dry mass; for calculating LDMC we divided their dry mass by their fresh weight. For more information and the datasets, see the Digital supplements 1–4. The species nomenclature follows Király (2009).

Acknowledgements

This research was supported by the National Research, Development and Innovation Office (K124671, FK128465, PD123997) grants. We thank Tamás Rédei for his help in field sampling design, field sampling and species determination.

Author contributions

Zoltán Botta-Dukát formulated the idea of trait sampling, Barbara Lhotsky and Anikó Csecserits designed a part of the field sampling, Boglárka Berki, Sándor Barabás, Anikó Csecserits, Adrienn Gyalus, Melinda Kabai, Attila Lengyel and Barbara Lhotsky collaborated during field sampling and species determination, Boglárka Berki, Sándor Barabás, Anikó Csecserits, Adrienn Gyalus, Melinda Kabai and Barbara Lhotsky collaborated during the lab work, Adrienn Gyalus wrote the manuscript, Anikó Csecserits and Zoltán Botta-Dukát helped during the writing.

Electronic supplements

Appendix 1, Appendix 2, Appendix 3, and Appendix 4.

References

  • Abalos, D., van Groenigen, J. W., Philippot, L., Lubbers, I. M. and De Deyn, G. B. (2019): Plant trait-based approaches to improve nitrogen cycling in agroecosystems.–J. Appl. Ecol. 56(11): 24542466.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carmona, C. P., de Bello, F., Azcárate, F. M., Mason, N. W. H. and Peco, B. (2019): Trait hierarchies and intraspecific variability drive competitive interactions in Mediterranean annual plants.–J. Ecol. 107: 20782089.

    • Crossref
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  • Cornelissen, J. H. C., Lavorel, S., Garnier, E., Díaz, S., Buchmann, N., Gurvich, D. E., Reich, P. B., ter Steege, H., Morgan, H. D., van der Heijden, M. G. A., Pausas, J. G. and Poorter, H. (2003): A handbook of protocols for standardised and easy measurement of plant functional traits worldwide.–Aust. J. Bot. 51: 335380.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cresswell, C., Cunningham, H., Wilcox, A. and Randall, N. (2019): A trait-based approach to plant species selection to increase functionality of farmland vegetative strips.–Ecol. Evol. 9: 45324543.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Halassy, M., Botta-Dukát, Z., Csecserits, A., Szitár, K. and Török, K. (2019): Trait-based approach confirms the importance of propagule limitation and assembly rules in old-field restoration.–Restor. Ecol. 27: 840849.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kattge, J., Bönisch, G., Diaz, S., Lavorel, S., Prentice, I., Leadley, P., Tautenhahn, S., Werner, G., Aakala, T., Abedi, M., Acosta, A., Adamidis, G., Adamson, K., Ryo, M., Albert, C., Alcántara, J., Alcázar C, C., Aleixo, I., Ali, H. and Wirt, C. (2020): TRY plant trait database–enhanced coverage and open access.–Glob. Change Biol. 26: 119188.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Király, G. (ed.) (2009): Új Magyar Füvészkönyv. Magyarország hajtásos növényei. Határozókulcsok. [New Hungarian Herbal. The vascular plants of Hungary. Identification keys]. – Aggtelek National Park Directorate, Jósvafő, 616 pp.

    • Search Google Scholar
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  • Kleyer, M., Bekker, R. M., Knevel, I. C., Bakker, J. P., Thompson, K., Sonnenschein, M. et al. (2008): The LEDA Traitbase: a database of life-history traits of the Northwest European flora.–J. Ecol. 96: 12661274.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Knevel, I. C., Bekker, R. M., Bakker, J. P. and Kleyer, M. (2003): Life-history traits of the Northwest European flora: the LEDA database.–J. Veg. Sci. 14(4): 611614.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lehsten, V. (s.d.): Lafore: Calculating leaf area, leaf width and length from ordinary scans. – https://uol.de/en/landeco/download-and-service/software/lafore

    • Search Google Scholar
    • Export Citation
  • Read, Q. D., Henning, J. A. and Sanders, N. J. (2017): Intraspecific variation in traits reduces ability of trait-based models to predict community structure.–J. Veg. Sci. 28(5): 10701081.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Santangelo, J. S., Thompson, K. A. and Johnson, M. T. (2019): Herbivores and plant de-fences affect selection on plant reproductive traits more strongly than pollinators.–J. Evol. Biol. 32(1): 418.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schöb, C., Macek, P., Piston, N., Kikvidze, Z. and Pugnaire, F. I. (2017): A trait-based approach to understand the consequences of species plant interactions for community structure.–J. Veg. Sci. 28(4): 696704.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Violle, C., Navas, M. L., Vile, D., Kazakou, E., Fortunel, C., Hummel, I. and Garnier, E. (2007): Let the concept of trait be functional!Oikos 116(5): 882892.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Abalos, D., van Groenigen, J. W., Philippot, L., Lubbers, I. M. and De Deyn, G. B. (2019): Plant trait-based approaches to improve nitrogen cycling in agroecosystems.–J. Appl. Ecol. 56(11): 24542466.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carmona, C. P., de Bello, F., Azcárate, F. M., Mason, N. W. H. and Peco, B. (2019): Trait hierarchies and intraspecific variability drive competitive interactions in Mediterranean annual plants.–J. Ecol. 107: 20782089.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cornelissen, J. H. C., Lavorel, S., Garnier, E., Díaz, S., Buchmann, N., Gurvich, D. E., Reich, P. B., ter Steege, H., Morgan, H. D., van der Heijden, M. G. A., Pausas, J. G. and Poorter, H. (2003): A handbook of protocols for standardised and easy measurement of plant functional traits worldwide.–Aust. J. Bot. 51: 335380.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cresswell, C., Cunningham, H., Wilcox, A. and Randall, N. (2019): A trait-based approach to plant species selection to increase functionality of farmland vegetative strips.–Ecol. Evol. 9: 45324543.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Halassy, M., Botta-Dukát, Z., Csecserits, A., Szitár, K. and Török, K. (2019): Trait-based approach confirms the importance of propagule limitation and assembly rules in old-field restoration.–Restor. Ecol. 27: 840849.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kattge, J., Bönisch, G., Diaz, S., Lavorel, S., Prentice, I., Leadley, P., Tautenhahn, S., Werner, G., Aakala, T., Abedi, M., Acosta, A., Adamidis, G., Adamson, K., Ryo, M., Albert, C., Alcántara, J., Alcázar C, C., Aleixo, I., Ali, H. and Wirt, C. (2020): TRY plant trait database–enhanced coverage and open access.–Glob. Change Biol. 26: 119188.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Király, G. (ed.) (2009): Új Magyar Füvészkönyv. Magyarország hajtásos növényei. Határozókulcsok. [New Hungarian Herbal. The vascular plants of Hungary. Identification keys]. – Aggtelek National Park Directorate, Jósvafő, 616 pp.

    • Search Google Scholar
    • Export Citation
  • Kleyer, M., Bekker, R. M., Knevel, I. C., Bakker, J. P., Thompson, K., Sonnenschein, M. et al. (2008): The LEDA Traitbase: a database of life-history traits of the Northwest European flora.–J. Ecol. 96: 12661274.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Knevel, I. C., Bekker, R. M., Bakker, J. P. and Kleyer, M. (2003): Life-history traits of the Northwest European flora: the LEDA database.–J. Veg. Sci. 14(4): 611614.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lehsten, V. (s.d.): Lafore: Calculating leaf area, leaf width and length from ordinary scans. – https://uol.de/en/landeco/download-and-service/software/lafore

    • Search Google Scholar
    • Export Citation
  • Read, Q. D., Henning, J. A. and Sanders, N. J. (2017): Intraspecific variation in traits reduces ability of trait-based models to predict community structure.–J. Veg. Sci. 28(5): 10701081.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Santangelo, J. S., Thompson, K. A. and Johnson, M. T. (2019): Herbivores and plant de-fences affect selection on plant reproductive traits more strongly than pollinators.–J. Evol. Biol. 32(1): 418.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schöb, C., Macek, P., Piston, N., Kikvidze, Z. and Pugnaire, F. I. (2017): A trait-based approach to understand the consequences of species plant interactions for community structure.–J. Veg. Sci. 28(4): 696704.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Violle, C., Navas, M. L., Vile, D., Kazakou, E., Fortunel, C., Hummel, I. and Garnier, E. (2007): Let the concept of trait be functional!Oikos 116(5): 882892.

    • Crossref
    • Search Google Scholar
    • Export Citation
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