of plant communities (Hilderbrand et al., 2005). However, this assumption neglects key processes that underpin the establishment and persistence of insect populations in sites to be restored, such as their ability to naturally reach these areas.

Ensuring that species can move between habitats or from preserved to degraded areas is vital for their maintenance and for ecosystem functioning and restoration (Massol et al., 2011; Poli et al., 2020). Considering species movements should therefore be a prerequisite when planning species conservation and habitat restoration (Katzner and Arlettaz, 2020). Currently, however, movement data are too often neglected when implementing conservation plans (Allen and Singh, 2016), reducing the effectiveness of traditional approaches such as protected areas given the spatial scale of species' movements (Thirgood et al., 2004). One of the challenges in species conservation is therefore to determine how, where, when and why species move.

The recent emergence of the science of movement that provides detailed spatio-temporal data is a significant advance in species conservation (Allen and Singh, 2016). Movement processes inform the foraging ecology and dispersal capacity of organisms (Ramos-Fernández et al., 2004). Research in movement ecology is generating knowledge of factors like the extent and use of geographical ranges, migratory pathways, phenology and activity period, the knowledge required for flexible conservation strategies in space and time (Le Gouar et al., 2015; Bérces and Růžičková, 2019). For example, to estimate the migratory range of stag beetles (*Lucanus cervus*) as a measure of connectivity among neighbouring populations for future conservation measures, Rink and Sinsch (2007) equipped individuals with 350 mg transmitters. They observed that about 1% of males are capable of maintaining gene flux among nest sites within a radius of about 3 km. Thus, isolated populations more than 3 km apart have an increased probability of local extinction.

Movement ecology has evolved thanks to recent technological advances such as radio frequency identification, hereafter RFID (e.g., Moreau et al., 2011), harmonic radar (e.g., Milanesio et al., 2016) or radio telemetry tags also called very high frequency (VHF) radio telemetry (e.g., Růžičková and Veselý, 2016). These technologies have been widely used to study the space use and movement behaviour of vertebrates (Holyoak et al., 2008). In comparison, insect movement ecology remains relatively neglected, despite the recent miniaturisation of tracking devices that has enabled accurate estimation of movements, even for small organisms like insects (Reynolds and Riley, 2002; Milanesio et al., 2016). Riecken and Raths (1996) were the first to use small radio-transmitters (0.6–0.7 g) to study the dispersal and habitat use of a terrestrial ground-dwelling insect, *Carabus coriaceus*, a large beetle about 40 mm long. Since then, a wide array of ground and flying arthropods has been tracked (Kissling et al., 2014), from tarantulas (e.g., Janowski-Bell and Horner, 1999) and beetles such as Carabidae (e.g., Negro et al., 2008) to hymenopterans (Henry et al., 2012) and dragonflies (Moskowitz and May, 2017).

When used on insects, tracking devices are commonly glued either directly on their external tegument (e.g., Batsleer et al., 2020) or to a line that is itself fixed onto the insects' back (e.g., Vinatier et al., 2010). However, this equipment may constrain insect behaviour and affect different aspects of an arthropod's life history (e.g., energy, movement, foraging, mating), potentially reducing the reliability of data and conclusions (Henry et al., 2012). Batsleer

et al. (2020) recently called for more systematic documentation of potential effects of tags on arthropods' behaviour. Their review found that only 12% of the papers quantified the impacts of tags on insects. Most of the remaining papers claimed no effect, based on tag/body weight rules. The 5% rule—developed for flying or swimming vertebrates—considers that a tag/body weight ratio above 5% induces significant impacts (Kenward, 2001). Boiteau and Colpitts (2001) recommended that tags should weigh no more than 23–33% of the beetle's acceptable extra loading to limit impacts on the number and quality of flights. However, such general rules do not make much sense, as tag impacts are most likely dependent on study species, tag type, sex and environmental context (Jepsen et al., 2005). For example, predator and scavenger beetles of similar size and weight are unlikely to be affected in the same way by the tag. Unlike scavengers, predators often have to move quickly and sometimes over large areas to detect and catch their prey, which may make them more sensitive to additional weight.

Each of the available technologies has its own advantages and drawbacks for the study of arthropod movements (Kissling et al., 2014; Batsleer et al., 2020). Active radio transmitters allow individuals to be tracked over distances of more than 300 m for ground-dwelling insects (Negro et al., 2008); however, the problem is the weight of the transmitter, sometimes as heavy as a given arthropod. Passive tags (harmonic radar and RFID) have been applied to a broader range of arthropods, but the short detection distance complicates the monitoring of arthropods in the field. How much of a drawback this is depends, however, on the structure of the habitat; passive tags may be more appropriate in open habitats such as grasslands, where tagged individuals are easier to detect. For smaller arthropod species, where tag weight makes passive tags the only option, current challenges in monitoring movements include the limited detection distance and potential impacts on the animals' behaviour.

This study investigated the potential of passive RFID transmitters to track the movements of three small ground-dwelling beetle species typical of the Plaine de la Crau (Southern France) dry grassland: a predator (*Poecilus sericeus*, Fischer von Waldheim, 1824, Carabidae), a detritivore [*Asida sericea* (Olivier, 1795), Tenebrionidae] and a granivore [*Acinopus picipes* (Olivier, 1795), Carabidae]. We first explored how the tags impacted beetle behaviour, using a before-and-after design under laboratory conditions. Then we tracked tagged individuals in their natural environment, located in a protected nature reserve. Our findings are discussed in terms of their relevance to the conservation of beetle species in a protected dry grassland.

# 2. Materials and methods

## 2.1. Study site

La Crau is a plain dominated by dry grasslands located in the former delta of the Durance river (Southern France), to the east of the Rhône valley and the Camargue. This region is characterised by a Mediterranean climate, with low annual precipitation (400–500 mm per year), long hot summers and mild winters (mean annual temperature: 14° C). On average, the strong predominant wind (“mistral”) blows from the North-West 334 days per year
and the sun shines 3,000 h per year, generating very high levels of evapotranspiration (Devaux et al., 1983). In La Crau dry grasslands, about 50% of the soil surface is covered with stones transported by the Durance river 650,000 to 30,000 years ago. The substratum is an impermeable conglomerate bedrock, 40 cm deep, which limits the accessibility of groundwater for vegetation. Our field experiment took place in the centre of the sheepfold "Peau de Meau" (43.571525°N, 4.831853°E, elevation 10 m, 160 ha). The site is representative of the remaining 11,500 ha of dry grassland vegetation typical of the area, i.e., dominated by *Brachypodium retusum* P. Beauv. L., Poaceae and *Thymus vulgaris* L., Lamiaceae (Buisson and Dutoit, 2004; Römermann et al., 2005).

## 2.2. Study species

We focussed on three apterous beetle species: *Asida (polasida sericea)* (Olivier 1795), *Poecilus sericeus* (Fischer von Waldheim, 1824), *Acinopus (acinopus) picipes* (Olivier, 1795) (Figure 1). They are among the most abundant non-flying beetle species on the La Crau dry grassland, *A. sericea* and *P. sericeus* often jointly accounting for nearly 40% of the individuals caught (Blight et al., 2011). The three species are of similar size, with average body length from 11 to 14 mm (Jeannel, 1942; Soldati, 2006), but belong to three different feeding guilds. As a *Tenebrionidae*, *A. sericea* is a detritivore species. *Acinopus picipes* is an omnivorous-granivorous species with a large head and stout mandibles (Talarico et al., 2016), whereas *P. sericeus* is a predator with an elongated body and long mandibles (Jeannel, 1942). Their life cycles also differ: *P. sericeus* overwinters in adult stage, *A. picipes* overwinters in larval stages (Talarico et al., 2016) and *A. sericea*'s imago can be found all year long (Soldati, 2006).

## 2.3. Monitoring devices

Based on preliminary tests with harmonic radar technology (RH, unpublished results), we decided to use radio frequency identification (RFID) to monitor the beetles' movement. The major issue with harmonic radar is individuals' movements being hindered by the long wire antennas getting caught in vegetation, as described in O'Neal et al. (2004). Despite a shorter detection range, RFID eliminates the problem of the protruding antenna and allows tagged individuals to be distinguished according to unique signals. We used miniature passive RFID tags (Mini HPT8 PIT Tag, Biomark Inc., Boise, ID, USA) 8 mm long by 1.4 mm wide, i.e., shorter and narrower than our study species. These tags weigh about 30 mg, which means that individuals equipped with glued diodes carried roughly 30% of their body mass. Tagging our study individuals added 26% extra weight to *A. picipes*, which weighs on average 0.12 g, 35% to *A. sericea*, which weighs on average 0.14 g, and 26% to *P. sericeus*, which weighs on average 0.12 g (Table 1).

Tags were glued to the insect's elytra with cyanoacrylate glue (Super glue 3 power flex mini trio, Loctite, Henkel, Germ). We tracked the tagged insects with a hand-held battery-powered transponder reading device (HPR Plus Reader, Biomark) equipped with a 40 cm diameter portable antenna (BP Plus Antenna, Biomark). The antenna had to pass over a tag to detect it.

Detection height was also limited to a few centimetres (up to 30 cm, depending on the presence of stones under which beetles can hide).

## 2.4. Lab experiments

We first conducted an experiment to assess the impact of laboratory conditions and tags on the movements of the three species. A control group ($N = 6$ for *P. sericeus* and $N = 5$ for *A. picipes* and *A. sericea*) was tested for signs of familiarisation with an arena where they were repeatedly released. We hypothesised that their exploratory behaviour might be reduced by repeated release in the arena, through habituation to this new context. Individuals were released three times in the centre of a 42 cm × 27 cm plastic box (hereafter the arena), its bottom covered with white blotting paper to increase contrast with the dark insects. They were filmed for 4:30 min using a camera (alternatively 2 cameras: Nikon Coolpix P100, 10 megapixels and Nikon Coolpix P7700, 12 megapixel) attached to a copy stand. A second group of individuals ($N = 10$ for *A. sericea*, $N = 14$ for *P. sericeus* and $N = 7$ for *A. picipes*) was tested for the effect of the tags on behaviour and movements. Each individual was released three times in the arena and their behaviour recorded. The first time, the individual was "undisturbed"; the second time, a drop of glue was placed on it; the third time, the tag was glued onto its back. With or without tags, the glue was allowed to dry for 20 min before the individual's movements were filmed for 4:30 min using the device described above. We hypothesised that small tags glued to their elytra would not alter the movement capability of these ground-dwelling non-flying beetles.

Temperature in the experimental room was about 23°C. Filming was done in daylight and additional artificial light was used to improve image quality and avoid shading. Note that if an insect did not move for the first 2 min, we switched to the next individual.

All the individuals used in these experiments were hand-caught in the field and stored in boxes with soil and rocks retrieved from the field. Boxes were kept moist and oxygenated. Lab experiments were conducted in the days following their capture.

Data for each individual was treated in three steps. First, pictures (1920 × 1088 px) were extracted from the films (30 frames per sec.) at regular 5-s intervals with VLC® (scene filter on and recording ratio of 150), yielding 54 images per film. Second, the individual's spatial coordinates in the arena were calculated *via* automated image analysis, as in Mallard et al. (2013). Third, two variables related to the individual's activity in the arena were calculated: (1) average distance travelled in 5 s. time steps (pixels), and (2) total area explored, defined by number of pixels visited in an arena divided into 200 square pixels.

The average behaviours of individuals from the different species and treatments were compared *via* repeated measures ANOVA (hereafter anova), which allows for the same individuals to be measured on the same outcome variables under different conditions (three consecutive runs with or without equipment), using the function *anova_test* from the package *rstatix* (Kassambara, 2022). We accounted for multiple comparisons with Holm's adjustment, less conservative than the Bonferroni method (Holm, 1979). Non-normal variables were transformed using the function *bestNormalize* (Peterson, 2021).
<figure><img src="image_52.png" /><figcaption>FIGURE 1</figcaption></figure>

Study species and study area (A) the dry grasslands of la Crau and marking of release points, (B) *Asida sericea*, (C) *Acinopus picipes*, (D) *Poecilus sericeus* equipped with an RFID-tag on its back, (E) *Asida sericea* equipped with an RFID-tag and released in the field.

<table><caption>TABLE 1 Species weight alone (± SD) and with the diode, and additional weight generated.</caption><thead><tr><td>Species</td><td>Weight alone (g)</td><td>Weight with diode (g)</td><td>Ratio</td><td>Add.weight (g)</td></tr></thead><tbody><tr><td>A. picipes (N = 2)</td><td>0.120 ± 0.021</td><td>0.158 ± 0.011</td><td>1.248 ± 0.028</td><td>0.038</td></tr><tr><td>A. sericea (N = 8)</td><td>0.136 ± 0.032</td><td>0.180 ± 0.031</td><td>1.347 ± 0.107</td><td>0.044</td></tr><tr><td>P. sericeus (N = 14)</td><td>0.121 ± 0.016</td><td>0.152 ± 0.016</td><td>1.260 ± 0.043</td><td>0.030</td></tr></tbody></table>

To investigate how different individuals responded to our treatments, we used the intraclass correlation coefficient (ICC) with the function `icc` from package `irr` (Gamer et al., 2019). The ICC measures the reliability of ratings in inter-raters or in test-retest designs by comparing the variability of different ratings for the same individuals to the total variation across all ratings

and all individuals (Shrout and Fleiss, 1979). Both agreement and consistency were measured. An ICC value above 0.9 means agreement (or consistency) is excellent, a value between 0.75 and 0.9 good, a value between 0.5 and 0.75 moderate and below 0.5 poor (Koo and Li, 2016). Non-normal variables were transformed using the function `bestNormalize` (Peterson, 2021).
<figure><img src="image_53.png" /><figcaption>**FIGURE 2** Monitoring beetle movements in the lab, (A) example of an experimental run with all-time steps overlapped, (B) example of three contrasting trajectories in blue, green and red. White square correspond to the release point.</figcaption></figure>

## 2.5. Field experiment

The movements of individual beetles in the field were monitored every 4 h for 48 h (17–19 May 2021). Individuals were hand-caught in the morning of day 1 and kept in plastic boxes before their release. They were equipped with the same RFID tags as in the laboratory experiment (see above) and observed for 30 min minimum to confirm successful tag attachment. Individuals were released on day 1 at 14h30. Release points were located 10 m apart to facilitate detection procedures, reduce interference among tagged individuals and maximise the heterogeneity of stone and vegetation cover encountered in the dry grassland. Release points were located in a 40 m diameter circle to facilitate logistics and were marked with a labelled and coloured pole (Figure 1).

Initially, we released 25 individuals (N = 7 for *A. sericea* and N = 9 for *P. sericeus* and *A. picipes*), the number of individuals per species reflecting capture success. Every 4 h, all individuals were detected and their new position marked with a labelled pole. We recorded the time, the distance travelled since release

with a decametre and the direction taken since release (deviation from compass direction, distance-bearing approach (Růžiěková and Elek, 2021) with the compass application of a smartphone (using a single iPhone 5S to avoid bias). This provided two daily time steps per time of day: afternoon (10:30–14:30, 14:30–18:30), night (18:30–22:30, 22:30–2:30), morning (2:30–6:30, 6:30–10:30).

When the individual appeared motionless after three consecutive detections, its physical condition was checked. Twelve hours after starting the experiment, there were two dead individuals and seven lost their tag. Nine additional individuals were released at 14h30 on day 2 (N = 3 for each species). One week later, an exhaustive field search was conducted over a circle of 6 m around the release points. The distance and angle to release point were recorded for each detected individual; undetected individuals were considered to have left these search areas.

This experiment took place under typical spring weather conditions, mainly sunny days with 30–50 km/h northerly wind and light rain (< 0.5 mm for 2 h). The temperatures of the soil (10 cm below soil surface) and air (at 1.2 m above soil in the shade)
were recorded with two loggers (Hobbo®, Pendant temp logger 64K). There was a clear night-day temperature contrast, with an average temperature of 18.8°C in the soil and 19.0°C in the air, a minimum temperature of 14.1°C in the soil and 8.6°C in the air and a maximum temperature of 27.0°C in the soil and 31.0°C in the air.

To test for differences between sessions in distance travelled for each species (morning, day and night), we used the non-parametric Kruskal-Wallis test from the package *rstatix* (Kassambara, 2022), as the data did not follow a normal distribution, even after transformation. Pairwise comparisons were performed using the pairwise.wilcox.test function with Holm's correction from the package *rstatix* (Kassambara, 2022).

All statistical analyses were performed using R Statistical Software (v4.1.2 R Core Team, 2022).

# 3. Results

## 3.1. Lab experiments

We observed strong individual variations in the behaviour of beetles in the arena, with some individuals circling along the edges, some widely exploring the surface and some remaining still in a corner (Figure 2). No clear sign of habituation to the arena was found, none of the analysis being significant (Figure 3). Moreover, the area explored by individuals differed in a completely idiosyncratic manner between arena sessions (ICC < 0.5) (Figure 3B). The distance travelled was moderately consistent (ICC ~ 0.6) for *A. sericea* and *A. picipes* across the three runs, with some individuals travelling fast while others remained slow.

In contrast, for the tag-effect test, we observed an overall effect on *A. sericea* [*F*(2,18) = 15.15; *p* < 0.001]. Individuals covered significantly shorter distances per time step with the diode on their back than when carrying nothing (*df* = 2; *p* = 0.004) (Figure 4A), and also tended to cover shorter distances when they had glue alone on their backs compared to nothing (*df* = 2; *p* = 0.067) (Figure 4B). An overall effect was also observed on *A. picipes* [*F*(2,12) = 4.71; *p* = 0.031] and *P. sericeus*, [*F*(1.31,17.02) = 5.22; *p* = 0.028], but none of the comparisons were significant after applying Holm's correction. Neither carrying the glue alone nor the diode affected the area explored. None of the ICC values were above 0.5, indicating poor consistency in the individuals' behaviour and poor agreement in their ranking among treatments.

## 3.2. Field experiment

In the end, movement data was obtained on 25 individuals over 24 to 48 h: 8 *A. picipes* (out of 12 released), 10 *A. sericea* (out of 10 released) and 7 *P. sericeus* (out of 12 released). The other individuals were preyed on (2) or lost their diodes (7). One week later, within a 6 m radius of the release points, the field search identified 11 individuals that had moved farther than a week earlier (2 *A. picipes*, 5 *A. sericea*, 4 *P. sericeus*) and five that had not moved (due to territoriality, death or lost diode); the 9 other individuals were not found (Table 2, see Appendix 1 for trajectory examples).

The distances travelled by the tagged individuals did not significantly differ between species due to high individual variability (all the metrics yielded the same results). After 24 h, *A. picipes* individuals were found approximately 0.81 metres from their starting point (max = 2.63 m), having travelled an average of 0.22 metre in 4 h (max = 2.17). *Asida sericea* individuals were found approximately 1.03 metres from their starting point (max = 3.62 m), having travelled an average of 0.33 metre in 4 h (max = 3.42). *Poecilus sericeus* individuals tended to travel less and were found approximately 0.5 metres from their starting point (max = 1.91 m), having travelled an average of 0.13 metre in 4 h (max = 1.98). On average, individuals started to move after 3.5-time steps for *A. picipes*, 4.6 for *A. sericea* and 5.8 for *P. sericeus*.

We observed a significant effect of time of day on movement patterns (df = 2; $\chi^2$ = 12.78; *p* < 0.01) (Figure 5). Individuals moved more at night than in the morning (df = 2; *p* = 0.026) and substantially more at night than in the afternoon (df = 2; *p* = 0.003), with no significant difference between morning and afternoon (df = 2; *p* = 0.226). The effect was, however, not equally strong for all three species. Time of day significantly affected the movements of *Asida sericea* (df = 2; $\chi^2$ = 8.47; *p* = 0.015), individuals moving significantly more at night than in the afternoon (df = 2; *p* = 0.022). In contrast, no significant effect was observed for *A. picipes* (df = 2; $\chi^2$ = 4.6; *p* = 0.1) or *P. sericeus* (df = 2; $\chi^2$ = 1.27; *p* = 0.53). Mobility was largely idiosyncratic, with some individuals moving more during the different time steps than others (Figure 6).

# 4. Discussion

Assessing the movement capability of insects is essential for the implementation of effective conservation and restoration measures. While the recent miniaturisation of tags is making it easier to track animals, including insects, there remain constraints such as the impact of tag weight on individual movement and the short detection distance. Here, we found weak effects of the tag on individual behaviours of three small ground-dwelling beetles in the laboratory, effects that were limited to the detritivore species. We obtained data on their daily behaviour by closely monitoring individuals in their habitat for 48 h and then a week later, but with a significant number of losses. In the light of these results, we discuss the implications of these beetle species' daily movements for the recovery of their populations in degraded areas of the Plaine de la Crau dry grassland.

## 4.1. Validation of the tracking technique

Previous radio tracking using passive tags was limited to beetles of more than 20 mm in length and a 0.4 g body mass (Kissling et al., 2014; Testud et al., 2019). Here, we demonstrated the validity of this technique even for smaller beetles (15 mm and 0.12 g). Despite a tendency toward shorter displacements, we observed few significant changes in the behaviour of tagged individuals under laboratory conditions. Only *A. sericea* covered significantly shorter distances per time step with the diode on. However, caution is required in interpreting these results; although we did not observe strong short-term behavioural effects, the tags could have impacts over several days or weeks.
<figure><img src="image_54.png" /><figcaption>FIGURE 3</figcaption></figure>

Control test, (A) Mean distance (± SE) travelled per time step among species and runs in the arena in pixels and (B) Mean explored area (± SE) among species and runs in the arena. n.s. = non-significant. Each coloured line represents an individual.

Because insects are known to be able to carry large extra loads for feeding or building activities, studies on insects' movements are generally conducted using a tag-to-body-mass ratio greater than the 5% body-mass rule established for vertebrates. Here, the full tagging system did not seem to strongly affect the beetles' movements, despite adding 26% to the body weight of *A. picipes*, 26% to *P. sericeus* and 35% to *A. sericea*. Actually, despite the growing use of telemetry techniques for tracking insects, their impacts are rarely assessed. Only 12% of the 173 studies reviewed by Batsleer et al. (2020) quantified the effect of tags on arthropods. In one example, the activity of the flightless cricket, *Gryllus locorojo*, reduced as tag weight increased from 18 to 127% of the individual's body mass (Kaláb et al., 2021). Boiteau et al. (2010), studying the beetle *Conotrachelus nenuphar*, reported that a tag weighing

around 15% of its body mass did not reduce its mean walking speed. Another approach is to consider that tag weight must not exceed the maximum mass of an item the species can lift (Batsleer et al., 2020). This would, however, be difficult to determine for our studied species, which does not have to grab and carry food before eating it.

Our field experiment successfully used RFID to track small ground-dwelling beetle movements in the species' habitat. Despite the short detection distance (the antenna having to pass over the tag to detect it), we were able to locate all individuals except those that lost their tag or were preyed on. This meant we could track a reasonable proportion of the total tagged individuals (25 out of 34). However, our ability to locate individuals decreased greatly after 7 days, with only 16 out of 25 found after thoroughly searching an
<figure><img src="image_55.png" /><figcaption>FIGURE 4</figcaption></figure>

Effect of the diode, (A) Mean distance (± SE) travelled per time step among species and runs in the arena in pixels and (B) Mean explored area (± SE) among species and runs in the arena. Different letters indicate significant differences between runs (*P* < 0.05), n.s. = non-significant. Each coloured line represents an individual.

area 6 metres around the release point. It is therefore unlikely that we could track individuals over several weeks or months without close monitoring, which would be time-consuming and uncertain to succeed. The nature of the data collected is therefore limited to species' daily movements and foraging behaviour, without covering dispersal *sensu stricto* (Silcox et al., 2011). The method's applicability is also limited to species moving over short distances.

## 4.2. Species and individual-level data acquisition

Although limited in time, the data we collected provide useful knowledge on the behaviour and ecology of the three studied species, such as differences according to diet and daily activity. We observed differences between species in the distances travelled.
<table><caption>TABLE 2 Movements of the three species in the field.</caption><thead><tr><th>Species</th><th>ID</th><th>Mean (m)</th><th>sd (m)</th><th>Max (m)</th><th>Sum (m)</th><th>1 week (m)</th></tr></thead><tbody><tr><td rowspan="8">A. picipes</td><td>1</td><td>0.06</td><td>0.10</td><td>0.21</td><td>0.38</td><td>-</td></tr><tr><td>2</td><td>0.09</td><td>23.00</td><td>0.78</td><td>1.03</td><td>0.86</td></tr><tr><td>3</td><td>0.13</td><td>0.19</td><td>0.53</td><td>1.52</td><td>-</td></tr><tr><td>4</td><td>0.22</td><td>0.22</td><td>0.58</td><td>2.60</td><td>1.92</td></tr><tr><td>5</td><td>0.36</td><td>0.63</td><td>1.70</td><td>4.34</td><td>-</td></tr><tr><td>6</td><td>0.53</td><td>0.73</td><td>2.18</td><td>6.37</td><td>-</td></tr><tr><td>7</td><td>0.11</td><td>0.13</td><td>0.31</td><td>0.66</td><td>-</td></tr><tr><td>8</td><td>0.02</td><td>0.05</td><td>0.13</td><td>0.13</td><td>-</td></tr><tr><td rowspan="8">A. sericea</td><td>1</td><td>0.84</td><td>0.83</td><td>3.01</td><td>10.13</td><td>-</td></tr><tr><td>2</td><td>0.11</td><td>0.14</td><td>0.32</td><td>0.67</td><td>1.46</td></tr><tr><td>3</td><td>0.10</td><td>0.19</td><td>0.59</td><td>1.24</td><td>-</td></tr><tr><td>4</td><td>0.11</td><td>0.28</td><td>0.68</td><td>0.68</td><td>0.72</td></tr><tr><td>5</td><td>0.18</td><td>0.20</td><td>1.05</td><td>2.12</td><td>3.95</td></tr><tr><td>6</td><td>0.27</td><td>0.59</td><td>1.96</td><td>3.21</td><td>-</td></tr><tr><td>7</td><td>0.01</td><td>0.04</td><td>0.13</td><td>0.13</td><td>5.47</td></tr><tr><td>8</td><td>0.65</td><td>0.76</td><td>2.23</td><td>7.83</td><td>-</td></tr><tr><td rowspan="8">P. sericeus</td><td>9</td><td>0.65</td><td>1.05</td><td>3.43</td><td>7.80</td><td>5.45</td></tr><tr><td>10</td><td>0.05</td><td>0.13</td><td>0.32</td><td>0.32</td><td>-</td></tr><tr><td>1</td><td>0.22</td><td>0.25</td><td>0.49</td><td>1.34</td><td>-</td></tr><tr><td>2</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.35</td></tr><tr><td>3</td><td>0.04</td><td>0.10</td><td>0.31</td><td>0.51</td><td>2.33</td></tr><tr><td>4</td><td>0.14</td><td>0.13</td><td>0.35</td><td>1.71</td><td>5.51</td></tr><tr><td>5</td><td>0.16</td><td>0.31</td><td>0.80</td><td>1.91</td><td>-</td></tr><tr><td>6</td><td>0.45</td><td>0.77</td><td>1.98</td><td>2.69</td><td>2.16</td></tr><tr><td>7</td><td>0.02</td><td>0.05</td><td>0.13</td><td>0.13</td><td>-</td></tr></tbody></table>

Mean = mean distance (m) / time step; sd = sd distance (m) / time step; max = the maximum distance travelled (m) / time step; sum = the total distance travelled (m); 1 week = the distance (m) travelled from the release point after 1 week (the 11 individuals were all alive).

Unexpectedly, *Asida sericea* travelled the most and farthest in the field, whereas it was the least active and most impacted by the tag in the laboratory. *Poecilus sericeus*, the predator needing to search for prey, could have been expected to move around more than a detritivore or a granivorous species with easy access to food resources. Two non-exclusive explanations can be put forward. Firstly, while it appeared to be unaffected by the tag in the laboratory, *P. sericeus* may suffer more from the extra weight in a more structured environment of stones and dense vegetation, the species being thinner and lighter than the detritivore *A. sericea*. Secondly, *P. sericeus* might prefer to remain hidden from its prey, rather than actively hunting. Our experimental setup, limited in time and space, did not allow us to properly assess distance travelled and our arenas contained no hiding places.

Using both day and night sessions provided fundamental data on the phenology of the three species. They were all more active at night, which is relatively common in beetles, especially dark species. Dark nocturnal species have evolved as an interspecific adaptation to avoid predation (Hernández, 2002), and being nocturnal also allows them to avoid the warmer and drier daytime conditions.

Radio frequency identification tracking also provided useful data at the individual level. Confirming our observations in

the laboratory, we recorded high within-species variability in behaviour. The individuals that were the least active the first day remained less active the following day, regardless of species. These consistent inter-individual differences might suggest the presence of personality traits (Sih et al., 2004) in these three beetles; however, this question will need to be more thoroughly investigated based on a larger number of individuals. From a conservation perspective, animal personality has important implications. Dispersal is often phenotype-biased, with bolder and more exploratory individuals showing a higher dispersal tendency (Cote and Clobert, 2007; Cote et al., 2010). Such data could help explain colonisation dynamics (Cote et al., 2010) and the degree of success of species re-introduction (de Azevedo and Young, 2021).

## 4.3. Implications for the conservation of grassland beetle populations

This study highlights the limitations of using passive tags to track the movements of small terrestrial beetles. The fact that detection requires the antenna to pass over
<figure><img src="image_56.png" /><figcaption>FIGURE 5
Step length per time of day for the three study species in the field.</figcaption></figure>

<figure><img src="image_57.png" /><figcaption>FIGURE 6
Step length in metre during night time per individual and species.</figcaption></figure>

the tag makes it impossible to track individuals that cover
several metres per day over several weeks, and thus to
accurately identify their dispersal capabilities and home
range. However, the data collected here provide valuable
information on the biology of the three species, such as their
nocturnal activity.

We were also able to determine their daily movements,
which might have implications for their conservation and
restoration in the study grassland. This dry grassland has
been degraded by years of cultivation requiring the removal
of the original stone cover (Buisson and Dutoit, 2006).
Stones are a structuring factor for beetle communities
(Blight et al., 2011), probably creating better microclimatic
conditions (havens of moisture and low temperatures in

summer, Lamb and Chapman, 1943; Nobel et al., 1992). These
daily movement data shed light on the dynamics of natural
colonisation of degraded areas from the original habitat. *Asida
sericea* and *P. sericeus*, the two most abundant species in the
original ecosystem, remain present in the formerly cultivated
areas but in significantly lower abundance (Fadda et al.,
2007; Blight et al., 2011). Although both ground-dwelling
species move relatively short distances in the course of a
day, they do move, confirming the hypothesis put forward
by Fadda et al. (2008) of a possible natural colonisation of
degraded areas from the nearby original habitat. Indeed,
in the study area, degraded grasslands are contiguous with
preserved grassland and there are no physical barriers
such as concrete roads. The lower population densities
found in formerly cultivated areas are therefore more likely due to less suitable habitats rather than to limited movement.

Knowing the rate of daily movement is also relevant for the implementation of effective restoration actions. One such proposed action is the restoration of stone cover, key for beetle communities. Even small stone patches dispersed randomly appear to be an effective way to increase beetle richness and abundance on formerly cultivated fields, as suggested by Blight et al. (2011) "several stone patches dispersed over a wide area maximises edge effects between the ecosystem to be restored and the restored habitat patches." However, the spatial distribution of the patches that will ensure the most efficient management depends on the beetles' movement capability. Our RFID monitoring suggests that this distance should not exceed 6 m, as 58% of individuals were found within 6 m of the release point 1 week later.

## 5. Conclusion

While we confirm the limitations of using RFID technology to track small ground-dwelling beetles over a long period in a dry Mediterranean grassland, the data collected provide interesting data on their biology, that may help in the development of restoration actions. Further work should address the challenge of tracking individuals' movements between restored habitat patches.

### Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

### Author contributions

OB, BG, and CA conceived the ideas. OB, BG, LM, and CA designed the experiment and collected the data. LM and CA analysed the data. OB and CA wrote the first draft. All authors contributed critically to the drafts.

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## Funding

This study was supported by the European Research Council, project ERC STG SCALED no. 949812.

## Acknowledgments

We thank Nicolas Bachelier, Paul Guerra, Marine Rousseau, Hélène De Meringo, Victorine Demiralp, and Karolina Argote for their help in the field. We also thank Axel Wolf and the Eco-Musée de Crau for allowing us access to the Nature Reserve of Peau de Meau.

## 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.2023.1040931/full#supplementary-material

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# Appendix 1

Trajectories in the field for individuals that moved at least 1 m from their release point. Release points have been overlapped. Each individual is represented by a given colour. The white square shows their release point. Dots represent the position of the individuals during the 48 h and open circles the position after 1 week (when known). Dotted circles represent distances of 1 m and 6 m from the release point.
<figure><img src="image_58.png" /></figure>

OPEN ACCESS

EDITED BY

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

REVIEWED BY

Ádám Lovas-Kiss,
Hungarian Academy of Sciences, Hungary
Stephen Bonser,
University of New South Wales, Australia

*CORRESPONDENCE

Katalin Szitár

<figure><img src="image_59.png" /></figure>

szitar.katalin@ecolres.hu

RECEIVED 31 January 2023

ACCEPTED 14 April 2023

PUBLISHED 03 May 2023

CITATION

Szitár K, Tölgyesi C, Deák B, Gallé R, Korányi D and Batáry P (2023) Connectivity and fragment size drive plant dispersal and persistence traits in forest steppe fragments. *Front. Ecol. Evol.* 11:1155885.
doi: 10.3389/fevo.2023.1155885

COPYRIGHT

© 2023 Szitár, Tölgyesi, Deák, Gallé, Korányi and Batáry. This is an open-access article distributed under the terms of the [Creative Commons Attribution License (CC BY)](https://creativecommons.org/licenses/by/4.0/). 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.

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

Katalin Szitár¹*, Csaba Tölgyesi², Balázs Deák¹,³, Róbert Gallé¹, Dávid Korányi¹ and Péter Batáry¹

¹'Lendület' Landscape and Conservation Ecology, Institute of Ecology and Botany, Centre for Ecological Research, Vácrátót, Hungary, ²MTA-SZTE 'Momentum' Applied Ecology Research Group, University of Szeged, Szeged, Hungary, ³'Lendület' Seed Ecology Research Group, Institute of Ecology and Botany, Centre for Ecological Research, Vácrátót, Hungary

**Introduction:** Land use changes have seriously fragmented grasslands leading to extensive biodiversity loss worldwide. Habitat fragmentation affects grasslands at both local and landscape scales, adversely affecting the probability of species colonisation and extinction. In our study, we addressed the effects of fragment size and landscape-scale habitat connectivity on the vegetation composition in two grassland types, i.e., loess steppe fragments (situated on kurgans) and sand steppe fragments of the Pannonian forest steppe region.

**Methods:** We collected frequency data on vascular plant species in 12 1 mx1m quadrats in altogether 60 fragments along a connectivity gradient in sand steppes and loess steppe fragments. We analysed whether habitat specialists, generalists and exotic species were affected by the level of fragmentation based on species richness and traits related to local persistence (life span, clonality and soil seed bank type) and dispersal (dispersal strategy and seed mass) in the two grassland types using linear mixed-effects models.

**Results:** Based on our results, both fragment size and landscape-scale connectivity were important in shaping the trait composition of the vegetation. We observed more fragmentation effects in generalist than in specialist species. We found that isolation resulted in fewer specialist species with autochorous dispersal strategy in loess steppe fragments, but, at the same time, also fewer exotics. Isolated loess steppe fragments harboured fewer generalist species with persistent seed bank. Large loess steppe fragments supported more wind-dispersed species than smaller ones. In isolated sand steppe fragments, generalists were more frequent with endozoochorous dispersal strategy and without clonal propagation. Life span, clonal propagation and seed mass did not depend on the level of fragmentation in the two grassland types.

**Discussion:** Our results imply that both sand and loess steppe fragments can rely to some extent on the persistence of clonal perennial specialist and generalist species in small and isolated patches to mitigate fragmentation effects. In conclusion, these processes should be supported by the preservation of large fragments, increase of habitat connectivity combined with targeted management of exotic species.

KEYWORDS

adventive species, functional trait, habitat specialist, habitat isolation, terrestrial habitat island, kurgan, Pannonic loess steppic grassland, Pannonic sand grassland
# 1. Introduction

Land use change is one of the primary drivers of biodiversity loss worldwide, causing degradation and reduced habitat availability (Isbell et al., 2022). Temperate grasslands represent exceptionally high conservation values as they are among the most species-rich communities when considering small (<50 m²) spatial scales (Wilson et al., 2012). However, they have been increasingly fragmented due to ploughing and afforestation (Habel et al., 2013). Despite the drastic level of habitat loss, grasslands still contribute significantly to global and local biodiversity by harbouring many endangered animal and plant species confined to these habitats (Squires and Feng, 2018). Species preservation is essential to provide an insurance biodiversity capacity to reduce the risk caused by the temporal variability of ecosystem processes under current global changes (Loreau et al., 2001).

Habitat fragmentation may affect species at both local and larger spatial scales (Auffret et al., 2018). At the landscape scale, the compositional and configurational heterogeneity of the surrounding habitats shape the species pool by affecting diaspore flow (Gaujour et al., 2012). At the local scale, species pool is filtered primarily by altered abiotic conditions and species interactions (Maurer et al., 2003). Increasing fragmentation leads to an increased distance among habitat patches as it can considerably limit dispersal processes (Taylor et al., 1993) and reduce gene flow (Heinken and Weber, 2013). At the local scale, fragmentation results in reduced habitat patch sizes (Uroy et al., 2019) increasing the extinction risk of species populations due to reduced habitat quality and stronger edge effects (Soons et al., 2005). Unpredictable catastrophic events and demographic stochasticity can also lead to population extinctions more frequently in small patches (Turner, 1996). As isolation and fragment size reduction can amplify each other's effect (Didham et al., 2012), we can gain deeper insights with their joint assessment.

Functional plant traits are effective tools for investigating fragmentation effects offering more general and mechanistic insights into ecosystem processes and higher predictability than taxonomic approaches (McGill et al., 2006). Colonisation and extinction processes cause direct changes in community composition in the course of fragmentation (Jackson and Sax, 2010). These processes are driven by species-specific functional traits linked to population biological processes (Janečková et al., 2017). We might expect that species with efficient propagule dispersal or local persistence traits are more successful and well-preserved in habitat fragments than species without these traits (Marini et al., 2012).

Dispersal potential can be best captured by assessing the main dispersal modes and propagule characteristics of the species, such as seed mass, shape and size (Ottaviani et al., 2020). The long-distance dispersal ability is critically important for species survival in fragmented landscapes (Bacles et al., 2006). Species dispersing by wind or animals efficiently are assumed to be able to colonise more isolated fragments (Vittoz and Engler, 2007). Species with small seed mass have higher dispersal potential by wind because light seeds have lower terminal velocity (Lindborg et al., 2012), whereas heavy seeds with appendices may disperse by animals more effectively (Amar tavshin et al., 2019). Plant species with high dispersal potential are expected to be less vulnerable to fragmentation (Eriksson, 1996), although some studies detected similar (Hemrová and Münzbergová,

2015) or even higher sensitivity to fragmentation of long-distance than short-distance dispersers (Deák et al., 2018).

Long life span, clonal reproduction and persistent soil seed bank are the main traits that are likely to contribute to local persistence (Maurer et al., 2003). Long-lived species are assumed to be less susceptible to fragmentation because of their smaller fluctuations in abundance (Heinken and Weber, 2013). Species capable of clonal propagation with a potentially unlimited life span are not dependent on sexual reproduction for population survival; therefore, they are expected to be less impacted by isolation (Heinken and Weber, 2013). However, environmental suppression of sexual propagation can also lead to monoclonal populations lowering long-term population viability (Honnay and Bossuyt, 2005). The persistent seed bank in the soil also enables plant populations to survive disturbances and tolerate environmental fluctuations, thus prolonging species persistence in the community (Eriksson, 1996). Based on the contradictory results of the different case studies, fragmentation effects on plant traits seem to be context and habitat specific, highlighting the need to assess them in various ecosystems (Heinken and Weber, 2013).

Inspecting only total species richness patterns can hide important aspects of underlying mechanisms of responses to fragmentation (Lindborg et al., 2012). Depending on habitat specialisation, fragmentation effects vary on plant species (Yan et al., 2022). Specialist species have narrow environmental tolerances and thus are limited to specific habitat types (Pandit et al., 2009), and are more susceptible to disturbances than generalist species (Vázquez and Simberloff, 2002). Habitat generalists are important grassland constituents contributing to the total richness and abundance of the vegetation but do not indicate directly good or bad ecological status (Deák et al., 2020). Generalists can persist under a wide range of abiotic conditions; therefore, they are assumed to be less affected by fragmentation (Yan et al., 2022). Non-indigenous species may behave similarly to generalists but have exceptionally high practical importance as drivers of unfavourable ecosystem changes and degradation indicators (Didham et al., 2005). In this paper, we used species groups based on habitat specialisation and origin to understand how the functional composition of the vegetation changes due to fragmentation.

The forest-steppe fragments of the Pannonic biogeographical region provide an ideal setting to assess the effects of fragmentation. The region is the westernmost part of the Eurasian forest-steppe biome, a distinct vegetation zone between closed forests and steppes in subhumid-semi arid climate zones (Erdős et al., 2018a,b). The vegetation is of a mosaic nature where both the forest and steppe are stable vegetation components (Fekete et al., 2002). Two substrate types, sand and loess, are widely distributed in the region, and both harbour valuable habitats listed as Natura 2000 priority habitat types (Pannonic loess steppic grasslands and Pannonic sand steppes) in Annex I of EU's Habitat Directive (European Commission, 2013). Loess and sand steppes represent two extremes in terms of abiotic conditions and productivity (Molnár et al., 2012). Sandy substrates create highly stressed abiotic conditions, whereas water and nutrient cycling is more favourable for plant life on loess (Fekete et al., 2002). Loess and sand steppes have been exposed to extensive anthropogenic habitat loss and fragmentation (Gallé et al., 2022). Because of their clearly defined borders and unsuitable matrix, they can be regarded as terrestrial habitat islands (Deák et al., 2016), serving as excellent model systems to study the effects of fragmentation (Ottaviani et al., 2020).
In our study, we tested if species groups with different origin and habitat specialisation (i.e., specialists, generalists and exotics) show general response patterns against fragmentation in two contrasting steppe types of the Pannonian forest steppe region. We focused on the vegetation of open sand steppe and loess steppe fragments on forest steppes and kurgans (ancient burial mounds) in the Great Hungarian Plain. We assessed the effects of fragment size (large vs. small fragments) and landscape-scale connectivity (Hanski's connectivity index) on the richness and frequency of species with traits related to local persistence (life span, clonal propagation and soil seed bank type) and propagule dispersal (dispersal strategy and seed mass). We expected that (i) specialist plant species would experience more significant effects of connectivity and fragment size than generalists or exotics because they are more dependent on the fragmented steppe habitats; (ii) the importance of connectivity would be higher for dispersal-limited species and (iii) fragment size would affect local persistence trait distribution primarily.

## 2. Materials and methods

### 2.1. Study area

Our study region lies in the Southern part of the Great Hungarian Plain (Figure 1). This is a lowland region with a continental climate characterised by mean annual temperature of 11°C and mean annual precipitation of 550 mm. The semi-natural vegetation of the Pannonian forest-steppe zone can be characterised by a mosaic of dry and open oak (*Quercus* spp.), and poplar (*Populus* spp.) forests and *Festuca* and *Stipa* species dominated steppes (*Molnár et al., 2012*). Here we focused on two major grassland components of the vegetation, i.e., open sand steppe and loess steppe.

Open sand steppes are endemic communities (*Festucetum vaginatae*) to the Pannonian biogeographical region. They are semi-desert-like perennial grasslands occurring in inland sand dune ridges. The average cover of vascular plants is relatively sparse, ranging between 40 and 70% (Erdős et al., 2018a,b). The rest of the surface is usually covered by cryptogams (lichens and mosses) and bare ground. Tussock-forming *Festuca vaginata* and *Stipa borysthenica* dominate

the vegetation, with many rare and threatened forbs confined to this vegetation type (*Csecserits et al., 2011*). The soil is wind-blown arenosol with extremely low (below 3%) humus content and low water-retention capacity (*Csecserits et al., 2011*). Because of the low productivity of the soil, open sand steppes were mostly grazed by sheep or remained unmanaged until the 19th century (*Molnár et al., 2012*). In the 1920s, intensive lowland afforestation programmes started, and by the end of the 20th century, most of the open sand grasslands were converted to non-native tree plantations in the region (*Biró et al., 2008*).

Loess steppes (*Salvio-Festucetum rupicolae*) are highly productive perennial vegetation types developed on chernozem soil (*Fekete et al., 2002*). The vegetation is diverse, dominated by several perennial grasses (e.g., *Festuca rupicola*, *Brachypodium pinnatum* and *Stipa* spp.) and are rich in threatened forbs (*Deák et al., 2016*). Because of their favourable edaphic conditions and flat topography, loess steppe transformation most probably started already in the Neolithic, and was accelerated from the 18th century due to agricultural expansion and intensification (*Deák et al., 2021a,b*). It resulted in the loss of 90% of their original area by the end of the 20th century (*Deák et al., 2016*). In this study, we focused on kurgans, i.e., ancient burial mounds created in the IV-I millennia BC (*Deák et al., 2016*). Kurgans usually take on a hemispherical shape with a height ranging between 0.5 and 15 m, and a diameter between 10 and 110 m (*Dembicz et al., 2021*). As most kurgans are small and isolated in the region, they are usually left unmanaged resulting in the survival of semi-natural vegetation but also unfavourable spontaneous shrub encroachment and litter accumulation (*Deák et al., 2016*).

The sand and loess steppe fragments of our study could be characterised by contrasting surrounding landscape (Figure 1). The sand fragments were embedded into the matrix of small-scale plantation forests planted with non-native *Pinus sylvestris*, *P. nigra* and *Robinia pseudoacacia* trees, and some native *Populus canescens* (*Biró et al., 2008*). These were even-aged plantation forests created after ploughing and harvested with clear-cutting (*Csecserits et al., 2016*). The loess fragments were surrounded by intensively used large-scale agricultural fields, with some farmhouses and pastures. The region's main crops are winter cereals, maize, sunflower and alfalfa (*Gallé et al., 2022*).

<figure><img src="image_60.png" /><figcaption>FIGURE 1</figcaption></figure>

(A) Map of Central Europe showing Hungary, (B) map of the Great Hungarian Plain in Southeast Hungary with the study sites and (C) a loess fragment study site with the 1,000m-buffer that was used to estimate Hanski's connectivity. Note that for sand steppe fragments a 500m-buffer was used.
## 2.2. Study sites

We selected 15 small and 15 large fragments for each steppe type along a connectivity gradient (Figure 1). We considered fragment size as a patch-scale characteristic and connectivity as a landscape-scale predictor. We visited 160 fragments around three (Fischerbócsa, Kéleshalom and Pirtó) and four villages (Dévaványa, Kunágota, Makó and Szentes) for sand and loess steppes, respectively. The available fragment sizes differed in the two types; therefore, we applied differing size ranges for the selection. For sand steppes, the size of the small and large fragments ranged between 0.16 and 0.48 ha, and 0.93–6.88 ha, respectively. In the case of loess steppes, the size of the small and large fragments varied between 0.01–0.10 ha, and 0.20–0.44 ha, respectively.

For measuring connectivity, we calculated Hanski's connectivity index (Hanski and Ovaskainen, 2000) for all potential fragments:

$$CI_i = \sum_{j \neq i} \exp(-\alpha d_{ij}) A_j^{\beta}$$

where $d_{ij}$ stands for the shortest edge-to-edge distance (in km) between fragment i and j within the search radius, $A_j$ is the size of habitat patch j (in m²), $\alpha$ is a constant scaling the species-specific dispersal ability over distance $d_{ij}$ and $\beta$ is an emigration parameter scaled over the size of patch j as a source of migration (Moilanen and Hanski, 2001). Following Rösch et al. (2013), both parameters were set to 0.5 as we applied the index to entire communities. The grain size of the landscape matrix differed in the two steppe types, with a small-scale forest plantation matrix in the first, and a large-scale agricultural matrix in the latter case (Kuli-Révész et al., 2021). Therefore, we applied different buffer radii for the connectivity index calculations (500 for sand and 1,000 m for loess steppes) based on the ecosystem base map of Hungary (Tanács et al., 2021) and Google aerial photographs by using Quantum GIS 3.6.1 (QGIS Development Team, 2019). We considered all semi-natural vegetation patches (open sand grasslands, loess steppe, other forest-steppe fragments and alkali grasslands) as sources of immigration. The connectivity values ranged between 24 and 811 for sand steppe (mean = 394, SD = 206), and from 0 to 2,637 for loess steppe fragments (mean = 689, SD = 748).

## 2.3. Vegetation sampling

We sampled the vegetation in 12 1×1 m quadrats in each fragment. Six quadrats were placed 1–2 m from fragment edges, and six were positioned in the centre to cover habitat heterogeneity. They were located at least 5 m from each other to avoid spatial autocorrelation. We recorded the presence of each vascular plant species in the quadrats in May–June 2019 and 2020. We summed up the occurrences of each plant species for all quadrats in the two sampling periods for each fragment. Thus, the frequency of a species (used as a proxy for abundance) could range between zero and 24 in a fragment.

We divided the plant species according to their habitat specialisation into the following categories: (i) steppe specialists with a regional preference for open sand or loess steppes; (ii) generalist species including all other native species not confined exclusively to sand or loess steppe habitats and (iii) exotic species. Species were assigned to groups based on field guides and expert knowledge

(Király, 2009; Gallé et al., 2022). We assessed five traits related to local persistence and dispersal potential to reveal whether functional traits of the three species groups respond differently to local- and landscape-scale fragmentation effects in the two grassland types. We chose traits that are rather stable within species because we collected trait values from databases that were not observed in the field.

For local persistence, these were the following: life span, clonal propagation and soil seed bank longevity. Life span was categorised into two levels, short-lived species, including annuals and biennials, and long-lived species. The life span of some species could be both short and long. For these, we used the most common life span category according to Király (2009). Clonality was used as a categorical trait with two values (clonal and non-clonal). We differentiated between transient and persistent soil seed bank types, where transient stands for longevity shorter than 1 year and persistent longer than a year, including short- and long-term persistent seed banking. In cases where more than one value was available, we assigned the longer term value for the species. We used seed dispersal strategies as a functional trait related to diaspore dispersal potential, according to Sádlo et al. (2018). They described dispersal mode combinations with different relative importance corresponding to similar diaspore morphological features and ecological demands of the species. They characterised nine strategies based on dispersal mode combinations. In our fragments, four strategy types occurred [dispersal strategy names follow the nomenclature suggested by Sádlo et al. (2018)]: (i) Allium type was the most common strategy with mainly autochory and to a small degree epi-, endozoochory and anemochory; (ii) Bidens type is dominated by autochory and epizoochory, and to a lesser extent endozoochory; (iii) in Cornus type, species disperse predominantly with autochory and endozoochory and (iv) Epilobium type can be characterised by anemochory beside autochory, and rarely zoochory. Seed mass has an important role in both local persistence and dispersal potential, and we considered it in relation to both processes. Seed mass was measured as thousand seed weight. Trait values were collected from various databases such as PADAPT (Sonkoly et al., 2022), Pladias (Wild et al., 2019), LEBA (Kleyer et al., 2008), CLO-PLA (Klimešová and de Bello, 2009), TRY (Kattge et al., 2020) and regional seed mass records (Csontos et al., 2003, 2007; Török et al., 2013, 2016), and the field guide of the Hungarian flora (Király, 2009). For details of species list and trait values see Supplementary Table 1.

## 2.4. Statistical analyses

We analysed the effects of fragment size and connectivity and their interaction on the richness of the three species groups (i.e., specialists, generalists and exotics) and the richness and frequency of plant species with different trait categories. Dispersal strategy categories with less than three species were not tested statistically (i.e., Bidens type and Cornus type specialists and exotics except for Cornus type exotics in loess steppe fragments). For each fragment, we calculated the number and frequency of species assigned to each species group and trait category. We also quantified the fragment-level community-weighted mean for the seed mass weighted by species frequency. Statistical analyses were performed using R version 4.1.1 (R Core Team, 2022). We implemented the analyses for the two grassland types separately. We modelled the relationships with
generalised linear mixed-effects models (GLMMs) using Poisson error
terms and log link function for the categorical traits (Bates et al., 2021)
and linear mixed-effects models for the continuous variable,
community-weighted mean of seed mass after log transformation
(Pinheiro et al., 2017). Hanski's connectivity index values were
log-transformed and ranged between 0 and 1. We treated fragment
size as a categorical fixed variable (small vs. large), the ranged
connectivity index as a continuous explanatory variable and location
(village) served as a random factor in the models. The models were
visually inspected for violations of homoscedasticity by checking
residuals against fitted values. We tested the models for overdispersion
and zero inflation using the DHARMa package (Hartig, 2022). When
we detected overdispersion, we recalculated the models with negative
binomial error term. In the case of significant zero-inflation,
we refitted the model as a zero-inflated Poisson or negative binomial
model using fragment size as the explanatory variable in the zero part
of the model, while fragment size and connectivity and their
interaction were used in the non-zero part of the models using the
glmmTMB package (Brooks et al., 2017). We calculated the conditional
coefficient of determination (i.e., variance explained by the entire
model including both the fixed and random effects) for the models via
the delta method with the MuMln package (Barton, 2022). Data were
visualised using the ggplot2 package (Wickham, 2011).

3. Results

We recorded a total of 178 species in the sand steppe fragments and 270 species in the loess grassland fragments during the 2 years of sampling (Table 1). Sandy fragments harboured 67 specialists, 97 generalists and 14 exotic species, while loess grassland fragments were more diverse, with altogether 43 specialist, 193 generalist and 34 exotic species. The mean richness was 22.3 (SD = 3.9) for specialist, 32.7 (SD = 7.9) for generalist and 4.4 (SD = 1.7) for exotic species in the sand steppe fragments, and 4.4 (SD = 2.9), 54.3 (SD = 8.0) and 5.5 (SD = 2.7) in the loess steppe fragments, respectively. We found that the specialist species pool was dominated by perennial and clonal species as opposed to generalist species in both grassland types (Table 1). In both grassland types, species with a persistent seed bank and autochory-dominated Allium-type dispersal strategy dominated the vegetation in every species group. The average seed mass was the lowest in the case of specialists and the highest in exotics in both grassland types.

In the sand steppe fragments, we found no effect of either
fragment size or connectivity on the richness of the three species
groups (Supplementary Table 2). In contrast, the species richness of
specialist and exotic species was higher with 69 and 31% in the most
connected fragments compared to the most isolated ones in loess
steppe fragments regardless of their size (Figures 2A,B).

We did not find any significant effect of connectivity and fragment
size on the richness or the frequency of short-lived, long-lived or
clonal species in any species groups of the two steppe types
(Supplementary Tables 3, 4). In contrast, isolated sand steppe
fragments had a higher richness of non-clonal generalists than
connected patches (Figure 3A). In the case of loess steppe specialists,
we found that non-clonal species were more abundant in smaller
fragments than in the larger ones (Figure 3B). Exotic species did not
show any significant pattern in clonality along connectivity gradient

or fragment size in either of the grassland types (Supplementary Table 4). We did not observe any effects of connectivity or fragment size on the richness or frequency of specialists with different soil seed bank persistence in either fragment type (Supplementary Table 5). We found that both generalist and exotic species forming persistent seed bank were more frequent in well-connected loess fragments (Figures 3C,D). This difference was not observed in the case of sand steppe fragments. Species with transient seed bank did not show any trend along the connectivity gradient or fragment size in either species groups or grassland types (Supplementary Table 5).

Species with *Allium* and *Epilobium* dispersal strategies (i.e., autochory and anemochory) dominated both grasslands with altogether 71% and 17%, and 77% and 11% in sand and loess fragments, respectively. Autochorous *Allium*-type species did not respond to either connectivity or fragment size in our study, except for loess fragments, where increased connectivity resulted in a higher richness of *Allium*-type specialists (Supplementary Table 6; Figure 4A). Isolation resulted in a higher frequency of generalist species with autochory- and endozochory-dominated *Cornus*-type dispersal in smaller compared to larger fragments in the sand steppes (Figure 4B). We observed more species and higher frequency of generalists *Epilobium* dispersal strategy characterised by anemochory and autochory in large than in small loess steppe fragments (Figures 4C,D). We showed that *Cornus*-type exotic species were more abundant in terms of both richness and frequency in small compared to large isolated fragments (Figures 4E,F). *Bidens* dispersal type with autochory and epizochory dispersal modes was not different based on fragment size and connectivity in either species group and fragment type (Supplementary Table 6). Community-weighted means of seed mass did not have any trend along the connectivity gradient or with increasing fragment size for either species group in the two grassland types (Supplementary Table 7).

4. Discussion

Our results highlighted that both local and landscape-scale factors
were important in shaping the vegetation composition of Pannonic
steppe fragments. We observed more fragmentation effects in
generalists than in specialist species. We found that isolation resulted
in fewer specialist species with autochorous (Allium type) dispersal in
loess steppe fragments. Isolated loess steppe fragments also harboured
fewer generalist species with persistent seed bank but, at the same
time, also fewer exotics. Large loess steppe fragments supported more
species with Epilobium-type dispersal strategy than smaller ones.
We did not find any systematic change along the two fragmentation
factors in the sand fragments, except for the high frequency of
generalists without clonal propagation and Cornus-type
(endozochory- and autochory-dominated) dispersal strategy in
small and isolated fragments.

4.1. Fragmentation effects on species
groups

In sand steppes, we did not observe any fragmentation effects
on the trait composition of the specialist flora. This was contrary
<table><caption>TABLE 1 Number of species occurred in each species groups, percentage of species assigned to each category of local persistence and dispersal potential traits, and average thousand seed weight of the species for each species groups found in sand and loess steppe fragments.</caption><thead><tr><th rowspan="2"></th><th colspan="3">Sand steppe fragments</th><th colspan="3">Loess steppe fragments</th></tr><tr><th>Specialist</th><th>Generalist</th><th>Exotic</th><th>Specialist</th><th>Generalist</th><th>Exotic</th></tr></thead><tbody><tr><td>Number of species</td><td>67</td><td>97</td><td>14</td><td>43</td><td>193</td><td>34</td></tr><tr><td><strong>Life span</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Long-lived (%)</td><td>91.0</td><td>42.3</td><td>64.3</td><td>86.0</td><td>36.8</td><td>38.2</td></tr><tr><td>Short-lived (%)</td><td>9.0</td><td>57.7</td><td>35.7</td><td>14.0</td><td>63.2</td><td>61.8</td></tr><tr><td><strong>Clonality</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Clonal (%)</td><td>61.2</td><td>36.1</td><td>50.0</td><td>51.2</td><td>31.1</td><td>29.4</td></tr><tr><td>Non-clonal (%)</td><td>38.8</td><td>63.9</td><td>50.0</td><td>48.8</td><td>68.9</td><td>70.6</td></tr><tr><td><strong>Soil seed bank persistence</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Persistent (%)</td><td>50.7</td><td>62.9</td><td>50.0</td><td>55.8</td><td>71.5</td><td>70.6</td></tr><tr><td>Transient (%)</td><td>17.9</td><td>25.8</td><td>21.4</td><td>18.6</td><td>11.4</td><td>11.8</td></tr><tr><td>No data (%)</td><td>31.3</td><td>11.3</td><td>28.6</td><td>25.6</td><td>17.1</td><td>17.6</td></tr><tr><td><strong>Dispersal strategy</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Allium type (%)</td><td>80.6</td><td>68.0</td><td>42.9</td><td>90.7</td><td>76.2</td><td>61.8</td></tr><tr><td>Bidens type (%)</td><td>0</td><td>7.2</td><td>7.1</td><td>0</td><td>8.3</td><td>5.9</td></tr><tr><td>Cornus type (%)</td><td>1.5</td><td>10.3</td><td>14.3</td><td>0</td><td>4.7</td><td>20.6</td></tr><tr><td>Epilobium type (%)</td><td>17.9</td><td>14.4</td><td>35.7</td><td>9.3</td><td>10.9</td><td>11.8</td></tr><tr><td>Mean seed mass<br>(mg/1000 seeds + SD)</td><td>2.1 (3.9)</td><td>6.1 (22.8)</td><td>30.8 (58.5)</td><td>1.6 (1.7)</td><td>5.0 (16.2)</td><td>31.2(68.4)</td></tr></tbody></table>

to our expectations, as several studies showed that habitat specialists are sensitive to fragmentation (e.g., Auffret et al., 2018; Yan et al., 2022). The absence of an effect of sand steppe fragmentation on the distribution of specialists may refer to their better dispersal abilities (Hemrová and Münzbergová, 2015), long-term species persistence (Tilman et al., 1994) or their combination. This is in line with our results, as specialist species of the sand steppes have a high potential for local persistence because the majority of the species are long-lived clonal perennials and have lighter seeds helping dispersal among remnant patches (Bakker et al., 1996).

We observed more fragmentation effects in generalists and exotic species than in specialists. Rösch et al. (2013) found that community composition changes were primarily driven by the responses of generalist species during the fragmentation of dry calcareous grasslands as they compose the dominant part of the vegetation. Pandit et al. (2009) also suggested that generalists should respond strongly to patch configuration and connectivity gradients. In line with them, we observed most habitat fragmentation effects in the case of the generalist species group. We found that clonality and dispersal strategies of generalist species depended on fragment size, connectivity or both factors in the two grassland types, and soil seed bank persistence in loess fragments. Reduced patch size results in a high edge-core area ratio that can be exploited by generalists as opposed to specialists (Brückmann et al., 2010). In such case, habitat generalists offer insurance biodiversity, especially if the habitat is disturbed (Deák et al., 2020). However, the increasing dominance of generalist species following fragmentation relative to specialists can lead to biotic homogenisation and be considered an unfavourable degradation process (Öckinger et al., 2010).

We detected a two-fold frequency increase of exotic species in loess steppe fragments along the increasing connectivity gradient, but we found no such effect in sand fragments. This result suggests that exotic species in the sand steppes are mostly good dispersing invasives that are not hindered by fragmentation (Csecserits et al., 2016), while the exotics of loess remnants are dispersal limited to some extent. Moreover, forest plantations around sand fragments also facilitate the invasion of alien plants (Szitár et al., 2014). We found differential responses of the species groups, suggesting that focusing on only one group (e.g., specialists) may be insufficient to evaluate vegetation responses to habitat fragmentation.

## 4.2. Fragmentation effects on dispersal traits

Local species persistence and dispersal traits have been shown to influence plant species sensitivity to habitat fragmentation by several studies (e.g., Lindborg, 2007; Marini et al., 2012). Plant species with high dispersal potential are expected to be disproportionally overrepresented in isolated patches (Dupré and Ehrlén, 2002). We found that not only isolation but also fragment size affected dispersal strategies according to Sádlo et al. (2018). Endozoochorous dispersal (Cornus type) strategy was more frequent in small and isolated sites among sand generalists and exotics in loess fragments. Most of these species were shrubs and trees with efficient bird dispersal (e.g., Celtis occidentalis, Elaeagnus angustifolia, and Morus alba). Extensive shrub encroachment is considered unfavourable in this region as they take up the space from the herbaceous vegetation (Ónodi et al., 2021), and if they are
<figure><img src="image_61.png" /><figcaption>FIGURE 2
(A) Species richness of specialist and (B) exotic species along a connectivity gradient in loess steppe fragments. p-value shows the statistical significance of the explanatory variable, R² stands for the conditional coefficient of determination of the model, whereas the grey shaded area represent the standard error of the mean.</figcaption></figure>

non-native, transformative vegetation changes and biotic homogenisation can occur (Didham et al., 2005). Generalists dispersing predominantly with anemochory and autochory (*Epilobium* dispersal strategy type) in loess fragments were more species rich and frequent in large fragments showing that successful arrival and establishment by wind is proportional to habitat area; therefore, this strategy is less efficient in small remnants. We did not find any fragmentation impacts for the epizoochory- and autochory-dominated *Bidens*-type dispersal strategy, maybe because of the general absence of grazing in both ecosystem types, similar to the results of Soons et al. (2005). In fragmented landscapes, many habitat remnants can remain unoccupied by bad disperser species (Lindborg et al., 2012). In line with this, we found that isolation also negatively affected loess specialist species with autochorous *Allium*-type dispersal. This has important nature conservation implications as these species have the least efficient autochorous dispersal (Vittoz and Engler, 2007). Therefore, they are particularly sensitive to fragmentation and may need active interventions to mitigate dispersal limitation or species reintroduction.

Propagule size is an important functional trait for both species persistence and dispersal, as small diaspores are expected to have higher colonisation potential (Marini et al., 2012), whereas longer longevity but also higher local colonisation rates are predicted for larger ones (Fröborg and Eriksson, 1997). However, similar to our

results, seed mass was not always found to be correlated with remnant area or isolation (Dupré and Ehrlén, 2002; Lindborg, 2007).

## 4.3. Fragmentation effects on local persistence traits

Species longevity, the presence of persistent seed bank and clonal reproduction represent a potentially important form of temporal functional connectivity extending the life span of remnant populations and rescuing those that have gone locally extinct (Auffret et al., 2015). We did not find any fragmentation impact on the longevity of plant species in our study. This was opposing to our expectations, as several studies proved that perennial species are less sensitive to habitat loss because of their long generation time (e.g., Heinken and Weber, 2013), whereas short-lived species are more susceptible to fragmentation, especially fragment size, because of their larger natural fluctuations in abundance (Marini et al., 2012).

Fragmentation is expected to affect clonally reproducing species less than non-clonal species (Hemrová and Münzbergová, 2015). According to that, we did not observe any response of species with the ability of clonal propagation against fragmentation. However, we found that non-clonal species were more abundant in isolated and small patches in both sand and loess fragments. Likewise, Lindborg (2007) observed that long-lived species with clonal ability were unrelated to contemporary grassland connectivity and area whereas non-clonal species were more abundant in isolated fragments. However, they also found that small and isolated fragments in the 50 years' historical landscape had a high share of species with clonal propagation, inferring that an extinction debt existed in clonal plants and may exist in our case, too (Tilman et al., 1994).

The persistent seed bank can create a temporal rescue effect for communities (Honnay et al., 2008). We did not find any association of fragmentation with seed bank persistence in sand fragments. Lindborg (2007) suggested that in the long term, connectivity loss and area reduction would create a plant community dominated by long-lived and clonal plants and plants with a persistent seed bank. In the case of loess fragments, this potential seems to be depleted as we found a lower frequency of generalists with persistent seed bank in isolated sites.

## 4.4. Fragmentation effects on the two grassland types

Overall, the vegetation of loess steppe fragments seemed to be more affected by fragmentation than that of the sand steppe fragments, although we did not make a direct comparison of the two grassland types. In sand steppe fragments, the taxonomic richness of the species groups was similar in fragments with different sizes and levels of connectivity. In contrast, specialist and exotic species occurring in loess fragments were more species rich in connected fragments. This difference was most probably due to the smaller size of loess fragments and their functionally more hostile large-scale agricultural matrix compared to sand fragments (Gallé et al., 2022). Furthermore, we can consider sand fragments functionally less isolated because there are more road verges, forest fringes (Rédei et al., 2014), and thin grassland strips between forestry units that can serve
A

non-clonal generalists in sandy fragments

<figure><img src="image_62.png" /></figure>

C

generalists with persistent seed bank in loess fragments

<figure><img src="image_63.png" /></figure>

B

non-clonal specialists in loess fragments

<figure><img src="image_64.png" /></figure>

D

exotics with persistent seed bank in loess fragments

<figure><img src="image_65.png" /></figure>

FIGURE 3

(A) Species richness of non-clonal generalists in sand grassland fragments, (B) frequency of non-clonal specialists, (C) generalists with persistent seed bank and (D) exotics with persistent soil seed bank in loess steppe fragments in small and large fragments along a connectivity gradient. *p*-value shows the statistical significance of the explanatory variable, *R*² stands for the conditional coefficient of determination of the model, whereas the grey shaded area represent the standard error of the mean.

plant population persistence by supporting meta-population dynamics and thus immigration processes (Szitár et al., 2014). In contrast, road verges preserved only a small portion of grassland specialist plant species near loess grasslands in our study area because of frequent mowing and trampling (Deák et al., 2020, 2021b).

The absence of fragmentation effects of the current landscape can also refer to an extinction debt, that is a time-delayed extinction to be realised in the future without further habitat modification after habitat loss in the past (Kuussaari et al., 2009). A weak extinction debt was shown in the sandy steppe study region by Rédei et al. (2014), who found that the richness of sand specialist flora reflected the historical landscape composition in the 18th century, but they did not find any correlation with the present composition. Deák et al. (2021a) also showed for kurgans that the landscape structure of the 1970s best explained the species richness of loess grassland specialists, referring to an unpaid extinction debt. Their results are not in contradiction with our results, as they showed that contemporary connectivity explained specialist richness almost as well as that in the 1970s. It is also possible that the local management regime (e.g., mowing or grazing) not assessed in this study overrode and obscured fragmentation impacts (Gallé et al., 2022).

# 5. Conclusion

We found that habitat specialist plant species were less dependent on connectivity and habitat area than generalists and exotic species in sand and loess steppe fragments. However, there may be an extinction debt in the effect of fragmentation. Both habitat connectivity and fragment size, two important measures of habitat fragmentation, affected vegetation composition regarding local persistence and dispersal potential-related traits. Based on our analyses, we can predict how shifted species composition would enable communities to respond to further habitat fragmentation if they still own regeneration and resilience potential. We may rely on the persistence of long-lived and clonal specialist and generalist species in fragmented sand and loess steppes, as they showed no response for fragment size and connectivity loss. The regeneration potential of the vegetation following fragmentation can be improved by preserving large fragments and increasing habitat connectivity in parallel. However, given the fact that these also do not buffer against exotic species, active and targeted management of exotic species is also important, especially in times of climate change extremely threatening these habitats.
<figure><img src="image_66.png" /><figcaption>**C** Epilobium dispersal type generalists in loess fragments</figcaption></figure>

<figure><img src="image_67.png" /><figcaption>**E** Cornus dispersal type exotics in loess fragments</figcaption></figure>

<figure><img src="image_68.png" /><figcaption>**B** Cornus dispersal type generalists in sandy fragments</figcaption></figure>

<figure><img src="image_69.png" /><figcaption>**D** Epilobium dispersal type generalists in loess fragments</figcaption></figure>

<figure><img src="image_70.png" /><figcaption>**F** Cornus dispersal type exotics in loess fragments</figcaption></figure>

<figure><img src="image_71.png" /></figure>

FIGURE 4

(A) Richness of specialist species with Allium-type dispersal strategy in loess steppe fragments, (B) frequency of generalist species with Cornus-type dispersal strategy in sandy fragments and (C) species richness and (D) frequency of generalists with Epilobium-type dispersal strategy, (E) species richness and (F) frequency of exotic species with Cornus-type dispersal in loess grassland fragments. p-value shows the statistical significance of the explanatory variable(s), R² stands for the conditional coefficient of determination of the model, whereas the grey shaded area represent the standard error of the mean.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

PB, RG, and KS designed the study. CT, BD, RG, and DK performed data collection and preparation. KS performed data analyses with
substantial input from DK. KS wrote the first draft of the manuscript. All authors contributed to the article and approved the submitted version.

## Funding

This study was supported by the Hungarian National Research, Development and Innovation Office (NKFIH KKP 133839).

## 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.

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## Supplementary material

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<figure><img src="image_72.png" /></figure>

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EDITED BY

Armin Bischoff,
University of Avignon, France

REVIEWED BY

Paulo A. V. Borges,
University of the Azores, Portugal
Olivier Blight,
University of Avignon, France

*CORRESPONDENCE

Felix Helbing

<figure><img src="image_73.png" /></figure>

felix.helbing@uos.de

Received 19 January 2023

ACCEPTED 02 May 2023

PUBLISHED 25 May 2023

CITATION

Helbing F, Fartmann T, Morkel C and Poniatowski D (2023) Rapid response of vascular plants and insects to restoration of montane grasslands.

Front. Ecol. Evol. 11:1148266.

doi: 10.3389/fevo.2023.1148266

COPYRIGHT

© 2023 Helbing, Fartmann, Morkel and Poniatowski. This is an open-access article distributed under the terms of the [Creative Commons Attribution License (CC BY)](https://creativecommons.org/licenses/by/4.0/). 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.

# Rapid response of vascular plants and insects to restoration of montane grasslands

Felix Helbing<sup>1*</sup>, Thomas Fartmann<sup>1,2</sup>, Carsten Morkel<sup>3</sup> and Dominik Poniatowski<sup>1</sup>

**Introduction:** Industrialization has ushered in massive changes in agriculture. Particularly in low mountain ranges, large-scale afforestation with Norway spruce on traditionally managed, semi-natural grasslands has caused a severe decline in biodiversity. Tree removal, hay transfer and resumption of grazing or mowing are typical measures to re-create species-rich grasslands. The aim of this study was to use vascular plants and three insect taxa (leafhoppers, true bugs, and grasshoppers) as bioindicators to evaluate the success of montane grassland restoration on former spruce forests in Central Europe. In addition, we intended to identify the drivers of species richness within the studied grasslands in order to derive suitable recommendations for habitat management.

**Methods:** We analyzed two different treatments: (i) grazed restoration sites where trees had been cut and species-rich green hay had been applied (N = 9) and (ii) target sites with a long continuity of low-intensity grazing (N = 9).

**Results and Discussion:** Our study revealed that all studied taxa responded rapidly to the restoration measures. After a development period of 3 to 5 years, we found no differences in species richness and diversity of leafhoppers, true bugs and grasshoppers (all, target and threatened species). In addition, non-metric multidimensional scaling showed a large overlap in species composition between restoration and target grasslands. Among target and threatened species, vascular plants displayed the same pattern as insects and reached similar values when comparing the two treatments. However, total species richness and diversity of vascular plants were still higher on the target sites and species composition overlapped only partially. Grazing intensity was the predictor with the highest explanatory power in multivariable (Generalized) Linear Mixed-effects Models, being negatively related to species richness of leafhoppers and true bugs. We conclude that the measures implemented were effective in re-establishing target communities of different taxa. The transfer of seed-containing hay enabled or accelerated the development of the vegetation. Insects, on the other hand, were able to recolonize the restored grasslands on their own, given that these sites were embedded in a network of species-rich grasslands. With regard to insects (e.g., leafhoppers and true bugs), it should be ensured that grazing is applied at low intensity.

KEYWORDS

Auchenorrhyncha, green hay transfer, habitat quality, Heteroptera, host plant, nature conservation, Orthoptera, *Picea abies*

<footnote n="1">¹Department of Biodiversity and Landscape Ecology, Osnabrück University, Osnabrück, Germany,</footnote>

<footnote n="2">²Institute of Biodiversity and Landscape Ecology (IBL), Münster, Germany. ³Institute of Applied Entomology, Beverungen, Germany</footnote>
Introduction

For centuries, European landscapes were shaped by traditional
land-use practices (Plieninger et al., 2006; Eriksson, 2021; Fartmann,
2023). Small-scale low-intensity farming created a wide variety of
interconnected habitats, considerably fostering biodiversity
(Plieninger et al., 2006; Halada et al., 2011). With the onset of
industrialization, however, drastic changes in land use were ushered
in throughout Europe, accelerating from the mid-20th century
onwards (Fartmann, 2023). A wide range of organizational and
technological innovations, such as land consolidation instruments,
progressive mechanization and the increasing use of artificial
fertilizers, enabled large-scale intensification of agriculture on
productive soils (Stoate et al., 2001; Robinson and Sutherland, 2002;
Kleijn et al., 2009). By contrast, marginal land that became increasingly
unviable for agricultural use was often abandoned or afforested (Henle
et al., 2008; Fartmann, 2023). The transformation from traditional to
industrial agricultural landscapes is today considered the major driver
of the dramatic decrease in farmland biodiversity across Europe
(Plieninger et al., 2006; Pereira et al., 2012; Fartmann, 2023).

Temperate, semi-natural grasslands, arising from traditional
management, are very rich in plant and animal species and therefore
have an outstanding value for nature conservation (Bonari et al., 2017;
Feurdean et al., 2018; Fartmann et al., 2021). However, for decades,
they have suffered particularly from persistent pressure exerted by
land-use change, which has resulted in continuous habitat loss,
deterioration and fragmentation (Isselstein et al., 2005; Fartmann
et al., 2021; Fartmann, 2023). The contrasting drivers of this
development have been unevenly distributed along elevation
gradients: the conversion of semi-natural grassland to cropland and
the intensification of management have been more pronounced in
lowlands, whereas spontaneous (i.e., succession after abandonment)
and artificial afforestation on former grasslands have especially taken
place at higher elevations (Mottet et al., 2006; Fartmann, 2023).

In Central European low mountain ranges, montane grasslands in
particular have been widely planted with introduced Norway spruce
(Picea abies; Hölzel and Tischew, 2019). This has led to rapid changes
in habitat conditions. Following site preparation, trees severely alter
light and soil conditions as they grow, hampering the development of
ground vegetation (Strand et al., 2021). Grassland plant and animal
species not only lose habitat but are also hindered in dispersal between
remaining habitat patches (Poniatowski et al., 2016). Consequently,
the conversion of grasslands to shady high forests, primarily intended
to produce firewood and timber, has caused a strong decline in
montane species, and semi-natural montane grasslands are seriously
threatened today (Finck et al., 2017; Hölzel and Tischew, 2019).

Besides preserving and improving extant fragments of semi-
natural montane grasslands, habitat restoration is a key component of
nature conservation for increasing biodiversity. In the case of spruce
forests, restoration measures include clear-cutting and subsequent
tillage. However, the soil seed bank is often depleted after decades of
forest use and spontaneous recolonization by dispersing propagules is
limited for many plant species (Bakker et al., 2002; Kiehl et al., 2010).
Target species are therefore actively introduced by transferring green
hay or brush-harvested seeds from nearby species-rich donor
grasslands to restoration sites (Kiehl et al., 2010; Durbecq et al., 2022).

However, the success of implemented measures varies between
restoration projects as it depends on several factors, such as timing,

species composition of donor sites, soil conditions and effectiveness of
reintroduced habitat management (Kiehl et al., 2010; Wagner et al.,
2020). A careful evaluation of habitat restoration is thus essential.
Contrary to common practice, evaluation studies should ideally focus
not only on plants but also include animals, as otherwise there is a risk
of overestimating restoration success (Baur, 2014; McAlpine et al., 2016).
Although plant recovery is an important prerequisite for animal
recolonization, sites may lack suitable habitat quality in terms of
microclimate or vegetation structure (Jones and Davidson, 2016; Helbing
et al., 2021). Moreover, dispersal-limited species often fail to reach
restoration sites spontaneously, especially when dispersal corridors are
limited (Baur, 2014; Poniatowski et al., 2016). This applies in particular
to arthropods that are major drivers of ecosystem functioning in semi-
natural grasslands (Soliveres et al., 2016; Poniatowski et al., 2018; Neff
et al., 2020). Studies evaluating both the flora and arthropod fauna of
restored montane grasslands, though, are still rare (but see Kurtogullari
et al., 2020; Neff et al., 2020). In addition, research to date has tended to
focus on the restoration of montane grassland habitats in open areas (e.g.,
Lencová and Prach, 2011; Sullivan et al., 2020; Durbecq et al., 2022),
whereas restoration projects that involve clearing spruce forests are still
understudied (but see Dassonville et al., 2013).

The objective of this multi-taxon study was to use vascular plants
and three insect taxa (leafhoppers [Hemiptera: Auchenorrhyncha],
true bugs [Hemiptera: Heteroptera] and grasshoppers [Orthoptera])
as bioindicators to evaluate the success of montane grassland
restoration on former spruce forests in a Central European low
mountain range. We compared species richness, diversity and
composition of grazed restoration sites and nutrient-poor pastures
with long-term grazing history (target grassland). The studied insect
taxa (i) play an important role both as consumers and as an abundant
food source for insectivores in grassland ecosystems, (ii) occupy
different ecological niches, (iii) respond quickly to habitat changes and
(iv) allow standardized sampling (Kőrösi et al., 2012; Helbing et al.,
2020; Fartmann et al., 2022c). With a development period of 3 to 5
years after the implemented measures, we studied the short-term
effects of restoration.

In particular, we addressed the following questions:

(i) Do environmental conditions in restored grasslands differ from those in target grasslands?

(ii) What are the effects of restoration measures on species richness and diversity of vascular plants and insects (all, target and threatened species), and how do species compositions differ between both types of studied grasslands?

(iii) Which environmental parameters explain species richness of vascular plants and insects within the studied grasslands, and, on the basis of the results, which recommendations for further habitat management can be given?

Materials and methods

Study area

The study area is located in the Rothaar Mountains, a low
mountain range at the northwestern edge of the German uplands
(51°11′17N, 8°32′25 E; Figure 1). It covers an elevation range from
450 to 842 m a.s.l. and is characterized by a cool (mean annual temperature: 5°C) and humid (mean annual precipitation: 1,450 mm) montane climate with snowy winters (mean snow-cover duration: 100 days/year; Fartmann et al., 2022b). Oligotrophic cambisols on acidic bedrock are the prevalent soils (Geologisches Landesamt Nordrhein-Westfalen (NRW), 1998). Interspersed with grasslands, the landscape is dominated by Norway spruce forests (*Picea abies*), which are non-native to the study region. Although agriculture has been partially intensified here as well, montane grasslands that are grazed or mown at low intensity are still widespread. These comprise mountain hay meadows (order: *Arrhenatheretalia*, alliance: *Polygono-Trisetion*) and species-rich *Nardus* grasslands (order: *Nardetalia strictae*, alliance: *Violion caninae*), both of which are protected under the EU Habitats Directive (92/43/EEC, habitat types 6520 and 6230).

Within the study area, a large-scale EU LIFE project (“Mountain hay meadows near Winterberg”) was carried out from 2011 to 2016. It aimed to restore, improve and protect mountain hay meadows and species-rich *Nardus* grasslands. The project measures included the conversion of spruce forests into species-rich grasslands (Schulte, 2017). After the conduction of the restoration measures, the grasslands have been either grazed or mown at low intensity. In this study, we only considered grazed grasslands that were restored on former spruce forests.

## Restoration methods

The restoration measures were conducted 3 to 5 years prior to our study (i.e., between 2012 and 2014) and are described in detail in Schulte (2017). Overall, the restoration comprised four steps: (i)

deforestation of spruce forests, (ii) removal of remaining branches, (iii) forestry mulching, and (iv) transfer of autochthonous green hay from adjacent donor sites. Only in exceptional cases was the soil additionally milled and harrowed. Long-existing *Nardus* grasslands were rarely accessible by heavy machinery due to topographic and edaphic constraints. Thus, oligotrophic hay meadows with a high number of typical *Nardus* grassland species were mostly chosen as donor sites. For the green hay transfer, these were mown once in early to mid-August of the respective year with a rotary disc mower. The hay was then transported and spread onto the recipient sites using a forage wagon (application rate of 1:1). Only on steeper slopes was spreading by hand necessary.

## Study sites and plots

The effectiveness of the restoration measures was evaluated by a comparative approach. We analyzed two treatments:

(i) Montane grasslands where restoration measures described above were carried out and which have since been managed as rough pastures (restored grassland, *N* = 9, mean size: 0.66±0.11 ha, Figures 2A,B).

(ii) Species-rich pastures with a long continuity of low-intensity grazing. These include *Nardus* grasslands and closely related oligotrophic grassland communities. The pastures are characterized by a high phytodiversity and represent the target state of the restoration of grazed grasslands in the study area (target grassland, *N* = 9, mean size: 1.69±0.39 ha, Figures 2C,D).

<figure><img src="image_74.png" /><figcaption>FIGURE 1
Location of the study area and study sites in Germany.</figcaption></figure>
<figure><img src="image_75.png" /><figcaption>FIGURE 2
Impressions of the study area: (A,B) aerial views with restored grasslands framed in red (photos: F. Helbing), (C) species-rich pasture with long-term grazing history inhabited by *Geranium sylvaticum* (photo D. Poniatowski) and (D) long-term pasture grazed by red cattle (photo D. Poniatowski).</figcaption></figure>

The majority of the sites were grazed by cattle (61%), followed by horses (28%) and goats (11%). In the center of each site, we established a rectangular plot with a total size of 500 m² and a distance of at least 10 m to the site boundary (to avoid edge effects; cf. Kurtogullari et al., 2020). The plots were marked with magnets and tent pegs, which were placed in the ground together. With the help of a magnetic detector, the locations were accurately retrieved during subsequent visits. In order to address potential issues with spatial autocorrelation, the study area was divided into five subareas, each comprising at least one restored grassland site (Figure 1, see also the “Statistical analysis” section: LMM and GLMM with random effects). We attempted to balance the number of sites of the two treatments within each subarea. However, due to the limited availability of suitable pastures, this was not feasible in subarea IV. We therefore increased the number of studied target grasslands in the adjacent subarea V.

## Species sampling and classification

We sampled vascular plants and insects in 2017. Insect sampling was always conducted under favorable weather conditions (dry and sunny days with temperatures > 15°C). Depending on the phenology of each species group, the period and frequency of the surveys varied. In order to evaluate the effects of grassland restoration, we classified three groups of vascular plants and insects: all, target and threatened

species. Criteria for defining target species were determined individually for each species group and are described below. If available, we obtained the threat status of the species from the latest red data books of the federal state North Rhine-Westphalia (vascular plants, grasshoppers), otherwise red data books of Germany (leafhoppers, true bugs) were used. Hereinafter, species that are listed as “critically endangered,” “endangered,” “vulnerable,” or “near threatened” (red-list categories: 1, 2, 3 and V) are termed “threatened species.” Literature on species identification, scientific nomenclature and the threat status of the studied taxa is listed in Supplementary material.

### Vascular plants

We established a subplot covering 16 m² (4 m × 4 m) in the center of each plot to record vascular plant species richness and cover. The main vegetation survey was carried out in early June. In early August, we revisited the subplots to search for late-flowering plants such as eyebright (*Euphrasia* spp.). Species cover was estimated according to the Wilmanns scale (Wilmanns, 1998). For statistical analyses, the categories were translated into percentage-cover values: r = 0.1%, + = 0.5%, 1 = 2.5%, 2 m = 2.5%, 2a = 10%, 2b = 20.5%, 3 = 38%, 4 = 63%, and 5 = 88% (Dierschke, 1994).

In addition to the quantitative data gathered within the subplots, we searched the 500 m² plots in their entirety for additional plant species during both surveys. From the resulting species list, we determined the host plants of sampled leafhoppers (Nickel and
Remane, 2002; Nickel, 2003) and true bugs (Wachmann et al., 2004, 2006, 2007, 2008) and used their counts as explanatory variables (see the “Statistical analysis” section). Both the donor and target sites were characterized by plant species typical of *Nardus* grasslands as well as mountain hay meadows. Thus, we defined all characteristic species of the phytosociological class *Nardo-Callunetea*, the alliance *Polygono-Trisetion* and their respective subunits as target species (Dierschke, 1997; Oberdorfer, 2001; Peppler-Lisbach and Petersen, 2001; Supplementary Table 1).

## Leafhoppers and true bugs

Leafhoppers and true bugs were surveyed together three times in early June, mid-July and early September. We combined a sweep net (30 cm diameter) and a G-Vac suction apparatus (Stihl SH 56, Waiblingen, Germany; 12.5 cm diameter suction tube; 710 m³h⁻¹ air flow rate) with a fine gauze collection bag (300 µm mesh size) on the inner side of the inlet nozzle to cover all available microhabitats and sample the complete range of herb- and ground-dwelling species (cf. Stewart, 2002; Helbing et al., 2020). We walked in loops over the whole plot and randomly performed 50 sweep net strokes and 50 suction samples. The latter was done by holding the nozzle onto the ground for 10 s (cf. Helbing et al., 2021). The catches were killed with ethyl acetate and identified in the laboratory using a digital microscope (leafhoppers: Keyence VHX-900F, Osaka, Japan) or binoculars (true bugs: Helmut Hund 7–90×, Wetzlar, Germany). Data from both sampling techniques were pooled for statistical analyses. For some genera, identification of females at the species level is not possible (e.g., *Aphrodes*, *Psammotettix*, *Ribautodelphax*). These females were identified at the genus level or, if present, assigned to the corresponding males. In the case of more than one species of a genus, the number of females was assumed to correspond to the number of males (cf. Helbing et al., 2021). We defined typical inhabitants of semi-natural grasslands as target species. For leafhoppers, we listed all sampled grassland species that avoid intensive to very intensive management, based on Nickel and Achtziger (1999). From this list, we then removed species that occur exclusively on unmanaged or wet grasslands, as well as pioneer species (Nickel and Achtziger, 1999; Nickel, 2003; Supplementary Table 2). True bug target species were classified according to Wachmann et al. (2004, 2006, 2007, 2008). We included all species that primarily occur on grasslands with a low management intensity except for typical inhabitants of fringe and wetland habitats as well as pioneer species (Supplementary Table 3).

## Grasshoppers

Grasshopper sampling took place once per plot in early August. We used a box quadrat (1.41 × 1.41 m ≅ 2.0 m²), which is a well-approved and accurate tool for surveying species richness and abundance of grasshoppers (Gardiner and Hill, 2006). In each plot, we randomly dropped the box quadrat at 10 different points, covering a total area of 20 m² (cf. Fartmann et al., 2022a). Species were identified in the field and released afterwards. As with leafhoppers and true bugs, we intended to classify grasshopper species typical of semi-natural grasslands as target species. Poniatowski et al. (2020) presented a species farmland index (SFI) for German grasshopper species that measures the average availability of high nature value farmland (HNV) within a species' range. HNV is a term used to describe biodiversity-rich farming

systems, usually resulting from low-intensity traditional land-use practices (Lomba et al., 2014). Habitat specialists that strongly depend on open, semi-natural habitats receive high SFI values, whereas values for habitat generalists are low. In this study, we classified all species with an SFI value of at least 17.0 as target species (Supplementary Table 4).

## Environmental conditions

### Local climate

We determined the mean elevation (m.a.s.l.) of the study sites from topographic maps using the geographical information system ArcGIS 10.6. Moreover, long-term averages of annual temperature (°C) and precipitation (mm; period 1981–2010) were derived from grid maps with a spatial resolution of 1 km² (German Meteorological Service, 2022). If sites covered more than one grid cell, we calculated mean values.

During fieldwork, we measured aspect and slope of the plots. In combination with the latitude of the study area (51°), these data were used to calculate the potential amount of direct incident radiation (in MJ cm⁻² yr⁻¹) as an approximate measure of the local climate (McCune and Keon, 2002).

### Habitat characteristics

We calculated the size of the study sites (ha) using orthophotos in ArcGIS 10.6. The intensity of grazing was determined on a metric scale. Combining own observations and information provided by farmers, we recorded the composition of grazing livestock and the duration of grazing (with an accuracy of 0.5 months) for each site during the 2017 season. Each type of animal (species and age) was converted into a livestock unit (LSU) using a conversion key for North Rhine-Westphalia (Table 1; LANUV (Landesamt für Natur, Umwelt und Verbraucherschutz Nordrhein-Westfalen), 2022). The grazing intensity of a site was calculated as the product of the density of livestock (summed LSU per hectare) and the months of grazing (MoG).

In the course of the main vegetation survey in June 2017, we recorded parameters of horizontal and vertical habitat structures within each subplot. We estimated the cover of grasses, herbs, cryptogams, bare soil and litter with an accuracy of 5%. If values were above 95% or below 5%, we used steps of 2.5% (Helbing et al., 2021). The vegetation height of the field layer was measured with an accuracy of 2.5 cm. To characterize soil conditions, we also calculated Ellenberg's indicator values for vascular plants (Ellenberg et al., 2001; mean values for moisture, nitrogen, and soil reaction).

<table><caption>TABLE 1 Conversion key for the calculation of livestock units per site [LANUV (Landesamt für Natur, Umwelt und Verbraucherschutz Nordrhein-Westfalen), 2022].</caption><thead><tr><td>Animal type</td><td>Livestock unit</td></tr></thead><tbody><tr><td>Cattle &lt; 6 months of age</td><td>0.4</td></tr><tr><td>Cattle 6 months–2 years of age</td><td>0.6</td></tr><tr><td>Cattle &gt; 2 years of age</td><td>1</td></tr><tr><td>Horse &gt; 6 months of age</td><td>1</td></tr><tr><td>Goat</td><td>0.15</td></tr></tbody></table>
# Statistical analysis

## Comparison of habitat types

All statistical analyses were performed using R 4.1.2 (R Core Team, 2022). We quantified the taxonomic richness and diversity of vascular plants and insects using Hill numbers, which provide a mathematically unified set of diversity indices in units of species (Hill, 1973; Jost, 2006; Chao et al., 2014). The sensitivity of these indices to species relative abundances is controlled by the order *q* (Chao et al., 2014). We considered Hill numbers at *q* = 0, which represents species richness, and at *q* = 1, which is equivalent to the exponential of Shannon entropy (hereinafter termed “diversity”; Jost, 2006; Chao et al., 2014). We tested for significant differences in environmental conditions, species richness and diversity between restored and target grasslands. For the former, we used the Mann-Whitney *U*-test since the majority of environmental variables showed highly skewed distributions and could thus not be analyzed by mixed-effects models (cf. Helbing et al., 2021). By contrast, species richness and diversity of vascular plants, leafhoppers, true bugs and grasshoppers (all, target and threatened species) were compared via Linear Mixed-effects Models (LMM) or Generalized Linear Mixed-effects Models (GLMM) with *habitat type* as a nominal predictor and *subarea* (*N* = 5; see the “Study sites and plots” section) as a random intercept (R package lme4; Bates et al., 2022). For normally distributed and log-transformed variables with a normal distribution, we applied LMMs, otherwise we calculated GLMMs with a negative-binomial error structure to account for overdispersion (Richards, 2008).

Species compositions of restored and target grasslands were compared via non-metric multidimensional scaling (NMDS; R package vegan, metaMDS function; Oksanen et al., 2022) with the Bray-Curtis distance as a distance measure and a maximum number of 200 random starts in search of a stable solution. The four studied species groups were analyzed separately. We included only those species in the analyses that were sampled on at least three plots. For each species group, we performed a Permutational Multivariate Analysis of Variance with 999 permutations (PERMANOVA; Bray-Curtis distance; R package vegan, adonis2 function; Oksanen et al., 2022) to test for significant differences between restored and target grasslands.

## Effects of environmental conditions on species richness of vascular plants and insects

We fitted (G)LMMs with the same random effects and error structure as described above to analyze the effects of environmental parameters on species richness of vascular plants and insects (target and threatened species). For each of the studied species groups, we included a specific and ecologically reasonable set of variables into the models (e.g., the number of leafhopper host plant species was used only to analyze leafhopper species richness, whereas Ellenberg indicator values characterizing soil conditions were included only in the modeling of vascular plant species richness). A detailed assignment of the parameters to the species groups is given in Table 2. Prior to the analyses, we standardized all fixed effects to achieve comparability of effect sizes (cf. Fumy and Fartmann, 2021). Furthermore, we graphically examined all combinations of response and predictor variables before computing the (G)LMMs. If we detected unimodal rather than linear relationships between two variables, we also entered

centered and squared values of the predictor into the full model in addition to the untransformed values (cf. Kämpfer and Fartmann, 2022). This was the case for the Ellenberg nitrogen value and threatened vascular plant species. To avoid multicollinearity, we also calculated Spearman's rank correlation (*r*<sub>s</sub>) for all combinations of predictor variables (Dormann et al., 2013). In cases where two or more variables were strongly intercorrelated (|*r*<sub>s</sub>| ≥ 0.6, *p* < 0.05), only one was included in statistical modeling (Supplementary Table 5). We applied model averaging based on an information-theoretic approach for all multivariable analyses (Grueber et al., 2011). In a first step, all possible combinations of environmental parameters were tested, resulting in a set of different candidate models. These candidate models were then ranked based on Akaike's information criterion (AIC<sub>c</sub>) using the “dredge” function (R package MuMln; Bartoń, 2022). Finally, the top-ranked models within ΔAIC<sub>c</sub> < 2 were used for model averaging (Grueber et al., 2011). We evaluated the explanatory power of the models by calculating marginal R<sup>2</sup> (variance explained by fixed effects) and conditional R<sup>2</sup> (variance explained by both fixed and random effects; Nakagawa et al., 2017). The *p*-values for LMMs were determined with the R package “lmerTest” (Kuznetsova et al., 2022).

# Results

## Environmental conditions

Restored and target grasslands differed only slightly in environmental conditions (Table 2). Local climate, grazing intensity, host plants of leafhoppers and true bugs as well as most parameters of habitat structure did not differ. Restored grasslands were merely smaller, had a lower cover of herbs and lower Ellenberg indicator values for nitrogen and soil reaction.

## Species richness, diversity, and composition of vascular plants and insects

We sampled a total of 267 species in the four species groups (Table 3; Supplementary Tables 1–4). Vascular plants and leafhoppers were the most species rich taxa, followed by true bugs and grasshoppers. On average, 16% of the species per group were classified as threatened (ranging between 8% in true bugs and 29% in grasshoppers) and 34% as target species (ranging between 15% in vascular plants and 58% in leafhoppers). With a frequency of 100% in both studied habitat types, *Agrostis capillaris*, *Festuca rubra* agg., *Luzula campestris*, and *Rumex acetosa* were the most widespread vascular plant species in our study. The most abundant species of leafhoppers were *Deltocephalus pulicaris* (*N*<sub>individuals</sub> = 4,051; 22%) and *Verdanus abdominalis* (*N*<sub>individuals</sub> = 3,451; 18%), those of true bugs were *Pachytomella parallela* (*N*<sub>individuals</sub> = 955; 46%) and *Nabis flavomarginatus* (*N*<sub>individuals</sub> = 385; 19%), and those of grasshoppers were *Chorthippus biguttulus* (*N*<sub>individuals</sub> = 512; 45%) and *Pseudochorthippus parallelus* (*N*<sub>individuals</sub> = 414; 36%).

When comparing restored and target grasslands, no differences in species richness and diversity of leafhoppers, true bugs and grasshoppers (all, target and threatened species) were found (Figures 3C–H). This was also true for target and threatened species of vascular plants (Figures 3A,B). It was only the total
<table><caption>TABLE 2 Metric environmental parameters [mean±standard error (SE) as well as minimum (Min) and maximum (Max) values] in restored (N =9) and target (N =9) grasslands.</caption><thead><tr><th rowspan="2">Parameter</th><th colspan="2">Restored grassland</th><th colspan="2">Target grassland</th><th rowspan="2">P</th><th rowspan="2">Used for (G)LMM analyses of<sup>a</sup></th></tr><tr><th>Mean±SE</th><th>Min-Max</th><th>Mean±SE</th><th>Min-Max</th></tr></thead><tbody><tr><td colspan="7"><strong>Local climate</strong></td></tr><tr><td>Elevation (m a.s.l.)</td><td>698 ± 29</td><td>(518-775)</td><td>660 ± 23</td><td>(531-757)</td><td>n.s.</td><td>P, L, T, G</td></tr><tr><td>Average annual temperature (C°)</td><td>6.4 ± 0.1</td><td>(5.8-7.2)</td><td>6.6 ± 0.1</td><td>(5.8-7.2)</td><td>n.s.</td><td>P, L, T, G</td></tr><tr><td>Annual precipitation (mm)</td><td>1,282 ± 21</td><td>(1,147-1,351)</td><td>1,261 ± 21</td><td>(1,147-1,351)</td><td>n.s.</td><td>P, L, T, G</td></tr><tr><td>Direct incident radiation<sup>b</sup><br>(MJ cm<sup>-2</sup> yr.<sup>-1</sup>)</td><td>0.78 ± 0.04</td><td>(0.63-0.91)</td><td>0.84 ± 0.04</td><td>(0.61-0.94)</td><td>n.s.</td><td>P, L, T, G</td></tr><tr><td colspan="7"><strong>Habitat characteristics</strong></td></tr><tr><td>Site size (ha)</td><td>0.66 ± 0.11</td><td>(0.22-1.25)</td><td>1.69 ± 0.39</td><td>(0.21-3.94)</td><td>*</td><td>P, L, T, G</td></tr><tr><td>Grazing intensity<sup>c</sup> (LSU MoG ha<sup>-1</sup>)</td><td>3.9 ± 0.8</td><td>(0.6-7.8)</td><td>5.3 ± 1.1</td><td>(0.6-8.9)</td><td>n.s.</td><td>P, L, T, G</td></tr><tr><td colspan="7"><strong>Habitat structure</strong></td></tr><tr><td>Cover (%)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Grasses</td><td>74.4 ± 4.5</td><td>(55-95)</td><td>63.9 ± 4.1</td><td>(50-90)</td><td>n.s.</td><td>L, T, G</td></tr><tr><td>Herbs</td><td>21.4 ± 4.2</td><td>(2.5-40)</td><td>40.0 ± 3.8</td><td>(15-50)</td><td>**</td><td>L, T, G</td></tr><tr><td>Cryptogams</td><td>58.3 ± 7.8</td><td>(20-90)</td><td>34.2 ± 11.9</td><td>(2.5-90)</td><td>n.s.</td><td>L, T, G</td></tr><tr><td>Bare ground</td><td>2.5 ± 1.2</td><td>(0-10)</td><td>3.6 ± 1.0</td><td>(0-10)</td><td>n.s.</td><td>L, T, G</td></tr><tr><td>Litter</td><td>40.0 ± 9.0</td><td>(15-85)</td><td>35.0 ± 7.8</td><td>(5-85)</td><td>n.s.</td><td>L, T, G</td></tr><tr><td>Vegetation height (cm)</td><td>14.9 ± 2.1</td><td>(8-27)</td><td>14.4 ± 1.8</td><td>(8-22)</td><td>n.s.</td><td>L, T, G</td></tr><tr><td>No. vascular plant species</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Leafhopper host plants</td><td>18.0 ± 1.7</td><td>(12-30)</td><td>21.6 ± 1.5</td><td>(14-29)</td><td>n.s.</td><td>L</td></tr><tr><td>True bug host plants</td><td>16.1 ± 1.5</td><td>(12-27)</td><td>17.2 ± 1.2</td><td>(13-23)</td><td>n.s.</td><td>T</td></tr><tr><td>Ellenberg indicator value (unitless)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Moisture</td><td>5.0 ± 0.1</td><td>(4.6-5.8)</td><td>5.0 ± 0.1</td><td>(4.6-5.3)</td><td>n.s.</td><td>P</td></tr><tr><td>Nitrogen</td><td>3.8 ± 0.2</td><td>(3.1-4.8)</td><td>4.5 ± 0.2</td><td>(3.4-5.2)</td><td>*</td><td>P</td></tr><tr><td>Soil reaction</td><td>4.0 ± 0.2</td><td>(3.1-4.9)</td><td>4.8 ± 0.1</td><td>(4.3-5.3)</td><td>*</td><td>P</td></tr></tbody></table>

Differences between the two habitat types were analyzed using the Mann-Whitney U-test. Statistical significances are indicated as follows: n.s., not significant, *p ≥ 0.05, **p < 0.05, ***p < 0.01.

<table><caption>TABLE 3 Overview of the studied taxa with numbers of species and individuals [total, mean±standard error (SE) as well as minimum (Min) and maximum (Max) values] per taxon (N<sub>sites</sub> =18).</caption><thead><tr><th colspan="2">Taxon</th><th colspan="3">Number of species</th><th colspan="3">Number of individuals</th></tr><tr><th>Scientific</th><th>Alias<sup>a</sup></th><th>Total</th><th>Mean±SE</th><th>Min-Max</th><th>Total</th><th>Mean±SE</th><th>Min-Max</th></tr></thead><tbody><tr><td>Tracheophyta</td><td>Vascular plants</td><td>129</td><td>30.3 ± 2.2</td><td>14-50</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Hemiptera: Auchenorrhyncha</td><td>Leafhoppers</td><td>73</td><td>25.9 ± 0.9</td><td>19-32</td><td>18,723</td><td>1,042.1 ± 93.9</td><td>378-1,811</td></tr><tr><td>Hemiptera: Heteroptera</td><td>True bugs</td><td>51</td><td>11.3 ± 1.0</td><td>4-21</td><td>2,073</td><td>115.8 ± 14.3</td><td>38-255</td></tr><tr><td>Orthoptera</td><td>Grasshoppers</td><td>14</td><td>4.9 ± 0.3</td><td>4-8</td><td>1,151</td><td>63.6 ± 10.5</td><td>10-145</td></tr></tbody></table>

species richness and the total species diversity of vascular plants that were higher in target than in restored grasslands (Figures 3A,B). NMDS revealed similar patterns in terms of species composition. There was a large overlap in leafhoppers (F<sub>1,16</sub> = 1.39, p = 0.20) and grasshoppers (F<sub>1,16</sub> = 1.13, p = 0.34) between restored and target grasslands (Figures 4B,D). True bugs also exhibited

similarity between the two grassland types, but only for the centrally located target grasslands, while other target grasslands were more dispersed (F<sub>1,16</sub> = 4.20, p < 0.01; Figure 4C). Vascular plants showed some overlap between restored and target grasslands as well, but overall, they were more segregated from one another (F<sub>1,16</sub> = 4.28, p < 0.01; Figure 4A).

<footnote>aP, Plants; L, Leafhoppers; T, True bugs; G, Grasshoppers.</footnote>

<footnote>bDirect incident radiation was calculated according to McCune and Keon (2002).</footnote>

<footnote>cLSU, Livestock units; MoG, Months of grazing (accuracy: 0.5 months; for details see the "Habitat characteristics" section).</footnote>

<footnote>aThis term is used throughout the paper.</footnote>
## Response of vascular plants and insects to environmental conditions

The (G)LMM analyses identified effects of environmental parameters on species richness of vascular plants, leafhoppers and true

bugs. The number of vascular plant target species increased with annual precipitation and decreased with Ellenberg nitrogen values (Table 4A; Figures 5A,B). By contrast, the number of threatened vascular plant species was highest at intermediate Ellenberg nitrogen values (Table 4B; Figure 5C). Grazing intensity was the parameter with the highest

<figure><img src="image_76.png" /></figure>

FIGURE 3

Mean values (± standard error) of species richness (Hill numbers of order *q* =0) and diversity (expressed as exponential Shannon diversity; Hill numbers of order *q* =1) for all, target and threatened species of (*A*,*B*) vascular plants, (*C*,*D*) leafhoppers, (*E*,*F*) true bugs, and (*G*,*H*) grasshoppers in restored (*N* =9) and target grasslands (*N* =9). Asterisks indicate a significant difference between the two habitat types (tested via mixed-effects models with *subarea* [*N* =5] as a random intercept; \* *p* <0.05).
<figure><img src="image_77.png" /></figure>

<figure><img src="image_78.png" /></figure>

<figure><img src="image_79.png" /></figure>

<figure><img src="image_80.png" /></figure>

FIGURE 4

NMDS ordinations (Bray-Curtis distance, four dimensions) for assemblages of (A) vascular plants (based on 65 species, stress=0.06), (B) leafhoppers (based on 47 species and 18,498 individuals, stress=0.10), (C) true bugs (based on 22 species and 2,003 individuals, stress=0.09), and (D) grasshoppers (based on 8 species and 1,133 individuals, stress=0.05) across restored (N =9) and target grasslands (N =9).

explanatory power in the multivariable analyses for two of the three insect groups: it negatively affected the species number of leafhoppers (target and threatened species) and true bugs (target species; Tables 4C-E; Figures 5D,E,H). Moreover, direct incident radiation had a positive effect on the number of threatened leafhopper species (Table 4D; Figure 5F) and the number of true bug host plant species was positively related to the number of true bug target species (Table 4E; Figure 5G). For the species richness of grasshoppers (both target and threatened species) and threatened true bugs, there was no relationship with any of the parameters analyzed. The explanatory power of all models was generally high ($R_m^2$ = 0.30-0.54; $R_c^2$ = 0.30-0.63).

# Discussion

## Evaluation of restoration measures

Our study revealed that vascular plants and insects (leafhoppers, true bugs, and grasshoppers) responded rapidly to the restoration of

species-rich montane grasslands on former spruce forests. After a development period of 3 to 5 years, restored and target grasslands showed a large overlap in the composition of insect species. Furthermore, the studied insect groups neither differed in species richness nor in diversity of all, target and threatened species between the two grassland types. In vascular plants, the same was true for species richness and diversity of target and threatened species. By contrast, total species richness and diversity of vascular plants was still higher in target grasslands and species composition overlapped only partially.

The transfer of seed-containing green hay is an effective method to restore species-rich semi-natural grasslands (Kiehl et al., 2010; Durbecq et al., 2022). Nearby donor sites ensure the preservation of the genetic identity of local plant communities (Albert et al., 2019). In addition, the plant material is usually cut close to the soil surface, enabling the transfer of low-growing plant species as well, and the hay protects seedlings from solar radiation, drought and the competition of ruderal plants (Kiehl et al., 2010; Durbecq et al., 2022). However, a certain proportion of species usually fail to establish on the restoration
<table><caption>TABLE 4 Model-averaging results: influence of environmental parameters (predictor variables) on species richness (Hill numbers of order q =0; target and threatened species) of (A,B) vascular plants, (C,D) leafhoppers, (E,F) true bugs, and (G,H) grasshoppers, analyzed with Linear Mixed-effects Models (LMM) (A,C,D,E) and Generalized Linear Mixed-effects Models (GLMM; negative binomial error structure) (B,F,G,H).</caption><thead><tr><th>Parameter</th><th>Estimate</th><th>SE</th><th>z/t</th><th>P</th><th>Parameter</th><th>Estimate</th><th>SE</th><th>z</th><th>P</th></tr></thead><tbody><tr><td colspan="10"><strong>Vascular plants</strong></td></tr><tr><td colspan="10">(A) Target species<sup>a</sup> R<sup>2</sup><sub>LMMm</sub> = 0.33-0.44, R<sup>2</sup><sub>LMMc</sub> = 0.35-0.44</td></tr><tr><td>(Intercept)</td><td>1.45</td><td>0.12</td><td>11.50</td><td>***</td><td colspan="5">(B) Threatened species<sup>b</sup> R<sup>2</sup><sub>GLMMm</sub> = 0.30, R<sup>2</sup><sub>GLMMc</sub> = 0.30</td></tr><tr><td>Ellenberg nitrogen value</td><td>-0.30</td><td>0.13</td><td>2.23</td><td>*</td><td>(Intercept)</td><td>1.40</td><td>0.34</td><td>3.97</td><td>***</td></tr><tr><td>Annual precipitation</td><td>0.26</td><td>0.12</td><td>2.03</td><td>*</td><td>Ellenberg nitrogen value (CSV<sup>c</sup>)</td><td>-1.18</td><td>0.50</td><td>2.11</td><td>*</td></tr><tr><td>Ellenberg moisture value</td><td>0.18</td><td>0.11</td><td>1.52</td><td>n.s.</td><td colspan="5"></td></tr><tr><td colspan="10"><strong>Leafhoppers</strong></td></tr><tr><td colspan="10">(C) Target species<sup>b</sup> R<sup>2</sup><sub>LMMm</sub> = 0.51, R<sup>2</sup><sub>LMMc</sub> = 0.51</td></tr><tr><td>(Intercept)</td><td>15.94</td><td>0.51</td><td>31.48</td><td>***</td><td colspan="5">(D) Threatened species R<sup>2</sup><sub>LMMm</sub> = 0.37-0.54, R<sup>2</sup><sub>LMMc</sub> = 0.45-0.54</td></tr><tr><td>Grazing intensity</td><td>-2.19</td><td>0.52</td><td>-4.21</td><td>***</td><td>(Intercept)</td><td>4.82</td><td>0.33</td><td>13.49</td><td>***</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>Grazing intensity</td><td>-1.09</td><td>0.31</td><td>3.17</td><td>**</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>Direct incident radiation</td><td>0.71</td><td>0.30</td><td>2.16</td><td>*</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>Herbs</td><td>0.65</td><td>0.30</td><td>1.94</td><td>n.s.</td></tr><tr><td colspan="10"><strong>True bugs</strong></td></tr><tr><td colspan="10">(E) Target species R<sup>2</sup><sub>LMMm</sub> = 0.31-0.49, R<sup>2</sup><sub>LMMc</sub> = 0.41-0.63</td></tr><tr><td>(Intercept)</td><td>6.34</td><td>0.55</td><td>10.48</td><td>***</td><td colspan="5">(F) Threatened species</td></tr><tr><td>No. host plant species</td><td>1.10</td><td>0.46</td><td>2.18</td><td>*</td><td colspan="5">n.s.</td></tr><tr><td>Grazing intensity</td><td>-1.08</td><td>0.43</td><td>2.32</td><td>*</td><td colspan="5"></td></tr><tr><td colspan="10"><strong>Grasshoppers</strong></td></tr><tr><td colspan="10">(G) Target species</td></tr><tr><td>n.s.</td><td></td><td></td><td></td><td></td><td colspan="5">(H) Threatened species</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>n.s.</td><td></td><td></td><td></td><td></td></tr></tbody></table>

Model-averaged coefficients (conditional average) were derived from the top-ranked linear models (ΔAIC<sub>c</sub> < 2). The variable *subarea* (N = 5) was set as a random intercept. All fixed effects were standardized prior to analyses. R<sup>2</sup><sub>GLMMm</sub> = variance explained by fixed effects, R<sup>2</sup><sub>GLMMc</sub> = variance explained by both fixed and random effects (Nakagawa et al., 2017). Statistical significances are indicated as follows: n.s., not significant, p ≥ 0.05, *p < 0.05, **p < 0.01, ***p < 0.001.

<sup>a</sup>The number of vascular plant target species was log-transformed prior to analysis.

<sup>b</sup>No range for R<sup>2</sup> because model-averaged coefficients were derived from only one model.

<sup>c</sup>CSV, centered and squared values (for details see the “Statistical analysis” section).

sites when green hay is applied (Kiehl et al., 2010; Wagner et al., 2020). As we discuss in the following: (i) limitations inherent to the transfer method and (ii) microsite limitations are the key constraints (Kiehl et al., 2010; Wagner et al., 2020).

The study by Wagner et al. (2020) showed that species with low abundance on a donor site often have a reduced establishment rate on a restoration site. This was probably also the case for some species in the study area. For example, *Nardus stricta*, the eponymous species of *Nardus* grasslands, was absent from most donor sites and was therefore rarely transferred to the restoration sites (Schulte, 2017). Moreover, the timing of hay cutting is always a compromise that may exclude species with an unusual phenology from the transfer of mature seeds (Bakker et al., 2002; Sullivan et al., 2020). In our study, we recorded low establishment rates for several late flowering species such as *Knautia arvensis* and *Sanguisorba officinalis*. This might be explained by the mowing in early to mid-August and hence before seed development had been completed (see also Schulte, 2017; Sullivan et al., 2020).

As with vascular plant and insect species, our study revealed a high degree of similarity between restored and target grasslands in terms of environmental conditions. However, the cover of herbs and Ellenberg indicator values for nitrogen and soil reaction were still lower on the restored grasslands, i.e., on sites that had been covered with spruce forests for decades. Spruce forests are typically characterized by low light availability at the ground and a pronounced layer of needles and other tree components with a limited

decomposition rate (Janišová et al., 2007; Fischer and Fischer, 2012). As a consequence, the soil is subject to acidification, a reduced microbial activity and an increased C/N ratio (Fischer and Fischer, 2012; Strand et al., 2021). Additionally, in our case, the restoration sites were only mulched after the trees had been removed, usually without further tillage. Particularly near the mulched tree stumps, this measure produced a layer of wood chips with presumably similar chemical properties as the litter layer (Schulte, 2017). The wood chips may also have limited the direct contact of the seeds with the mineral soil (Schulte, 2017). Nevertheless, according to our results, these sites were suitable for colonization by the majority of target and threatened species adapted to oligotrophic and acidic soils (van Daele et al., 2017; Kurtogullari et al., 2020). Seedling establishment of other grassland species, however, was partially hampered by site characteristics (Roem and Berendse, 2000; Schulte, 2017). This was probably another reason for the differences in species richness, diversity and composition of all vascular plants. There were mainly herbs among the species with low establishment rates, which was also reflected by a generally lower herb cover in restored grasslands. However, the site characteristics in combination with the green hay transfer and subsequent management had the advantage that nitrophilous and ruderal species occurred only rarely on the restored grasslands. In other restoration projects, especially on fertile soils such as on arable land or improved grassland, they may reach high cover and jeopardize the success of the restoration (cf. Kiehl et al., 2010; Lencová and Prach, 2011).
<figure><img src="image_81.png" /><figcaption>FIGURE 5</figcaption></figure>

Results of mixed-effects model analyses: relationship between significant environmental parameters of the averaged synthesis models and species richness (Hill numbers of order *q*=0; target and threatened species) of (A–C) vascular plants, (D–F) leafhoppers, and (G,H) true bugs. The regression slopes were fitted using multivariable linear models (see Table 4 for detailed model statistics). No relationships are presented for threatened true bugs and for grasshoppers as the analyses did not reveal any significant parameters. Blue bands indicate 95% confidence intervals.

Similar to plants, the recolonization of a restoration site by insects mainly depends on (i) the availability of species-rich sites with abundant source populations in the surroundings and (ii) a suitable habitat quality (Keene et al., 2020; Helbing et al., 2021). The dispersal ability of the studied insect taxa is largely species-specific. On the one hand, numerous species are known to be highly mobile, being able to

move long distances either actively or by passive drift (Reynolds et al., 2017; Florio et al., 2020; Poniatowski et al., 2020). On the other hand, there are many dispersal-limited species that rely on a high degree of habitat connectivity with suitable dispersal corridors to migrate (Nickel, 2003; Littlewood et al., 2009; Poniatowski et al., 2016, 2020). Given that the study area still contains a dense network of
species-rich grasslands, we assume that even those species with low mobility were often able to reach restoration sites. One remarkable example is the endangered leafhopper target species *Delphacinus mesomelas*. Although long-winged individuals occasionally occur, the species is usually short-winged. Nevertheless, we sampled it in high abundance on 89% of the restored grasslands, which equals the species' occupation rate on the target grasslands. We suppose that the transfer of the studied insect taxa with the green hay was negligible for species establishment. The number of transferred individuals was very likely rather small, particularly when mown with a disc mower (Stöckli et al., 2021). Moreover, the restoration sites were not vegetated during the conduction of the restoration measures and therefore did not yet provide a suitable habitat for typical insect species of grasslands.

The interaction of trophic resources, spatial structure of the vegetation and microclimatic conditions is often summarized as habitat quality (Mortelliti et al., 2010; Poniatowski et al., 2018; Helbing et al., 2021). Insects that reach a restoration site will only establish if their requirements in habitat quality are fulfilled (cf. Helbing et al., 2021; Hussain et al., 2022). As described above, environmental conditions 3 to 5 years after restoration hardly differed between restored and target grasslands. Thus, habitat quality was well suited for successful colonization of the restored sites by grassland insects.

## Drivers of species richness

We found only minor differences between restored and target grasslands with regard to species richness of vascular plants and insects as well as environmental conditions. By contrast, the data showed greater variation in species richness (target and threatened species) within all studied grassland sites, and statistical modeling revealed several drivers responsible for this.

The species number of vascular plants was related to the Ellenberg nitrogen value, i.e., to soil fertility. In the case of target species, this relationship was negative. The majority of target species are characteristic of *Nardus* grasslands and are therefore adapted to very oligotrophic conditions (Ellenberg and Leuschner, 2010; van Daele et al., 2017). Only some character species of mountain hay meadows, such as *Crepis mollis*, grow preferentially at more mesotrophic soils. However, these species were hardly present on the study plots. The number of target vascular plant species therefore increased with decreasing soil fertility. For threatened vascular plant species, intermediate Ellenberg nitrogen values resulted in the highest species richness. This unimodal response corresponds with the intermediate productivity hypothesis: it states that only a few species can tolerate the environmental stress at very low productivity and that at the same time a few highly competitive species dominate sites with high productivity (Fraser et al., 2015).

Vascular plant species were also associated with precipitation. The higher the precipitation, the more target species occurred. We assume that an indirect relationship explains this pattern. Precipitation increased with elevation ($r_s = 0.63^{**}$). At higher elevations—i.e. in areas with higher precipitation—the overall intensity of land use is usually lower than at lower elevations (e.g., Strebel and Bühler, 2015; Buzhdygan et al., 2020). Accordingly, we interpret the environmental variable “precipitation” as a proxy for the overall land-use intensity.

Leafhoppers (target and threatened species) and true bugs (target species) were sensitive to grazing intensity. Although the studied gradient was rather small and did not include intensive grazing, it exhibited a negative relationship with species richness. This is typical of both taxa. Numerous studies have shown that species richness and abundance of small insects such as leafhoppers and true bugs often reach the highest values on grasslands with very low land-use intensity or even on abandoned sites (e.g., Dennis et al., 1998; Kruess and Tscharntke, 2002; Biedermann et al., 2005). The reason for this is that species-rich grassland communities characterized by the coexistence of different life strategy types rely on a pronounced field layer with a complex plant architecture (Biedermann et al., 2005; Zurbrügg and Frank, 2006; Helbing et al., 2017, 2021). Each grazing period reduces the height and structural complexity of the vegetation, leading to negative responses in numerous leafhopper and true bug species (Biedermann et al., 2005; Zurbrügg and Frank, 2006). However, very low-intensity grazing or abandonment is favorable only in the short to medium term since succession in the long run results in a lower richness of (host) plant species and an adverse (cool) microclimate (Biedermann et al., 2005). Furthermore, some habitat specialists of both taxa (Nickel, 2003; Wachmann et al., 2004, 2006, 2007, 2008) and other species groups, such as grasshoppers (Fumy et al., 2021), depend on spatial heterogeneity within grasslands, including areas of short turf and bare ground. This is best achieved through a low to intermediate intensity of grazing (van Klink et al., 2015; Fumy et al., 2021).

Threatened leafhopper species were also positively associated with direct incident radiation. Insects are thermophilic organisms, and the local climate of a habitat is an important driver of insect species richness (e.g., Kurtogullari et al., 2020). Helbing et al. (2017) studied leafhopper assemblages on acidic grasslands adjacent to the study area at slightly lower elevations (300–680 m a.s.l.). Numerous of the species detected by the authors were absent in our study. We suggest that climatic limitations may explain these differences. Some species reached their upper range limit in the study area. They probably prefer sites with a warm local climate.

The occurrence of insect herbivores is generally fostered by high plant species richness (Haddad et al., 2001; Joern and Laws, 2013). The majority of true bugs feed on plants, and many species are monophagous or oligophagous (Wachmann et al., 2004, 2006, 2007, 2008). Accordingly, our results revealed a positive relationship between the number of host plant species and the number of target species in true bugs. The same observation was made for leafhoppers in other studies (e.g., Rösch et al., 2013; Helbing et al., 2021). However, although this group of insects is entirely phytophagous and many species exhibit a high degree of host plant specialism (Nickel, 2003; Biedermann et al., 2005), we found no relationship with leafhopper host plants. This is probably a result of the different host plant preferences of leafhoppers and true bugs. For example, a total of 29 sampled leafhopper species (40%) feed on the four vascular plant species that occurred on all study plots (see the “Results” section). In contrast, only 12 true bug species (24%) are known to feed on these widespread plants. We therefore assume that the occurrence of host plants was not a limiting factor for leafhopper species in the study area.

We found no effect of environmental parameters on threatened true bugs or threatened and target grasshoppers. This was likely due to the low number of species in these groups, resulting in limited variance between the sites.
## Conclusion

Based on our findings, we conclude that the recovery of species-rich communities of the studied taxa has progressed well in the study area, particularly with respect to insects. The restoration of montane grasslands is thus an important tool for increasing habitat networks and enhancing biodiversity in upland landscapes. This is particularly important in times of global warming since species adapted to cool-humid mountain climates rely on the ability to migrate between habitat patches (Freeman et al., 2018; Stuhldreher and Fartmann, 2018). However, we analyzed only the short-term effects of restoration. The development of the grassland sites should ideally be monitored in the long term. In a positive scenario, species richness and diversity will remain stable or even increase over time. Missing vascular plant species may be reintroduced through selective sowing by conservationists (Wagner et al., 2020). Moreover, species colonization is likely to progress, facilitated by the dense network of grassland patches in the study area (Waldén et al., 2017). On the other hand, target plant species that occur with few individuals on the restoration sites run the risk of not being able to persist in the long term (Kiehl et al., 2010). Moreover, atmospheric nitrogen deposition represents a continuous threat to the studied types of grassland (Bobbink et al., 2010). Insufficient management often results in the dominance of a few grass species such as *Agrostis capillaris* or *Deschampsia flexuosa*, while other species are suppressed (Stevens et al., 2004; Ellenberg and Leuschner, 2010). This also affects insects, as exemplified by true bug host plants. To counteract grass encroachment and in order to promote different insect taxa, including those sensitive to grazing intensity (e.g., leafhoppers and true bugs), lenient grazing with low stocking density is recommended. As an option, annually rotating small areas could be excluded from grazing, as this has been shown to have a positive effect on insect diversity (Kruess and Tscharntke, 2002).

## Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

## Author contributions

FH, TF, and DP contributed to the conception and design of the study. FH conducted the field work, identification of leafhopper species in the laboratory and statistical analysis, and wrote the first

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## Funding

This study was funded by the German Federal Agency for Nature Conservation (Bundesamt für Naturschutz; grant number 3516892017).

## Acknowledgments

We sincerely thank Axel M. Schulte (Biologische Station Hochsauerlandkreis e.V.) for his dedicated assistance throughout the research work. Moreover, we are grateful to Raïna Wendland for support during fieldwork, to Herbert Nickel for assistance in the identification of difficult taxa, and to two reviewers for valuable comments on an earlier version of the manuscript. We further acknowledge support by Deutsche Forschungsgemeinschaft (DFG) and Open Access Publishing Fund of Osnabrück University. The restoration measures were co-financed by the EU LIFE project “Mountain hay meadows near Winterberg.”

## 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.

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