Eric Meineri
email: eric.meineri@imbe.fr

Kari Klanderud

John Guittar

Deborah E Goldberg

Vigdis Vandvik

Functional traits, not productivity, predict alpine plant community openness to seedling recruitment under climatic warming

Keywords: Climate Change, invasibility, emergence, effect traits, biotic interactions, biomass 2

Introduction:

Seedling recruitment is an important process in the life cycle of plants, being a key determinant of population dynamics, rates of community turnover, and species range dynamics [START_REF] Tilman | Community invasibility, recruitment limitation, and grassland biodiversity[END_REF][START_REF] Walck | Climate change and plant regeneration from seed[END_REF]. Rates of seedling recruitment hence affect diversity across scale, from intraspecific variability to community patterns to regional species pools. The rates of natural seedling recruitment in plant communities are controlled by both abiotic conditions such as temperature and precipitation [START_REF] Meineri | Seedling emergence responds to both seed source and recruitment site climates: a climate change experiment combining transplant and gradient approaches[END_REF][START_REF] Klanderud | Biotic interaction effects on seedling recruitment along bioclimatic gradients: testing the stress-gradient hypothesis[END_REF], and by biotic characteristics of the community such as vegetation density and biomass [START_REF] Milbau | Plant community type and small-scale disturbances, but not altitude, influence the invasibility in subarctic ecosystems[END_REF][START_REF] Klanderud | Biotic interaction effects on seedling recruitment along bioclimatic gradients: testing the stress-gradient hypothesis[END_REF][START_REF] Frei | Biotic and abiotic drivers of tree seedling recruitment across an alpine treeline ecotone[END_REF]. Biotic control of seedling recruitment is typically assessed through seed sowing experiments in intact vegetation vs. vegetation removal plots. While experimentally removing biomass often leads to higher recruitment rates [START_REF] Klanderud | The relative role of dispersal and local interactions for alpine plant community diversity under simulated climate warming[END_REF][START_REF] Milbau | Plant community type and small-scale disturbances, but not altitude, influence the invasibility in subarctic ecosystems[END_REF][START_REF] Frei | Biotic and abiotic drivers of tree seedling recruitment across an alpine treeline ecotone[END_REF], we do not know if smaller-magnitude natural variation in community biomass, such as observed along elevation gradients in response to decreasing temperature [START_REF] Bloor | Effects of Warming, Summer Drought, and CO2 Enrichment on Aboveground Biomass Production, Flowering Phenology, and Community Structure in an Upland Grassland Ecosystem[END_REF][START_REF] Kardol | Climate change effects on plant biomass alter dominance patterns and community evenness in an experimental old-field ecosystem[END_REF][START_REF] Klanderud | The importance of biotic vs. abiotic drivers of local plant community composition along regional bioclimatic gradients[END_REF], would be sufficient to render alpine communities more open to seedling recruitment than their warmer-climate sub-alpine or boreal counterparts.

Understanding the role of such more subtle changes in community biomass is critical for understanding how climate-related variation in biotic filtering will affect community dynamics under climate change.

In parallel with biomass changes, the functional composition of vegetation also varies along bioclimatic gradients. In particular, plant functional traits related to competition for light, such as maximum plant height [START_REF] Westoby | A leaf-height-seed (LHS) plant ecology strategy scheme[END_REF][START_REF] Westoby | Plant ecological strategies: some leading dimensions of variation between species[END_REF], leaf area and specific leaf area (SLA) [START_REF] Grotkopp | Toward a causal explanation of plant invasiveness: seedling growth and life-history strategies of 29 pine (Pinus) species[END_REF][START_REF] Grotkopp | High seedling relative growth rate and specific leaf area are traits of invasive species: phylogenetically independent contrasts of woody angiosperms[END_REF][START_REF] Gallagher | Trait differences between naturalized and invasive plant species independent of residence time and phylogeny[END_REF] all decrease towards colder, alpine climates [START_REF] Dubuis | Predicting current and future spatial community patterns of plant functional traits[END_REF][START_REF] Guittar | Can trait patterns along gradients predict plant community responses to climate change?[END_REF]). This suggests a potential alternative driver of variation in natural seedling recruitment rates along elevation gradients, where the functional composition of the resident vegetation limits seedling recruitment towards warmer climates (i.e. the "effect traits" of the vegetation, sensu [START_REF] Suding | Scaling environmental change through the community-level: a trait-based response-and-effect framework for plants[END_REF]). Note that this potential role of functional traits in affecting recruitment through controlling the competitive effects of the extant community, and hence it's openness to recruitment, is different from the more common "response traits" framework approach which explores how the traits of the colonizing species affects their ability to recruit into new sites (e.g. [START_REF] Dolezal | Vegetation dynamics at the upper elevational limit of vascular plants in Himalaya[END_REF][START_REF] Dolezal | Functionally distinct assembly of vascular plants colonizing alpine cushions suggests their vulnerability to climate change[END_REF]. Until now, very few studies have used functional trait-based approaches to explore the role of community effect traits in controlling variation in seedling recruitment rates across communities (but see [START_REF] Blonder | Microenvironment and functional-trait context dependence predict alpine plant community dynamics[END_REF].

In this study, we ask if colder-climate alpine or sub-alpine communities are inherently more open to recruitment than warmer-climate sub-alpine or boreal communities, respectively. We use an "effect traits" framework to investigate the extent to which differences in community openness to recruitment are related to plant community biomass and/or to the functional trait composition of the extant vegetation. These are important questions in a climate change context because higher inherent community openness of colderclimate communities would translate into lower biotic resistance to colonization from warmer-climate species, and hence potentially higher and faster onset of negative impacts from novel competitors [START_REF] Alexander | Novel competitors shape species/' responses to climate change[END_REF]. Because community characteristics such as biomass and mean trait values associate with climate [START_REF] Wright | Modulation of leaf economic traits and trait relationships by climate[END_REF][START_REF] Mcgill | Rebuilding community ecology from functional traits[END_REF][START_REF] Violle | Let the concept of trait be functional![END_REF], it is non-trivial to disentangle their effects from the direct effects of climate on recruitment (e.g., through variation in seed availability or germination). To solve this, we performed a whole-community transplant experiment where intact grassland vegetation turfs (25 x 25 cm) were moved from alpine and sub-alpine sites to sub-alpine and boreal sites, respectively, resulting in a ca. 2℃ experimental warming treatment (Fig 1). The transplanted colder-climate 'foreign' communities and their paired locally replanted control communities thus differ in the climate under which they assembled, and hence in vegetation structure and trait characteristics [START_REF] Guittar | Can trait patterns along gradients predict plant community responses to climate change?[END_REF], but were exposed to the same climates and other biotic and abiotic site conditions during the experimental trials.

We thus compared community openness to recruitment between paired higherelevation plant communities transplanted to warmer climate and locally replanted control plant communities two years after transplantation. Community openness to recruitment was approximated by quantifying natural seedling emergence in each turf, which captures the first step in the seedling recruitment process. By focusing on the first and critical step in the seedling recruitment process (Graae et al. 2011, Guittar et al. in review), we isolate variation in and drivers of colonization success per se, and avoid confounding this event with later lifehistory stages such as differential survival due to the various processes operating on the already-emerged seedlings (plant-plant interactions, predation, etc.). As such, our study tests the biotic resistance of higher-elevation biodiversity to colonization by seed in the face of climate change. The transplant experiment was performed under two temperature regimes; alpine-to-sub-alpine transplants and sub-alpine-to-boreal transplants (Fig. 1), each replicated under four precipitation levels (ca. 600 -2700 mm of annual precipitation) allowing assessment of climate context-dependencies and hence the degree of generality of responses. Specifically, we ask:

1.

Does community openness to recruitment vary systematically along climatic gradients?

2. Do community biomass and functional trait composition vary along climatic gradients? If so, do these differences in biotic characteristics remains after placing colder-and warmer-climate communities under similar climatic conditions?

3.

If such climatically driven differences in community openness to recruitment exist, are they associated with differences in community biomass and/or with differences in community functional trait composition between the colder-adapted and the warmeradapted communities?

4.

Are there climatic context-dependencies in these associations along temperature and/or precipitation gradients?

We hypothesize greater community openness to recruitment in colder-climate communities because of lower vascular plant biomass and/or dominance by species that have traits that render them poorer competitors for light.

Material and methods

Study design

We used twelve calcareous grassland sites in southern Norway, situated in a climate 'grid'

where three levels of summer temperature (alpine ca 7.5°C; sub-alpine ca 9.5°C; boreal ca 11.5°C) are replicated across four levels of annual precipitation (1 = continental ca 600 mm; 2 = sub-continental ca 1200 mm; 3 = sub-oceanic ca 2000 mm; 4 = oceanic ca 2700 mm). The climatic grid was designed using interpolated data from the normal period 1961-1990 at a resolution of 100 m (Norwegian Meteorological Institute, www.met.no).

We selected the sites to keep vegetation type, bedrock, slope, aspect, land-use regime and history as constant as possible across sites. All sites were fenced to avoid animal disturbance, but mowed at the end of each growing season to mimic a standardized grazing regime (see [START_REF] Klanderud | The importance of biotic vs. abiotic drivers of local plant community composition along regional bioclimatic gradients[END_REF] for additional informations). All the plant communities were within the phytosociological association Potentillo-Festucetum ovinae in the alpine, tending towards Potentillo-Polygonum vivipari, and in some lowland sites tending towards Nardo-Agrostion tenuis [START_REF] Fremstad | Vegetasjonstyper i Norge[END_REF][START_REF] Meineri | Seedling emergence responds to both seed source and recruitment site climates: a climate change experiment combining transplant and gradient approaches[END_REF][START_REF] Klanderud | The importance of biotic vs. abiotic drivers of local plant community composition along regional bioclimatic gradients[END_REF].

Within each site, we selected five replicate blocks within a patch of the target grassland. Within each block, two 25*25 cm 2 plots were assigned randomly to the two treatments. The two turfs were cut and dug out to a depth of 5 to 10 cm, depending on the rooting depth. One of the cut turfs was replanted at the same site and the other was transplanted into a site one level warmer at the same precipitation level in the climate grid. At each site and block, the analyses described below contrast locally replanted turfs (hereafter warmer-climate communities or controls) vs. transplanted turfs originating from a colder climate (hereafter colder-climate communities or transplants) two years after transplantation.

The two-year delay between transplantation and data collection removes any effects of differences in current climate or other site-level factors between the control and transplanted communities. The experiment thus explicitly quantifies the openness to recruitment of communities that were assembled under a colder relative to a warmer climate, while controlling for the current climate and other abiotic conditions during the experimental trial (Fig. 1). A total of 80 transplanted and locally replanted turfs were used in the study, which is part of a larger experiment that also contained intact control plots (i.e., not dug out and replanted) as a control of the transplantation treatment per se. Preliminary analyses showed that community openness to recruitment (see below) was slightly higher in locally replanted controls than in these untouched plots (mixed effect linear models nested on block within site, p.value=0.048) for the main effect of plot replanting. We therefore used the locally replanted plots as controls for the remainder of this study to eliminate any effects of the transplantation process itself.

The species richness of vascular plants recorded within the turfs ranged from 10 to 40 species, with a mean canopy height of 9 ±6 cm (SD) [START_REF] Guittar | Can trait patterns along gradients predict plant community responses to climate change?[END_REF].

Seedling counts and vegetation sampling

We used the total number of naturally occurring dicotyledonous seedlings emerging within each turf as a measure of community openness to recruitment. We excluded graminoids because of difficulties in distinguishing monocotyledonous seedlings from clonal offshoots. In 2011, we counted all dicotyledonous seedlings with visible cotyledons in each turf. The survey was conducted at peak growing season, which is in the two first weeks of August at these sites. This timing of the census enabled a fairly comprehensive index of total dicot emergence, but with the trade-off that many of the seedlings were not yet identifiable to species. Indeed, some species in this system require several years for fully mature leaves to appear and allow confident identification.

To characterise the community, vegetation analyses of all turfs were conducted at peak season in 2009, before transplantation, and again in 2011. We recorded the percentage cover of each vascular plant species in each turf, and the total cover of all vascular plants and bryophytes. Height of vascular plants and height of the moss layer were recorded at four fixed positions within each turf during each census, and averaged to obtain one value per variable, turf and census. For each turf, we calculated a biomass index for vascular plants (Vbryo) and bryophytes (Bbryo) as:

𝐵 𝑣𝑎𝑠𝑐 = 𝐶𝑂𝑉 𝑣𝑎𝑠𝑐 × 𝐻 𝑣𝑎𝑠𝑐 𝐵 𝑏𝑟𝑦𝑜 = 𝐶𝑂𝑉 𝑏𝑟𝑦𝑜 × 𝐻 𝑏𝑟𝑦𝑜
Where COVvasc and COVbryo are the total percentage cover of vascular plants and bryophytes, respectively; and Hvasc and Hbryo are the average height of vascular plants and the bryophyte layer, respectively.

We assembled data on three plant functional traits, specific leaf area (SLA; m 2 /kg), leaf area (mm 2 ) and potential maximum plant height (hereafter plant height; m), related to competition for light [START_REF] Grime | Plant Strategies, Vegetation Processes, and Ecosystem Properties[END_REF][START_REF] Suding | Functional-and abundance-based mechanisms explain diversity loss due to N fertilization[END_REF]. Data on SLA and leaf area were derived from a combination of field measurements using the protocols described in [START_REF] Cornelissen | A handbook of protocols for standardised and easy measurement of plant functional traits worldwide[END_REF] and, for rare species where field measurements were not feasible, from the LEDA database [START_REF] Kleyer | The LEDA Traitbase: a database of life-history traits of the Northwest European flora[END_REF]. Plant height was derived from [START_REF] Lid | Norsk flora[END_REF] Nordic Flora. A full description of the trait collection and database is available in [START_REF] Guittar | Can trait patterns along gradients predict plant community responses to climate change?[END_REF]. All trait values were log-transformed to better achieve normal distribution criteria, and to prevent relatively small differences among species, which can be biologically relevant, being overpowered by larger ones [START_REF] Májeková | Evaluating Functional Diversity: Missing Trait Data and the Importance of Species Abundance Structure and Data Transformation[END_REF]. For each trait, plot, and census, community weighted means (CWMs) were calculated as the average across species of the trait value of each species found in the plot x its percentage cover in that plot.

We did not detect any strong collinearity between the three CWMs.

Statistical analyses

We used a log-linear mixed effect model to test if colder-climate communities were more open to recruitment than warmer-climate communities. Specifically, the model compared the natural seedling emergence recorded in each locally replanted control turf to the emergence in the paired transplanted turf originating from a colder site. This approach focuses on differences based on climatic origin while experimentally controlling for abiotic factors between the sites (Fig. 1).

We then compared the measured biotic characteristics (biomass of vascular plants and bryophytes, CWM of the traits SLA, leaf area, and plant height) between the control warmer-climate communities and transplanted colder-climate communities both before and two years after transplantation, using linear mixed effect models.

Finally, we determined whether differences in community characteristics between control warmer-climate and transplanted colder-climate communities could explain differences in seedling emergence between the turfs, using linear mixed effect models. We regressed differences in seedling emergence between local control warmer-climate and transplanted colder-climate communities (hereafter: Δ seedling.emergence) against differences in community characteristics between the same communities (hereafter: Δ vascular.plants, Δ bryophytes, Δ SLA, Δ leaf.area, Δ plant.height). These analyses were based on seedling and vegetation data two years after transplantation. A separate model was fitted for each individual biotic characteristic to avoid overfitting models and to ease interpretation.

In all models, interpolated values of site temperature and precipitation, as well as their interactions with the treatment (control vs. transplant) were included as covariates to assess if the patterns varied systematically with the climatic context. When such interactive effect were found significant, we ran additional separate mixed effect models for each gradient level in order to assess where along the gradient(s) transplanted colder community turfs differed significantly from the control communities. We used interpolated climate data in all models. However, temperature measurements at 2m height recorded during the summer 2011 were highly correlated with the interpolated temperature data (Pearson correlation coefficient = 0.98). Temperature and precipitation did not strongly correlate with our hypothesized explanatory variables (traits and biomass), excluding potential multicollinearity issues.

For the two first models, assessing if natural seedling emergence and biotic community characteristics differed between local control warmer-climate and transplanted colder-climate communities, destination block nested within destination site was included as a random variable. This enabled us to contrast paired control -versus transplanted communities in the same blocks and sites, and to control for the experimental design (i.e., avoiding pseudo-replication). A observation-level random term was also included in the model assessing seedling emergence to control for over-dispersion [START_REF] Harrison | Using observation-level random effects to model overdispersion in count data in ecology and evolution[END_REF]. For the last model, relating Δ seedling.emergence to the Δs of community characteristics, only site was included as a random term in the analyses as the records from the paired control and transplanted community in each block were combined into one single data point.

Three turf pairs were clear outliers due to very high seedling numbers and were omitted from the analyses (this was due to locally high densities of annual Euphrasia spp.

seedlings in these plots). The intercepts of all models were set at the sub-alpine sites and average precipitation. Precipitation was expressed in 100 mm units to obtain coefficients of similar magnitude for the two climate variables. Centering the models was chosen over full standardization in order to keep the units of the variables for their respective model coefficients and thus facilitate their quantitative interpretation. Stepwise backward variable selections were applied based on maximum likelihood ratio tests to meet the principle of parsimony and avoid overfitting models. All analysis were run in R (R Development Core

Team 2018; version 3.5.2) and all models were fitted with the packages lme4 [START_REF] Bates | Fitting Linear Mixed-Effects Models using lme4[END_REF]; version 1.1-20) and lmerTest [START_REF] Kuznetsova | lmerTest: Tests in Linear Mixed Effects Models[END_REF]version 3.1-0).

Data deposition

Data are available from the Dryad Digital Repository: < http:// dx.doi.org/10.5061/dryad.d39d356 > (Meineri et al. 2019).

Results:

An average of 169.6 seedlings/m 2 emerged in the turfs transplanted from colder sites whereas 116.8 seedlings/m 2 emerged in the warmer-climate control turfs. Seedling emergence was thus on average 44% higher (based on raw means; +58% according to the model estimate) in communities originating from 2ºC colder climates (p = 0.003, Table 1, Fig. 2). This means that the communities assembled under a colder climate are significantly more open to the early stages of seedling recruitment, after experimentally controlling for the effects of the current temperature. The magnitude of this effect was unaffected by climate, as we found no significant interactions between the treatment effect and the site position across the climate grid.

In 2009, before the onset of the experiment, all community characteristics except vascular plant biomass were significantly lower in alpine communities compared to subalpine communities (p<0,001 in all models). Vascular plant biomass (p=0.041), bryophyte biomass (p<0.014) and CWM plant height (p<0.001) were also lower in subalpine relative to boreal communities (Table 1, Fig. 3). On average, for each colder 'step' along the temperature gradient, vascular plant biomass decreased by 25%, bryophyte biomass decreased by 56%, SLA decreased by 2.4% , leaf area decreased by 3.5%, and plant height decreased by 36%

(based on raw means; note that for biomass this is based on the subalpine-boreal contrast and for SLA on the alpine-subalpine contrast, as the other contrasts were not significant for these variables; Table 1, Fig. 3).

Most of these differences in characteristics between transplanted communities and controls remained significant two years after the plots had been transplanted to experience the same climate, albeit with smaller magnitudes (Table1, Fig. 3). Of the original differences in community characteristics between colder-and warmer-climate communities, 35% remained for vascular plant biomass (as for the original effect, this difference was found only between sub-alpine and boreal sites), 67% for bryophyte biomass, 75% for SLA (as for the original effect, only between alpine and sub-alpine sites), 74% for leaf area, and 37% for plant height, (Table 1, Fig 3).

Among these community characteristics, only CWM leaf area (p=0.005) and CWM plant height (p<0.001) could explain differences in seedling emergence between the local controls and transplanted colder-climate communities (Table 2, Fig. 4, Appendix S1).

The models indicate that the consistently higher openness to seedling recruitment in colderclimate communities was associated with higher abundance of plants with lower stature, and with smaller leaves. However, for both leaf area and plant height, these correlations were only found for alpine communities transplanted to sub-alpine sites, as indicated by the significant interactions between the transplant treatment and temperature for both traits (p=0.009 and p=0.002 for leaf area and plant height interactions with temperature, respectively, Table 2, Fig. 4). For these communities, an increase of 1 cm 2 in CWM leaf area and 1 cm in CWM plant height is associated with an average decrease of 48 and 80 seedlings/m 2 , respectively.

Discussion:

Our study demonstrates that community openness to seedling recruitment, measured as the number of naturally-emerging dicot seedlings, was consistently higher in grassland plant communities originating from higher elevation (colder-climate communities) than communities originating from lower elevation (warmer-climate communities), when these communities were experimentally grown under the same climate. The results were consistent across seven out of eight replicate experimental sites, spanning broad-scale precipitation and temperature gradients, supporting the generality of the observed pattern. Further, these differences in community openness to recruitment could not be accounted for by differences in community biomass. Instead, they were associated with differences in plant functional traits, especially between alpine and sub-alpine communities, suggesting that the functional attributes of the species within these communities, and specifically traits related to their competitive effects, are important regulators of community openness to recruitment.

Although transplanted and local control communities had been exposed to the same climates and seed-rains from the same surrounding area for two years, it could be argued that factors other than differences in biomass or in traits could have led to these differences in openness to seedling recruitment. For example, transplantation to warmer sites might enhance seed production and recruitment rates of species and seeds that were already represented within the turfs. However, earlier field work in alpine and sub-alpine systems suggests that seed production and seedling recruitment of these species are not enhanced by a warmer climate, on the contrary, they often declined [START_REF] Shevtsova | Critical periods for impact of climate warming on early seedling establishment in subarctic tundra[END_REF][START_REF] Graae | Strong microsite control of seedling recruitment in tundra[END_REF][START_REF] Milbau | Plant community type and small-scale disturbances, but not altitude, influence the invasibility in subarctic ecosystems[END_REF]. In our specific sites, we found no changes in fecundity, assessed via numbers of flowers and natural seedling emergence, in four forbs in the same transplanted turfs across the climate grid [START_REF] Töpper | The devil is in the detail: Nonadditive and context-dependent plant population responses to increasing temperature and precipitation[END_REF]. Second, a seed transplant experiment of these same four forbs across the same sites, revealed that seeds sown into warmer climates actually emerged at lower rates than seeds sown at their home sites [START_REF] Meineri | Seedling emergence responds to both seed source and recruitment site climates: a climate change experiment combining transplant and gradient approaches[END_REF].

Last, we also assessed natural seedling emergence in intact vegetation in the same sites, and found that emergence rate of alpine species decreases with increasing temperature [START_REF] Klanderud | Biotic interaction effects on seedling recruitment along bioclimatic gradients: testing the stress-gradient hypothesis[END_REF]. A second potential explanation for the elevated numbers of seedlings in alpine communities transplanted to warmer sites could simply be that colder-climate communities have a larger seedbank or higher within-plot seedrain than warmer-climate communities, as found in other systems [START_REF] Pakeman | Potential climatic control of seedbank density[END_REF]. However, in earlier work in the same study sites, we found no patterns in seedbank density with temperature [START_REF] Vandvik | Seed banks are biodiversity reservoirs: species-area relationships above versus below ground[END_REF]) and seed rain density was lower, not higher, in colder sites (Guittar et al. in review). Therefore, the difference in functional traits of the communities emerges as the most likely explanation for the observed systematic decrease in community openness to seedling recruitment in communities originating from warmer climates.

Our results may underestimate the actual impact of functional differences between the communities on openness to recruitment because the transplanted communities had already shifted somewhat in community composition and hence community traits two years after transplantation [START_REF] Guittar | Can trait patterns along gradients predict plant community responses to climate change?[END_REF], and because intraspecific variation, which is not accounted for, contributes significantly to realized trait trends along these gradients [START_REF] Albert | A multi-trait approach reveals the structure and the relative importance of intra-vs. interspecific variability in plant traits[END_REF][START_REF] Gya | The role of intraspecific variability in driving community trait shifts along temperature and precipitation gradients in alpine and boreal semi-natural grasslands[END_REF]. Therefore, natural sub-alpine and alpine communities likely differ even more in functional traits than the experimentally paired communities we studied, and our estimates, which imply that the considerable differences in seedling emergence reported here (44% higher in communities originating from 2°C colder climates), are likely conservative.

In this study we focus on seedling emergence as a simple metric to compare the openness of warm-vs. cold-climate communities. Longer-term survival and growth of these recruits may, of course, show different patterns, potentially enhancing or dampening the patterns we observe here, although the early seedling emergence phase has been shown to be highly selective and important for population and community dynamics in our and similar systems (Graae et al. 2011, Guittar et al. in review) suggesting it is reasonable to expect that the consequences of these differences will remain into later stages of the life-cycle.

Biomass and trait effects on community openness to recruitment

Higher vascular plant biomass should reduce light penetration to the soil surface, and higher bryophyte biomass should prevent seeds from the seed rain reaching the soil and/or seeds from the seedbank to access light [START_REF] Jeschke | Effects of a dense moss layer on germination and establishment of vascular plants in newly created calcareous grasslands. -Flora -Morphology, Distribution[END_REF]. High biomass of either vascular plants or bryophytes is therefore expected to reduce community openness to seedling recruitment [START_REF] Jutila | Effects of disturbance on germination and seedling establishment in a coastal prairie grassland: a test of the competitive release hypothesis[END_REF]Grace 2002, Jeschke and[START_REF] Jeschke | Effects of a dense moss layer on germination and establishment of vascular plants in newly created calcareous grasslands. -Flora -Morphology, Distribution[END_REF]. If vascular plant and bryophyte biomass is to play a role in community openness along elevation, this requires variation in these variables along the elevation gradient. While this was generally found, it did not hold for vascular plant biomass between alpine and subalpine sites, and it is thus not surprising that biomass did not affect community openness for this particular contrast. However, community openness was also unrelated to vascular plant or bryophytes biomass across all other site and elevation contrasts. Previous studies that have found strong effects of biomass on seedling recruitment are typically based on seed-sowing experiments in intact vegetation vs. bareground plots where all vegetation has been removed [START_REF] Cooper | Plant recruitment in the High Arctic: Seed bank and seedling emergence on Svalbard[END_REF][START_REF] Gough | Neighbor effects on germination, survival, and growth in two arctic tundra plant communities[END_REF][START_REF] Jeschke | Effects of a dense moss layer on germination and establishment of vascular plants in newly created calcareous grasslands. -Flora -Morphology, Distribution[END_REF][START_REF] Tingstad | Temperature, precipitation and biotic interactions as determinants of tree seedling recruitment across the tree line ecotone[END_REF][START_REF] Klanderud | Biotic interaction effects on seedling recruitment along bioclimatic gradients: testing the stress-gradient hypothesis[END_REF]. The increase in biomass caused by the ca. 2°C temperature increase between the sites at adjacent altitudinal levels is of much smaller magnitude, which may explain why we did not find any effect of biomass on community openness to recruitment. Consistent with this interpretation, [START_REF] Milbau | Plant community type and small-scale disturbances, but not altitude, influence the invasibility in subarctic ecosystems[END_REF], using small gaps of 3 cm and 6 cm in their seed-sowing experiments, concluded that in relatively productive alpine habitats, comparable to our grasslands, larger-scale disturbance may be necessary to promote seedling recruitment. Furthermore, [START_REF] Milbau | Plant community type and small-scale disturbances, but not altitude, influence the invasibility in subarctic ecosystems[END_REF] and another study in a comparable alpine habitat [START_REF] Graae | Strong microsite control of seedling recruitment in tundra[END_REF], found only weak effects of productivity on seedling recruitment in intact vegetation. An alternative explanation for the lack of biomass effects on seedling emergence is that we used a relatively coarse nondestructive estimate of biomass (based on cover and height), which may not have been accurate enough to detect subtle effects.

In contrast, we found differences in natural seedling emergence between alpine and subalpine communities to be consistently associated with the plant functional traits of the vegetation, and specifically with differences in community-weighted means of leaf area and plant height, two traits related to competition for light. Therefore, our results suggest that alpine communities are more open to recruitment than sub-alpine communities primarily because the alpine vegetation is comprised of relatively small-statured and small-leaved species, traits that confer weak competitive effects (sensu [START_REF] Suding | Scaling environmental change through the community-level: a trait-based response-and-effect framework for plants[END_REF] relative to the taller and larger-leaved plants dominating at lower elevations. Therefore, even if biomass increases, for example in response to warming, the dominance of alpine communities by species with relatively low competitive effect traits may lead them to be inherently more open to recruitment than their warmer-climate adapted counterparts. This relatively weaker biotic filtering in cold-adapted communities could, in turn speed up colonization and establishment of warmer-adapted immigrant species into the alpine, eventually allowing better tracking of climate warming by lower-elevation species and shorter dispersal lags towards higher altitudes, which again may cause greater loss of alpine species with nowhere to migrate to as competitive effects from these warmer-climate adapted novel competitors set in [START_REF] Alexander | Novel competitors shape species/' responses to climate change[END_REF].

Importantly, differences in the traits plant height and leaf area between warmerand colder-communities explained differences in seedling emergence only between the alpine and the subalpine communities, and not between the sub-alpine and the boreal communities.

This was unexpected, because these community-weighted mean trait values also differed significantly between subalpine and boreal communities, suggesting there may be nonlinearities in responses or shifts in the key effect traits along these gradients. In line with our results, [START_REF] Blonder | Microenvironment and functional-trait context dependence predict alpine plant community dynamics[END_REF] suggest that the effects of several functional traits on vital rates and on seedling recruitment depend on both microenvironment and crowding by neighbors.

Alternatively, traits affecting light availability below the canopy may be important in both the crowded sub-alpine and boreal environments, but with different functional traits being relevant to describe the effects of the established community on seedling recruitment in the boreal zone. Using more complex trait associations via factorial analyses [START_REF] Blonder | Microenvironment and functional-trait context dependence predict alpine plant community dynamics[END_REF] or structural equation modelling [START_REF] Shipley | Reinforcing loose foundation stones in trait-based plant ecology[END_REF]) might help to detect or to understand if and to what extent climate effects on community structure indirectly affect community openness to recruitment.

We found no association between SLA and seedling emergence, although the transplanted colder-climate alpine communities had lower community-weighted mean SLA than the local control warmer-climate sub-alpine communities. High SLA species have high relative growth rates, short life spans and rapid turnover of leaf material [START_REF] Westoby | A leaf-height-seed (LHS) plant ecology strategy scheme[END_REF].

While these characteristics make high-SLA species good invaders i.e., they are efficient response traits [START_REF] Grotkopp | Toward a causal explanation of plant invasiveness: seedling growth and life-history strategies of 29 pine (Pinus) species[END_REF][START_REF] Grotkopp | High seedling relative growth rate and specific leaf area are traits of invasive species: phylogenetically independent contrasts of woody angiosperms[END_REF][START_REF] Gallagher | Trait differences between naturalized and invasive plant species independent of residence time and phylogeny[END_REF], the role of SLA as an effect trait, i.e., its effect on seedling emergence and establishment, has not yet been systematically studied. Even if such effects exist, the differences in SLA between higher-and lower-elevation communities may not be sufficient to affect seedling recruitment, since the difference in SLA between the transplanted and local control communities, although significant, was only 2.5%.

We found no relationship between community openness to recruitment and precipitation regime. This is unsurprising, given the lack of precipitation-based trends in biomass and community trait values in our system [START_REF] Guittar | Can trait patterns along gradients predict plant community responses to climate change?[END_REF]. Annual precipitation at our sites ranges from ca. 600 mm to 2700 mm; hence, water is likely not a limiting resource in any of our sites. Seedling recruitment may thus trend with precipitation in other systems, where water is more limiting and/or where biomass or traits change with precipitation [START_REF] Pedrol | Phenotypic plasticity and acclimation to water deficits in velvet-grass: a long-term greenhouse experiment. Changes in leaf morphology, photosynthesis and stressinduced metabolites[END_REF][START_REF] Moles | Global patterns in plant height[END_REF][START_REF] Kardol | Climate change effects on plant biomass alter dominance patterns and community evenness in an experimental old-field ecosystem[END_REF].

Conclusion and implications under climate change

Colder-climate alpine and subalpine plant communities were inherently more open to seedling recruitment than warmer-climate communities, even after experimentally controlling for differences in current climate and in local propagule pressure. This result could have significant implications for response to climate change, because the openness of the resident communities to recruitment in the cold climate habitats is a key factor controlling the rate and degree to which species can migrate to new locations to track climate change. If highelevation communities had low openness to seedling recruitment, this would constitute a strong biotic filter to colonization, limiting the degree to which the colder-climate species and communities would be exposed to novel competitors from warmer climates. However, our results suggest the opposite; alpine communities are more open to seedling recruitment, potentially resulting in weaker biotic filtering and hence higher rates of colonization than lower-elevation communities.

In contrast to earlier studies, which have mostly focused on biomass constraints and ignored potential effects of plant functional composition, our results suggest that the effect traits of the vegetation, specifically lower community-weighted mean plant height and leaf area, may explain the higher openness of alpine communities relative to sub-alpine communities. Our results therefore suggest that alpine species may lack the competitive effect traits needed to make their communities resistant to the expected colonization of novel species from lower elevation under a warming climate.

Declarations

of the manuscript. VV designed he SeedClim grid and obtained funding. All authors contributed critically to improve the manuscript and gave final approval for publication.

Tables and figures:

Table 1: Mixed effect models assessing differences in community openness to natural seedling recruitment, biomass, and functional trait composition between colder-climate communities (transplanted turfs originating from colder sites) and warmer-climate control communities (locally replanted turfs at the experimental site). Note that the pre-treatment data were sampled when the communities of each pair were still in their origin sites, and this contrast thus reflects the pre-treatment climate gradient contrasts. Turfs were transplanted in September 2009; the communities of each pair were thereafter growing in the same site so that any remaining differences reflect the effect of community Δseedling.emergence did not respond significantly to Δvascular plant biomass, Δbryophyte biomass and ΔSLA (see appendix S1 for similar plots for these traits).

  characteristics, independent of current climate. Community-weighted means are used for SLA, leaf area and plant height. A positive coefficient means larger values in transplanted colder-climate relative to control warmer-climate communities. Note that natural seedling emergence was not recorded in 2009. -: Factored out during stepwise selection. DF: Degrees of freedom estimated by Satterthwaite approximations. Note that DF is not reported for GLMM because of ongoing discussions about their correct calculation.

Figure 1 :

 1 Figure 1: Design of the turf transplant experiment. Turfs with intact plant communities were

Figure 2 :

 2 Figure 2: Effect of climate of origin on community openness to recruitment. The figure

Figure 3 :

 3 Figure 3: Averaged community characteristics in warmer-climate communities ("Ctrl":

Figure 4 :

 4 Figure 4: community openness to recruitment (Δseedling emergence between transplanted

Acknowledgements -We thank Siri Lie Olsen and the many SeedClim field assistants for help with the field work. We thanks anonymous reviewer for helpful comments and critics.

Funding -Norwegian Research Council for funding (KLIMAFORSK project 184912).

Authors' contributions -VV, DG, KK and EM conceived the idea and designed the methodology; VV, KK, JG collected the data; EM analyzed the data; EM wrote the first draft

Supplementary material:

Appendix s1: Seedling emergence non-responses to vascular plant biomass (a), bryophyte biomass (b) and SLA (c). Δseedling.emergence (#): differences in seedling emergence 34 between warmer-and colder-climate communities in number of seedlings.; Δvascular plant biomass, Δbryophyte biomass and ΔSLA: differences in these community characteristics between warmer-and colder-climate communities.


Charlotte Roemer
email: croemer@biotope.fr

Thierry Disca

Aurélie Coulon

Yves Bas

Bat flight height monitored from wind

Keywords: bat, wind turbine, carcass, impact assessment study, wind mast, actichiro

teaching and research institutions in France or abroad, or from public or private research centers.

Introduction

Green energy development is today one of the top priorities of European governments. To answer this requirement, wind farm implantations have increased tremendously over the last years [START_REF] Leung | Wind energy development and its environmental impact: a review[END_REF]. Meanwhile, their impact has been proven lethal for numerous bird and bat species (Rydell et al., 2010a;Drewit and Langston, 2006;[START_REF] Frick | Fatalities at wind turbines may threaten population viability of a migratory bat[END_REF][START_REF] Hammerson | Strong geographic and temporal patterns in conservation status of North American bats[END_REF]. In Europe, cases of fatalities by collision or barotrauma around wind turbines (WT) have been reported in 27 bat species over the 51 extant European species for a total amount of circa 7,000 individuals and France alone has an impact on at least 17 species [START_REF] Rodrigues | Guidelines for consideration of bats in wind farm projects-Revision 2014[END_REF]. Since a very small proportion of wind farms were surveyed and for a limited period of time, this number is only the tip of the iceberg. Estimates show that in Germany alone, wind turbines may account for more than two million bats killed over the past 10 years, if mitigation measures were not practiced [START_REF] Voigt | Wildlife and renewable energy: German politics cross migratory bats[END_REF].

All European bat species are under strict protection (Habitat Directive, Annex IV -Council Directive 92/43/EEC, 1992), hence the necessity to develop proper tools to assess as accurately as possible the impacts of human activities before their occurrence on bat populations. Today, European impact assessment studies monitor bat activity with methods ranging from evening transects with ultrasound detectors or autonomous overnight recordings from the ground to long-term recordings with microphones at height [START_REF] Rodrigues | Guidelines for consideration of bats in wind farm projects-Revision 2014[END_REF].

To explain bat fatalities at WT and in the hope of predicting them, numerous hypotheses have emerged concerning the ultimate causes of collisions [START_REF] Cryan | Causes of bat fatalities at wind turbines: hypotheses and predictions[END_REF]. The simplest explanation would be that mortality is directly linked to specific activity rates on site, independently from altitudinal distributions. However, uncommon species are sometimes more impacted than others (e.g. [START_REF] Georgiakakis | Bat Fatalities at Wind Farms in North-Eastern Greece[END_REF]. Some hypotheses suggest that species mostly impacted are annual migrants that might be seasonally manoeuvring at heights with collision risks, or that they are tree roosting species that might mistake wind towers for trees [START_REF] Cryan | Causes of bat fatalities at wind turbines: hypotheses and predictions[END_REF][START_REF] Cryan | Behavior of bats at wind turbines[END_REF][START_REF] Jameson | Activity of tree bats at anthropogenic tall structures: Implications for mortality of bats at wind turbines[END_REF]. Rydell et al. (2010b and2016) doubt that migration is the only explanation for collisions because resident species are very often the most impacted species, and because insects resting on WT were identified in the stomach contents of bat carcasses found at wind farms. They conclude that there might not be a single explanation to the complex phenomenon of bat collisions at wind farms.

Before investigating complex hypotheses, it is important to focus on straightforward relationships. In all simplicity, bats spending most of their time foraging and commuting at similar heights as blade heights should be more susceptible to collisions. This assumption of coincidental collisions [START_REF] Cryan | Causes of bat fatalities at wind turbines: hypotheses and predictions[END_REF] has never been thoroughly investigated because of the lack of appropriate tools, i.e. tools that would not produce any attraction phenomenon.

Yet, in order to estimate impacts before the setting up of wind farms, the more the setting resembles a WT, the easier it will be to estimate future impacts and draw conclusions. Hence it is not necessarily desirable to free the survey material from any effect on bat behaviour. [START_REF] Korner-Nievergelt | Estimating bat and bird mortality occurring at wind energy turbines from covariates and carcass searches using mixture models[END_REF] demonstrated that bat activity at WT nacelles is correlated with the number of carcasses found at their foot. But it has never been formally proven that this correlation is also valid for pre-construction acoustic surveys from wind masts, which are recommended for impact assessment studies [START_REF] Rodrigues | Guidelines for consideration of bats in wind farm projects-Revision 2014[END_REF]. An attempt by [START_REF] Hein | Relating pre-construction bat activity and postconstruction bat fatality to predict risk at wind energy facilities: a synthesis[END_REF] was not conclusive because of the variability in the methods of the studies that were available. Yet, this relationship most probably exists, notably because there is evidence that tall anthropogenic structures engender an attraction phenomenon toward tree roosting/migratory bats at the same time of the year where mortality peaks at WT are found [START_REF] Jameson | Activity of tree bats at anthropogenic tall structures: Implications for mortality of bats at wind turbines[END_REF]. Those bats are not the only species affected by WT collisions and others such as exclusive cave roosting species are also implicated although at much lower rates (e.g. Miniopterus schreibersii, [START_REF] Rodrigues | Guidelines for consideration of bats in wind farm projects-Revision 2014[END_REF]. It might be that specific differences in flight behaviour play an important role in explaining differences in collision susceptibility among tree roosting/migratory species but more generally among all bats, and this concomitantly to an attraction phenomenon. [START_REF] Müller | From ground to above canopy ? Bat activity in mature forests is driven by vegetation density and height[END_REF] showed that wind turbine fatality counts are numerous for most species flying more often around tree canopy than close to the ground. But a clear identification of the role played by bat flight height distribution in species susceptibilities to collisions, independently of species relative densities, is still missing. This distinction is for instance essential in order to rank species susceptibility. To perform this distinction between species behaviour and density, the latter must be corrected by using a reference scale for species activity levels (see [START_REF] Haquart | Actichiro. Référentiel d'activité des chiroptères : éléments pour l'interprétation des dénombrements de chiroptères avec les méthodes acoustiques en zone méditerranéenne française[END_REF].

Our study aims at testing the relevance of using activity data from wind masts in wind farm impact assessment studies. Our hypotheses are that (1) WT collision susceptibility is strongly linked to the preference of species flying at altitudes similar to those of WT blades, and that (2) this correlation can be established from observations at wind masts, as they act as a similar stimulus as WT toward bats.

Material and Methods

Acoustic recordings

Recordings were conducted at 23 sites in France and Belgium (see Figure 1) between 2011 and 2016.

Habitats consisted in pine, spruce and mixed forest clearings (11 sites), bocage (3 sites) wetlands (1 site) and cultivated fields (8 sites). Sites in Southern and Eastern France were either located in mountainous areas or in plains while the remaining sites were in plains only. Months between April and October cumulated the maximum number of sites surveyed per night (Figure 2). In total, bat activity was monitored on 3,260 nights (µ = 142, σ = 72 nights per site). The recording period at each site did not exceed one year.

In order to establish a link between bat behaviour before the presence of WT and the collision risk after their activation, a proper manner to assess bat flight height distribution had to be chosen. [START_REF] Collins | Differences in Bat Activity in Relation to Bat Detector Height: Implications for Bat Surveys at Proposed Windfarm Sites[END_REF] obtained differences between bat activity at ground level and at height by mounting one microphone at ground level and one at 30 m on a mast. With two unsynchronised microphones however, the most detectable species might be counted twice (i.e. at both microphones). Some species can indeed be acoustically detected at more than 90 m [START_REF] Holderied | Echolocation range and wingbeat period match in aerialhawking bats[END_REF][START_REF] Barataud | Acoustic Ecology of European Bats. Species Identification, Study of Their Habitats and Foraging Behaviour[END_REF]. Here, we performed a binary location of the bat position (i.e. near the nacelle height or near the ground), without any double count, while at the same time enabling a specific identification through the echolocation calls.

We installed microphones on lattice or monopole wind masts of 50-100 m high that all had aviation lighting at night. Arrays with two microphones were achieved with two SMX-US microphones plugged to an SM2BAT (all models, Wildlife Acoustics, Massachusetts, USA). Microphones were inserted into aluminium tubes, facing downward, in protection from weather alterations. The omnidirectionality of the setting was ensured by a custom-made round shaped 6 cm diameter aluminium reflector placed below the microphone with a 45° angle. Microphones were respectively installed at heights ranging from 4 to 85 m (see Figure 3). Recorders were programmed to start each day 30 min before sunset and stop 30 min after sunrise. For study sites between 2013 and 2016 (13 sites), whole night recordings were performed. On study sites from before 2013 (10 sites), samplings were collected during 10 minutes every 20 minutes. Gain was set at 36 dB, sampling rate at 192 kHz, trigger at 6 dB above background noise and trigger window at 2.5 sec. A 1 kHz high pass filter was used. Files were compressed in WAC4 format and analysed in WAV format.

Species identification and flight height classification

Files were decompressed using the WAC2WAV (Wildlife Acoustics, Massachusetts, USA) software.

When longer, files were automatically cut in 5 second bouts after each triggered recording to be used as a proxy for a bat pass, according to Barataud's method (2015). Species identifications were performed on SonoChiro (Biotope, France) [START_REF] Newson | A novel citizen science approach for large-scale standardised monitoring of bat activity and distribution, evaluated in eastern England[END_REF]. The verification of acoustic sequences was done on Syrinx (John Burt, USA) or BatSound (Pettersson Elektronik AB, Sweden) with spectrogram representations, allowing to measure acoustical parameters. Identification criteria are based on the association between acoustic call type, call shapes and measurable parameters (initial frequency, terminal frequency, signal length, maximum energy and its repartition …), their rhythms (interval duration between calls) and the environment (distance to obstacles). With the knowledge accumulated today, this method born from Barataud's work (2015) allows the identification, in good recording conditions, of 29 species from the 33 extant in France and Belgium. Yet, sonar calls of certain species are sometimes very close, even identical in certain flight circumstances. Hence, they are assembled in species groups. In the present case, Myotis were grouped in two categories: Myotis myotis and M. blythii in a "large Myotis" group and all others in a "small Myotis" group, and all Plecotus individuals in the Plecotus sp. group. Within those two groups, species present flight heights comparable to the other species of their group [START_REF] Rodrigues | Guidelines for consideration of bats in wind farm projects-Revision 2014[END_REF]. It was however not acceptable to group unidentified species from Pipistrellus or Nyctalus/Eptesicus/Vespertilio genera, because they display very different flight heights within their group. These unidentified bat passes (2.95 % of all bat passes) were not used for further analyses.

In order to classify flight heights, SonoChiro was used to automatically determine the time at which each call starts on each microphone. Then, using the find.matches function of Hmisc package [START_REF] Harrell | with contributions from Charles Dupont and many others[END_REF] from R (R Core Team, 2014), we obtained the time differences of arrival for each call detected.

For each site, a height threshold was defined as the median height between the two microphones (see figure 3). This threshold corresponds for each site to the lowest height at which the planned WT blade would operate and therefore the altitude above which collisions can occur. This means that in forests also, the median height represents the height above which bats would be at collision risk. This threshold was used to assign bat calls to two classes: "at height" if the source of the signal is above the threshold and "at ground level" if it is below the threshold. If a bat call is detected by the highest or the lowest microphone only, the call is considered to be respectively located at height or at ground level.

If several calls of the same bat pass give different location results (both at ground level and at height), location is determined by a majority vote among the calls (e.g. if 12 calls are at ground level and three calls are at height, the bat pass is assigned to "at ground level"). We then calculated a ratio of the time spent at height for each species. This method has also the advantage of freeing the comparison of several study sites from detectability bias linked to the type or the quality of the recording equipment.

The count of the number of bat passes at height would be itself more prone to such bias.

Calculation of collision susceptibility index

Mortality data (total amount of bat carcasses found at WT) were transmitted by the agreement on the conservation of populations of European bats EUROBATS (2015 update). The identity of the sites surveyed and the months during which carcass searching was performed were not available for data after 2014. Before 2014, the surveyed months were not available for half of the sites. From the information we could obtain, the seasonal distribution of fatality searches during the year was very similar to the distribution of our acoustic samplings (see figure A1 in suppl. Material). The spatial distribution of the mortality survey sites was very similar to the one of wind masts (see figure A2 in suppl. material), except for Northern and Eastern France, where we had more wind masts. Fatality data were collected from 2008 to 2012. From the information available, the zone swept by the rotor blades was then above 32 (+/-8) meters high. We defined species susceptibility to collisions as the mortality rate relative to species density. To calculate this latter value, we used acoustic data and accounted for variations in acoustic detectability between species. For each species, for the whole French territory, the density index was calculated as follows: eqn 1 , where detection distance is the approximate maximal distance from which an individual of a species can be acoustically detected [START_REF] Barataud | Acoustic Ecology of European Bats. Species Identification, Study of Their Habitats and Foraging Behaviour[END_REF] and where mean activity was taken from the French reference scale of activity levels "Actichiro" [START_REF] Haquart | Actichiro. Référentiel d'activité des chiroptères : éléments pour l'interprétation des dénombrements de chiroptères avec les méthodes acoustiques en zone méditerranéenne française[END_REF]. The latter was built from acoustic recordings on more than 2,757 nights between 2007 and 2011 and orders species on a scale from the least to the most commonly recorded. This reference scale used recordings from microphones installed at ground level only. However, in our dataset, species relative activity recorded from ground is similar to species relative total activity (sum of ground level and height activity) (Pearson's r = 0.98; see table A1 in suppl. material). The recordings in Actichiro oversampled the Mediterranean region (see table A2 in supplementary material) while our sampling was more balanced (see table A5 in supplementary material). Thus, we used a mean activity weighted by the areas of the four biogeographical regions to get more accurate measures of species relative density all over the country. To do this, we multiplied the mean activities for each of the four biogeographical regions by a regional area ratio (i.e. region area divided by the area of the whole French territory). We then summed all weighted mean activities to obtain a French mean activity. Since no activity data was available for Belgium, our collision susceptibility index relied only on data from France. It was calculated as follows for each species: eqn 2 , where number of carcasses is the total amount of bat carcasses found at French wind farms. We added one to the number of carcasses for each species to avoid a multiplication by zero. The limit of this method lies in the overcorrection of the susceptibility of rare species.

Correlation between the ratio of time spent at height and collision susceptibility index

We used a generalised linear mixed model (GLMM) to estimate rates of flight at height for each species. Bat pass height was modelled as a binomial variable (at height or at ground level) according to species as a fixed effect. In order to take into account the local environment effect on flight behaviour, study sites were introduced as a random variable. The GLMM was built using the glmmPQL function of the MASS package (Venable and Ripley, 2002) of R (R Core Team, 2014).

The estimated species rate of flight at height was then correlated to species collision susceptibility index. The first variable did not follow a normal distribution and for this reason a Spearman's rank correlation test was performed. The same method has been applied to test the correlation between the total amount of bat passes at height and the raw fatality counts.

Results

Flight heights of 340,797 bat passes have been recorded, among which 330,740 could be attributed to a species or a group of species and used for further analysis. At least 28 species have been determined.

The most commonly recorded species was P. pipistrellus. On average, 10 % of its time was spent at height (Table A3: Ratio of time spent at height for each species.Figure 4). The small Myotis group contains data from at least M. alcathoe, M. bechsteinii, M. brandtii, M. capaccinii, M. emarginatus, M. nattereri, M. daubentonii, M. dasycneme and M. mystacinus (see table A4 in suppl. material for details). The only bat passes at height that could be identified for this group were from M. daubentonii and for a probable M. dasycneme. The Plecotus group contains data from at least P. auritus and P. austriacus and both have been recorded at height. Rhinolophus bats are the only genus that was never recorded at height. All Nyctalus bats, Tadarida teniotis and Vespertilio murinus spent more than 40 % of their time at height. The collision susceptibility index, which takes into account the abundance of species, classified V. murinus, Nyctalus bats and P. nathusii as most susceptible to WT collisions (Erreur ! Source du renvoi introuvable.). P. pipistrellus had a low level of susceptibility to collisions (Erreur ! Source du renvoi introuvable.) despite being the most common species found in mortality surveys [START_REF] Rodrigues | Guidelines for consideration of bats in wind farm projects-Revision 2014[END_REF]. Small Myotis, Plecotus, Barbastella and Rhinolophus had a very low level of susceptibility (Erreur ! Source du renvoi introuvable.).

A significant correlation (rho = 0.94; p = 4.57e-06) could be demonstrated between species' susceptibility to WT collisions and their preference to fly at height (Figure 5). Low flying species (Rhinolophus, small Myotis and Plecotus bats) correspond to species with a low index and high flying species (Nyctalus, Vespertilio and Tadarida bats) to a high index. A significant correlation has also been found between the total amount of bat passes at height and the raw fatality counts (see figure A3 in suppl. material).

There was a high correlation between the number of bat passes recorded from the ground microphone and the number of bat passes recorded from the upper microphone for certain species (e.g. N. noctula and N. leisleri), however the activity at height of several species (e.g. Small Myotis or P. pipistrellus) could not be explained by the ground microphone only, or poorly (see Table A1 in suppl. Material).

Discussion

Flight behaviour

The dataset presented here is the first objective assessment of flight height distribution of European species, at similar environments to where wind blades operate. It extends the results found by [START_REF] Müller | From ground to above canopy ? Bat activity in mature forests is driven by vegetation density and height[END_REF] by covering several landscape types with a very large sample size, ensuring a fair representativeness of the variability that may occur across several biogeographical regions.

Our results show that species flight behaviour can be organised into three different categories embracing [START_REF] Denzinger | Bat guilds, a concept to classify the highly diverse foraging and echolocation behaviors of microchiropteran bats[END_REF] guilds definitions. The first category includes four different guilds, namely edge space trawling foragers and narrow space active gleaning foragers (i.e. small Myotis), narrow space flutter detecting foragers (i.e. Rhinolophus) and narrow space passive gleaning foragers (i.e. Plecotus, Barbastella and large Myotis). These species were always or almost exclusively located at ground level. The second category corresponds to the guild of edge space aerial foragers with species flying more often close to the ground or vegetation than at height (i.e.

Miniopterus, Pipistrellus, Eptesicus and Hypsugo species). The third category corresponds to the guild of open space aerial foragers (i.e. Nyctalus, Tadarida and Vespertilio species), that spent a considerable proportion of time at high heights. These results underline the close relationship between bat sonar and flight behaviour. Indeed, the first group mainly uses very high-pitched frequencies and/or strongly modulated frequencies, with short duration (Rhinolophus excluded because of their use of a specific strategy to detect prey flutter [START_REF] Schnitzler | Auditory fovea and Doppler shift compensation: adaptations for flutter detection in echolocating bats using CF-FM signals[END_REF]), implying a short acoustical range. The third group on the other hand often uses quasi-constant frequencies with very short bandwidth and long duration calls, which carries a signal over long distances [START_REF] Barataud | Acoustic Ecology of European Bats. Species Identification, Study of Their Habitats and Foraging Behaviour[END_REF].

The first acoustical strategy is adequate to forage and commute close to the ground and vegetation whereas the second is on the contrary best suited for high flight. Between those two groups, one can clearly observe a progressive range of those acoustical strategies (e.g. Eptesicus serotinus, which displays low frequencies but large bandwidths). The specific distribution of flight heights found in our study is concordant with what is described in the literature [START_REF] Arthur | Les Chauves-souris de France[END_REF][START_REF] Dietz | Bats of Britain, Europe and Northwest Africa[END_REF][START_REF] Rodrigues | Guidelines for consideration of bats in wind farm projects-Revision 2014[END_REF].

Correlation between fatalities and behaviour

In order to establish a relationship between species distinctive flight height distribution and their susceptibility to WT collisions, a proper method for the assessment of this susceptibility had to be chosen. Since study sites with standardised methods in both pre-construction acoustic surveys and post-activation fatality surveys are very scarce, we chose to use publicly available mortality data from French wind farms. Here, to distinguish between the effect of behaviour and density, French carcass counts had to be corrected for species abundance. Relative densities for bat species are only available in the literature for the French territory [START_REF] Haquart | Actichiro. Référentiel d'activité des chiroptères : éléments pour l'interprétation des dénombrements de chiroptères avec les méthodes acoustiques en zone méditerranéenne française[END_REF]. This approach is worth considering for other territories and opens novel possibilities for assessing correlations such as the one presented here.

Our results demonstrate that species susceptibility to WT collision is highly correlated with their propensity to spend time at height (i.e. at collision risk) when monitored from wind masts. This novel finding disentangles the roles played by species densities on one hand, and by species flight height on the other hand, and brings new elements to the understanding of the ultimate causes of WT collisions (see [START_REF] Cryan | Causes of bat fatalities at wind turbines: hypotheses and predictions[END_REF]. Furthermore, the behavioural relevance of this relationship is that tall structures like wind masts or WT seem to act as similar auditory or visual stimuli to bats, as this was suggested by [START_REF] Jameson | Activity of tree bats at anthropogenic tall structures: Implications for mortality of bats at wind turbines[END_REF] for North American species.

Limits and proposals for improvement

The robustness of the correlation has to be enhanced with more observations for rare species. T. teniotis and N. lasiopterus populations for instance are suspected to be significantly impacted by WT, although few data have been reported in France -1 and 6 carcasses respectively [START_REF] Rodrigues | Guidelines for consideration of bats in wind farm projects-Revision 2014[END_REF]. Spain and Portugal studies report the majority of mortality data for these two large European species. According to French population densities calculated by [START_REF] Haquart | Actichiro. Référentiel d'activité des chiroptères : éléments pour l'interprétation des dénombrements de chiroptères avec les méthodes acoustiques en zone méditerranéenne française[END_REF], they are among the five rarest species in the French Mediterranean region (57 000 km²). The estimates are of about 16 000 individuals for T. teniotis and about 600 individuals for N. lasiopterus. The impact of WT might be underestimated because of the low probability to find the carcasses of rare species.

The results presented here were obtained from data originating from relatively small WT (rotor blades above 32 (+/-8) meters high) or wind masts compared to many WT that are currently being built. However, we can assume that flight height distribution of each species are simple gradients, thus species ordering along the susceptibility gradient should not change according to WT height. Bat fatalities at wind farms collected by EUROBATS are not corrected for predation rates, the efficiency of the observer and the surface prospected. It is one of the reasons why the correlation established in our study is a relative correlation and cannot be used as such to predict the number of carcasses that would be found at a WT by an acoustic survey alone. To achieve this goal, a different method has to be used, where flight height monitoring and carcass searches would be performed at the same sites. [START_REF] Korner-Nievergelt | Estimating bat and bird mortality occurring at wind energy turbines from covariates and carcass searches using mixture models[END_REF] achieved this work in Germany with the formulation of an N-mixture model from acoustic surveys at WT nacelles. This allowed the prediction of bat fatalities from acoustic monitoring data at the WT nacelle. The same undertaking has to be done before and after the wind farm installation in order to predict bat fatalities from pre-construction acoustic surveys. This has been attempted by [START_REF] Hein | Relating pre-construction bat activity and postconstruction bat fatality to predict risk at wind energy facilities: a synthesis[END_REF] but the relationship between both variables was not conclusive. It will be greatly improved if the data collection methods are standardised and if precision in bat species identification is enhanced.

Applications of the collision susceptibility index

Finally, the creation of an index for species susceptibility to WT collisions, independently of their abundance, is an important achievement for the objectivity of impact assessment studies. The latter need this index in order to assess a local susceptibility to collisions, using additional information such as local activity level recorded from the ground and site function (e.g. presence of roost, presence of foraging activity). Unless bat flight height distribution is significantly different from one geographical region to anotherwhich remains to be studiedthis index could potentially be used in studies from any European region where those species are extant. But this index neglects possible variations in flight behaviour across locations, that can be assessed with recordings from wind masts. Our results indeed support that studying bat acoustic activity on a wind mast is a powerful method to assess impacts prior to the settlement of wind farms.

Variability of flight height

Abiotic and biotic factors, such as wind speed, insect concentrations, or vegetation height are known to influence bats flying heights (e.g. [START_REF] Menzel | Effect of habitat and foraging height on bat activity in the coastal plain of South Carolina[END_REF][START_REF] Arthur | Les Chauves-souris de France[END_REF][START_REF] Kunz | Ecological impacts of wind energy development on bats: questions, research needs, and hypotheses[END_REF], Rydell et al., 2010). In addition, knowledge about the precise distribution of migration flight routes is missing in the literature. The position of a study site on one of these routes might significantly alter flight heights. While the response of bats to meteorological factors that fluctuate year-round at one study site are easily monitored, very little information exists about the precise influence operated by habitat variables on bat flight altitude. Some studies explored the link between, on one hand, bat mortality and activity, and on the other hand, bat mortality and habitat (e.g. [START_REF] Ferreira | Do habitat characteristics determine mortality risk for bats at wind farms? Modelling susceptible species activity patterns and anticipating possible mortality events[END_REF][START_REF] Johnson | Bat activity, composition, and collision mortality at a large wind plant in Minnesota[END_REF][START_REF] Arnett | Impacts of wind energy development on bats: a global perspective[END_REF]. However, the question of how habitat alters flight height was to our knowledge only addressed by [START_REF] Menzel | Effect of habitat and foraging height on bat activity in the coastal plain of South Carolina[END_REF] on five bat species with one sampling per habitat. Throughout Europe, a multitude of small datasets with similar methodologies are collected each year for the purpose of WT impact assessment studies. Put together, they would offer an excellent opportunity to study this relationship more thoroughly. A3 in the supplementary material. microphone and the activity recorded at the upper microphone where each study site in an observation. NA stands for species that were not observed at height (i.e. Rhinolophus) and for species that were not recorded at more than 15 study sites. Estimates (log (total amount of bat passes at height+1))

Source

height (and respectively at ground) for each species. These estimates were then correlated to species fatality counts.

Table A5: Detail of the proportion of bat passes between microphones at ground and height for the three different biogeographical regions. Species names are the three first letters of the genus and of the species name excepted for small Myotis (Smyo) and large Myotis (Lmyo).

Region

Figure 2 :

 2 Figure 2: Cumulative number of sites surveyed per month for the six study years.

  482

Figure 3 :

 3 Figure 3: Microphone height and median height for all 23 study sites.

Figure 4 :

 4 Figure 4 : Ratio of time spent at height for each species. Predicted rates are calculated from the GLMM output and are available in more details in TableA3in the supplementary material.

Figure 5 :

 5 Figure 5: Ratio of time spent at height in function to susceptibility to WT collision. Spearman correlation coefficient rho = 0.94; p = 4.58e-06. Species names are the three first letters of the genus and of the species name excepted for small Myotis (Smyo) and large Myotis (Lmyo).

Figure A3 :

 A3 FigureA3: Correlation between the raw count of bat carcasses and the estimated species number of bat passes at height (rho = 0.84). We used the same generalised linear mixed model (GLMM) structure as the one described in Material and Methods to estimate the numbers of bat passes at

Table 1 :

 1 Values taken from the literature to calculate a collision susceptibility index to WT. Mean activity at ground and at height microphones correspond to the values of our study sites which contain continuous recordings overnight (i.e. after 2013), for comparison with Actichiro.

	Species Mean	Detection	Number of	Collision	Mean	Mean
	activity	distance	carcasses	susceptibilit	activity	activit
	(Positive	(m)	FR	y index	at	y at
	minutes	(Barataud,	(EUROBATS		groun	height
	of		2015)	, 2015)		d
	activity
	/night)
	(Haquart
	, 2013)
	small Myotis	19.59	15	3	3	2.32	0.02
	R. hipposideros	0.66	5	0	8	0	0
	Plecotus sp.	1.52	23	0	14	0.8	0.01
	R.	0.52	10	0	19	0.04	0
	ferrumequinum
	B. barbastellus	3.21	15	3	19	0.35	0
	M. schreibersii	1.44	30	5	125	0.11	0.02
	large Myotis	0.49	20	4	204	0.11	0.01
	P. pipistrellus	79.85	35	622	273	27.08	5.86
	E. serotinus	3.34	40	23	287	1.28	0.36
	P. kuhlii	9.55	30	130	411	3.48	1.97
	P. pygmaeus	5.93	25	125	532	2.61	0.33
	T. teniotis	0.18	150	1	815	0.02	0.01
	H. savii	1.78	40	36	833	0.2	0.11
	P. nathusii	3.15	35	178	1991	1.36	0.89

Table A2 :

 A2 Data used for estimations of species density. Sampling effort for each of the biogeographical areas in[START_REF] Haquart | Actichiro. Référentiel d'activité des chiroptères : éléments pour l'interprétation des dénombrements de chiroptères avec les méthodes acoustiques en zone méditerranéenne française[END_REF].

		< median height	> median height	Total	Percentage	R²
	Species Ground mic	Ground and height mic	Ground and height mic	Height mic		of bat passes recorded	between ground and
							from ground	height
							mic	mic
	Barbar	4,600	55	1	6	4,662	99.87	0.14
	Eptnil	123	6	5	33	167	80.24	NA
	Eptser	7,631	696	219	768	9,314	91.75	0.39
	Hypsav	666	56	24	135	881	84.68	NA
	Minsch	192	4	9	9	214	95.79	NA
	L Myotis	617	14	3	22	656	96.65	0.55
	S Myotis	8,104	118	3	30	8,255	99.64	0.03
	Nyclas	1	1	3	24	29	17.24	NA
	Nyclei	1,629	353	626	2,684	5,292	49.28	0.85
	Nycnoc	1,298	194	292	445	2,229	80.04	0.80
	Pipkuh 33,454	2,779	491	6,136	42,860	85.68	0.79
	Pipnat	3406	135	90	1,869	5,500	66.02	0.74
	Pippip 207,392	5,029	1,608	22,856 236,885	90.35	0.52
	Pippyg	8,743	66	59	471	9,339	94.96	NA
	Plesp	4,023	44	2	22	4,091	99.46	0.23
	Rhifer	198				198	100	NA
	Rhihip	9				9	100	NA
	Tadten	38	5	21	21	85	75.29	NA
	Vesmur	4	4	16	50	74	32.43	NA
	Biogeographical area Number of	Area (km2) Number of
				sampling			sampling sites
				sites			per 1000 km2
	Alpine			28	30,658		0.91
	Atlantic			768	268,155	2.86
	Continental			169	184,203	0.92
	Mediterranean (Corsica excluded) 752	56,918		13.21

Table A3 :

 A3 Ratio of time spent at height for each species. Predicted rates are calculated from the GLMM output. Standard error for Rhinolophus species could not be estimated (NE) because of the nonexistence of occurrences at height.

	Species GLMM value	Standard	Predicted rate N bat
		error		passes
	R. ferrumequinum -24.30	NE	0	198
	R. hipposideros -22.93	NE	0	9
	B. barbastellus -6.38	3.06	0.002	4,662
	small Myotis -5.94	1.43	0.003	8,255
	Plecotus sp. -5.29	1.67	0.005	4,091
	large Myotis -3.58	1.7	0.027	656
	P. pygmaeus -3.05	0.44	0.045	9,339
	M. schreibersii -2.68	2.04	0.064	214
	P. pipistrellus -2.06	0.23	0.113	236,885
	E. serotinus -1.93	0.36	0.127	9,314
	P. kuhlii -1.41	0.25	0.197	42,860
	H. savii -1.36	0.75	0.205	881
	E. nilsonii -1.18	1.51	0.235	167
	P. nathusii -1.01	0.33	0.267	5,500
	N. noctula -0.30	0.48	0.427	2,229
	T. teniotis -0.12	1.93	0.470	85
	N. leisleri 0.68	0.34	0.664	5,292
	V. bicolor 2.23	3.06	0.903	74
	N. lasiopterus 2.57	6.03	0.929	29

Table A4 :

 A4 Detailed number of bat passes located at ground or at height for all species, before pooling species into groups for further analysis.

	M. mystacinus	48		48
	M. mystacinus/brandtii	6		6
	M. nattereri	781		781
	Small myotis	6,949	30	6,979
	N. lasiopterus	2	27	29
	N. leisleri	1,982	3,310	5,292
	N. noctula	1,492	737	2,229
	P. kuhlii/nathusii	6,256	1,114	7,370
	P. kuhlii	36,233	6,627	42,860
	P. nathusii	3,541	1,959	5,500
	P. pipistrellus	212,421	24,464	236,885
	P. pygmaeus	8,809	530	9,339
	Plecotus sp.	3,582	17	3,599
	P. auritus	382	3	385
	P. austriacus	99	1	100
	R. ferrumequinum	198		198
	R. hipposideros	9		9
	T. teniotis	43	42	85
	V. murinus	8	66	74
	Total	299,461	41,336	340,797
	Species Ground	Height	Total
	B. barbastellus	4,655	7	4,662
	Chiroptera sp.	317	73	390
	Eptesicus/Nyctalus/Vespertillio sp.	1,205	1,101	2,306
	E. nilssonii	129	38	167
	E. serotinus	8,327	987	9,314
	H. savii	722	159	881
	M. schreibersii	196	18	214
	M. alcathoe	1		1
	M. bechsteinii	150		150
	M. brandtii	9		9
	M. capaccinii	1		1
	M. dasycneme	3		3
	M. dasycneme (probable)		1	1
	M. daubentonii	236	2	238
	M. emmarginatus	38		38
	Large Myotis	631	25	656

Acknowledgments

The present work was a collaboration between Biotope and the Muséum national d'Histoire naturelle in the form of a PhD thesis funded by Biotope and the Association Nationale de la Recherche et de la Technologie. We would like to thank EUROBATS and all the contributors for providing mortality data and Alexandre Haquart for his remarkable work developing Actichiro, and for advising us for this study. We would also like to thank Sébastien Devos, Marie-Lilith Patou, Julien Mérot, Alexandre Haquart, Julien Tranchard, Philippe Ferragne, Matthieu Guyot, Antonin Dhellemme and Julien Renglet for their important contributions to equipment design and installation, data collection and acoustic analysis.

Conflict of interest

Biotope is an environmental consultancy involved in wind turbine impact assessment studies. Two of the authors, Charlotte Roemer and Thierry Disca, were employees at Biotope at the time of submission. Yves Bas was an employee at Biotope until March 2014. Authors thus declare a direct conflict of interest according to Elsevier ethics. However, all data used to calculate bat susceptibility to wind turbines were taken from the literature and are completely independent from Biotope's activities and clients. Authors furthermore take complete responsibility for the integrity of the data related to flight behaviour and the accuracy of their analysis.

Supplementary material