# Origin, Conservation, and Restoration of the Threatened European Grassland Ecosystem in the Anthropocene

Grégory Mahy, Thierry Dutoit, Kathrin Kiehl, Armin Bischoff, Péter Török

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Grégory Mahy, Thierry Dutoit, Kathrin Kiehl, Armin Bischoff, Péter Török (Dir.). Origin, Conservation, and Restoration of the Threatened European Grassland Ecosystem in the Anthropocene. Mahy, Grégory; Dutoit, Thierry; Kiehl, Kathrin; Bischoff, Armin; Török, Péter. Frontiers Media SA, pp.5-7, 2024, 978-2-8325-4406-8. 10.3389/978-2-8325-4406-8. hal-04770786

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# Origin, conservation, and restoration of the threatened European grassland ecosystem in the Anthropocene

**Edited by**

Grégory Mahy, Thierry Dutoit, Kathrin Kiehl, Armin Bischoff and Péter Török

**Published in**

Frontiers in Ecology and Evolution
Frontiers in Environmental Science

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ISSN 1664-8714
ISBN 978-2-8325-4406-8
DOI 10.3389/978-2-8325-4406-8

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# Origin, conservation, and restoration of the threatened European grassland ecosystem in the Anthropocene

**Topic editors**

Grégory Mahy — University of Liège, Belgium

Thierry Dutoit — UMR7263 Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), France

Kathrin Kiehl — Osnabrück University of Applied Sciences, Germany

Armin Bischoff — University of Avignon, France

Péter Török — University of Debrecen, Hungary

**Citation**

Mahy, G., Dutoit, T., Kiehl, K., Bischoff, A., Török, P., eds. (2024). *Origin, conservation, and restoration of the threatened European grassland ecosystem in the Anthropocene*. Lausanne: Frontiers Media SA.
doi: 10.3389/978-2-8325-4406-8
Table of
contents

05 **Editorial: Origin, conservation, and restoration of the threatened European grassland ecosystem in the Anthropocene**

Grégory Mahy, Peter Torok, Armin Bischoff, Kathrin Kiehl and
Thierry Dutoit

08 **Why grazing and soil matter for dry grassland diversity: New insights from multigroup structural equation modeling of micro-patterns**

Gabrielle Martin, Anouk Courtial, Alexandre Génin, Hervé Ramone
and Thierry Dutoit

21 **Long-term success of floodplain meadow restoration on species-poor grassland**

Leonhard Sommer, Yves P. Klinger, Tobias W. Donath,
Till Kleinebecker and Sarah Harvolk-Schöning

36 **Positive long-term effects of year-round horse grazing in orchid-rich dry calcareous grasslands—Results of a 12-year study**

Martina Köhler, Annika Schmidt, Norbert Hölzel, Annett Baasch and
Sabine Tischew

48 **Structurally rich dry grasslands – Potential stepping stones for bats in open farmland**

Sophie P. Ewert, Mirjam Knörnschild, Kirsten Jung and
Karl-Heinz Frommolt

63 **Erratum: Structurally rich dry grasslands – Potential stepping stones for bats in open farmland**

Frontiers Production Office

66 **Sowing wildflower meadows in Mediterranean peri-urban green areas to promote grassland diversity**

Mariana P. Fernandes, Paula Matono, Erika Almeida, Carla Pinto-Cruz
and Anabela D. F. Belo

79 **Potential of RFID telemetry for monitoring ground-dwelling beetle movements: A Mediterranean dry grassland study**

Olivier Blight, Benoît Geslin, Lola Mottet and Cécile H. Albert

92 **Connectivity and fragment size drive plant dispersal and persistence traits in forest steppe fragments**

Katalin Szitár, Csaba Tölgyesi, Balázs Deák, Róbert Gallé,
Dávid Korányi and Péter Batáry

103 **Rapid response of vascular plants and insects to restoration of montane grasslands**

Felix Helbing, Thomas Fartmann, Carsten Morkel and
Dominik Poniatowski
118 Soil fertility and landscape surrounding former arable fields drive the ecological resilience of Mediterranean dry grassland plant communities
Renaud Jaunatre, Elise Buisson, Elsa Leborgne and Thierry Dutoit

128 The contribution of seedbank to the green roof plant community dynamics analogous to semi-natural grasslands

Lucie Rivière, Alizé Sellier, Thierry Dutoit, Christel Vidaller, Elise Buisson and Grégory Mahy

138 Photovoltaic power stations: an opportunity to promote European semi-natural grasslands?

Quentin Lambert, Armin Bischoff, Morgane Enea and Raphael Gros

151 Success of passive and active restoration of lowland hay meadows with regard to current and historical references

Maiké Dellicour, Thibaut Goret, Julien Piqueray, Adeline Fayolle, Jérôme Bindelle and Grégory Mahy

162 Persisting effects of seed bed preparation and early grazing on plant communities in grassland restoration

Aure Durbecq, Renaud Jaunatre, Elise Buisson, Cassandra Favale, Nolwenn Maudieu and Armin Bischoff

174 Both management practices and landscape influence plant communities in urban grasslands

Clément Gros, Adeline Bulot, Stéphanie Aviron, Véronique Beaujouan and Hervé Daniel
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## OPEN ACCESS

EDITED AND REVIEWED BY
Fernanda Michalski,
Universidade Federal do Amapá, Brazil

*CORRESPONDENCE

Grégory Mahy

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g.mahy@uliege.be

Thierry Dutoit

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thierry.dutoit@univ-avignon.fr

RECEIVED 27 August 2024

ACCEPTED 30 August 2024

PUBLISHED 30 October 2024

## CITATION

Mahy G, Torok P, Bischoff A, Kiehl K and Dutoit T (2024) Editorial: Origin, conservation, and restoration of the threatened European grassland

ecosystem in the Anthropocene.

Front. Ecol. Evol. 12:1487211.

doi: 10.3389/fevo.2024.1487211

## COPYRIGHT

© 2024 Mahy, Torok, Bischoff, Kiehl and Dutoit. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Editorial: Origin, conservation, and restoration of the threatened European grassland ecosystem in the Anthropocene

Grégory Mahy ID<fnref n="1" />,²*, Peter Torok ID³, Armin Bischoff ID<fnref n="1" />,
Kathrin Kiehl ID⁴ and Thierry Dutoit ID<fnref n="1" />*

## KEYWORDS

grassland, meadow, steppe, conservation, restoration, Anthropocene, biodiversity

## Editorial on the Research Topic

### Origin, conservation, and restoration of the threatened European grassland ecosystem in the Anthropocene

The European continent boasts a rich tapestry of natural and semi-natural grasslands, formed through intricate interactions between humans and nature, representing not only biodiversity hotspots but also invaluable cultural heritage (Poschlod and WallisDeVries, 2002). While based on a recent estimate, Europe harbors more than 650 thousand square kilometer of permanent grasslands, on average only up to a half of this area is covered by grasslands of high natural value (HNV) (Dengler et al., 2020). Beside of the area loss and fragmentation, both intensification and abandonment of traditional extensive land use, as well as the steadily increasing urbanization threaten the species composition and diversity of these ecosystems (Habel et al., 2013; Dengler et al., 2014). As we navigate the complexities of the Anthropocene, these ecosystems face unprecedented impacts, compelling us to challenge our historical approaches to conservation and restoration. In recent years, scientific research has delved deep into understanding the diverse array of European grasslands. From some intact large and continuous grassland stands (e.g. some steppes in Eastern Europe), to patches nested within urban sprawls and the emergent green roofs adorning urban landscapes, researchers have unraveled the unique ecological dynamics and management challenges associated with each type of grassland.

With the Research Topic "Origin, Conservation, and Restoration of the Threatened European Grassland Ecosystem in the Anthropocene", we set the stage for a journey through the nuanced landscapes of European grasslands, offering an overview of recent scientific endeavors and a call to action for the preservation and restoration of these unique ecosystems, as well as the integration of urban and novel grassland ecosystems in a global conservation strategy. The findings of the 14 studies presented in this Research Topic underline the importance of recognizing the heterogeneity within European grasslands. Whether it is the biodiversity-rich semi-natural grasslands, spawning mediterranean and temperate dry

<footnote n="1">¹Mediterranean Institute of Marine and Terrestrial Biodiversity and Ecology (IMBE), Aix Marseille University, National Centre for Scientific Research (CNRS), French National Research Institute for Sustainable Development (IRD), Avignon University, Avignon, France, ²Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium, ³Department of Ecology, University of Debrecen, Debrecen, Hungary, ⁴Vegetation Ecology and Botany, Osnabrück University of Applied Sciences, Osnabrück, Germany</footnote>
grasslands (Martin et al., Ewert et al., Blight et al., Köhler et al., Jaunatre et al.), floodplain and hay meadows (Sommer et al., Dellicour et al.), montane grasslands (Helbing et al., Durbecq et al.), loess and sand steppe fragments of the Pannonian forest steppe region (Szitár et al.), the intricate dynamics of urban green spaces (Fernandes et al., Gros et al.) or the emergent novel ecosystems such as green roofs or solar parks (Lambert et al., Rivière et al.), those ecosystems present both similar and own sets of challenges and opportunities for conservation, management and restoration. Preservation of large fragments, targeted management, and innovative restoration techniques offer pathways towards safeguarding the ecological integrity of natural and semi-natural grasslands.

Landscape complexity and configuration are key factors for the conservation of grassland biodiversity. Grassland fragments, in loess steppes and sand steppe fragments, exhibit diverse vegetation compositions influenced by the size of fragment and landscape connectivity (Szitár et al.). Both types of grasslands rely on the persistence of clonal perennial specialist and generalist species in small and isolated patches to mitigate fragmentation effects. These results are well in agreement with Deák et al. (2018), who found that generalist species were not affected but specialist species with a good dispersal strategy were the most affected by isolation via the lack of appropriate dispersal vectors in the landscape. Ewert et al. demonstrate for the first time the importance of European dry grassland fragments for bats under certain local and landscape compositional conditions in a heterogeneous agricultural region of Germany. By underlining the value of structurally heterogeneous dry grassland fragments acting as potential stepping-stones in intensively used farmland areas, they challenge the current management goals of dry grasslands, aiming to reduce shrub and tree encroachment. Besides, their results also highlight the necessity of connectivity networks in agricultural landscapes. To go further in the study of connectivity, Blight et al. explore how recent technological advances in movement ecology (passive RFID tags), make it possible to track the individual movements of three small ground-dwelling beetle species in a Mediterranean dry grassland. While the study highlight limitations of using passive tags to track the movements of small terrestrial beetles, it helps predicting the ability of species to recolonize degraded areas, enabling appropriate restoration actions to be designed based on landscape ecology principles.

Livestock grazing, that is used in conservation practice to mimic natural grazing regimes provided by wild large herbivores is also recognized as a major management driver of the composition of plant communities in natural and semi-natural grasslands. So far, very few studies have analyzed its impact on micro-scale patterns of biodiversity and vegetation dynamics. Martin et al. present the first overview of the multiple effects of grazing and soil characteristics on plant communities of micro-patterns at the micro-local scale in Mediterranean dry grasslands. They demonstrate that there is no one-size-fits-all strategy to influencing the trajectory of the plant communities and one of the main levers of restoration strategies, changing grazing pressure, may have contrasting effects depending on the community type. Moreover, Köhler et al. indicate how megaherbivore grazing, that aims to substitute extinct wild grazers, should be considered for restoration of temperate dry

grassland. Year-round horse grazing as a relatively new grassland restoration tool has the potential to enhance floristic biodiversity of dry calcareous grasslands not only in the short, but also in the long term. Finally, Durbecq et al. demonstrate that, in mountain grasslands of the French Alps, initial grazing exclusion is not necessary for restoration success under current livestock density.

Restoration of European natural and semi-natural grasslands is a major challenge and face multiple questions relative to the diversity of techniques and to success monitoring. Sommer et al. show that long-term monitoring of restoration projects is necessary, as factors determining restoration success may only become evident in the long term. When restoring floodplain meadows with transfer of seed-containing plant material from species-rich donor sites, a widely used method to restore semi-natural grasslands, the positive effect of soil preparation on the number and cover of target species, which is regularly reported in short-term studies, diminishes over time, while the effects of local site conditions become more important. The importance of long-term monitoring is also confirmed in dry grassland where Köhler et al. reveal that short-term evaluation of restoration schemes can be misleading, particularly at slow-changing indicators such as dry calcareous vegetation types and slow-growing and long-lived species or those exhibiting high interannual population fluctuations such as many orchid species. Not only monitoring but also definitions of adequate restoration targets is important to promote restoration of grasslands in a changing world. Dellicour et al. show how restoration of hay meadows faces challenges in defining relevant reference ecosystems and adapting restoration techniques for the present-day ecological and socio-economic context.

Natural and semi-natural grassland restoration success is also under the control of a diversity of socio-environmental factors and requires fine-tuned methods adapted to the socio-economic context. Restoration efforts for degraded temperate lowland hay meadows show varying success rates, with techniques such as passive restoration mowing, active fresh hay transfer, and sowing of threshing material being implemented based on the initial level of degradation and proximity to well-preserved meadows (Dellicour et al.). Either abiotic, biotic and dispersal filters drive the limitation to recovery in Mediterranean dry grassland more than 40 years after an intermediate period of arable use (Jaunatre et al.). In afforested landscapes, tree removal, hay transfer and resumption of grazing or mowing are typical measures to re-create species-rich grasslands. The application of these restoration measures is effective in re-establishing target communities of different taxa (vascular plants and three insect taxa (leafhoppers, true bugs, and grasshoppers)) for German montane grasslands (Helbing et al.). Durbecq et al. highlight also the complex interactions among seed sowing, grazing regimes and soil disturbance on restoration success of mountain grasslands in the Southern French Alps. A strong grazing-by-soil disturbance interaction show that a combination of both is the best strategy to restore this grassland type.

In urban environment, landscape configuration, targeted management, and innovative restoration techniques are also key drivers for enhancing biodiversity of urban grassland. Gros et al. illustrate the importance of considering factors that act at both local and landscape scales when identifying the drivers of plant
communities in urban grasslands in Western France. Mowing practices and landscape composition do not affect the richness or diversity of plant species but significantly influence the composition of communities. Landscape composition favors plant species according to their strategies, preferential habitats, and life spans. Furthermore, diversification of management practices limits the establishment of non-native species and induces a wider range of functional strategies. Moreover, the application of seed mixes with regional native species allows the promotion of native flora in Mediterranean peri-urban green areas, enhancing the potential of these spaces as tools for biodiversity conservation and diminishing the risk of introducing exotic species with invasive ability (Fernandes et al.). In the Mediterranean context and given the small number of native seed mixes tested, this study represents an innovation and provides practical insights into grassland rehabilitation, contributing to the improvement of plant diversity management in peri-urban and urban Mediterranean areas.

Novel opportunities for grasslands such as green roofs and novel land uses such as solar parks, also offer opportunities to strengthen the ecological network for grassland biodiversity while not replacing historical natural and semi natural grasslands. Lambert *et al.* explore how the increasing construction of solar parks may provide an opportunity to restore or even create semi-natural grasslands. Solar parks allow the establishment of semi-natural grassland communities, but solar panels partially disintegrate the relationship between climate and plant species composition. Ecosystem services provided by soil organisms such as carbon storage, nutrient regulation, and soil conservation, are thus hampered by solar panels. The ecological integration of solar parks to favor the establishment of semi-natural grasslands needs to limit the effect of panels on plant communities and soil quality. In an urban area, *Riviere et al.* explore how extensive green roofs support native biodiversity analogous to natural or semi-natural habitats like grasslands, highlighting their potential for urban biodiversity enhancement. The study shows the importance of seed banks in the dynamics of green roof vegetation and demonstrates that native species on green roofs exhibit similar behavior as in their natural environment.

The Research Topic demonstrates that it is imperative to learn the lessons obtained from scientific studies as we stand at the crossroads of grasslands conservation and restoration in the Anthropocene. By embracing the complexity and diversity of European grasslands and drawing upon the wealth of knowledge generated by recent research, we can chart a course towards a more sustainable coexistence with nature. Through concerted efforts, informed decision-making, and a

shared commitment to stewardship, we can ensure the resilience and vitality of European grasslands for future generations.

## Author contributions

GM: Conceptualization, Writing – original draft, Writing – review & editing. PT: Conceptualization, Validation, Writing – review & editing. AB: Conceptualization, Validation, Writing – review & editing. KK: Validation, Writing – review & editing. TD: Conceptualization, Validation, Writing – original draft, Writing – review & editing.

## Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. PT was supported by the National Research, Development and Innovation Office during the manuscript preparation [NKFIH KKP 144068 and K 137573]. GM was supported by FNRS (Fonds National de la Recherche Scientifique) for a sabbatical mission during the coordination of the Research Topic.

## Acknowledgments

The guest editors are thankful for the authors of the Research Topic for contributing with their research to this initiative.

## Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

## Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

## References

Deák, B., Valkó, O., Török, P., Kelemen, A., Bede, A., Csathó, A. I., et al. (2018). Landscape and habitat filters jointly drive richness and abundance of specialist plants in terrestrial habitat islands. *Landscape Ecol.* 33, 1117–1132. doi: 10.1007/s10980-018-0660-x

Dengler, J., Biurrun, I., Boch, S., Dembicz, I., and Török, P. (2020). “Grasslands of the palaearctic biogeographic realm: introduction and synthesis,” in *Encyclopedia of the World’s Biomes*, vol. Volume 3. (Elsevier Inc.). doi: 10.1016/B978-0-12-409548-9.12432-7

Dengler, J., Janišová, M., Török, P., and Wellstein, C. (2014). Biodiversity of Palaearctic grasslands: a synthesis. *Agric. Ecosyst. Environ.* 182, 1–14. doi: 10.1016/j.agee.2013.12.015

Habel, J. C., Dengler, J., Janišová, M., Torok, P., Wellstein, C., and Wiezig, M. P. (2013). European grassland ecosystems: threatened hotspots of biodiversity. *Biodivers. Conserv.* 22, 2131–2138. doi: 10.1007/s10531-013-0537-x

Poschlod, P., and Wallis DeVries, M. F. (2002). The historical and socioeconomic perspective of calcareous grasslands—lessons from the distant and recent past. *Biological Conservation.* 104 (3), 361–376.
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OPEN ACCESS

EDITED BY
Orsolya Valkó,
Hungarian Academy of Sciences, Hungary

REVIEWED BY
Antonio Greco,
University of Salento,
Italy
Gonzalo García-Baquero,
University of the Basque Country, Spain

*CORRESPONDENCE
Gabrielle Martin
gabrielle.martin@univ-tlse3.fr

SPECIALTY SECTION
This article was submitted to Conservation and Restoration Ecology, a section of the journal Frontiers in Ecology and Evolution

RECEIVED 18 February 2022

ACCEPTED 07 October 2022

PUBLISHED 03 November 2022

CITATION
Martin G, Courtial A, Génin A, Ramone H and Dutoit T (2022) Why grazing and soil matter for dry grassland diversity: New insights from multigroup structural equation modeling of micro-patterns.
*Front. Ecol. Evol.* 10:879060.
doi: 10.3389/fevo.2022.879060

COPYRIGHT
© 2022 Martin, Courtial, Génin, Ramone and Dutoit. This is an open-access article distributed under the terms of the *Creative Commons Attribution License (CC BY)*. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Why grazing and soil matter for dry grassland diversity: New insights from multigroup structural equation modeling of micro-patterns

Gabrielle Martin¹,²,³,⁴*, Anouk Courtial², Alexandre Génin⁵,⁶, Hervé Ramone² and Thierry Dutoit²

¹Laboratoire EDB Évolution and Diversité Biologique UMR 5174, Université Toulouse 3 Paul Sabatier, UPS, CNRS, IRD, Université de Toulouse, Toulouse, France, ²Institut Méditerranéen de Biodiversité et d'Ecologie marine et continentale (IMBE), Univ Avignon, Aix Marseille Univ, CNRS, IRD, IUT site Agroparc, Avignon, France, ³Centre d'Ecologie et des Sciences de la Conservation (CESCO), Muséum national d'Histoire naturelle, Centre National de la Recherche Scientifique, Sorbonne Université, UMR7204 Centre des Sciences de la Conservation (CESCO), Paris, Île-de-France, France, ⁴Laboratoire Cogitamus, Paris, Languedoc-Roussillon, France, ⁵Université de Montpellier, CNRS, EPHE, IRD. UMR5554 Institut des Sciences de l'Evolution de Montpellier (ISEM), Montpellier, France, ⁶Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, Netherlands

Grazing is recognized as a major process driving the composition of plant communities in grasslands, mostly due to the heterogeneous removal of plant species and soil compaction that results in a mosaic of small patches called micro-patterns. To date, no study has investigated the differences in composition and functioning among these micro-patterns in grasslands in relation to grazing and soil environmental variables at the micro-local scale. In this study, we ask (1) To what extent are micro-patterns different from each other in terms of species composition, species richness, vegetation volume, evenness, and functioning? and (2) based on multigroup structural equation modeling, are those differences directly or indirectly driven by grazing and soil characteristics? We focused on three micro-patterns of the Mediterranean dry grassland of the Crau area, a protected area traditionally grazed in the South-East of France. From 70 plant community relevés carried out in three micro-patterns located in four sites with different soil and grazing characteristics, we performed univariate, multivariate analyses and applied structural equation modeling for the first time to this type of data. Our results show evidence of clear differences among micro-pattern patches in terms of species composition, vegetation volume, species richness, evenness, and functioning at the micro-local scale. These differences are maintained not only by direct and indirect effects of grazing but also by several soil variables such as fine granulometry. Biological crusts appeared mostly driven by these soil variables, whereas reference and edge communities are mostly the result of different levels of grazing pressure revealing three distinct functioning specific to each micro-pattern, all of them coexisting at the micro-local scale in the studied Mediterranean dry grassland. This first overview of the multiple effects of grazing and soil characteristics on communities in micro-patterns is discussed within the scope of the conservation of dry grasslands plant diversity.
**Introduction**

Grasslands have been defined as ecosystems dominated by
graminoids (i.e., grasses and grass-like plants) and forbs (Jacobs
et al., 1999; Gibson, 2009). They constitute an important ecosystem
type comprising about one-third of the Earth's vegetative cover
(Jacobs et al., 1999; Suttie et al., 2005) and covering over 900,000 km²
in Europe (Eurostat, 2017). Typical temperate grasslands are almost
continuous ecosystems of grasses, sedges, and herbaceous
dicotyledonous species in varying amounts, with scattered bushes
and low tree cover (Jacobs et al., 1999). Their characteristics vary
with local climate (i.e., water, wind, and light), soil, and topography
(i.e., edaphic factors), biotic interactions but also natural and human
disturbances such as fires and grazing (Burke et al., 1998; Jacobs
et al., 1999; White et al., 2000; Gibson, 2009; Dantas et al., 2016).

Grazing is known to be a major driver of the composition of plant communities in grasslands, especially at the micro-local scale where grazing increases spatial heterogeneity and plant diversity relative to ungrazed habitat (McNaughton, 1983; Milchunas and Lauenroth, 1993; Adler et al., 2001; Ge and Liu, 2022). Grazing leads to the heterogeneous removal of plant species due to differences in plant palatabilities and animal selectivity (Bakker et al., 1983; Ge and Liu, 2022). These can yield a mosaic-like structure in vegetation, called micro-patterns (Bakker et al., 1983), where patches of tall vegetation coexist with shorter patches containing more palatable plants. This direct effect may be reinforced by indirect effects of grazers: for example, because grazers may forage more in patches with shorter plants, such patches can be denser, which further reduces plant development (Chenot et al., 2017). Both such direct and indirect effects combine with possible pre-existing spatial variations in soil characteristics to produce heterogeneity in vegetation composition, structure, and local functioning. Nevertheless, to our knowledge, no study has sought to disentangle so far the double effect of grazing and soil conditions on micro-pattern species composition and diversity (but see Bakker et al., 1983), especially to highlight the specific functioning at work due to grazing pressure and soil characteristics at a micro-local scale.

Yet, understanding these related effects on the species
composition, abundance, and functioning of grassland
communities remains crucial for the implementation of effective
management strategies, restoration and conservation programs for
species-rich grasslands. Indeed, some old-growth grasslands are
composed of plant communities that require centuries or millennia
to assemble (Henry et al., 2010; Poschlod and Baumann, 2010;
Robin et al., 2018; Saatkamp et al., 2021) and exhibit an exceptional
biodiversity both in terms of high plant species richness and

endemism (Veldman et al., 2015). One example is the 26,000 km² of dry grasslands of the Northwestern Mediterranean Basin (Buisson et al., 2020). These grasslands are typically resilient to endogenous disturbance regimes such as wildfires (Bond and Keeley, 2005; Vidaller et al., 2019) or grazing pressure variability (Saatkamp et al., 2017), but extremely vulnerable to human-caused exogenous perturbations, for example those arising from cultivation (Römermann et al., 2005; Coiffait-Gombault et al., 2012; Helm et al., 2019). They are also currently threatened by an increase in farmland abandonment leading to shrub encroachment, especially in the Mediterranean area where the decrease in livestock is considered a major cause of changes in landscapes (Buisson et al., 2020). Therefore, initiatives to conserve and restore old-growth Mediterranean grasslands are urgently needed based on our understanding of processes at work in maintaining their plant diversity and functions (Veldman et al., 2015).

To shed new light on the processes that maintain the heterogeneity and plant diversity in dry grasslands, we conducted our study at the micro-local scale, focusing on three micro-pattern plant communities of the Crau nature reserve, a protected Mediterranean dry grassland located in the South-East of France. This area is the only French Mediterranean pseudo-steppe, whose origin and sustainability arise from the combination action of climate, specific soil conditions, and the traditional practice of sheep grazing for several millennia (Buisson and Dutoit, 2006). At this micro-local scale, we addressed the following questions: (1) To what extent are the plant communities of the micro-patterns different from each other in terms of species composition, species richness, vegetation volume, evenness, and functioning? and (2) are those differences directly and/or indirectly driven by grazing and/or soil variables? In order to identify the processes maintaining heterogeneity in space, and potentially affecting the temporal dynamics of these micro-patterns, we performed univariate, multivariate analyses and applied structural equation modeling for the first time to this type of data to reveal direct and indirect effects of explanatory variables. We discussed our results within the scope of plant community ecology and applications to the biological conservation of species-rich Mediterranean dry grasslands.

**Materials and methods**

**Study area and sites**

Vegetation data were collected in the Crau nature reserve,
hereafter called Crau area (Figure 1). This area is characterized
by a Mediterranean climate (dry summers, mild winters, with rainfall peaking in autumn, some detailed temperature and precipitation data are available for the 1997–2006 period in Wolff et al., 2015), frequent strong northwesterly winds (Saatkamp et al., 2021) and is dominated by “pseudo-steppic” vegetation (Tatin et al., 2013). Dominant species composition is characteristic of Mediterranean *Thero-Brachypodietea* habitat “Pseudosteppe with grasses and annuals,” a high priority habitat for conservation (Corine Biotopes Code 34.512, Bissardon et al., 1997; Natura 2000 habitat type 6,220, San Miguel, 2008; EUNIS habitat E1.311 and E1.312, Louvel et al., 2013). This pseudo-steppic vegetation located in the fossil delta of the Durance river is characterized by a high stone cover (mainly pebbles) that limits the installation and the development of dense grasslands. Plant communities are highly diverse and dominated by low or very short herbaceous vegetation (49.4% of all plant species are annuals, Devaux et al., 1983; Helm et al., 2019; Pfeiffer et al., 2019), as a result of the combined effects of climate, soil, fire, and grazing. Grazing by itinerant sheep flocks has been reported since at least 2000 BP on the basis of Roman archeological remains (Badan et al., 1995; Henry et al., 2010; Robin et al., 2018; Saatkamp et al., 2021). This extensive grazing, occurring mostly from February to June, is heterogeneous throughout the steppe in the Crau area (Buisson and Dutoit,

2006; Saatkamp et al., 2017). These different parameters, Mediterranean climate, strong northwesterly winds, high stone cover, and two millennia of extensive grazing, all participate to shape this ecosystem.

We selected four study sites locally named in French "Coucou, Négreiron, Petit Carton, and Le Merle," along a South-West/North-East gradient following the geomorphological-pedological-climatic gradient to cover all the environmental variability in the area (climate, topography, geology, pedology, and water accessibility) and in grazing pressures (Molinier and Tallon, 1950; Tatin et al., 2013; Table 1; Figure 1). An increase in fine elements (clay, silt) relative to decrease of coarse elements (sand, pebbles) has been shown to drive the presence of the biological crust micro-patterns in the south and their absence in the north of the plain (Rieux et al., 1977). Finally, the four sites are grazed by sheep kept in enclosures or led by a shepherd at an average grazing pressure of 400.8 ± 150 grazed day sheep/ha/year (see below, unpublished data from the Agricultural Chamber of the Bouches-du-Rhône department and the Le Merle Domain). Two out of the four sites had long-term, established ungrazed areas (exclosures): one of approximately 0.2 ha since 1982 at Le Merle and another of approximately 3 ha since 2001 at Négreiron (Bourrelly et al., 1983; Pilard and Brun, 2001).

<figure><img src="image_7.png" /><figcaption>FIGURE 1
Locations of the four study sites in the Crau area, South-East of France.</figcaption></figure>
<table><caption>TABLE 1 Number of plant community relevés carried out for each micro-pattern and site of the Mediterranean dry grassland of the Crau area (South-East France), broken down by treatment (grazed vs. ungrazed in exclosures).</caption><thead><tr><th rowspan="2">Site</th><th rowspan="2">Treatment</th><th rowspan="2">Grazing pressure (number of sheep grazing days per ha and year)</th><th colspan="3">Vegetation micro-patterns</th></tr><tr><th>Biological crusts</th><th>Reference communities</th><th>Edge communities</th></tr></thead><tbody><tr><td>Coucou</td><td>Grazed</td><td>241</td><td>10</td><td>5</td><td>5</td></tr><tr><td rowspan="2">Négreiron</td><td>Grazed</td><td>588</td><td>5</td><td>5</td><td>5</td></tr><tr><td>Ungrazed</td><td>0</td><td>5</td><td>5</td><td>0</td></tr><tr><td>Petit Carton</td><td>Grazed</td><td>330</td><td>0</td><td>5</td><td>5</td></tr><tr><td rowspan="2">Le Merle</td><td>Grazed</td><td>444.2</td><td>0</td><td>5</td><td>5</td></tr><tr><td>Ungrazed</td><td>0</td><td>0</td><td>5</td><td>0</td></tr></tbody></table>

Grazing pressure is indicated for each site and treatment.

## Sampling design and data collection

Within the four sites described above, three micro-patterns in plant communities have been primarily reported: (i) Mediterranean grasslands, locally named “coussoul” or *Asphodeletum fistulosi* (Thero-Brachypodietalia) following the phytosociological typology by Molinier and Tallon (1950), hereafter named as lightly grazed reference communities, (ii) biological crusts, areas dominated by lichens on shallower soils, locally named “tonsure” or *Crassuletum tillaeae* (Tuberarietalia guttati) following the phytosociological typology by Molinier and Tallon (1950), corresponding to present or historically high grazing pressure areas (Rieux et al., 1977), and (iii) edge communities dominated by the tussock perennial grass [*Brachypodium retusum* (Pers.) P.Beauv.] of this grassland, locally named “grossier” and associated to the absence of grazing or very low grazing pressure areas, often localized at the edge of grazing plots (Dureau and Bonnefon, 1998). A total of 70 relevés, i.e., a list of each vascular plant species in a community for a defined spatial area, were carried out in the three Mediterranean vegetation micro-patterns: 20 in biological crusts (5 in exclosures), 30 in reference communities (10 in exclosures) and 20 in edge communities (Table 1). This difference in the number of relevés was due to the absence of long-term exclosures at two sites (i.e., no exclosure in sites *Coucou* and *Petit Carton*) or the absence of biological crusts in the north of the plain (i.e., in sites *Le Merle* and *Petit Carton*). Each relevé delimitation was defined taking into account the floristic, structural, and ecological homogeneity necessary to set up a phytosociological survey and on previous phytosociological studies already realized in the Crau area (Molinier and Tallon, 1950; Rieux et al., 1977). A minimum distance of 10 m between relevés located in a same site was observed to avoid any influence of each type of plant community on one another, and relevés were done at least 10 m away from fences (Buisson and Dutoit, 2006; Saatkamp et al., 2017). The floristic data were gathered from April to May 2018, which is the period of the year during which most plants can be identified to the species level in South-East France. All vascular plants were recorded in each relevé, and abundance data were estimated for each species according to the six abundance classes defined by

Braun-Blanquet (+, 1, 2, 3, 4, 5; Braun-Blanquet, 1932). The sampled areas of the 70 relevés ranged from 4 to 40 m² (average area of grazed biological crusts 8.5 ± 7.9 m² vs. ungrazed biological crusts 7.2 ± 2.2 m²; of grazed reference communities 14.4 ± 9.2 m² vs. ungrazed reference communities 6.6 ± 2.8 m²; of edge communities 13.4 ± 7.8 m², sampled area of each relevé are detailed in Supplementary Table A1). The variability of the sampled areas arose from differences in the area occupied by the three different micro-patterns and to their species richness, as we stopped samples when 95% of the species of the plant community was incorporated into the relevé, ratio also based on previous phytosociological surveys realized in the Crau area (Molinier and Tallon, 1950; Rieux et al., 1977). To avoid potential bias, the area was included in all subsequent analyses.

For each relevé, we defined five independent indices that captured the main local environmental parameters: (i) an index of vegetation volume, based on visual estimates of vegetation cover, bare ground, and maximum height of the herbaceous stratum; (ii) a soil fertility index, based on 12 parameters related to soil chemistry (cation exchange capacity, pH water, and pH KCl, available phosphorus, potassium oxide, magnesium oxide, calcium oxide, sodium oxide, total nitrogen, organic carbon, and carbon-to-nitrogen ratio); (iii) an amount of fine soil particles, measured as the amount of clay and fine silt; (iv) an amount of coarse soil particles, i.e., fine sand; and (v) an amount of pebbles (>5 cm), based on visual cover estimates. These indices capture known gradients at the scale of the Crau area (Details in Supplementary Material Appendix I; Supplementary Figure A1) that broadly influence vegetation characteristics. All visual estimations have been collected by the same observer to reduce subjective variability. Grazing pressure was retrieved from inquiries of pastoralists realized by the Agricultural Chamber of the *Bouches-du-Rhône* department and the *Merle* Domain for the four study sites concerning the 55 grazed relevés out of the 70 relevés (15 were located in exclosures) in 2018. We calculated the number of sheep grazing days per ha and per year as Ns * Nd/ha for the grazed season of the year 2018 (autumn 2017 and spring 2018, before the transhumance to the mountain pastures), where Ns the number of sheep in a herd, Nd the number of days of sheep presence on the grazed area, and ha the area of the site (Table 1).
It is important to note that we used two grazing variables. We used first a quantitative variable, described above and named hereafter "grazing pressure." This variable was mostly used in statistical analyses. Second, we compiled a qualitative variable, grazed vs. ungrazed in exclosures, hereafter named "treatment" and used in some graphical representations where appropriate.

## Statistical analyses

We calculated the species richness and Pielou's measure of species evenness, hereafter named evenness, which is weakly sensitive to rare taxa, not sensitive to median or dominant taxa, and independent of species richness for sites with more than 20 species (Beisel et al., 2003; Gosselin, 2006). Evenness was calculated as $J=H'/\ln(S)$ where H' is the Shannon diversity index based on the abundance of species in a relevé and S is the total number of species in a relevé.

To explore the possible relationships between the three micro-patterns and the considered response variables, i.e., amount of clay and fine silt, amount of fine sand, soil fertility, pebble cover, vegetation volume, species richness, and evenness, we fitted linear mixed-effects models using the restricted maximum likelihood algorithm as recommended in case of unbalanced design associated to random effect (Pinheiro and Bates, 2000; Bolker et al., 2009). We included three fixed-effect predictors: micro-patterns (qualitative, three levels), grazing pressure (quantitative), and the interaction between both variables, and included the site identity as a random effect on the intercept. We included the logarithm of the sampled area as a control, fixed-effect variable for the models that included species richness, evenness, vegetation volume, and pebble cover as response variables. For the model with pebble cover as response, we did not include grazing pressure and the interaction between grazing pressure and micro-pattern as explanatory variable. Equations are detailed in Supplementary Material Appendix II. We adjusted the *p*-values obtained from the linear mixed-effects models (Kuznetsova et al., 2017) and from the ANOVA applying the Holm correction (Sinclair et al., 2013). We checked visually using quantile-quantile plots that the residuals were consistent with the assumption of a normal distribution. We calculated the pairwise comparison Wilcoxon tests between micro-pattern group levels according to each response variables with corrections for multiple testing (Benjamini and Hochberg, 1995; Benjamini and Yekutieli, 2001) and between grazed and exclosures micro-patterns.

Multivariate analyses were used to study the relationship between the species composition of plant communities, environmental variables, and grazing pressure. In order to analyze plant community data, Braun-Blanquet scores were transformed into percentage cover on the basis of the average percentage of cover of each class: $+=1\%$; $1=5.5\%$; $2=17.5\%$; $3=37.5\%$; $4=62.5\%$; $5=87.5\%$. We performed Adonis and pairwise Adonis post-hoc tests with Bonferroni adjustments to check whether the plant communities were significantly different between and within

groups defined by the micro-pattern, the treatment (grazed vs. exclosure), and the interaction of both variables. Moreover, we implemented a redundancy analysis (RDA) to investigate the variability in plant community composition at the micro-local scale in the Crau area constrained by centered environmental variables and grazing pressure. Note that we considered site and area as conditional variables, to account for the spatial nesting of sampled areas in sites and for the variable area sampled per relevés, respectively. As recommended by Borcard et al. (2011), we Hellinger-transformed the abundance data to reduce the wide disparity in magnitude between species abundances prior to the analysis. We retained all environmental variables (i.e., amount of clay and fine silt, amount of fine sand, soil fertility, and pebble cover) and grazing pressure as explanatory variables according to the Variance Inflation Factor testing collinearity between explanatory variables (all VIF<5; Borcard et al., 2011). We finally performed a global permutation test to assess the significance of the RDA and a test of the canonical axes significance.

Finally, in order to evaluate and compare direct and indirect effects of grazing versus soil variables on species richness, evenness, and vegetation volume of the three micro-patterns communities, we performed a single multigroup structural equation modeling (SEM), a probabilistic model including multiple predictors and response variables in a single causal network. It provides a means of representing complex hypotheses about causal networks, accounting for factors that are both causes and effects, taking into account interaction effects, and testing for model and data consistency (Grace, 2006; Lefcheck, 2019). We proposed an initial conceptual model containing six regression analyses based on an a priori knowledge about the relations among the variables that was both consistent with our data and which made biological sense (Supplementary Figure A2). We considered species richness, vegetation volume, and evenness as endogenous variables, i.e., responses variables, and amount of clay and fine silt, amount of fine sand, soil fertility, pebble cover, and grazing pressure as exogenous variables, i.e., predictors. Note that an endogenous variable can also predict other variables in the model and be characterized simultaneously as endogenous and exogenous variables. This is the case for vegetation volume, species richness, and amount of clay and fine silt which were both endogenous and exogenous variables. A logarithm term of the area was considered as an exogenous variable influencing species richness, vegetation volume, and evenness to account for the variable area sampled per relevé (Supplementary Figure A2). As expected, this term had a direct significant and positive effect on species richness of biological crusts (Standardized estimate=0.72, value of *p* < 0.001), reference communities (Standardized estimate=0.3, value of *p* < 0.001), and edge communities (Standardized estimate=0.6, value of *p* < 0.001), i.e., the larger the sampled area, the higher the species richness. It has not been represented in figures as this variable is a sampling artifact. In each regression analyses of the multigroup SEM, we included an independent random effect to account for the spatial nesting of sampled areas in site. We performed a single multigroup SEM testing relationships between variables for the
three micro-patterns of the Mediterranean dry grassland of the Crau area. This single multigroup SEM allows testing for significant differences in the relationships between variables across and between micro-patterns. According to the test of directed separation, no relation was missing in the conceptual model. To evaluate the model and the goodness-of-fit with the data, we used a Fisher's C test (high *p*-values indicate a good fit, with values well above 0.05 considered acceptable since the null hypothesis here tested is that the data predicted by the model and the observed data are consistent; Lefcheck, 2019).

All analyses and figures were done using R version 3.2.4 (R Development Core Team, 2008), and the packages vegan v2.5.6 (Oksanen et al., 2019), nlme v3.1.142 (Pinheiro et al., 2017), piecewiseSEM v2.1.0 (Lefcheck, 2016), ggplot2 v3.3.1 (Wickham, 2009).

# Results

## Evidence of differences between the three micro-patterns of dry grasslands

We found differences between the three micro-patterns in terms of species composition. All groups constituted by grazed and ungrazed communities of the three micro-patterns of the Crau area were different from each other in terms of species composition (Pairwise Adonis test, adjusted value of *p* < 0.01; Supplementary Tables A2, A3) except grazed reference communities and grazed edge communities (Pairwise Adonis test, *F* value = 2.21, adjusted value of *p* = 0.41; Supplementary Tables A2, A3). We found a significant effect of the three micro-patterns (Adonis test, *F* value = 11.33, value of *p* < 0.001), of the treatment (Adonis test, *F*-value = 6.82, value of *p* < 0.001) and of the interaction of the both variables micro-patterns and the treatment (Adonis test, *F*-value = 0.38, value of *p* = 0.015) on the species composition of all groups.

We found differences between the three micro-patterns in terms of soil characteristics, vegetation volume, and species composition. Considering the RDA analysis, permutation tests supported the significance of the RDA (F-value = 4.03, value of *p* < 0.001; Supplementary Table A4): variance in plant community composition was explained to 20.55% by the explanatory variables and to 29.35% by the conditional variables (RDA adjusted R² = 16.4; Supplementary Table A4). In addition, the first and second canonical axes were significant (Permutation test, RDA 1 F-value = 12.16, value of *p* < 0.001; RDA 2 F-value = 7, value of *p* < 0.001; Supplementary Table A4) and accounted together for 79.17% of the total explained variance. The first RDA axis captured differences in composition of micro-patterns and vegetation volume: it contrasted biological crusts, which had higher level of fine sand and soil fertility, whereas reference communities and edge communities had higher levels of clay, fine silt, and vegetation volume (Figure 2). The second RDA axis separated grazed plant communities from ungrazed plant communities, i.e., exclosures.

We found evidence of differences between the three micro-patterns in terms of species richness, evenness, vegetation volume, and soil characteristics. Linear mixed models showed significantly higher levels of fine sand for biological crusts compared to the other micro-patterns, significantly higher levels of clay and fine silt, of vegetation volume for reference communities and edge communities compared to biological crusts (Table 2; Figure 3; Supplementary Tables A5, A6). Thus, biological crusts were characterized by coarse silt and fine sand, whereas reference communities and edge communities were characterized by a mixture of variables element size: clay and fine silt and coarse sand. Edge communities were characterized by the lower amount of fine sand in soil than for other micro-patterns (i.e., the higher amount of coarse sand (Figure 3). Finally, linear mixed models did not show significant differences among micro-patterns concerning soil fertility and pebble cover. We found significantly higher levels of clay and fine silt for ungrazed communities compared to grazed communities, higher levels of soil fertility for grazed biological crusts, lower levels of species richness, and evenness for ungrazed reference communities (Supplementary Figure A3).

## Micro-patterns exhibit distinct functioning, all of them coexisting at the micro-local scale in dry grasslands

We investigated the direct and indirect effects of grazing pressure and soil variables on species richness, vegetation volume, and evenness of plant communities of the three micro-patterns and the fitting parameters of the adequate multigroup SEM were correct (Fisher's C = 9.75, value of *p* = 0.78, ddl = 14, *n* = 70; Figure 4). This analysis showed that the direct effect of grazing varied across micro-patterns (significant interaction between grazing pressure and micro-patterns against species richness, value of *p* < 0.05), whereas effects of other predictors were similar across micro-patterns (value of *p* > 0.05; Figure 4). Effect sizes revealed three distinct functioning, each one specific of a micro-pattern. Soil variables and grazing had stronger direct and indirect effects on plant communities of biological crusts than on reference communities and edge communities. Direct effects of grazing on species richness differed among each micro-pattern, being negative in biological crusts and positive in reference and edge communities. Finally, soil fertility and pebble cover did not appear to influence plant communities of any micro-patterns according to the multigroup SEM.

# Discussion

For the first time, our work disentangles grazing and soil characteristics impacts on micro-pattern patches by showing differences in species composition, vegetation volume, species richness, evenness, and functioning at the micro-local scale among the micro-patterns of a Mediterranean grassland.
<figure><img src="image_8.png" /><figcaption>FIGURE 2</figcaption></figure>

Ordination triplot of redundancy analysis (RDA) of the three micro-patterns of the Mediterranean dry grassland of the Crau area (full polygons for grazed relevés, hatched polygons for ungrazed relevés in exclosures) considering grazing and environmental variables (blue, stars precise significance) and two conditional variables (site and sampled area). Only the 30 most abundant species are represented and the size of species' labels is proportional to their frequency.

<table><caption>TABLE 2 ANOVA Type II (Chi-square tests) and significance level for effects of grazing pressure and micro-patterns against environmental variables, namely amount of clay and fine silt, amount of fine sand, soil fertility, pebble cover, and vegetation volume, species richness, and evenness.</caption><thead><tr><th>Effect</th><th>df</th><th>Amount of clay and fine silt</th><th>Amount of fine sand</th><th>Soil fertility</th><th>Pebble cover</th><th>Vegetation volume</th><th>Richness</th><th>Evenness</th></tr></thead><tbody><tr><td>Grazing pressure (GP)</td><td>1</td><td>18.41***↓</td><td>1.11</td><td>0.83</td><td>-</td><td>9.18**↓</td><td>29.31***↑</td><td>10.09**↑</td></tr><tr><td>Micro-patterns (MP)</td><td>2</td><td>22.43***</td><td>15.9**</td><td>6.48</td><td>1.56</td><td>164.3***</td><td>8.85*</td><td>29***</td></tr><tr><td>MP x GP</td><td>2</td><td>0.38</td><td>0.06</td><td>3.38</td><td>-</td><td>3.65</td><td>24.6***</td><td>8.5*</td></tr></tbody></table>

MP × GP, Micro-patterns × Grazing pressure. Factor effect: ↓ decrease; ↑ increase. All parameter estimations are reported and detailed in Supplementary Tables A4A,B. Bold represents significance level.

## Origin and maintenance of micro-patterns

This work highlights the contrasted functioning across micro-patterns, as grazing had a variable impact on species richness and soil granulometry. Micro-patterns with higher vegetation cover

and volume are those that tend to be less grazed (although this has not been quantified here)—biological crusts are thus likely to be where grazing is the highest, followed by the reference communities and edge communities. Grazing exhibited a negative effect on species richness in biological crusts versus a positive one on richness in reference communities and an indirect and smaller

<footnote>*p < 0.05; **p < 0.01; ***p < 0.001.</footnote>
<figure><img src="image_9.png" /></figure>

positive one on richness of edge communities. This is consistent with the theoretical impact of grazing on species richness—intense grazing decreases diversity (in biological crusts) but lower levels favor diversity, which is what we observe in other micro-patterns (Milchunas et al., 1988; Tatin et al., 2013).

Differences among micro-patterns were particularly stark between biological crusts and the two other micro-patterns, as the former showed very different soil granulometry and vegetation volume. Biological crusts appeared primarily driven by soil variables, and second by grazing. They were more homogeneous in terms of species composition, and had an upper soil containing more fine particles (fine sand, coarse silt) than the other two micro-patterns. Such differences in soil characteristics suggest that biological crust communities may have their origin in present or former grazing practices (Saatkamp et al., 2021). Indeed, soil characteristics are influenced by grazing, suggesting that trampling could be the main driver of local soil differences, which compound with already-existing larger-scale differences, such as the combined geomorphological-pedological-climatic gradient of the Crau area and the spatial heterogeneity of the vegetation (Molinier and Tallon, 1950; Adler et al., 2001; Tatin et al., 2013). Soil trampling and compaction by animals alter the soil structure by compressive deformation: particles are brought closer together by the applied charge, which reduces the total pore space and permanently expels air or water from the soil pores (Patto et al., 1978; Silva et al., 2003). These alterations of the upper part of the

soil affect soil physical properties, density, water dynamics, mineral element cycle, and plant growth (Lowery and Schuler, 1991; Schlotzhauer and Price, 1999; De Neve and Hofman, 2000; Drewry et al., 2008). Biological crusts could correspond to past high-impact areas of grazing, which are known to have a long-lasting effect, and to finely textured soils, which are more compressible than others (Larson et al., 1980), especially under stronger grazing pressures. Indeed, the higher amount of fine sand in soil composition could promote biological crusts by compaction, which may impair the installation of the dominant and key species in the Crau area *Brachypodium retusum*. In contrast, the heterogeneity of soil particle sizes in reference and edge communities seems to promote *Brachypodium retusum* establishment, as observed in field. Also, the increased abundance of this perennial graminoid species has been related to lightly grazed edge communities (Porensky et al., 2017). The installation of this key species facilitated by soil grain size characteristics and fire resilience could then result in changes in the microenvironment by improving water infiltration, reducing radiation to the soil, and accumulating seeds, fine soil particles, and nutrients between plant roots (Aguiar and Sala, 1999; Vidaller et al., 2019; Davies et al., 2022). This could also reduce herbivory through a phenomenon of facilitation between species (survival of seedlings protected by the dominant species, Aguiar and Sala, 1999). Taken altogether, these processes could explain the persistence of such contrasted community types at a local scale (<10 m).
<figure><img src="image_10.png" /><figcaption>Reference communities (n=30)</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>Edge communities (n=20)</figcaption></figure>

<figure><img src="image_12.png" /><figcaption>FIGURE 4</figcaption></figure>

Direct and indirect effects of grazing and soil variables on vegetation richness, evenness and volume according to the three micro-patterns of the Mediterranean dry grassland of the Crau area (relations among variables on the left and total direct and indirect effect size on the right resulting from a piecewise multigroup structural equation model, coefficients correspond to standardized estimates). Red (negative effect) and blue (positive effect) arrow widths are proportional to the standardized estimate of each significant effect (numbers along arrows). Gray arrows are non-significant effects.

Reference and edge communities appeared much more similar to each other than to biological crusts, as they had similar species compositions and abundances, species richness, evenness, and vegetation volume, all consequences of variable levels of

herbivory (Génin et al., 2021). However, they differ in terms of soil composition (amount of fine sand). Edge communities appeared directly driven by soil variables and in a minor way by grazing, thus contrasting with reference communities which were directly
influenced by grazing. Edge communities are often associated with abiotic modifications such as water infiltration (Masson et al., 2015) and not only to low grazing pressure, which does not affect plant community composition unlike high grazing pressure. One notable implication in terms of conservation and restoration is that it is not enough to remove grazing to produce a transition from reference to edge community in the short term because changes must also occur in soil granulometry (i.e., high amount of coarse sands in the soils of edge community). In fact, only long-term grazing removal affects will change the species composition of reference communities into that of edge communities (Saatkamp et al., 2017). Despite being more similar, switching from one reference to edge community (or the other way around) may thus require more than short-term changes in grazing pressure.

## No demonstrated effect of pebble cover and soil fertility on micro-patterns

No effect of pebble cover has been found, although it is widely thought to impact positively species richness, vegetation volume, and evenness, by constituting a root shelter allowing the installation of *Brachypodium retusum* (Bourrelly et al., 1983) and other species, improving microenvironmental conditions and reducing herbivory by physically protecting the species from sheep's mouths (Dureau and Bonnefon, 1998; Aguiar and Sala, 1999). This is probably due to the differences in sampled area among micro-pattern (more pebbles in the less grazed areas are also the largest sampled areas), which is not independent from the variable size and density of pebble related to the gradient of the alluvial deposits of the Durance river (Devaux et al., 1983), the largest pebbles at the highest recovery being encountered in the north-west where we did not sample biological crusts (Le Merle site; Figure 1), while the fine elements in the superficial part of the soil are more present in the south of the Crau area (Coucou site; Figure 1). Likewise, no effect of soil fertility has been found and no difference among each micro-pattern even though the former over-grazed areas could be suspected to be characterized by accumulation of nutrients and animal waste, beneficial to plant growth, long-term fertility, and known to cause a shift in community diversity and composition (Matches, 1992; Liu et al., 2016). These persistent legacies of historical sheep concentration, as Roman ones, on soil properties have persistent effects on today's vegetation in this area (Saatkamp et al., 2021).

## Consequences for biological conservation and restoration of mediterranean dry grasslands

This work showed that ecosystem functioning varies over very small spatial scales: the three distinct communities at the micro-local scale are maintained by different direct and indirect effects of

grazing and soil characteristics. Thus, there is no one-size-fits-all strategy to influencing the trajectory of the plant communities and one of the main levers of restoration strategies, changing grazing pressure, may have variable effects depending on the community type it is applied to. Grazing has a long-term residual effect on plant communities and soils, so it is not sufficient to remove it in the short term to restore a particular Mediterranean dry grassland community (Buisson et al., 2020). Indeed, grazing-induced changes in soil characteristics and fertility *via* long-term persistent eutrophication (soil phosphorus, calcium, and nitrogen) and trampling have effects on historical time-scales, as there is little opportunity to uncompact soil structure (Greenwood and McKenzie, 2001; Saatkamp et al., 2021). Grazing thus acts as a one-way lever: given the relative similarity between reference and edge community, it is likely that increased grazing pressure in edge communities would make them shift toward reference communities. However, the sole removal of grazing in reference communities is unlikely to drive them into edge-type communities on short time-scales, because of the need to reverse soil characteristics too. A similar and more pronounced effect is also likely in biological crusts: driving them toward other community types would require undoing the high soil compaction, which only occurs on very long time-scales (centuries) without drastic human intervention. Indeed, effect of past sheepfolds and intense grazing are still detectable on vegetation and soils, even after two millennia (Saatkamp et al., 2021).

In this situation, there is little opportunity to reverse such effects for restoration purposes. However, authors have already shown that a species of harvesting ant, *Messor barbarus*, could play an important role in the restoration of plant communities in the Crau area, by displacing a large quantity of plant seeds and changing physical and chemical soil characteristics toward that of the reference communities (Cramer et al., 2008; García-Ruiz and Lana-Renault, 2011; De Almeida et al., 2020). Typical dry grassland species are known to have low capacity to colonize new habitats or persist in the soil seed bank (Buisson et al., 2006; Metzner et al., 2017). Thus, increasing pebble cover and re-introducing *Messor barbarus* may provide an interesting and low-cost tool to reverse compaction and disperse seeds (Bulot et al., 2014; De Almeida et al., 2020).

In this work, we presented the first overview of the multiple effects of grazing and soil characteristics on plant communities of micro-patterns at the micro-local scale. Our results should enable conservation planners to use grazing and/or ecological engineer species as effective tools to influence plant community composition and soil structure. A more complete picture may emerge by measuring additional processes influencing the distribution of micro-patterns such as water infiltration capacity in case of compacted soil, wind-based redistribution of seeds, and fine soil elements that may accumulate in tall vegetation patches, and fire (Burke et al., 1998; Aguiar and Sala, 1999; Vidaller et al., 2019). Evaluating these additional effects would bring an understanding of the governing forces that shape community assembly in the context of Mediterranean dry grasslands conservation and restoration (Török et al., 2018).
## Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author. Full plant and soil data are available in the open repository Zenodo: https://doi.org/10.5281/zenodo.7222092.

## Author contributions

AC, TD, and GM conceived the research idea. AC, HR, and TD collected data. GM performed statistical analyses. GM, with contributions from TD and AG wrote the manuscript. All authors contributed to the article and approved the submitted version.

## Funding

This work was supported by grants from the French Ministry of Ecological and Solidarity Transition, i.e., Ministère de la Transition Écologique et Solidaire, within the framework of the national research project (CARHAB – project no. 2101536326, Approche multi-scalaire de l'organisation des parcours substeppiques des Thero-Brachypodietea dans le sud-est de la France: apport à la compréhension des liens entre géocurtaséries et impacts anthropiques actuels et/ou passés. Received by TD). AG has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 896159.

## Acknowledgments

We thank Frédéric Bioret for his help initiating this project and Tania de Almeida, Elise Buisson, Julie Chenot, Aure Durbecq,

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Cannelle Moinardeau, and Daniel Pavon for their help with collecting floristic and soil data; Gaelle Besche and Fanny Sauguet for their help with obtaining grazing data; Christel Vidaller, Armin Bischoff, Olivier Blight, François Duchenne, and Mathieu Santonja for their constructive comments and advice during the data analyses; and the Federal State Nature Conservation Authority (CEN-PACA), the Crau nature reserve, and the *Le Merle* Domain and training center for shepherds for their permission to set up the experiments. We also thank two reviewers and one editor for their comments on a previous version of this manuscript.

## Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

## Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

## Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fevo.2022.879060/full#supplementary-material

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**EDITED BY**
Péter Tórök,
University of Debrecen,
Hungary

**REVIEWED BY**
László Erdős,
Hungarian Academy of Science,
Hungary
Stephen Venn,
University of Łódź,
Poland

*CORRESPONDENCE
Leonhard Sommer
✉ leonhard.sommer@umwelt.uni-giessen.de

**SPECIALTY SECTION**
This article was submitted to Conservation and Restoration Ecology, a section of the journal Frontiers in Ecology and Evolution

RECEIVED 04 October 2022
ACCEPTED 28 December 2022
PUBLISHED 16 January 2023

**CITATION**
Sommer L, Klinger YP, Donath TW, Kleinebecker T and Harvolk-Schöning S (2023) Long-term success of floodplain meadow restoration on species-poor grassland. *Front. Ecol. Evol.* 10:1061484. doi: 10.3389/fevo.2022.1061484

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© 2023 Sommer, Klinger, Donath, Kleinebecker and Harvolk-Schöning. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Long-term success of floodplain meadow restoration on species-poor grassland

Leonhard Sommer¹*, Yves P. Klinger¹, Tobias W. Donath², Till Kleinebecker¹ and Sarah Harvolk-Schöning¹

¹Division of Landscape Ecology and Landscape Planning, Department of Landscape Ecology and Resources Management, Justus Liebig University Giessen, Giessen, Germany, ²Department of Landscape Ecology, Institute for Natural Resource Conservation, Kiel University, Kiel, Germany

Restoration of floodplain meadows remains a challenge, as many degraded sites suffer from seed limitation. The transfer of seed-containing plant material from species-rich donor sites is a widely used method to restore semi-natural grasslands. However, most studies on the success of such restoration projects comprise limited time frames. As factors determining restoration success may only become evident after many years, long-term observations are crucial. We re-investigated 20 restored grassland sites in the floodplain of the Northern Upper Rhine 13–16 years after plant material transfer with different soil preparation treatments. To this end, we carried out vegetation surveys on 254 permanent plots and studied the potential influence of soil preparation, soil nutrients, and hydrology on plant species composition, diversity, and transfer of target species. Since sustainable agricultural use is important to ensure the long-term stability of restored semi-natural grasslands, we further investigated biomass productivity and feeding value. While most target species increased in frequency or remained stable over time, we found no positive long-term effect of soil preparation on vegetation development and target species establishment. Instead, increased biomass yield and flooding frequency led to reduced restoration success, while higher soil C/N ratios had a positive effect. Overall, restoration measures did not affect the agricultural value of the restored grasslands, which had higher dry matter biomass yields compared with the donor sites. Our results indicate that the positive effect of soil preparation on the number and cover of target species, which is regularly reported in short-term studies, diminishes over time, and other factors such as site conditions become increasingly important. Furthermore, additional plant material transfer or manual seeding may be necessary to support target species establishment. Concerning agricultural usability, the integration of restored floodplain meadows in farming systems is possible and can ensure long-term management and thus stability of these ecosystems. Our study shows that long-term monitoring of restoration projects is necessary, as factors determining restoration success may only become evident in the long-term.

**KEYWORDS**

conservation, farming, feeding value, green hay transfer, plant material transfer, seed limitation, soil disturbance
Introduction

The worldwide degradation of ecosystems is one of the most
urgent problems of our time (Díaz et al., 2019). Ecological
restoration is a major tool to counteract ecosystem degradation,
helping the health, integrity, and sustainability of ecosystems to
recover (Society for Ecological Restoration, 2004; IPBES, 2019).
The current UN “Decade on ecosystem restoration” (UN General
Assembly, 2019) underpins the increasing importance of this field.
Growing focus is given to the conservation and restoration of
grasslands, as they cover a large proportion of land surface and
provide high capacity to support biodiversity, multiple ecosystem
services and are integral to human well-being (Bardgett et al.,
2021). In Central Europe, semi-natural grasslands are of particular
importance. They are the result of centuries of human activity, and
low-intensive management by mowing or grazing is required to
restore and maintain these semi-natural ecosystems and the
services they provide (Bakker, 1989; Hejcman et al., 2013).

Floodplain meadows are outstandingly diverse grassland
ecosystems with many rare and endangered plant species
(Rodwell, 1992; Wesche et al., 2012). Historically, due to their high
productivity, they served as an important source for forage
provision for livestock (Rothero et al., 2016). Over the last decades,
massive structural changes in agriculture resulted in severe
consequences for floodplain meadows (Jefferson and Pinches,
2009). Conversion to arable fields, fertilisation, higher cutting
frequencies, and alterations of the hydrological conditions have
led to a drastic decline both in the amount of floodplain meadows
and their ecological quality (Böger, 1991; Joyce and Wade, 1998;
Bissels et al., 2004). The restoration of the plant diversity of
floodplain meadows is therefore urgent, but is a challenging and
long-lasting process (Engst et al., 2016).

The mere return to low-intensive management on degraded
floodplain meadows often fails, as typical plant species hardly
re-establish spontaneously. This is due to the transient soil seed
bank of many typical floodplain meadow species (Bekker et al.,
2000; Hölzel and Otte, 2004a) and lacking connectivity to the few
species-rich remnant populations (Donath et al., 2003; Bissels
et al., 2004). Therefore, active diaspore introduction is required to
re-establish the typical vegetation within a reasonable timespan
(Bissels et al., 2004; Vécrin et al., 2007; Jõgar and Moora, 2008;
Ludewig et al., 2021). Research projects have shown the suitability
of active species introduction for grassland restoration (Kiehl
et al., 2010). Out of the available methods, the transfer of freshly
cut plant material is considered particularly advantageous with
respect to genetic diversity and autochthonism, and additionally
enables the transfer of organisms other than plants, such as
invertebrates (Harnisch et al., 2014; Stöckli et al., 2021).

Generally, the restoration of species-rich grassland using
freshly cut plant material is more challenging on species-poor
grassland sites compared to arable fields or raw soils (Kiehl et al.,
2010; Hansen et al., 2022; Valkó et al., 2022). Soil preparation is
commonly regarded as an important prerequisite for successful
target species introduction. While it reduces competition by the

existing grassland vegetation and creates niches for germination
and successful establishment of seedlings with low competitive
power (Schmiede et al., 2012), there is increasing evidence that its
positive effects can diminish over longer time periods (Harvolk-
Schöning et al., 2020; Freitag et al., 2021). This affirms the
importance of long-term monitoring to evaluate the success of
restoration measures (Resch et al., 2019), as well as considering a
range of driving factors (Hölzel, 2019).

However, in addition to restoration, semi-natural grasslands
require adapted management to create adequate disturbance
regimes and to overcome seed limitation (Klinger et al., 2021).
Typically, management of floodplain meadows consists of
mowing, which was traditionally complemented by grazing in
some areas (Kapfer, 2010). To ensure an adequate management,
farmers often receive subsidies as part of agri-environment
schemes (Donath et al., 2021; European Environment Agency,
2022). However, the acceptance for low-intensity management
practices might be increased if the biomass produced on these
sites could be used profitably. Thus it is desirable to keep floodplain
meadows integrated in the regional farming systems (Tallowin
and Jefferson, 1999; Donath et al., 2015). This was commonly the
case until the middle of the last century, but with more possibilities
to increase productivity, e.g., by fertiliser input, the interest of
farmers to continue this practice decreased (Hejcman et al., 2013).
If it could be shown that species diversity and composition had
neutral or positive effects on fodder quantity and/or quality, this
might increase the motivation of farmers to re-establish the
management of sites with high nature conservation value (Donath
et al., 2015). Donath et al. (2015) found that in comparison to sites
with low nature conservation value, the fodder quality was
comparable or even higher in sites with high nature conservation
value, and that the harvested material could be integrated in
farming systems. If this were the case also for restored semi-
natural grasslands, a sustainable management of these sites and
thus long-term restoration success could be ensured easier.

Soil conditions and productivity of floodplain meadows are
linked to their agricultural value, which may consequently result
in a conflict of goals for any restoration efforts (Donath et al.,
2015). Increased nutrient levels can hamper the establishment of
target species (Gough and Marrs, 1990; Pywell et al., 2006; Waldén
and Lindborg, 2016), but relevant nutrients and respective
thresholds vary between study systems. In addition, nutrient
stoichiometry can modify restoration outcomes, as, e.g., limitation
by nitrogen (N) has been shown to compensate for negative
impacts of high P and K availability, restricting productivity and
species competition (Pywell et al., 2002; Donath et al., 2007).
Additionally, hydrological conditions such as flood and drought
frequencies can strongly affect species composition in floodplains
(Hölzel, 1999; Mathar et al., 2015), but their impact on restoration
success has barely been studied so far.

In a large-scale floodplain meadow restoration experiment
with plant material transfer at the Northern Upper Rhine in
Germany, the effect of soil preparation and soil properties on
species establishment on species-poor grassland had been
investigated over the first 3 years (Schmiede et al., 2012). Here, we re-investigated the sites 13–16 years after the restoration to answer the following questions:

a. How have the target species developed on the restoration sites, and is the effect of soil preparation on species richness and composition still detectable after 13–16 years?

b. Do the restoration sites differ from the donor sites and the unrestored grassland in the close surrounding with respect to their ecological properties?

c. What is the agricultural value of the restoration sites, compared to unrestored reference grassland in the surrounding and the donor sites?

d. Which effect do soil properties, productivity, nutrient stoichiometry, and hydrological characteristics of the restoration sites have on the long-term restoration success?

# Materials and methods

## Study site

The study area is located approximately 30 km southwest of Frankfurt in Hesse (Germany), in the floodplain of the Northern Upper Rhine. The mean annual temperature of 11.1°C marks the region as one of the warmest in Germany, and the mean annual precipitation is relatively low with 550 mm (HLNUG, 2022; stations Frankfurt (Main) Airport for temperature and Groß-Gerau-Wallerstädten for precipitation, 1992–2021). The fluctuating water level of the river Rhine results in both floods and droughts, with groundwater levels of up to 5 m below the surface (HLNUG, 2021). Soils are characterised by high clay contents often exceeding 50% (Burmeier et al., 2010), which adds to the alternating soil water conditions. The specific site conditions and low-intensive haymaking supported the development of species-rich floodplain meadows of the alliances *Molinion* and *Cnidion* (habitat types 6410 and 6440 according to the EU Fauna-Flora-Habitat directive), containing a high number of rare and endangered (alluvial) grassland species (Hölzel, 1999; Donath et al., 2003). However, intensification and conversion into arable fields caused massive habitat losses in the course of the 20th century, leaving only small isolated remnants of species-rich floodplain meadows (Böger, 1991; Hölzel and Otte, 2003).

## Restoration sites and measures

After a series of major floods in 1983, 150 ha of arable fields were converted to non-intensively managed, unfertilized grassland in order to re-establish species-rich floodplain meadows (Böger, 1991; Bissels et al., 2004). However, typical species hardly re-immigrated, and the re-established grassland in the study area remained rather species-poor (Schmiede et al., 2012). From 2005

to 2008, freshly mown plant material (seed-containing green hay sensu Kiehl et al., 2010) was gained from eight donor sites to create 20 strips (“restoration sites”) on different species-poor grassland sites. The donor sites consisted of species-rich *Molinion* or *Cnidion* meadows. Each restoration site was 120 m long and 10 m wide and divided in three segments of 40 m length, each of which had been prepared 2–7 weeks before the plant material transfer. All three segments had been mown, and then treated as following:

* rotovated twice,

* ploughed and harrowed, or

* left *untilled*.

Rotovating broke up the soil surface, while ploughing turned over the topsoil, with subsequent harrowing breaking up the new surface and levelling it (Supplementary Figure A1). Both treatments left a fine-grained seedbed with close to no intact vegetation, but elimination was more complete after ploughing and harrowing. However, depending on the timespan until plant material application, modest regrowth occurred on both treatments. Treatments were randomly arranged on each restoration site. Plant material transfer took place between mid-September and the end of October, when most species on the donor sites carried ripe seeds. Harvest coincided with the first cut (two donor sites, five restoration sites) or second cut (six donor sites, 15 restoration sites), depending on the mowing regime at the donor sites. A detailed description of restoration measures and sites can be found in Schmiede et al. (2012).

## Vegetation sampling

Between 10 May and 13 June 2021, we investigated the vegetation on 254 plots (25 m²). From these, 180 were located on the 20 restoration sites (nine per site, three per treatment). For nine of the 20 restoration sites, the plots had been previously studied by Schmiede et al. (2010) annually in the first 3 years after restoration, enabling comparison over time.

Additionally, as a reference, we placed 40 plots (two per restoration site) on the unrestored grassland surrounding all restoration sites, with a distance > 15 m to the restoration sites. Furthermore, on the eight donor sites, 34 plots were surveyed (3–5 per site, depending on their size). To enable comparability with the data of Schmiede et al. (2012), species abundance was recorded using the modified Braun-Blanquet scale (van der Maarel, 1979). For data analysis, species abundance classes were transformed to percentage values following the approach of Schmiede et al. (2012). In addition to the vegetation plots, we recorded whole-site species lists for restoration and donor sites and estimated species abundances using a DAFOR scale (Norfolk Wildlife Trust, n.d.) with modifications (Supplementary Table A1).
## Soil and biomass sampling and analysis

In April and May 2021, we gathered soil samples from each of the 254 plots. To this end, composite samples of four topsoil cores (0–10 cm) were collected using a soil corer of 2.5 cm diameter. Samples were air-dried and sieved to 2 mm. Soil pH was measured in CaCl₂ solution. The samples were extracted with calcium-acetate-lactate solution (CAL) for the determination of plant-available potassium (K) and phosphorus (P) (Blume et al., 2000). Total soil nitrogen (N) and carbon (C) were measured via elementary analysis (device “Unicube,” co. “elementar”; DIN EN 16168, 2012; DIN EN 15936, 2012), an organic C was calculated from the CaCO₃ content determined with the Scheibler method (Blume et al., 2000). The organic C content was calculated as the difference between total and anorganic C content, and the C/N ratio as the ratio between organic C and total soil N content (Kuntze et al., 1994).

For each plot, aboveground biomass was harvested in four randomly placed quadrats of 0.1 m² at a height of 5 cm. Sampling took place between end of May and beginning of June, shortly before the regular first grassland cut at 8 June. Most of the donor sites are cut later in summer, but were sampled at the same time for comparability. Biomass samples were merged for each plot to one composite sample, dried at 60°C for 48 h, weighed, and milled to 0.5 mm. The acid detergent fibre (ADF), N, K, and P contents were determined via Near Infrared Spectroscopy (NIRS, details see Kleinebecker et al., 2011). As measures of nutrient stoichiometry, we calculated the N/K and N/P ratios. For feeding value assessment, we calculated the crude protein content (XP; Roth et al., 2011), the digestible energy (DE) for horses (National Research Council, 1999), the metabolisable energy (ME) for ruminants, and the net energy for lactation (Kirchgeßner and Kellner, 1982).

## Hydrological variables

For calculation of hydrological variables, we used data from 33 groundwater wells (HLNUG, 2021) and daily water levels for 12 points of the river Rhine along the study area between 1 January 2001 and 31 December 2020. If data gaps for the groundwater wells were ≤ 30 days, we interpolated the groundwater levels (GWL) between adjacent time points to obtain daily groundwater water levels. The daily Rhine water levels were linearly interpolated between gauging stations Mainz, Nierstein-Oppenheim, and Worms (Wasserstraßen-und Schifffahrtsverwaltung des Bundes, 2021). The 45 groundwater points were used for daily Delaunay triangulation (Sinclair, 2016), including all points with an entry for the respective day. The daily groundwater level of each of the 254 plots was estimated as the inverse-distance weighted mean of the three nearest groundwater points. For each plot, we calculated three relevant hydrological predictors for species distribution (following Gattringer et al. (2019)):

* days per year with GWL > 0.7 m below ground (“Drought frequency”).

* days per year with inundation height > 0.5 m (“Flood frequency”).

* standard deviation of the GWL (“SD of GWL”).

The location in the fossil floodplain, which is protected from flooding by a dyke, and the recent functional floodplain is often used as a hydrological predictor for ecological properties of floodplain meadows (e.g., Bissels et al., 2004; Donath et al., 2007). For our restoration sites, it was well represented by the SD of GWL. The mean was 0.72 m ± SD of 0.14 m for sites located in the functional floodplain, and 0.37 m ± 0.11 m for sites located in the fossil floodplain, respectively. Thus, we focused on the SD of GWL for further analysis, instead of the floodplain compartment.

## Statistical analysis

To assess the impact of soil preparation over time, we compared the number and cover of target species (Schmiede et al., 2012, slightly modified, Table 1) as well as the number of species of the three soil preparation treatments for each of the first 3 years after restoration and for 2021 separately for the previously studied restoration sites. If an ANOVA indicated significant differences, these were identified with a Tukey honest-significant difference test (HSD; α = 0.05). Data were ln-transformed to meet normality and homoscedasticity, and model assumptions were checked visually using diagnostic plots (Kozak and Piepho, 2018).

To assess temporal trends of the individual target species, we calculated their occurrence frequencies in the third year after restoration and in 2021 for the previously studied restoration sites on a plot basis. For comparison, occurrence frequencies in the plant material and mean diaspore input per target species for each restoration site were calculated from the plant material data of Schmiede et al. (2010). We performed analogous frequency calculations for the corresponding unrestored reference plots of the previously studied restoration sites and for the donor site plots from the 2021 data.

We explored the temporal development of the vegetation composition on the restoration sites using non-metric multidimensional scaling (NMDS) ordination for the previously studied restoration sites for (a) the first 3 years after restoration and (b) for 2021, including the corresponding unrestored reference and donor site plots. We performed a second NMDS for all restoration sites, unrestored reference plots, and donor sites. Ordinations were based on Bray-Curtis Distances, max. 100 iterations, and a random starting configuration. Three-dimensional solutions were chosen by visually checking the decrease of stress values with increasing number of dimensions, according to Leyer and Wesche (2008). To explore underlying ecological gradients, we included vectors for the number of species and target species, the proportions of plant life forms and life span groups, mean Ellenberg indicator values for light (L),
<table><caption>TABLE 1 Development of target species over time.</caption><thead><tr><th rowspan="2">Target species</th><th rowspan="2">RL</th><th rowspan="2">Trend on RS</th><th colspan="7">Frequency (%)</th></tr><tr><th>RS (third year)</th><th>RS (2021)</th><th>UG</th><th>DS</th><th>PM</th><th>MDI</th></tr></thead><tbody><tr><td colspan="9"><strong>Increased frequency</strong></td></tr><tr><td>Arabis hirsuta</td><td>V</td><td>✓</td><td>0</td><td>17</td><td>11</td><td>15</td><td>0</td><td>0</td></tr><tr><td>Bromus erectus</td><td>*</td><td>✓</td><td>0</td><td>6</td><td>0</td><td>32</td><td>22</td><td>6</td></tr><tr><td>Carex praecox</td><td>V</td><td>✓</td><td>2</td><td>15</td><td>6</td><td>12</td><td>78</td><td>12</td></tr><tr><td>Galium boreale</td><td>V</td><td>✓</td><td>9</td><td>17</td><td>0</td><td>15</td><td>78</td><td>225</td></tr><tr><td>Genista tinctoria</td><td>V</td><td>✓</td><td>2</td><td>11</td><td>0</td><td>41</td><td>22</td><td>9</td></tr><tr><td>Inula britannica</td><td>V</td><td>✓</td><td>9</td><td>11</td><td>0</td><td>6</td><td>89</td><td>1,636</td></tr><tr><td>Inula salicina</td><td>V</td><td>✓</td><td>17</td><td>26</td><td>11</td><td>53</td><td>100</td><td>890</td></tr><tr><td>Iris spuria</td><td>2</td><td>✓</td><td>0</td><td>21</td><td>0</td><td>12</td><td>33</td><td>9</td></tr><tr><td>Peucedanum officinale</td><td>3</td><td>✓</td><td>9</td><td>17</td><td>0</td><td>50</td><td>56</td><td>6</td></tr><tr><td>Pimpinella saxifraga</td><td>*</td><td>✓</td><td>4</td><td>5</td><td>0</td><td>6</td><td>33</td><td>6</td></tr><tr><td>Scutellaria hastifolia</td><td>2</td><td>✓</td><td>2</td><td>4</td><td>0</td><td>3</td><td>33</td><td>1</td></tr><tr><td>Viola pumila</td><td>2</td><td>✓</td><td>0</td><td>5</td><td>0</td><td>6</td><td>56</td><td>15</td></tr><tr><td>Viola stagnina</td><td>2</td><td>✓</td><td>1</td><td>4</td><td>0</td><td>12</td><td>11</td><td>5</td></tr><tr><td colspan="9"><strong>Reduced frequency</strong></td></tr><tr><td>Arabis nemorensis</td><td>2</td><td>✓</td><td>47</td><td>31</td><td>11</td><td>12</td><td>89</td><td>1,294</td></tr><tr><td>Bupleurum falcatum</td><td>V</td><td>✓</td><td>4</td><td>0</td><td>0</td><td>3</td><td>0</td><td>0</td></tr><tr><td>Dipsacus laciniatus</td><td>*</td><td>✓</td><td>6</td><td>0</td><td>0</td><td>0</td><td>11</td><td>0</td></tr><tr><td>Linum catharticum</td><td>*</td><td>✓</td><td>14</td><td>1</td><td>6</td><td>12</td><td>78</td><td>39</td></tr><tr><td>Rhinanthus alectorolophus</td><td>*</td><td>✓</td><td>5</td><td>0</td><td>0</td><td>6</td><td>0</td><td>0</td></tr><tr><td>Selinum carvifolia</td><td>V</td><td>✓</td><td>6</td><td>2</td><td>11</td><td>18</td><td>44</td><td>16</td></tr><tr><td>Senecio aquaticus</td><td>V</td><td>✓</td><td>5</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Silaum silaus</td><td>V</td><td>✓</td><td>7</td><td>5</td><td>6</td><td>21</td><td>33</td><td>4</td></tr><tr><td colspan="9"><strong>Stable frequency</strong></td></tr><tr><td>Sanguisorba officinalis</td><td>V</td><td>↔</td><td>20</td><td>19</td><td>0</td><td>62</td><td>67</td><td>2</td></tr><tr><td>Thalictrum flavum</td><td>V</td><td>↔</td><td>4</td><td>4</td><td>6</td><td>9</td><td>33</td><td>2</td></tr><tr><td>Valeriana pratensis.</td><td>*</td><td>↔</td><td>15</td><td>15</td><td>11</td><td>21</td><td>11</td><td>1</td></tr><tr><td>Veronica maritima</td><td>V</td><td>↔</td><td>19</td><td>19</td><td>0</td><td>6</td><td>56</td><td>89</td></tr><tr><td colspan="9"><strong>No establishment</strong></td></tr><tr><td>Allium angulosum</td><td>3</td><td>-</td><td>0</td><td>0</td><td>0</td><td>15</td><td>78</td><td>139</td></tr><tr><td>Betonica officinalis</td><td>V</td><td>-</td><td>0</td><td>1</td><td>0</td><td>12</td><td>0</td><td>0</td></tr><tr><td>Bromus racemosus</td><td>3</td><td>-</td><td>0</td><td>2</td><td>11</td><td>12</td><td>0</td><td>0</td></tr><tr><td>Carex panicea</td><td>V</td><td>-</td><td>0</td><td>0</td><td>0</td><td>18</td><td>22</td><td>1</td></tr><tr><td>Carex tomentosa</td><td>3</td><td>-</td><td>1</td><td>0</td><td>0</td><td>29</td><td>89</td><td>4</td></tr><tr><td>Cirsium tuberosum</td><td>3</td><td>-</td><td>2</td><td>1</td><td>6</td><td>15</td><td>0</td><td>0</td></tr><tr><td>Gentiana pneumonanthe</td><td>2</td><td>-</td><td>0</td><td>0</td><td>0</td><td>3</td><td>0</td><td>0</td></tr><tr><td>Hippocrepis comosa</td><td>V</td><td>-</td><td>1</td><td>0</td><td>0</td><td>6</td><td>0</td><td>0</td></tr><tr><td>Iris sibirica</td><td>3</td><td>-</td><td>0</td><td>1</td><td>0</td><td>12</td><td>11</td><td>0</td></tr><tr><td>Juncus alpinoarticulatus</td><td>V</td><td>-</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Lathyrus palustris</td><td>3</td><td>-</td><td>0</td><td>0</td><td>0</td><td>3</td><td>0</td><td>0</td></tr><tr><td>Lotus maritimus</td><td>3</td><td>-</td><td>1</td><td>0</td><td>0</td><td>9</td><td>22</td><td>1</td></tr><tr><td>Lotus tenuis</td><td>V</td><td>-</td><td>2</td><td>0</td><td>0</td><td>3</td><td>33</td><td>3</td></tr><tr><td>Melampyrum cristatum</td><td>3</td><td>-</td><td>2</td><td>0</td><td>0</td><td>21</td><td>0</td><td>0</td></tr><tr><td>Molinia caerulea</td><td>*</td><td>-</td><td>2</td><td>0</td><td>0</td><td>24</td><td>56</td><td>40</td></tr><tr><td>Potentilla erecta</td><td>*</td><td>-</td><td>2</td><td>0</td><td>0</td><td>12</td><td>22</td><td>1</td></tr><tr><td>Sanguisorba minor</td><td>*</td><td>-</td><td>1</td><td>0</td><td>0</td><td>6</td><td>0</td><td>0</td></tr><tr><td>Selinum dubium</td><td>2</td><td>-</td><td>0</td><td>0</td><td>0</td><td>3</td><td>0</td><td>0</td></tr><tr><td>Serratula tinctoria</td><td>3</td><td>-</td><td>1</td><td>1</td><td>0</td><td>32</td><td>56</td><td>10</td></tr><tr><td>Succisa pratensis</td><td>V</td><td>-</td><td>1</td><td>0</td><td>0</td><td>32</td><td>11</td><td>0</td></tr><tr><td>Viola elatior</td><td>2</td><td>-</td><td>0</td><td>0</td><td>0</td><td>6</td><td>44</td><td>1</td></tr></tbody></table>

Red List status (RL) refers to Germany (Metzing et al., 2018). *, not endangered; V, warning list; 3, endangered; and 2, seriously endangered. For the previously studied restoration sites (RS), plot-level frequencies are given for the third year after restoration and for 2021 (n = 81, respectively). The trends are only given for species with a frequency > 3% in at least 1 year. If the change is ≤20% of the third year value, the trend is regarded as stable. Plot-level frequencies for the unrestored reference grassland (UG, n = 18) and the donor sites (DS, n = 34) refer to the 2021 vegetation surveys. Frequencies for plant material (PM) and the mean diaspore input (MDI, units per m²) refer to plant material samples (n = 9) taken by Schmiede et al. (2010).
temperature (T), continentality (K), moisture (F), nutrients (N), and soil reaction (R), the proportion of indicator species for alternating water levels (data from Klotz et al., 2002), as well as the soil, biomass, and hydrological variables described above. The package “vegan” was used for the ordination (Oksanen et al., 2020).

We compared the different soil preparation treatments of all restoration sites with the unrestored reference grassland and the donor sites concerning soil C/N ratio, total soil N, plant available soil P and K, species and target species numbers, cover of target species, biomass yield, and energy content measures. Variables were pooled at the treatment level for the restoration sites and at the site level for the references. To this end, we performed an ANOVA, followed by a Tukey HSD test (α=0.05). Data were ln-transformed if diagnostic plots indicated violations against model presumptions (Kozak and Piepho, 2018).

We calculated four indicators to quantify the long-term restoration success of the restoration sites at the site level, following Kiehl et al. (2010) (Supplementary Table A2). These were (a) absolute transfer rate of species, (b) absolute transfer rate of target species, (c) relative transfer rate of species, and (d) relative transfer rate of target species. We defined absolute and relative transfer rates for all species and for target species as the ratios between transferred and transferable species. For absolute transfer rates, species were regarded as transferable if their DAFOR abundance was R2 or higher on at least one corresponding donor site of a restoration site. For relative transfer rates, species found in the plant material from the respective restoration site (Schmiede et al., 2010) were regarded as transferable. A transferable species was regarded as transferred if recorded on a restoration site in 2021. Species from the corresponding unrestored reference plots were regarded as resident and excluded from the pool of transferable and transferred species for the respective restoration site. We opted for the calculation of both absolute and relative transfer rates as we had more data points for the absolute transfer rates (n=20). However, since the relative transfer rates (n=15) are based on the species composition of the plant material used for restoration, they are considered a more direct success measure. At plot level, we calculated the (e) increase in target species number and (f) increase in target species cover as the difference between the plot on the restoration site and the mean of the corresponding unrestored reference plots.

To identify factors determining the restoration success, linear regression models were used for the six success variables (a–f) separately at site level. Eleven explanatory variables were included in the model selection using the “dredge” function (R package MuMln, Bartoń, 2020). These were the N/P and N/K ratio of the biomass, biomass yield, soil pH, plant-available P and K, soil organic C content, and the C/N ratio. Soil N content was not included due to high correlation with soil organic C (r=0.995). Drought and flood frequency and the SD of GWL were included as hydrological variables. The explanatory variables were centred to a mean of 0 and scaled to a standard deviation of 1. The model with the lowest AIC that showed no multicollinearity (all variance inflation factors ≤2.5) was selected.

# Results

## Development of the restoration sites over time

The development over time can only be assessed for the previously studied restoration sites, which were restored in 2005 and 2006, so the observation period is 15–16 years here. After that time, the differences between soil preparation treatments concerning target species number and cover vanished (Figure 1). Compared with the first years after restoration, in the long-term, both variables remained relatively stable for the ploughed and rotovated treatments but increased for the untilled treatment. In 2021, the mean number of target species per 25 m² ranged from 2.2 ± 0.5 (ploughed, mean ± SE) to 3.0 ± 0.5 (rotovated), and mean target species cover ranged from 3.1 ± 0.8 (untilled) to 3.5 ± 0.9% (rotovated). The mean number of species per plot was around 25 for all treatments. For the untilled treatment, this marked a stable trend since the third year after restoration, whereas the species number per plot decreased from around 38 to 25 species for the treatments with soil preparation. This finding was supported by the NMDS ordination of the previously studied restoration sites indicating that species composition of soil disturbance plots became more similar to the unrestored reference plots until 2021 (Supplementary Figure A2).

Out of the 46 target species, 13 showed a higher frequency at the restoration sites in 2021 compared to 3 years after restoration (Table 1). Among these, we found a range of Red List species, such as Carex praecox, Galium boreale, Genista tinctoria, Iris spuria, and Peucedanum officinale. During the investigation period, eight target species decreased in frequency. These had been mostly recorded with low frequencies by Schmiede et al. (2010) already, such as Bupleurum falcatum, Rhinanthus alectorolophus, and Selinum carvifolia. An exception was Linum catharthicum, which was recorded only in 1% of the restoration plots in 2021, compared to 14% 3 years after restoration. Sanguisorba officinalis and Veronica maritima remained relatively stable with a frequency of around 20%, respectively.

## Ecological comparison between restoration sites and references

The NMDS of all restoration sites and the references for 2021 revealed that the donor sites were separated from the unrestored reference grassland and the restoration sites (Figure 2). While there was a wide overlap between the latter two groups, the centroid of the unrestored reference grassland was separated from the centroids of the restoration soil treatments, which were all slightly shifted towards the donor sites. The donor sites were characterised by higher target species and species numbers, energy contents, Ellenberg R values, and drought frequency compared to the other groups. Both the restored and unrestored sites were characterised by higher productivity levels, indicated by
<figure><img src="image_14.png" /><figcaption>FIGURE 1</figcaption></figure>

Development of the number (A) and cover (B) of target species and the number of species (C) per 25m² over time after the transfer of plant material on the previously studied restoration sites for the three different treatments ploughed, rotovated, and untilled (n=9, respectively). Significant differences within years (p<0.05, In-transformed data) are indicated by different letters above the bars. Whiskers refer to the standard errors.

<figure><img src="image_15.png" /><figcaption>FIGURE 2</figcaption></figure>

Non-metric multidimensional scaling (NMDS) of the vegetation plots for all restoration sites, the unrestored reference grassland and the donor sites in 2021 (axis 1 and 2 of the three-dimensional solution are shown). Final stress: 16.9. Plots are grouped by donor sites (DS), unrestored reference grassland (UG), and restoration sites with the treatments ploughed (RP), rotovated (RR), and untilled (RU). The group labels are located at the centroids of the groups. Vectors with r²>0.3 are displayed. For better readability, the cover of target species, the metabolisable energy (high correlation with number of species and target species) were removed despite r²>0.3.

increased Ellenberg N values and biomass yields compared with the donor sites.

Concerning soil nutrient status, the restoration sites and the unrestored reference grassland were very similar (Figure 3). Their C/N ratio averaged at 11.0±0.1 (± SE), compared to 11.9±0.3 for

the donor sites. No significant differences between the groups were found for total nitrogen, plant-available P and K contents. However, soil nutrient contents of the donor sites were lower than those of the restoration sites and unrestored reference plots. Especially the low and very narrow plant-available P content of the donor sites (0.9±0.1%) was noticeable.

In 2021, over all restoration sites, the number of target species per plot was similar for all soil treatments with an average of 1.9±0.3 (Figure 4A) and significantly higher than for the unrestored reference grassland (0.7±0.2), but significantly lower than for the donor sites (7.0±1.4). Although not significant, mean cover of target species was higher on the restoration sites (2.1±0.4%) than on the unrestored reference grassland (1.3±0.6%; Figure 4B). For the donor sites, however, target species cover was significantly and markedly higher (mean = 19.7±5.0%). The same held true for the number of recorded plant species (Figure 4C).

## Feeding value of the grassland stands

The biomass yield levels of the restoration sites (407±26 g/m²) and the unrestored reference grassland (421±36 g/m²) did not differ but both were significantly higher compared to the donor sites, which had an average yield of 239±29 g/m² (Figure 5A). The energy content variables for cattle and horses were similar between restoration sites and the unrestored reference grassland, with those of the donor sites being 4–5% higher (Figures 5B–D).

## Drivers of restoration success

Absolute transfer rates of both all species and target species averaged at 40.1±3.9 and 36.4±6.2%, respectively
<figure><img src="image_16.png" /><figcaption>FIGURE 3</figcaption></figure>

Box-whisker plots of the soil C/N ratio (A), total nitrogen (%; B), plant-available P (mg/100g; C), and plant-available K (mg/100g; D) in 2021 on the different site categories—donor sites (DS, n=8), all restoration sites with treatments ploughed (RP), rotovated (RR), and untilled (RU), and unrestored reference grassland (UG; n=20, respectively). Plot data were averaged on the treatment level or, in case of DS and UG, on the site level. Red dots display the mean values. Significant differences (*p*<0.05) are indicated by different letters above the boxes (testing on ln-transformed data for soil P and soil K).

(Supplementary Table A2). The corresponding relative transfer rates were 24.9 ± 1.6 and 34.7 ± 3.7%. Higher biomass yield was generally associated with lower numbers of target species and reduced absolute transfer rates of species and target species (Table 2). The C/N ratio was positively associated with both the number and the cover of target species. Out of the hydrological variables, higher flood frequency tended to reduce restoration success, while higher drought frequency and variation of the groundwater level tended to have positive effects. The R² of the selected models ranged from 36 to 65%, except for the relative transfer rate of species, which could not be explained (R² = 1%).

# Discussion

## Vegetation development over time

We found no effect of soil preparation on vegetation development and target species establishment 13–16 years after restoration. This is surprising, as one of the main findings of Schmiede et al. (2012) was that soil disturbance, especially

ploughing, enabled better (target) species establishment due to suppression of the existing grassland vegetation. This is a common observation among different grassland types, so that soil preparation prior to diaspore introduction in species-poor grassland is often recommended (Kiehl et al., 2010). However, studies deriving such advice from their findings mostly have short observation timeframes and to the best of our knowledge do not exceed 8 years (Edwards et al., 2007; Bischoff et al., 2018; Durbecq et al., 2021). In line with our findings, recent studies on floodplain meadow restoration by Harvolk-Schöning et al. (2020) and Heilscher (2020) indicate that the positive effect of soil preparation on the number and cover of introduced species diminishes in the long run.

Initially, soil disturbance creates micro-niches for germination and establishment of species from the plant material (Harvolk-Schöning et al., 2020), but also activates the soil seed bank (Schmiede et al., 2012; Ludewig et al., 2021). In the short term, this leads to promotion of ruderal species (Klaus et al., 2018). Accordingly, in our experiment, ruderal species, such as *Cirsium arvense*, *Galium aparine*, or *Lactuca serriola* emerged in high frequencies over the first 3 years after restoration, but receded in
<figure><img src="image_17.png" /><figcaption>FIGURE 4</figcaption></figure>

Box-whisker plots of the number of target species per plot (A), the cover of target species (%: B), and the number of species per 25m² plot (C) in 2021 on the different site categories—donor sites (DS, n=8), all restoration sites with treatments ploughed (RP), rotovated (RR), and untilled (RU), and unrestored reference grassland (UG; n=20, respectively). Plot data were averaged on the treatment level or, in case of DS and UG, on the site level. Red dots display the mean values. Significant differences (p<0.05) are indicated by different letters above the boxes (testing on ln-transformed data for number and cover of target species).

the long run. In contrast, some target species such as *Inula britannica* or *Carex praecox* emerged later or developed more slowly. This was presumably due to competition with the resident vegetation, but these species established in the long run even without tillage.

Across all treatments, target species that were already present 3 years after restoration mostly remained stable or increased in frequency until 2021. This is in accordance with the stable target species number on plots with soil disturbance and the observed increase for the untilled treatment. An especially encouraging case is *Iris spuria*, which was not detected by Schmiede et al. (2012) in the first 3 years after restoration, but was detected in considerable amounts on two restoration sites in 2021. The hard seed coat of this species can delay germination, so that establishment happens only after longer time periods (Hölzel and Otte, 2004b). Harvolk-Schöning et al. (2020) observed a similar pattern for *Iris spuria* on former arable fields. Our results clearly show that in the longer term, the establishment of this highly endangered species is possible on grasslands lacking typical floodplain meadow species.

Many target species were not successfully established, some of them despite frequent occurrence on the donor sites. For example, *Succisa pratensis* was barely captured in the plant material, which may be due to asynchronous fruit ripening with only a small proportion of ripe seeds when the plant material was harvested, as this species has a long flowering and seed shedding period (Adams, 1955). However, after-ripening of seeds may lead to increased germination even when they are harvested in an unripe state, as was shown for the non-native *L. polyphyllus* in mountain grasslands (Klinger et al., 2020). Diaspores of *Allium angulosum*, *Selinum carvifolia*, and *Serratula tinctoria* were captured in considerable amounts (in ≥44% of plant material samples and with ≥10 diaspores per m² on average, respectively), but established poorly or not at all, with an occurrence frequency of 6% at maximum on the previously studied restoration sites over the whole observation period. This matches with observations by Harvolk-Schöning et al. (2020), and could be a consequence of specific germination requirements, e.g., characteristic temperature regimes (Hölzel and Otte, 2004a; Wagner et al., 2021).
<figure><img src="image_18.png" /><figcaption>FIGURE 5</figcaption></figure>

Box-whisker plots of the biomass yield (g/m²; A), the digestible energy for horses (MJ/kg; B), the metabolisable energy for ruminants (MJ/kg; C), and the net energy for lactation (MJ/kg; D; all referring to dry matter) in 2021 on the different site categories—donor sites (DS, n=8), all restoration sites with treatments ploughed (RP), rotovated (RR), and untilled (RU), and unrestored reference grassland (UG; n=20, respectively). Plot data were averaged on the treatment level or, in case of DS and UG, on the site level. Red dots display the mean values. Significant differences (*p*<0.05) are indicated by different letters above the boxes (testing on ln-transformed data for biomass yield).

## Ecological comparison of restoration sites, unrestored reference grassland, and donor sites

Our findings on the nutrient levels for the grassland sites overall matched those of former studies in the region (Donath et al., 2007, 2015; Schmiede et al., 2012). Grasslands of high nature conservation value, often used as donor sites, consistently had much lower plant-available P contents and moderately lower plant-available K contents than species-poor grassland sites often chosen for restoration. For the N contents, no such pattern had been found in those studies. In our study, the tendency to increased N contents of the restoration sites and the untreated reference grasslands compared with the donor sites is probably due to seven restoration sites with high organic C contents of 8.6 ± 0.5% (mean ± standard error; vs. 4.9 ± 0.3% for the other 13 restoration sites). The higher average C/N ratios of the donor sites are mainly driven by two poor Molinion sites with very wide ratios of 12.9 and 13.7, respectively.

A range of rare and endangered plant species of floodplain meadows, many of which are listed in the Red Lists of Germany and Hesse, were successfully established on the restoration sites. However, our results confirm that the ecological restoration of grassland is challenging, even if the sward is disturbed prior to diaspore introduction (Kiehl et al., 2010; Harvolk-Schöning et al., 2020; Hansen et al., 2022). Thirteen to sixteen years after restoration, the vegetation composition of the restored plots was similar to the unrestored reference grassland plots, with only slight changes towards the composition of the donor sites. Nevertheless, the number of target species was significantly higher for restoration sites and also their cover increased, compared with the unrestored reference.

## Feeding value of the site categories

Different restoration measures affected neither the yield nor the energy content of the aboveground biomass. While a change in yield was not expected, a more diverse species composition
<table><caption>TABLE 2 Overview of the regression models selected by AIC criterion for the ecological restoration success variables on the site level.</caption><thead><tr><th></th><th>Absolute TR target species (%)</th><th>Absolute TR species (%)</th><th>Relative TR target species (%)</th><th>Relative TR species (%)</th><th>Increase in target species number per plot</th><th>Increase in target species cover (%)</th></tr></thead><tbody><tr><td>Intercept</td><td>5.578***</td><td>40.111***</td><td>21.993**</td><td>24.952***</td><td>1.231***</td><td>28.588***</td></tr><tr><td>Biomass yield</td><td>-1.564***</td><td>-9.817*</td><td>.</td><td>.</td><td>-0.591*</td><td>.</td></tr><tr><td>Soil C/N ratio</td><td>.</td><td>.</td><td>.</td><td>.</td><td>1.039***</td><td>4.657*</td></tr><tr><td>Soil P</td><td>.</td><td>5.968</td><td>.</td><td>.</td><td>.</td><td>.</td></tr><tr><td>Soil pH</td><td>.</td><td>.</td><td>15.183</td><td>.</td><td>.</td><td>.</td></tr><tr><td>SD of GWL</td><td>.</td><td>.</td><td>.</td><td>.</td><td>.</td><td>4.925*</td></tr><tr><td>Flood frequency</td><td>-0.998*</td><td>-4.351</td><td>.</td><td>-1.784</td><td>-0.567*</td><td>-2.682</td></tr><tr><td>Drought frequency</td><td>.</td><td>.</td><td>13.310*</td><td>.</td><td>.</td><td>.</td></tr><tr><td>n</td><td>20</td><td>20</td><td>15</td><td>15</td><td>20</td><td>20</td></tr><tr><td>R<sup>2</sup></td><td>0.65</td><td>0.39</td><td>0.36</td><td>0.01</td><td>0.60</td><td>0.42</td></tr><tr><td>AIC</td><td>78.2</td><td>166.4</td><td>120.2</td><td>100.2</td><td>60.4</td><td>145.9</td></tr><tr><td>λ</td><td>0.5</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1.5</td></tr></tbody></table>

TR, transfer rate. Rows represent the estimates for the different explanatory variables included in the selected models—the biomass yield, the C/N ratio, plant-available P content and pH of the soil, the SD of the groundwater level, the flood and drought frequency (all standardised to mean = 0 and SD = 1). Variables with a dot were not selected in the respective model. Significance levels are given as following: ***$p \le 0.001$, **$p \le 0.01$, and *$p \le 0.05$. n, number of observations; R², adjusted R² of the model; AIC, akaike information criterion; and λ, value of λ for the Box-Cox transformation of the response variable.

with a higher proportion of forbs can be associated with higher energy contents of the biomass in floodplain meadows (Donath et al., 2004). The similar biomass energy contents of restored and unrestored reference grasslands can be explained by the marginal effects of restoration measures on the overall vegetation composition.

The yield levels of the restored and unrestored grasslands in our study system are mostly within the previously observed range of non-intensively managed grasslands of wet and mesotrophic sites (Tallowin and Jefferson, 1999; Donath et al., 2015). With dry matter yields of up to 705 g/m², some sites exceeded the levels normally reached without fertilisation (Tallowin and Jefferson, 1999). Under these conditions and with regard to the current subsidy policy (EU area bonus and conservation contracts), haymaking is economically viable for the regional farmers. For lactating cows, the hay may be at best recommended as basic feed, as the net energy for lactation of 5.4 ± 0.2 MJ/kg dry matter (mean ± SD) would require supplementation with high-energy compounds (Donath et al., 2004, 2021; Schumacher, 2016). The metabolisable energy contents of 9.2 ± 0.3 MJ/kg dry matter indicate suitability as complete feed for non-lactating cows (Donath et al., 2004; Deutsche Landwirtschafts-Gesellschaft, 2009) and empty ewes or ewes in early pregnancy, as well as for integration in compound feed rations for calves (Bayerische Landesanstalt für Landwirtschaft (LfL), 2021). Practically, most of the hay harvested in the region is used for leisure horses. The hay from our restoration sites and their surroundings is suitable for this with regard to the observed digestible energy levels of 8.3 ± 0.3 MJ/kg dry matter (National Research Council, 1999; Donath et al., 2004).

Slightly higher energy contents of the biomass from highly species-diverse donor sites indicate that an increase in species diversity does not preclude the integration of species-rich swards into feeding rations (Tallowin and Jefferson, 1999; Donath et al., 2004). However, yield of the donor sites is on average 40% lower compared to the restoration sites, which makes it difficult for farmers to operate profitably. Thus, agri-environmental schemes obviously remain an important pre-requisite in the conservation of species-rich grasslands of high-nature value (Donath et al., 2021).

## Drivers of restoration success

The transfer rates we observed were within the typical range for plant material transfer on species-poor grassland, but lower than on former arable fields (Kiehl et al., 2010). This holds true for both target species as well as total species numbers. While biomass yield and flood frequency had negative impacts, wider C/N ratios positively affected restoration success. These three predictors were identified as significant for at least two success variables.

Biomass yield levels are the result of complex interactions of biotic and abiotic factors (Doyle, 1982), with different nutrients being decisive in different locations and years (Fay et al., 2015). Beside generally relatively fertile soils in floodplains, we suspect that productivity in our restoration sites is partly increased by remnants of former fertilisation, which may be the reason for the very high yield levels of some of the sites. Due to the dominance of tall and highly
productive grasses under fertile conditions (Honsova et al., 2007), high productivity reduced the suitability for the establishment of species-rich floodplain meadows.

Regular flooding events lead to nutrient deposition in close proximity to the river channel (Klaus et al., 2011; Poulsen et al., 2014) and increase the productivity of floodplain meadows by higher soil nutrient levels (Beltman et al., 2007). Apart from this, higher water availability increases mineralization and nutrient supply, which leads to highly variable biomass yield between years (Mathar et al., 2015), but also between sites (cf. Jakrlová, 1999). In our study, the positive relationship between flood frequency and biomass yield (r=0.35, Supplementary Figure A3) could result from a mixture of the fertilising and the mineralizing effect of frequent flooding events. This may explain the identification of flood frequency as negatively affecting restoration success along with the biomass yield observed in 2021. Another reason for the adverse effect of flood frequency on restoration success might be that long flooding of seedlings emerged from transferred plant material impedes survival (Bao et al., 2018; Gattringer et al., 2018).

Increased soil C/N ratios were significantly associated with increases in target species number and cover. The C/N ratio in the soil as an indicator of N availability could be another long-term determinant of productivity. However, the positive correlation between C/N ratio and yield (r=0.30) does not support this. Higher C/N ratios, although not reducing productivity, could facilitate the establishment of typical floodplain meadow species by reducing competition with generalist grassland species adapted to high and continuous N availability. Accordingly, adverse effects of soil nitrogen on target species establishment were observed in the floodplain of the river Elbe (Dullau et al., 2021).

While Schmiede et al. (2012) identified plant available P content in the soil to negatively affect target species numbers in our study system, our resurvey cannot confirm this for the long term. Considering an extended set of factors and sites, the restoration sites rich in organic C, which had not been covered by the study of Schmiede et al. (2012), were among the more productive ones, so that the overall effect of biomass yield might have masked the effect of soil P.

## Conclusion

In our study, we found no long-term effect of soil preparation on vegetation development and target species establishment across a large dataset. This indicates that the positive effect of soil preparation on the number and cover of target species, which is regularly reported in short-term studies, diminishes over time, while the effects of local site conditions become more important. Therefore, soil preparation prior to seed introduction may not be necessary in floodplain meadow restoration. To increase restoration success, the productivity of restoration sites, soil C/N ratios, and flooding frequency should fit to the respective restoration goals. For practitioners, choosing restoration sites with productivity levels not greatly exceeding those of the donor sites may be most

feasible. If restoration sites are too productive, management schemes that actively reduce site productivity are recommended.

Concerning biomass characteristics, we showed that despite considerable differences in yield, even restoration sites with low productivity provide biomass of sufficient amount and feeding value. Thus, the integration of restored grasslands in local farming systems is possible and can ensure long-term management and thus stability of these ecosystems. Furthermore, one-time introduction of target species showed only limited success. Thus, additional plant material transfer or manual seeding of target species is probably necessary. Further studies should investigate the potential of such supplementary measures. Overall, we strongly recommend long-term monitoring of restoration projects in other regions and grassland types, as factors determining restoration success may become evident only after longer time periods.

## Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

## Author contributions

TWD, TK, and SH-S conceived of the research idea and designed the study. LS gathered and analysed the data with the help of YPK and SH-S, and wrote the first draft of the manuscript. All authors contributed to the article and approved the submitted version.

## Funding

The study was funded by the German Federal Environmental Foundation (grant number 35171/01).

## Acknowledgments

We thank the German Federal Environmental Foundation for funding the study. We express our gratitude to J. Scholz vom Hofe for his exertion in soil and biomass sampling and sample processing, to J. Höhl for the lab analyses, and to S. Flecken for her input on the feeding value aspects of this manuscript. The authors thank M. Harnisch from the city of Riedstadt and R. Baumgärtel from the forestry administration Groß-Gerau for their professional and administrative help at the Northern Upper Rhine, as well as to the local farmers who patiently supported our investigations and are grateful to N. Hölzel from the University of Münster for his ideas on the sampling design and the interpretation of results, and to M. Hahn and K. Willkomm for their help during field work.
## Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

## Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated

organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

## Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fevo.2022.1061484/full#supplementary-material

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Triin Reitalu,
University of Tartu,
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Martina Köhler

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martina.koehler@hs-anhalt.de

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CITATION

Köhler M, Schmidt A, Hölzel N, Baasch A and
Tischew S (2023) Positive long-term effects of
year-round horse grazing in orchid-rich dry
calcareous grasslands—Results of a 12-year
study.

Front. Ecol. Evol. 11:1107987.
doi: 10.3389/fevo.2023.1107987

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comply with these terms.

Positive long-term effects of
year-round horse grazing in
orchid-rich dry calcareous
grasslands—Results of a 12-year
study

Martina Köhler*, Annika Schmidt, Norbert Hölzel, Annett Baasch
and Sabine Tischew

Nature Conservation and Landscape Planning, Department of Agriculture, Ecotrophology and Landscape Development, Anhalt University of Applied Sciences, Bernburg, Germany

**Introduction:** Dry calcareous grasslands are among the most species-rich habitats worldwide but strongly endangered by abandonment causing a severe decline of characteristic species such as orchids. To counteract further degradation, economically sustainable restoration tools such as megaherbivore grazing, that aim to substitute extinct wild grazers, should be considered. However, the long-term effects on target species of dry grasslands, and in particular for orchid populations, is still unclear.

**Methods:** To contribute to this knowledge gap, we applied vegetation surveys (5m x 5m), as well as large-scale census-based orchid observation and mapping of habitat structures (50m x 50m) in a year-round grazing scheme of a Natura 2000 site in Central Germany over 12 years. The horses and their grazing activity were observed via GPS telemetry. We fitted linear mixed models to evaluate whether *Ophrys apifera* density was affected by horse feeding frequency, habitat structure variables (bare soil patches, woody plant cover), grassland type or years.

**Results:** A The main results were that the target dry calcareous grassland vegetation significantly increased in species numbers and cover. The total abundance of *O. apifera* increased from 1,237 (2013) and 1,893 (2018), to 4,652 (2021) individuals. *Ophrys apifera* density was positively affected by horse feeding frequency as well as grazing-induced enhanced bare soil patches but underlying mechanisms varied between the three classified grassland types.

**Discussion:** Our results indicate that low-intensity year-round horse grazing as a relatively new restoration tool in dry calcareous grasslands has the potential to enhance floristic biodiversity in general, and particularly *O. apifera* density in the long run. Furthermore, we showed that highvalue xeric grasslands with outstanding orchid abundances can be integrated into the year-round grazing system and that there is no need of fencing off such sections.

KEYWORDS

*Ophrys apifera*, Orchidaceae, plant conservation, management, Konik horses, Natura 2000,
remote sensing

1. Introduction

Dry calcareous grasslands are among the most species-rich habitats of the European cultural
landscape (Poschlod and WallisDeVries, 2002; Wilson et al., 2012). They are an essential refugium for
low-competitive and often endangered species, such as orchids. Due to their high importance, these
grasslands are to be maintained and developed via the European Natura 2000 network (Habitats Directive 92/43/EEC). Many dry calcareous grasslands currently show severe management deficits, mainly grass and/ or shrub encroachment, due to the widespread cessation of domestic (seasonal) livestock grazing during the last century that has led to a loss of habitat function and biodiversity (Poschlod and WallisDeVries, 2002).

In the last two decades, year-round grazing systems with large herbivores aiming to substitute extinct wild grazers (Vera, 2000; Bunzel-Drüke et al., 2008; Svenning et al., 2016; Pedersen et al., 2020) are increasingly applied to counteract further degradation of nutrient-rich (Gilhaus et al., 2014) and nutrient-poor acidic grasslands or heathlands (Schwabe et al., 2013; Rupprecht et al., 2016; Henning et al., 2017a,b). For these habitats, large herbivores are known to shape the pasture through their specific feeding behavior and utilization (Putfarken et al., 2008; Gilhaus et al., 2014) creating diverse vegetation structures, appropriate biomass removal and improved light conditions at the soil surface through reduced litter layer and woody plant cover (Bokdam and Gleichnam, 2000; Hejcman et al., 2005; Borer et al., 2014). Periodic creation of bare soil patches by feeding and trampling can successfully reactivate the seed bank or provide better recruitment conditions especially for rare species with a high light requirement in the germination and establishment phase (Tischew et al., 2017; Elias et al., 2018), such as orchids (Hutchings, 2010).

EU Natura 2000 legislation has identified calcareous grasslands shaped by human intervention such as grazing and mowing as prime habitat for orchids (Olmeda et al., 2019). At the same time, orchids are believed to be very sensitive to disturbance (e.g., Catorci et al., 2013). Grazing before or during flowering is generally assumed to be (at least at some point) harmful to orchid species due to the mechanical destruction of sensitive leaves and inflorescences (Calaciura and Spinelli, 2008; Catorci et al., 2013). Hence, orchid-rich dry calcareous grasslands are often not integrated into grazing concepts due to expected damage by feeding and trampling through grazing animals, but are mown instead. Especially in the case of year-round grazing, negative grazing effects on orchid species are expected in the winter and spring months (Olmeda et al., 2019), as many species form leaf rosettes during this time. As a consequence, the most commonly applied management of orchid-rich habitats currently is single mowing or grazing within a vegetation season, ideally, after flowering and fruit set (e.g., Jersáková et al., 2015), while more frequent or year-round grazing is mostly considered as harmful and unsuitable. This point of view is often neglecting that grazing could provide open canopy gaps that are important for the regeneration of low-competitive and light demanding orchid species such as *Ophrys apifera*. This addresses the long-debated question in conservation of whether disturbance affects rare species generally in a negative or, in adjusted intensities, in a positive way and which mechanisms operate in this context in the long run (Grubb, 1977). However, only few studies investigated the dynamics of orchid populations under grazing regimes over several years revealing contrasting results. Hutchings (2010) recorded an increase of *Ophrys sphegodes* after the beginning of seasonal sheep grazing in a 32-year study, whereas Catorci et al. (2013) proclaimed spring grazing as threat for orchid species in general in a replicate study after 30 years. So far, Köhler et al. (2016) was the only study finding positive effects on the orchid species *O. apifera* in a year-round grazing system in a calcareous grassland. However, this study covered only 5 years and has raised questions about the long-term effects of year-round megaherbivore grazing on target species of calcareous grasslands.

This current study represents the rare case of a validation of findings from the early years of a large-scale real-life field experiment.

In addition to the much longer observation period of 12 years, we observed in details the effects of habitat structures (litter, bare soil, herb layer and woody plant cover) and horse feeding frequency on the development of *O. apifera*. Factors crucial for target orchid development were determined in three different calcareous grassland types (xeric, dry, and dry-mesic). We addressed the following questions:

1. How does the small-scale dry calcareous grassland vegetation develop in terms of the number and abundance over the 12-year grazing period?

2. How does the population of the most important orchid target species *O. apifera* develop in the different calcareous grassland types over the grazing period and how is the density of the orchid affected by horse feeding frequency or habitat structures?

# 2. Materials and methods

## 2.1. Study site and study species

The study area comprises the 90 ha horse pasture in the nature reserve and Natura 2000 site "Tote Täler südwestlich Freyburg" in Central Germany (51°13'N; 11°46'E), ca. 250 m above sea level (see also Köhler et al., 2016). The climate is slightly continental with mild winters and warm, relatively dry summers (mean annual temperature: 8.3°C; mean annual precipitation: 565 mm). Shallow loess Luvisols on middle Muschelkalk prevail in the hilly region (Reichhoff et al., 2001).

The study area, surrounded by deciduous forests and arable land, is characterized by a plain, semi-open landscape formed by large-scale dry calcareous grasslands (Festuco-Brometea), patches of shrubs and trees as well as scattered old orchards and several historical small-sized sparsely vegetated quarries (Köhler et al., 2016). From 1950 to 1992 the area was used as a Soviet military training ground. After that period sheep herding was introduced to maintain the calcareous grasslands, but habitat quality decreased because of irregular grazing management with too low stocking rates and biomass removal, leading to highly grass encroached stands dominated by tall grasses such as *Arrhenatherum elatius*, *Bromus erectus* and *Brachypodium pinnatum* (Köhler et al., 2016). As a consequence, the floristic species composition typical of the habitat type 6210\* orchid-rich semi-natural dry grasslands on calcareous substrates decreased in extent and quality. Further habitat information is given in Köhler et al. (2016).

In the study area, *O. apifera* Huds., the Bee Orchid has one of the largest regional populations. The critically endangered species of submediterranean distribution occurs on basophilic dry grasslands and light-rich forests (Jäger, 2017) but also is a major colonizer of former quarries and road verges (Gardiner and Vaughan, 2009). Currently, the species is expanding its range to the north, probably due to climate warming (in Saxony-Anhalt since about 1990: Meysel, 2011; in Poland since 2010: Osiadacz and Kręciała, 2014). *Ophrys apifera* is a long-lived perennial wintergreen geophyte and terrestrial orchid that is self-pollinating (Darwin, 1877) at its northern range of distribution (study area), but otherwise bee pollinated by the solitary bee genus *Eucera* (Kullenberg and Bergström, 2008). Plants produce one inflorescence with heights of 20–40 cm and 1–12 blossoms in May–June, fruit set begins in June–July (Ziegenspeck, 1936; Jäger, 2017). The plants emerge from tubers in early autumn and leaves continue to grow slowly during winter making the species exposed to grazing for a rather long period.
Leaves die back during flowering. Reproduction occurs by seeds and vegetatively (Lang, 1980).

## 2.2. Grazing management

In 2009, a year-round grazing system was introduced to manage the *ca.* 90 ha calcareous grassland (Köhler et al., 2016). The Konik Polski horses formed a herd with on average 18 adult horses (one stallion, 17 mares) and five foals. This results in a stocking rate of 0.3 livestock units (LU)/ha/a (assuming that one adult horse is counted as 1 LU and one foal 0.5 LU). In the first years of grazing, higher stocking rates up to 0.4 LU/ha/a helped repressing the encroachment with tall grasses and could be lowered with the improvement of the site. Additionally, single years of higher biomass production due to higher precipitation required slightly higher stocking rates. The robust breed was able to cope with near-natural conditions such as a very low level of additional winter feeding or rare veterinary intervention (further management information see Köhler et al., 2016).

## 2.3. Data collection and species classification

### 2.3.1. Small-scale observations of dry calcareous grassland vegetation

To study the vascular plant species composition of the target vegetation, we randomly established eight permanent 5m×5m vegetation survey plots on the strongly grass encroached parts of the pasture in 2009. We conducted vegetation surveys in June/July annually from 2009 to 2015, and in 2018, and 2020. The calculation of conservation value for vascular plant species is based on the red-lists for Germany (Metzing et al., 2018) and Saxony-Anhalt (Frank et al., 2020). Nomenclature of vascular plants follows Jäger (2017).

We classified vascular plant species into the following ecological groups: target forbs, target grasses (both categories were selected according to the characteristic species of calcareous grasslands following the Habitats Directive), other dry grassland species (including rare ecotone species), mesic grassland species, ruderals and woody plants (Jäger, 2017; species list see Supplementary Table SA1). Each species only belongs to one group.

### 2.3.2. Large-scale observations of *Ophrys apifera*, habitat structures and horse feeding frequency

*Ophrys apifera* and habitat structures were observed on grid cells. To stratify habitat structure in orchid census observation grid cells, three vegetation types were classified according to the habitat types of the EU Habitats Directive. Differences in vegetation cover and bare soil patches served as proxies for soil depth and grassland productivity. Xeric calcareous grasslands (xeric) on shallow soils harbored characteristic species of basophilic grasslands of the Alysso-Sedion albi, code 6110* and a range of xeric grassland species such as *Galatella linosyris*, *Teucrium botrys* or *T. chamaedrys* with a total area of 11 ha and 13.6% of the pasture, respectively (red sites in Figure 1). Dry calcareous grasslands (dry) covered 64 ha (76.5%) of the pasture and were dominated by *B. pinnatum*, *Festuca rupicola* or *Scabiosa ochroleuca* (Semi-natural dry grasslands and scrubland facies on calcareous substrates Festuco-Brometalia, code 6210*, green sites in Figure 1). Dry-mesic calcareous grasslands (dry-mesic) on slightly deeper and more productive soils

were characterized by dry as well as mesic grassland species such as *A. elatius*, *F. rupicola* or *Origanum vulgare*. In the study area, floristic species composition contains not only submediterranean but also a range of continental species. That vegetation type was found on 8 ha (9.9%) of the pasture (blue sites in Figure 1). The study area was divided into 449 50 m × 50 m grid cells using ArcGIS, of which 121 grid cells were randomly selected proportionally to the size of the three calcareous grassland types (number of grid cells on xeric: 17, dry: 96, dry-mesic: 8). Grid cells with larger patches of high woody vegetation and forests (white sites in Figure 1) were excluded from the selection procedures as not appropriate for *O. apifera*. The selected grid cells covered 32% (27.4 ha) of the *ca.* 90 ha pasture.

In April of 2013, 2018 and 2021, the number of *O. apifera* individuals at leaf rosette stage was counted in every grid cell in March. Since a few grid cells did not reach full plot size due to pasture fence boundaries, *O. apifera* density was calculated for each grid cell to equal the slightly different grid cell sizes. In 2011, 2012, 2014, 2018, and 2020, habitat structure data (percent cover of litter layer, bare soil patches, herb layer and woody plants) was collected on the grid cells via field surveys. Starting in January 2010, the position and activity of the free-ranging horses on the pasture were recorded using remote sensing via a GPS PLUS-4 collar (Vectronic Aerospace GmbH Berlin). As the horses showed gregorial behavior, one collar on a female horse recorded spatio-temporal information in 10-min intervals in WGS 84 and UTC time as well as angle and acceleration differences in 2-min intervals via a two-axis accelerometer. Inaccuracy of GPS signals due to atmospheric conditions or satellite errors may have resulted in some imprecision of our data. In order to interpret the collar activity data, we collected direct

<figure><img src="image_21.png" /><figcaption>FIGURE 1
Heat map of horse feeding frequency from April–March from 2011 to 2021 (black points correspond to GPS positions). Cover of calcareous grassland types are marked red (xeric), green (dry) and blue (dry-mesic). White sites refer to dense patches of high woody vegetation and forests without remarkable grassland vegetation.</figcaption></figure>
observational behavioral data in the field that was matched to the collar data *via* consistent timestamps (every minute for 881 h on 52 days from 2010 to 2012). During our direct behavioral observations, we did not detect abnormal behavior of the telemetered horse. A discriminant analysis was applied to classify the main behavioral groups feeding, resting and walking of the recorded telemetry data according to the direct observations in the field. As feeding, which always includes walking, was assumed to have the highest impact on the growth cycle of the target orchid species, we selected the horses' feeding frequency to explain orchid development (Figure 1). The amount of horse feeding frequency data was calculated in each grid cell for one m² in ArcGIS (amount of GPS positions classified into feeding per grid cell/grid cell area), as the grid cells cutting the pasture margins showed slightly reduced sizes.

## 2.4. Statistical analysis

We used non-parametric Friedman tests to test for differences of total species numbers, species numbers and covers within the ecological groups of the small-scale observations of dry calcareous grassland vegetation through time.

Linear mixed models (LMM) were fitted to evaluate whether the density of *O. apifera* was affected by horse feeding frequency, habitat structure variables (bare soil patches, woody plant cover), grassland type or years (Table 1), using lme4 1.1–21 (Bates et al., 2015) and MuMln 1.43.17 for multi-model selection and averaging (Bartón, 2020). The cover of the herb as well as litter layer had to be excluded from the modeling process to avoid strong inter-correlations among the predictors (|r| > 0.6, Pearson's correlation analysis, r<sub>bare soil - herb layer</sub> = -0.735, r<sub>bare soil - litter layer</sub> = -0.683). Moreover, we included all two-way interactions. To achieve normally distributed residuals and avoid heteroscedasticity, we inverse-transformed the density data prior to statistical analysis. Assumptions were checked graphically as recommended by Smith et al. (2009). Possible dependence in the data due to repeated measurements in the same permanent grid cells was controlled by incorporating grid number as random variable in the models. Multi-model selection was based on Akaike information criterion (AIC). For model averaging, we selected all models with ΔAIC<4 compared to the best model according to AIC.

We implemented all statistical analyzes in R version 4.0.2 (R Core Team, 2020), all telemetry data analyzes in SPSS version 20.0 (IBM Corp. Released, 2011; ArcGIS® 10.1 Software by Esri, 2012).

# 3. Results

## 3.1. Development of dry calcareous vegetation under year-round grazing (small scale)

In total, we observed 134 vascular plant species within the eight 5 m × 5 m vegetation survey plots during the entire period of observation, among them 13 endangered red list species (Supplementary Table SA1). Total mean species number significantly increased from 30.3 ± 3.5 to 38.5 ± 2.9 (mean ± SE; df = 8, Qui-square = 41.717, *p* < 0.001, Friedman test).

Different ecological species groups showed varying effects in response to horse grazing. In total, 35 target for species were recorded

on all plots with significantly increasing species numbers from 9.9 ± 1.5 to 14.5 ± 1.5 (mean ± SE; Figure 2). In addition, mean number of other dry grassland species and ruderals significantly increased, whereas mesic grassland species significantly decreased (Figure 2). Mean number of target grasses and woody plants remained constant.

From 2009 to 2020, cumulative cover of target forbs, e.g., *Asperula cynanchica*, *Hippocrepis comosa*, *Potentilla neumanniana*, *S. ochroleuca* or *Thesium linophyllon*, as well as other dry grassland species and ruderals significantly increased by 18.1, 4.4 and 2.6%, respectively (Figure 3). On the contrary, cover of ecological species groups indicating abandonment of dry calcareous grasslands such as target grasses and mesic grassland species significantly decreased by 24.2 and 5.6%, respectively (Figure 3). Grass encroachment was mainly built of the target grass species *B. pinnatum* and *B. erectus*. Mean cover of woody plants remained constant on the small-scale plots (Figure 3).

## 3.2. Development of the target orchid species *Ophrys apifera* under year-round grazing (large scale)

### 3.2.1. Habitat structures and horse feeding frequency

For large-scale grid cell observation, the study site was stratified in three different grassland types covering xeric, dry and dry-mesic

<table><caption>TABLE 1 Results of the linear mixed-effect model for effects of horse feeding frequency, woody plant cover, bare soil patches, year (three-level factor) and grassland type (three level factor) on density of the target orchid species *Ophrys apifera*.</caption><thead><tr><th>Density<br>Ophrys<br>apifera</th><th>Estimate</th><th>SE</th><th>P</th></tr></thead><tbody><tr><td>Intercept</td><td>-41.727</td><td>11.673</td><td>&lt;0.001</td></tr><tr><td>Mean woody plant<br>cover</td><td>-6.374</td><td>2.465</td><td>0.010</td></tr><tr><td>Mean horse feeding<br>frequency</td><td>42.843</td><td>10.879</td><td>&lt;0.001</td></tr><tr><td>Mean cover bare<br>soil patches</td><td>8.144</td><td>2.806</td><td>0.004</td></tr><tr><td>Dry grassland type</td><td>-41.735</td><td>12.065</td><td>0.001</td></tr><tr><td>Dry-mesic<br>grassland type</td><td>-45.078</td><td>17.317</td><td>0.009</td></tr><tr><td>Year 2021</td><td>29.042</td><td>6.605</td><td>&lt;0.001</td></tr><tr><td>Mean horse feeding<br>frequency: dry<br>grassland type</td><td>-50.294</td><td>11.130</td><td>&lt;0.001</td></tr><tr><td>Mean horse feeding<br>frequency: dry-<br>mesic grassland<br>type</td><td>-44.216</td><td>11.556</td><td>&lt;0.001</td></tr><tr><td>Dry-mesic<br>grassland type: year<br>2021</td><td>-27.434</td><td>11.115</td><td>0.014</td></tr></tbody></table>

Estimates of model-averaged coefficients are shrinkage estimates including all selected models from model averaging (full model average). Non-significant factors are not displayed but can be found in Supplementary Table SA2. Intercept: Year 2013, xeric grassland type.
<figure><img src="image_22.png" /><figcaption>FIGURE 2</figcaption></figure>

Mean vascular plant species number on grazed vegetation survey plots (5m×5m, *n*=8). Significant changes in ecological groups over 9 observational years (2009 to 2015, 2018, 2020) are marked with asterisks (n.s. not significant, \*p\<0.05, \*\*p\<0.01, \*\*\*p\<0.001; Friedman tests: Target forbs: df=8; Qui-square=37.479; *p*<0.001; target grasses: df=8; Qui-s. = 5.539; *p*=0.699; other dry grassland species: df=8; Qui-s. = 25.071; *p*=0.002; mesic grassland species: df=8; Qui-s. = 31.212; *p*<0.001; ruderals: df=8; Qui-s. = 15.550; *p*=0.049; woody plants: df=8; Qui-s. = 11.250; *p*=0.188). Error bars indicate standard error.

<figure><img src="image_23.png" /><figcaption>FIGURE 3</figcaption></figure>

Mean cumulative cover of vascular plant species in grazed vegetation surveys (5m×5m, *n*=8). Significant changes in ecological groups over 9 observational years (2009 to 2015, 2018, 2020) are marked with asterisks (n.s. not significant, \*p\<0.05, \*\*p\<0.01, \*\*\*p\<0.001; Friedman tests: Target forbs: df=8; Qui-s. = 36.800; *p*<0.001; target grasses: df=8; Qui-s. = 23.933; *p*=0.002; other dry grassland species: df=8; Qui-s. = 25.700; *p*=0.001; mesic grassland species: df=8; Qui-s. = 30.407; *p*<0.001; ruderals: df=8; Qui-s. = 21.201; *p*=0.007; woody plants: df=8; Qui-s. = 12.865; *p*=0.117). Error bars indicate standard error.

calcareous grasslands. Litter layer decreased in all calcareous grassland types but most in the dry grassland grid cells. Highest reduction occurred in the first years of grazing, before reaching a stable level of 15–20% in 2018 and 2020 (Figure 4). Area of bare soil patches showed highest values of about 55% in xeric grasslands from the beginning of the survey, whereas in both, dry and dry-mesic grasslands, values were half these maximum values but increased over time (Figure 4).

In general, litter layer decreased while herb layer increased. Highest increase in herb layer occurred in the dry grasslands, while dry-mesic grasslands remained constant at ca. 60–70% cover (Figure 4). Herb layer in xeric grasslands only slightly increased with significant values since 2018. According to the large-scale observation, woody plant cover was slightly higher in xeric grassland grid cells than in dry or dry-mesic grasslands where horse feeding frequency was highest (Figures 4, 5).
<figure><img src="image_24.png" /><figcaption>FIGURE 4</figcaption></figure>

Mean values (± SE) of percent cover of habitat structures litter layer (A), bare soil (B), herb layer (C) and woody plants (D) on the grid cells (50mx50m) in the year-round horse pasture in the different calcareous grassland types (n=121; xeric n=17, dry n=96, dry-mesic n=8) in the years 2011, 2012, 2014, 2018 and 2020. Points correspond to the respective data sets.

all vegetation types woody plant cover remained constant at about 15% until 2017 and only slightly increased in 2018.

Horse feeding frequency in xeric grassland grid cells showed lowest means and did not markedly change over the entire grazing period (Figures 1, 5). In grid cells harboring dry calcareous grasslands horse feeding frequency was twice as high compared to xeric grasslands, while highest horse feeding frequency was recorded in dry-mesic grassland grid cells with varying mean values over the period of observation (Figures 1, 5). In 2020, lower values correspond with the partial absence of horses (due to low fodder availability related to the extreme drought).

### 3.2.2. Development of *Ophrys apifera* and effects of habitat structures and horse feeding frequency

The total number of recorded individuals of the target orchid species *O. apifera* in the 121 grid cells continuously and significantly increased from 1,237 in 2013 and 1,893 in 2018, to 4,652 in 2021. Hence, the total number of individuals clearly increased, and was estimated to be at least 10,000 individuals in the entire pasture in 2021.

*Ophrys apifera* density significantly varied in the different calcareous grassland types showing highest values in xeric, medium in dry and lowest in dry-mesic grassland grid cells (Table 1; Figure 6). Within the observation period, density doubled in xeric (almost) and dry grassland (significantly) grid cells from 2018 to 2021 (Figure 6). Density in dry-mesic grasslands remained stable from 2013 to 2021. The total number of *O. apifera* individuals was highest in dry, and twice as high as in xeric grassland grid cells.

Horse feeding frequency affected the density of *O. apifera* positively but showed varying effects between grassland types (Table 1; Figures 7, 8; Supplementary Table SA2). In xeric grasslands, grid cells with higher horse feeding frequency also had a higher *O. apifera* density compared to xeric grassland grid cells of low horse feeding frequency. In contrast, in dry-mesic grasslands which generally exhibited the highest horse feeding frequency (compared to the xeric and dry grassland type), the grid cells with a higher *O. apifera* density tended to be frequented less often. The increase of *O. apifera* on dry grasslands covered a relatively broad range of horse feeding frequency and contributed most to the overall increase of individuals (Figure 7). A high cover of bare soil patches was predicted to have the second largest positive effect. In contrast, grid cells with a higher woody plant cover were predicted to show a lower density of *O. apifera*. High horse feeding frequency was negatively correlated with woody plant cover ($r_{woody plant cover-horse feeding frequency} = -0.382, p = <0.001$, Pearson's correlation coefficient).

## 4. Discussion

### 4.1. Year-round grazing effects on small-scale dry calcareous vegetation

We investigated the number and cover of characteristic dry calcareous grassland species over a study period of 12 years in a year-round horse grazing regime. We found a constant increase particularly of target forbs which only decreased in cover due to the severe drought
<figure><img src="image_25.png" /><figcaption>FIGURE 5</figcaption></figure>

Mean values (± SE) of horse feeding frequency per qm on the grid cells in the different calcareous grassland types (n=121; xeric n=17, dry n=96, dry-mesic n=8) from April–March from 2011–2021. Lower values in 2020 referred to partial absence of horses (due to low fodder availability related to the extreme drought). Points correspond to the respective single data sets.

<figure><img src="image_26.png" /></figure>

<figure><img src="image_27.png" /><figcaption>FIGURE 6</figcaption></figure>

Mean values (± SE) of the density (A) and total number (B) of *Ophrys apifera* on the grid cells in the different calcareous grassland types (n=121; xeric n=17, dry n=96, dry-mesic n=8) in the years 2013, 2018 and 2021. Values 0.546, 0.440 and 0.347 (A) and 407 (B) are not displayed. Points correspond to the respective data sets.

in Central Germany in 2018, whereas the cover of target grasses significantly decreased. Low competitive dry grassland species depending on bare soil patches benefited from grazing and increased. This finding emphasizes that the typical floristic species composition can

be maintained and even improved by year-round grazing not only over short periods (Köhler et al., 2016), but also in the long run. Several studies have reported a positive impact of year-round equid grazing on the abundance of target species of dry sandy grasslands (Süss and