Implications of heathland management for ant species composition and diversity – Is heathland management causing biotic homogenization?

Biological Conservation 242 (2020) 108422

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Implications of heathland management for ant species composition and diversity – Is heathland management causing biotic homogenization?

T

Rikke Reisner Hansena, , Knud Erik Nielsena, Joachim Offenberga, Christian Damgaarda, David Bille Byrielb, Inger Kappel Schmidtb, Peter Borgen Sørensena, Christian Kjæra, Morten Tune Strandberga ⁎

a b

Section for Plant and Insect Ecology, Department of Bioscience, Aarhus University, Vejlsøvej 25, DK-8600 Silkeborg, Denmark Department of Geosciences and Natural Resource Management, University of Copenhagen, Rolighedsvej 23, 1958 Frederiksberg, Denmark

ARTICLE INFO

ABSTRACT

Keywords: Composition Ecosystem engineers Heathland management Species conservation Species richness

Maintaining heathland ecosystems in an early successional stage is a major aim of most management regimes, such as harvesting, burning or grazing. However, how these types of management affect important ecosystem engineers such as ants, are poorly understood. We registered the density of ant colonies in managed plots (harvested, burned and grazed) and plots with long succession (so forth unmanaged) across six different dry lowland heath sites. With these data, we investigated how composition and richness varied across management regimes and elucidated the direct effects of management from the indirect effects of environmental covariates. Ant species richness was significantly lower in managed plots compared to unmanaged plots. Harvest and grazing regimes were associated with the lowest richness, while intermediate richness was registered in burned plots. Smallest variation in species composition was found in the harvested, followed by grazed, burned and unmanaged heathlands. There was an overall negative association between abundances of organic mound forming species and all types of management, while non-mound forming species where negatively affected by grazing. In addition, Non- and organic mound forming species were indirectly affected through decreasing vegetation complexity. Only ants with mineral mounds benefitted from grazing and burning, but not from harvesting. To promote ant richness and abundance, we propose to downscale the frequency and intensity of management, as well as designating certain parts of the heathland area for later successional vegetation stages.

1. Introduction In open terrestrial ecosystems, current management focuses on keeping the system at an early successional stage and on preventing nutrient accumulation in the system (Gimingham, 1994; Mobaied et al., 2015). Plant species are then applied as the model indicator from which all effects are estimated (Webb, 1998), occasionally with detrimental costs to arthropod diversity (Klink et al., 2013). Danish heathland ecosystems are strongly influenced by different management regimes roughly divided into the following categories: prescribed burning, harvesting, sod cutting and grazing (Degn, 2016). Each of these aimed at regenerating dwarf shrub vegetation, Calluna vulgaris (L.) Hull in particular. In the absence of management or naturally occurring disturbances (i.e. deer grazing, wild fires etc.), tree species like Mountain and Scots pine (Pinus mugo (Turra) and P. sylvestris (L.), respectively), will become dominant and the open heathland areas will diminish. Disturbances, whether caused by machinery, fire or large herbivores, will ⁎

influence biotic and abiotic variables mostly due to changes in vegetation complexity (Måren, 2009; Rosa García et al., 2013), and intuitively this will generate environmental variation. Conversely, when frequently applying one management regime to larger areas, the risk is a homogenization of the biotic as well as the abiotic environment, limiting the amplitude of available ecological niches (McKinney and Lockwood, 1999; Harpole and Tilman, 2007; Nordberg and Schwarzkopf, 2019). The degree to which management can be expected to affect ant communities, depend upon the frequency, intensity and timing, as well as the size of the managed parcel (Andersen et al., 2009; Philpott et al., 2009; Maravalhas and Vasconcelos, 2014). As well as for other arthropods, both abiotic and biotic factors govern the diversity of ants and determine the species distribution of ants (Cushman et al., 1988; Hölldobler and Wilson, 1990; Seifert, 2017), rendering them equally susceptible to management. This occurs both through the direct mechanistic forces of management to the colony (Morris, 2000), but also through the indirect effects on microclimate and vegetation structure

Corresponding author. E-mail address: [email protected] (R.R. Hansen).

https://doi.org/10.1016/j.biocon.2020.108422 Received 4 September 2019; Received in revised form 8 January 2020; Accepted 13 January 2020 0006-3207/ © 2020 Elsevier Ltd. All rights reserved.

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Fig. 1. A map of Jutland showing the location and size of the heathlands investigated in the study with the location within Europe depicted with a square in the inset box in the lower left corner. The inset figure in the lower right corner shows the location of the selected plot within the management parcel, as well as the experimental design within each plot and heathland site (upper right). Grey circles are subplot locations and the squares shows an example of the randomised locations for pin-point analyses and environmental covariate registration.

(Andersen, 2018), as well as a reduction of food resources (Blüthgen and Feldhaar, 2009). Reduced complexity in environmental heterogeneity may thus lead to a homogenization of ant communities through reduced species richness. This is then exemplified either through increased dominance of single species (Moranz et al., 2013; Vonshak and Gordon, 2015) or through a shift in microclimatic conditions favoring warm temperate species, and filtering out species dependent on accumulation of organic structures for nest building (Seifert, 2017; Andersen, 2018). Studies on ant responses to disturbances are widely applied in arid Australian ecosystems, where wild fires, grazing cattle and mining activities are the main source of disturbance (Andersen and Majer, 2004). Very few studies differentiate between the direct and the indirect effects of management on ant assemblages in pursuit of the optimal management scheme (Heuss et al., 2019). In temperate regions, studies on ant community responses to management are mostly limited to grassland habitats, where frequent disturbances are a prerequisite for habitat conservation (Dauber and Wolters, 2005; Pihlgren et al., 2010; Heuss et al., 2019), causing disturbance-tolerant ant assemblages (Arcoverde et al., 2018). However, in temperate and low productive heathland ecosystems, ant community responses to management-mediated disturbances have been less studied. Because ant species responses have been shown to differentiate between habitats of differing structural complexity and hydrological regimes (Arnan et al., 2006; Arcoverde et al., 2018), we would expect different responses of ant assemblages to disturbances in arid, acidic and low productive ecosystems. As abundant and important ecosystem engineers, ants play an important role as mediators of many ecological processes, including the decomposition of organic matter, soil turnover and structure, nutrient cycling, plant protection, seed dispersal, and seed predation (Hölldobler and Wilson, 1990; Folgarait, 1998;Frouz and Jílková, 2008; Nakamura et al., 2007). Their role as ecosystem engineers is especially important in acidic environments where earthworms and other soil-burrowing

organisms are scarce (Wallwork, 1976; Beylich and Graefe, 2009). Ants' ability to modulate the environment is exploited by a multitude of other organisms (Cagnolo and Tavella, 2015), ranging from soil bacteria and microarthropods (Wagner et al., 1997), to surface active arthropods (Päivinen et al., 2002), and butterflies (Fiedler et al., 2006). Some organisms, like birds, rely on ants for food and cleansing of plumage (Coudrain et al., 2010), while some utilize the warmer microclimate in or on the mound (Streitberger and Fartmann, 2015). Ants affect vegetation richness and structure, both positively through predation of herbivorous insects (Muniz et al., 2012), but also negatively through interactions with honeydew-producing hemipterans (Wills and Landis, 2018). In addition, ants increase plant species richness directly via soil disturbance, which help secure islands for less competitive plant species (Dean et al., 1997). However, this ecological importance of ants is in stark contrast to the lack of attention they receive in management planning and conservation. We studied how current heathland management practices affect ant species composition and diversity, and quantified how these components vary across four management regimes, burning, harvesting, grazing and unmanaged heathland. Through the appliance of multivariate methods in a Bayesian framework, we explored the following hypothesis. Species assemblages are significantly different across management treatments. We further explored the hypothesis that species with different nesting strategies (i.e mineral, organic or non-nesting ant species), responds not only to the direct effects of management, but also indirectly to the altered environmental conditions. For this purpose, we employed structural equation modelling. 2. Methods 2.1. Study system The study was conducted at six heathland sites in Denmark (Fig. 1). 2

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sampling for ants to enable a density measure. This would require too many person-hours to replicate for sampling of covariates.

The selected study sites were inland dry lowland heaths on acidic, lownutrient sandy soils. The parental soil geology of the selected locations consisted primarily of downwash sandy deposits with elements of Aeolian sand and glaciofluvial sand and gravel. The locations were typically dwarf shrub-dominated with patches of grass primarily dominated by purple moor grass (Molinia caerulea (L.) Moench) or wavy hair grass (Deschampsia flexuosa (L.) Trin.). Climatic parameters varied little across the selected heathland sites. Mean average temperature for 2018 ranged from 9.2 °C to 9.5 °C with minimum temperature ranging from −10.9 °C to −9.8 °C and maximum ranging from 32.3 °C to 33.1 °C across sites. Average yearly precipitation across sites varied from 666 mm to 726.1 mm. Average hours of sunshine across Denmark ranged from 1740 to 1830 h.

2.3. Ant sampling and identification Through active search, we manually registered colony abundances of all ant species in the 17 selected one-hectare plots during two weeks of similar warm and dry weather conditions in July 2018. At each subplot, we estimated a circle of four meters in diameter (17 plots with 100 subplots yielding 1700 subplots in total), and inspected all potential nest habitats, i.e. grass tussocks, mounds, sphagnum moss, soil, rocks and dead wood. In addition, we inspected three random places within each circle to detect species leaving few aboveground signs. Search time varied drastically with structural complexity. Highly structurally complex plots took an estimated six person-hours, whereas the more homogenous plots took a maximum of one person-hour. For the species where field identification was challenging, we sampled a few individuals from each colony for later identification in the laboratory. All ants were identified to species using the available identification keys (Seifert, 2000; Abenius et al., 2012; Seifert, 2018). The dataset is available through the Open Science Framework (Hansen et al., 2019).

2.2. Study design We selected the heathland sites based on four criteria to enable comparison between managed and unmanaged areas: (1) sites included an area of heathland unmanaged for > 30 years. (2) Sites should include a minimum of two areas with different management regimes (burned, grazed or harvest). (3) The management regime had to be consistent in type, as well as being applied with less than ten years in between, and with the latest application within the last four years. (4) Areas should be large enough to include a 1 ha square plot with a 100 m edge buffer. Unfortunately, none of the considered Danish heathland sites included all possible management combinations, which led to an unbalanced design (Table 1). The different management regimes included three areas of prescribed burning, performed in early spring. Five machine harvested areas, uniformly cut at a height of 5–10 cm. Three grazed areas, one heavily grazed by red deer, and two grazed by cattle in the summer with approximately 0.4 animal units per ha (one animal unit = 550 kg). Six unmanaged areas, where management has been abandoned > 30 years. The managed and unmanaged areas which met the criteria were mapped in QGis Version 2.14.21. Within each site and management polygon, we randomly established a 1 ha square plot, which we subdivided into 100 subplots with each 10 m between. These subplots formed the basis for ant-colony search. To avoid edge effects, we established a buffer of 100 m to the edge of the management polygon. Each plot was located > 400 m apart to avoid species exchange between plots. Apart from the subplots, we selected 10 vegetation survey plots to form the basis for registering environmental variables. These were randomly distributed within each plot (Fig. 1). Kongenshus heathland had grazing sheep in all three management types, however, we estimated that the sheep's use of the selected plots were negligible, based on presence/absence of sheep feces and bites to the vegetation. Borris heathland is a military area, where management is carried out yearly to prevent spontaneous fires caused by exploding artillery. The design encompasses to different spatial resolution levels of sampling. One for ant sampling and one for registering environmental covariates. The reason for this is that we chose a very high-resolution

2.4. Environmental covariates We registered plant species composition in each vegetation survey plot with a 50 cm × 50 cm pinpoint frame with 25 pins in total. At every pin, we measured vegetation height directly to get a solid base for averaging across the plot. We inserted a soil corer (Ø = 3 cm) in three positions close to each vegetation survey plot (center, North and South) with 1 m apart and registered the depth of each soil horizon. In the same positions, we measured soil moisture content (Volumetric Water Content) in the top 5 cm using a HH2 moisture meter with a ML3 Theta probe attached. The mean depth for all soil horizons, as well as, mean values for soil moisture and vegetation height was calculated across each plot. Pinpoint data were aggregated into five cover classes: Dwarf shrubs, graminoids, forbs, mosses and lichens and a measure for mean cover and the degree of spatial aggregation was calculated under the assumption that pin-point plant cover data was beta-binomial distributed (Damgaard and Irvine, 2019). As environmental covariates were measured on different scales, they were standardized to a zero mean and unit variance prior to analysis. All statistical analyses were carried out in R version 3.5.2. 2.5. Ant species richness We calculated species richness for each subplot and averaged it across plots for each management regime to estimate the amount of species per management regime. To estimate effects of management regime on species richness at the subplot level, we employed a Bayesian framework, which estimates credibility intervals of the posterior distributions of each management regime with site as a random factor. The statistical inferences were assessed using the calculated 95% percentiles of the marginal posterior distribution of the parameters (credibility intervals). For this purpose, we used the ‘R-INLA’ package (version 19.09.03) with default prior setting. (Rue et al., 2009). R-INLA is an R package that uses the Laplace approximation to calculate the joint posterior distribution of the model.

Table 1 An overview of the selected sites and the management carried out in the selected plots. The number under Burn, Harvest, and unmanaged is the number of years since the management was last applied. For grazing the number is the number of years it has been grazed. Site

Burn (years)

Harvest (years)

Harrild Kongenshus Borris Ovstrup Randboel Noerholm

3 1 1

2 1 1 2 2

Grazing (years)

> 50 > 30 > 50

Unmanaged (years)

2.6. Species composition

> 50 > 50 > 30 > 50 > 100 > 100

To assess how the species assemblages varied within and across management regimes, we investigated species composition in a multidimensional space. For this purpose, we employed latent variable modelling through the R package ‘boral’ (Hui, 2016). Latent variable 3

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modelling is a Bayesian model-based approach that models community composition through a set of underlying latent variables to account for residual correlation, for example due to biotic interaction. This method offers the possibility to adjust the distribution family to e.g., negative binomial distribution, which better accounts for over-dispersion in count data (Warton et al., 2012). Thus, it accounts for the increasing mean-variance relationship without confounding location with dispersion (Hui et al., 2015). We created a latent variable model at subplot level with a negative-binomial distribution and two latent variables to visualize how the ant communities were distributed. Site was added as a random factor and management regime as fixed effects. From the latent variable model, we extracted the posterior median values of the latent variables which we used as coordinates on ordination axes to represent species composition at subplot level (Hui et al., 2015). We drew convex hulls around posterior median values belonging to each management regime to visualize the difference. For this purpose, we used the function ‘ordihull’ in the r package ‘vegan’ (Oksanen et al., 2016). Because model based ordination lacks resampling, it is not well suited for hypothesis testing (Francis Hui, Pers. Comm.). We therefore tested our first hypothesis with a multivariate extension of GLMs as recommended by Warton et al. (2012), using the function ‘manyglm’ and subsequently ‘anova.manyglm’ in the package ‘mvabund’ (Wang et al., 2012). This method offers the possibility to model distributions, and test hypotheses based on multivariate count data by correlating each row of the dataset to an environmental covariate (column), assuming a negative binomial distribution. We ran two models, where we first tested for an interaction between site and management. In the second model, site was then included as a random effect, management regime as a fixed and we subsequently compared all management regimes against each other in a post-hoc comparison test offered via the function ‘anova.manyglm’ with site included as a random factor. The model assumptions of mean-variance and log-linearity were examined, for both models, with residual vs. fitted plot and a normal quantile plot.

heathlands towards higher forb and graminoid dominance (Newton et al., 2009). We also predicted that harvesting would have a direct and negative effect on the mineral mounds, due to the mechanistic impacts of harvesting, removing the mound construct entirely. Furthermore, they are often highly abundant on the heathland soils, which are missing a well-developed hardpan layer or where the eluvial layer (i.e. the sandy material in the soil horizon with maximum leaching of organic material and metals) is deep (Pers. Obs.). Consequently, we tested for indirect effects of mean forb cover, mean depth of the eluvial layer and mean vegetation height. The ant species, which do not form mounds, depend on the substrate in various ways, nesting in grass tussocks, moss pads and dwarf shrub swards (Groc et al., 2017; Seifert, 2017; Andersen, 2018). Furthermore, most species hibernate closer to the surface, and rely on a deep eluvial layer (Seifert, 2018). We therefore tested for indirect effects of mean depth of eluvial layer, mean depth of litter layer, mean vegetation height, mean cover of dwarf shrubs, mean cover of graminoids, and mean cover of mosses. However, as some non-mound-forming species are thermophilic and dependent on an open environment, we hypothesized grazing, burning and harvesting to have a direct positive effect. To account for multicolinearity, we first computed Pearson correlation coefficient between all sets of covariates and tested their significance with the function ‘cor test’ in R. When r2 values of the correlations were significant (p < 0.05), we specified a correlated error between the covariates. Site was included as a random effect and management regimes as fixed effects. The four management regimes were modelled by indicator variables. In this way, we test the effect of one management regime against the other three. We standardized the path regression coefficients via the latent theoretic approach for binomial models as recommended by Lefcheck (2016). The structure of each model can be found in the Appendix (Fig. A1) and a correlogram matrix of the significant covariate correlations Fig. A2. Model adequacy was verified by examination of residuals. 3. Results

2.7. Effects of environmental variables and management

We identified 20 ant species belonging to five genera. A species list including management and site-specific abundances is included in the Appendix (Table A1). Boxplots of the measured environmental covariates summarized over management regime can be found in the Appendix (Fig. A3).

We calculated abundance-weighted values for three different types of nest organization following Seifert (2018), which we hypothesized to be affected both directly and indirectly by management. The selected types of nest organization were mineral mound forming species (two species), organic mound forming species (six species) and non-mound forming species (12 species). An overview of species and their trait assignments can be found in Appendix (Table A1). To analyze the direct and indirect effects of management on ant species assemblages, we fitted a piecewise structural equation model using the R package “piecewiseSEM” (Lefcheck, 2016). As an important first step in every SEM model, we first formed an à priori model (Grace et al., 2010). This conceptual framework was based on available literature (Philpott et al., 2009; Seifert, 2017; Andersen, 2018; Li et al., 2018), and our ecological understanding of the three groups. Starting from hypotheses that species grouped into different nest strategies each depend on a specific substrate (Seifert, 2017; Andersen, 2018), we selected environmental covariates meaningful for the groups nesting microhabitat and strata of foraging, as described by Seifert (2017). Because most organic mound forming species are polydomous and have limited dispersal and foraging ranges (Seifert, 2017), we hypothesized that their ability to form these large complex structures would be negatively correlated with a decrease in mean vegetation height, litter layer, dwarf shrub cover and graminoid cover. This would also mean that all management forms, causing a direct destruction of their mounds (i.e. harvesting and burning), would negatively affect them. The abundances of mineral mound forming species are known to be promoted by grazing from large herbivores (Li et al., 2018), which we know decreases the vegetation height and shifts the dominance of the

3.1. Ant species richness When averaged across plots, we found a mean species richness of 4.4 ( ± 1.0 SE) in the harvested plots. The grazed plots had a mean species richness of 5.3 ( ± 1.5 SE), compared to 9.3 ( ± 1.9 SE) species in the burned plots and 11.8 ( ± 1.0 SE) in the unmanaged plots (Fig. 2a). Species richness at the subplot level differed significantly between some of the management regimes. There was no significant difference between unmanaged and burned plots, or between the harvested and the burned plots, as the credibility intervals of the posterior distributions overlapped. Burned and unmanaged plots were both significantly different from harvested and grazed plots with non-overlapping credibility intervals (Fig. 2b). 3.2. Species composition The latent variable analysis indicated higher species variation within the unmanaged plots (i.e. beta diversity), followed by the burned, and less in both the grazed and the harvested plots (Fig. 3). In the multivariate glm testing for the interaction between site and management, there was a significant effect of site (p = 0.001) and management as well as a significant interaction between them (p = 0.001). Following the inclusion of site as a random effect, management alone 4

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Fig. 2. a) A dotplot showing species richness of ants (Mean ± SE) at plot level for each of the four management regimes. b) A boxplot showing species richness at subplot level for each of the four management regimes and for each of the six sites. Outlayers are depicted as dots, whiskers display minimum and maximum, the box depicts the first quartile, the median and the third quartile. Letters a and b demonstrates statistical significance between management regimes (p < 0.05).

was no longer significant (p = 0.16). In the subsequent pairwise test however, all of the management regimes differed significantly from each other (p = 0.001).

burning had direct and positive effects (β = 7.99, p < 0.0001 and β = 7.51, p < 0.0001, respectively) Harvest also impacted nonmounds indirectly as harvest decreased vegetation height (β = −0.77, p < 0.0001), that acted positively on the non-mound forming ants (β = 0.99, p < 0.0001). Mean depth of the eluvial and litter layer both had significant and positive effects on non-mound forming ant species (β = 0.58, p < 0.0001 and β = 1.54, p < 0.0001, respectively), and the latter was significantly decreased by all three management regimes (harvest: β = −0.75, p ≤ 0.0001, grazing: β = −0.77, p ≤ 0.0001, burning: β = −0.56, p < 0.0001) (Fig. 4b). The total r2 value was 27% for the full model.

3.3. Effects of environmental variables and management In the Piecewise SEM all three management regimes exerted significant negative impacts on the abundance of organic mound forming ant species (harvest: β = −4.48, p < 0.0001, grazing: β = −6.16, p < 0.0001, burning: β = −3.85, p = 0.001) (Fig. 4a). Harvesting and grazing had indirect effects through the decreased vegetation height (β = −0.77, p < 0.0001, β = −0.53, p < 0.0001 respectively), which acted negatively on organic mounds (β = −0.27, p = 0.003). Grazing furthermore promoted the cover of graminoids (β = 0.54, p < 0.0001), but decreased the cover of dwarf shrubs (β = −0.55, p < 0.0001), both of which acted positively on the organic forming ants (β = 4.93, p < 0.0001, β = 4.49, p < 0.0001, respectively). Conversely, harvest and burning exerted indirect negative effects by decreasing the cover of graminoids (β = −0.09, p < 0.0001, β = −0.13, p < 0.0001, respectively). There was no significant effect of mean depth of the litter layer (p = 0.16) (Fig. 4b). The model had an overall r2 value of 0.36. The abundance of mineral mound forming species were positively impacted by grazing (β = 6.73, p < 0.0001) and burning (β = 4.38, p < 0.0001), but negatively by harvesting (β = −3.28, p = 0.02) (Fig. 4a). In addition, they were positively impacted by an increasing forb cover (β = 12.94, p < 0.0001), which was also significantly promoted by grazing (β = 0.57, p < 0.0001). Mean depth of the eluvial layer or mean vegetation height did not have significant effects (p = 0.72, p = 0.11 respectively) on abundance of mineral mound forming ant species (Fig. 4b). The model explained 32% of the variation. For non-mound forming ant species, the SEM showed that grazing was the only management regime with significant and negative impacts on the abundance (β = −5.77, p < 0.0001) (Fig. 4a). Harvest and

4. Discussion We have presented evidence of homogenization of ant assemblages caused by heathland management. Both the species richness analysis and the species composition analysis demonstrated how harvesting and grazing both exercised heavy impacts on ant communities, while the effects of burning were modest (Figs. 3–4). Structural equation modelling further showed how organic mound forming species (6 species) were directly and negatively affected by all three types of management, whereas the non-mound forming species (12 species) were negatively affected by grazing and indirectly by harvest. Only the mineral mound forming ants (two species) benefitted from the management regimes grazing and burning, directly as well as indirectly. In previous studies, ants have shown remarkable resilience towards grazing (Underwood and Christian, 2009; Heuss et al., 2019), but in this study, we found the studied grazing pressure (0.4 animal units) to have detrimental effects on overall ant species richness and composition (Figs. 2–3), but only for abundances of organic and non-mound forming species (Fig. 4). We believe the organic mound forming species are impacted because they are poor disperses (Seifert, 2018) and many, such as Formica rufa (Linnaeus, 1761) and F. pratensis (Retzius, 1783), are adapted to structurally complex environments. Trampling by

Fig. 3. Species distribution plot of the best fitted latent variable model showing the mean of the latent variable with a negative binomial distribution. Size of the hulls indicate the variation in species assemblages within management type. 6

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Fig. 4. a) Structural equation model showing direct effects of management types on the abundance weighted nest strategies over all sampled subplots (n = 1700). b) Structural equation model showing indirect effects of management regimes through environmental covariates on the abundance weighted nest strategies over all sampled subplots (n = 1700). a and b) Only significant (p < 0.05) interactions between variables are depicted (full lines show positive interactions and stipled show negative interactions). We report the significant path coefficients as standardized effect sizes on top of the arrows. Boxes feeding into both diagrams is the proportion of remaining unexplained variation.

grazing cattle further causes soil compaction, which negatively impacts soil fauna (Schlaghamerský et al., 2007), potentially decreasing the abundances of important prey items. Concomitantly, trampling would also directly affect the non-mound forming species as they nest close to the surface (Seifert, 2018). This was also indicated by a negative response in the model. Mineral mound forming ants were positively impacted by grazing and this was manifested by exceptionally high abundances of Lasius flavus (Fabricius, 1781) in grazed plots (Table A1).

As proposed by Li et al. (2018), this could be explained by reciprocal facilitation between grazing animals and Lasius species (Li et al., 2018). The large shift in vegetation cover in the grazed plots towards a more forb-dominated structure (Fig. A4) had positive effects on mineral mound abundances (Fig. 4b), and could promote additional suitable plant hosts for the ant-aphid symbiosis. In the present study, we chose to keep grazing pressure constant and to select areas with a long continuity of grazing animals. However, as the response of biodiversity to 7

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grazing is not easily generalizable and often complicated by a multitude of factors (Milchunas and Lauenroth, 1993; Heuss et al., 2019), there is an urgent need for controlled experiments to address the impact each grazing regime. We detected positive direct effects of harvest and burning on the non-mound forming species, indicating that some non-mound forming species benefit from an increase in open patches as generated by management. The abundances however, were quite low in most sites (Table A1). The species registered in the harvested plots were predominately L. niger (Linnaeus, 1758) (mineral mound), Myrmica scabrinodis (Nylander, 1846) (non-mound) and M. ruginodis (Nylander, 1846) (non-mound) (Table A1), all quite common species, and known to be rather tolerant to disturbances (Dauber and Wolters, 2005; Grill et al., 2008). In contrast to the other two management regimes, harvesting leaves a uniform imprint on the area, by consistent biomass removal in a short time period (Lepš, 2014), forming an environment with dwarf shrub dominated fields of equal age and height (Fig. A4), and few suitable nest sites. The overall low abundances and absence of a majority of species in the harvested plots is then likely to be caused by a reduction in available nest sites. Increasing vegetation height and mean depth of litter layer did also exhibit positive effects on the nonmound forming species and these variables were negatively affected by harvest, further substantiating this theory. Species, which form large polydomous colonies, such as F. exsecta (Nylander, 1846) or F. pratensis are highly vulnerable to the mechanistic forces destroying the nests (Heuss et al., 2019). This was corroborated in the present study as harvest affected the abundances of both types of mounds considerably and we detected no indirect effects. Burning only posed a direct immediate threat to the abundances of organic mounds, possibly due to the aboveground structure of the nests being destroyed in fire events. Furthermore, organic mound forming species on the heathlands are limited in their ability to rebuild nests by their short foraging ranges and poor dispersal capacity (Seifert, 2017; Seifert, 2018). Consequently, colonization from nearby areas is slow in post fire heathland patches. For non-mound building species the effect of burning was positive and there was also a positive effect of a deeper eluvial layer. The depth of the eluvial layer controls the extent of bioturbation (Hart and Humphreys, 2004) and thus the horizontal niche for some species (Seifert, 2018). A deeper eluvial layer may then buffer the direct effects of fire and control the capacity of non-mound forming species to evade lethal temperatures. However, long term fire regimes with short intervals can result in persistent impacts on vegetation structure, resonating in available nest sites, food resources and eventually lead to changes in ant assemblages (Andersen, 2018). The responses were not consistent across sites, as demonstrated by the multivariate extension of GLM. This indicates that the responses of the local assemblages to management rely on the local species composition, because prevailing conditions within each site promotes specific ant assemblages. For instance, available soil moisture may determine the severity of fire on ant communities (Arnan et al., 2006). Large to small-scale patches are usually left unaffected, due to increased soil moisture, which may cause ants to be less affected by fire in wetter sites. In addition, responses to disturbance may also be larger in more structurally complex habitats (Arcoverde et al., 2018), due to differentiated adaptations in functional trait assemblages. This also presents as a plausible explanation of the contrasting responses to grazing between this study and studies from more productive ecosystems. This study however, did not include an analysis of the surrounding areas, which is also an important factor shaping local ant communities (García-Martínez et al., 2017). Further studies should include this factor. According to literature, ants are seldom directly affected by disturbances as only parts of the massive colony are affected (Pihlgren et al., 2010). As such, impacts occur through the changes in vegetation

structure and microclimate (Andersen, 2018). Ants are, to some degree, able to manipulate their nest habitat to accommodate these changes (Philpott et al., 2009), but when the disruption in available niches is applied frequently and to large homogenous fields, there are no refuges and survival depends on dispersal capacity. As such, all three management types were detrimental to species with limited dispersal capacity and foraging ranges, as well as, species with complex polydomous nesting strategies. This study also demonstrated the importance of vegetation height and cover, but the importance differentiated among nest strategies. Contrasting responses between ants with different nesting strategies merely asserts the complexity of ant-ecosystem interactions and advocates for studies of ant responses at a higher taxonomic resolution. The unmanaged areas all bore resemblance to later successional stages with (for some sites) more tree encroachment, Empetrum dominated dwarf shrub assemblies and a thick litter layer. These factors will naturally produce a microclimate unsuitable for a large number of ectotherms, including thermophilic ant species, and small-scale disturbances may therefore be warranted in these ecosystems. We cannot dismiss the notion that some ant species may be very persistent under the unmanaged regimes. L. flavus and L. niger, for instance, are able to accommodate the increasing vegetation height through increased mound size, but tree encroachment would over time cause them to disappear. To our knowledge, no studies have attempted to link direct and indirect responses to management with specific life history traits, such as nest strategies. While this study sampled management regimes in situ, it was at the cost of replication numbers. However, the documented ant responses are substantiated by literature (Seifert, 2017; Andersen, 2018; Seifert, 2018). Because ant diversity integrates a multitude of traits, we advocate for more studies, aimed at disentangling the specific drivers of ant responses for species with similar traits. 5. Conclusion There is an urgent need to rethink current heathland management practices. Our results demonstrate that allowing heathland areas to reach later successional stages is pivotal in maintaining a high ant species diversity. In addition, the differentiated responses of ants with different nesting strategies, advocates for variation in management regimes. The indirect responses to the altered environment stress the need for a less frequent interference, while allowing the ecosystem longer time to regenerate. Hence, we recommend downscaling heathland management in both frequency, intensity and the size of the managed parcels. There is a need to study the timeframe in which management abandonment can persist, while still supporting high biodiversity. Maintaining high ant abundances and diversity, also maintains many ecosystem functions and is thus beneficial to other taxonomic groups. Role of the funding source All authors acknowledge the substantial funding provided by Aage V. Jensen foundation without which the project would not have been realized. Declaration of competing interest The authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.

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Appendix A

Fig. A1. Detailed description of SEMs used to analyze all direct and indirect effects of management and environmental variables, which were found to be important to ant species nesting strategy. One model was fitted to each nesting strategy. Site was included as random effect and the Piecewise SEM was modeled with a general linear mixed effect model for the response variable (nest strategy) with a binomial error distribution, and linear mixed effect models for the environmental covariates. %~~% means that a correlated error between variables were included. 9

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Fig. A2. S3: Correlogram showing the significant (p < 0.05) correlations of the correlation test. The size and color of the circle is scaled after r2 value.

Fig. A3. S3: Boxplots of environmental covariates by mangement type. B = Burn, G = Graze, H = Harvest and U = Unmanaged. 10

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Table A1

An overview of total abundances of the colonies registered as summarized over site and management regime (type). B, H, G and U indicate whether the plot was Burned, Harvested, Grazed or Unmanaged respectively. Site

Total across sites

Borris

Harrild

Kongenshus

Noerholm

Ovstrup

Randboel

Species

Nest organization

B

H

G

U

B

H

U

B

H

U

B

H

U

G

U

G

H

U

G

H

U

Formica exsecta Formica forsslundi Formica fusca Formica picea Formica pratensis Formica pressilabris Formica rufa Formica sanguinea Formica uralensis Lasius flavus Lasius niger Leptothorax acervorum Myrmica lobicornis Myrmica rubra Myrmica ruginodis Myrmica sabuleti Myrmica scabrinodis Myrmica schencki Myrmica sulcinodis Tetramorium caespitum

Organic mound forming Non-mound forming Non-mound forming Non-mound forming Organic mound forming Organic mound forming Organic mound forming Organic mound forming Organic mound forming Mineral mound forming Mineral mound forming Non-mound forming Non-mound forming Non-mound forming Non-mound forming Non-mound forming Non-mound forming Non-mound forming Non-mound forming Non-mound forming

37 6 16 28 0 0 0 4 0 152 64 0 6 5 22 0 6 0 9 39

6 1 2 5 0 0 0 1 0 0 11 0 7 2 47 0 13 0 1 0

34 0 4 10 0 0 0 0 0 420 66 0 3 0 5 0 2 0 0 0

246 16 97 133 7 4 3 3 2 77 12 11 30 18 168 2 64 2 21 21

37 6 11 21 0 0 0 4 0 104 26 0 5 3 10 0 4 0 3 13

0 0 0 0 0 0 0 1 0 0 3 0 0 0 5 0 0 0 0 0

48 9 6 35 0 0 0 1 0 43 2 4 2 3 19 0 11 0 1 2

0 0 0 7 0 0 0 0 0 0 23 0 0 1 8 0 1 0 4 26

0 0 1 2 0 0 0 0 0 0 1 0 0 0 5 0 0 0 0 0

59 1 0 44 0 0 0 1 0 0 0 1 4 5 24 0 8 0 2 5

0 0 5 0 0 0 0 0 0 48 15 0 1 1 4 0 1 0 2 0

0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 0 0 0 0 0

2 0 13 0 0 0 0 1 0 8 9 2 3 3 25 2 12 2 1 9

11 0 1 5 0 0 0 0 0 239 51 0 0 0 0 0 0 0 0 0

39 3 19 20 7 4 3 0 2 3 0 3 5 4 27 0 7 0 0 0

8 0 0 0 0 0 0 0 0 40 7 0 0 0 0 0 0 0 0 0

0 0 1 1 0 0 0 0 0 0 3 0 0 0 1 0 0 0 1 0

22 0 50 0 0 0 0 0 0 2 0 1 0 3 37 0 12 0 17 5

15 0 3 5 0 0 0 0 0 141 8 0 3 0 5 0 2 0 0 0

6 1 0 3 0 0 0 0 0 0 4 0 6 2 33 0 13 0 0 0

76 3 9 34 0 0 0 0 0 21 1 0 16 0 36 0 14 0 0 0

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