C Heiniger

S Barot

J F Ponge

S Salmon

L Botton-Divet

D Carmignac

F Dubs

Effect of habitat spatiotemporal structure on collembolan diversity 1

Keywords: Landscape structure and dynamics, collembolan diversity, colonization credit, patch age, 8 patch isolation, forest vs. agriculture. 9

Landscape fragmentation is a major threat to biodiversity. It results in the transformation of 11 continuous (hence large) habitat patches into isolated (hence smaller) patches, embedded in a matrix 12 of another habitat type. Many populations are harmed by fragmentation because remnant patches do 13 not fulfil their ecological and demographic requirements. In turn, this leads to a loss of biodiversity, 14 especially if species have poor dispersal abilities. Moreover, landscape fragmentation is a dynamic 15

process in which patches can be converted from one type of habitat to another. A recently created 16 habitat might suffer from a reduced biodiversity because of the absence of adapted species that need a 17 certain amount of time to colonize the new patch (e.g. direct metapopulation effect). Thus landscape 18 dynamics leads to complex habitat spatiotemporal structure, in which each patch is more or less 19 continuous in space and time. In this study, we define habitat spatial structure as the degree to which a 20 habitat is isolated from another habitat of the same kind and temporal structure as the time since the 21 habitat is in place. Patches can also display reduced biodiversity because their spatial or temporal 22 structures are correlated with habitat quality (e.g. indirect effects). We discriminated direct meta-23 community effects from indirect (habitat quality) effects of the spatiotemporal structure of habitats on 24 biodiversity using Collembola as a model. We tested the relative importance of spatial and temporal 1. Introduction 36 Habitat fragmentation is well known to be a major threat to biodiversity in many 37 macroorganisms [START_REF] Saunders | Biological consequences of ecosystem 836 fragmentation: a review[END_REF][START_REF] Tilman | Competition and Biodiversity in spatially structured habitats[END_REF][START_REF] Tilman | Habitat destruction and the extinction 871 debt[END_REF][START_REF] Finlay | Global diversity and body size[END_REF]38 Stratford and Stouffer, 1999;[START_REF] Cushman | Effects of habitat loss and fragmentation on amphibians: a review and 692 prospectus[END_REF][START_REF] Mapelli | Influence of patch and landscape characteristics on the distribution 784 of the subterranean rodent Ctenomys porteousi[END_REF][START_REF] Krauss | Habitat fragmentation causes immediate and 765 time-delayed biodiversity loss at different trophic levels[END_REF]. 39 Biodiversity is not only driven by local environmental conditions, but also by spatial processes 40 [START_REF] Hanski | Patch-occupancy dynamics in fragmented landscapes[END_REF][START_REF] Ettema | Spatial soil ecology[END_REF][START_REF] Holyoak | Metacommunities: Spatial Dynamics and Ecological 750 Communities[END_REF]. It is now largely recognized that 41 ecological processes shaping communities occur at least at two distinct organisation levels (Shmida 42 and Wilson, 1985;[START_REF] Ricklefs | Community diversity: relative roles of local and regional processes[END_REF][START_REF] Wardle | The influence of biotic interactions on soil biodiversity[END_REF]. (1) Regional processes occur since habitats within a 43 landscape are interconnected by dispersal, which gives birth to meta-community dynamics (Gilpin and 44 Hanski, 1991;[START_REF] Hubbell | The Unified Neutral Theory of Biodiversity and Biogeography[END_REF][START_REF] Leibold | The metacommunity 773 concept: a framework for multi-scale community ecology[END_REF]). At regional scale, an increase in habitat spatial 45 connectivity increases the probability of a species to reach an unoccupied habitat and thus may 46 enhance local diversity [START_REF] Bailey | Increasing connectivity in fragmented landscapes: an investigation of evidence for 649 biodiversity gain in woodlands[END_REF][START_REF] Brückmann | Butterfly and plant specialists suffer from 671 reduced connectivity in fragmented landscapes[END_REF]. [START_REF]dashed bars and recent, white bars) and Spatial Isolation (three isolation[END_REF] Local factors such as 47 environmental conditions and competition between organisms act as filters enabling species to 48 maintain a viable population in a patch of habitat [START_REF] Decaëns | Niche overlap and 703 species assemblage dynamics in an ageing pasture gradient in north-western France[END_REF][START_REF] Petit | Patterns of weed co-occurence at the field and landscape level[END_REF] and thus 49 reduce local diversity. Within this framework, patches are defined as spatial units of habitat differing 50 from the surrounding area [START_REF] Forman | Landscape Ecology[END_REF]. Even though patches may display an internal 51 heterogeneity at finer scale, e.g. microhabitat [START_REF] Leibold | The metacommunity 773 concept: a framework for multi-scale community ecology[END_REF], they contain a single type of 52 4 diversity in oilseed rape fields (i.e. in agricultural habitats). In this case, species are thought to express 81 preferences for different habitat types so that regional (gamma) diversity is increased by habitat 82 heterogeneity [START_REF] Vanbergen | Scale-specific correlations between habitat heterogeneity and 874 soil fauna diversity along a landscape structure gradient[END_REF]. Since these preferences are not strict, and species move 83 between patches, habitat heterogeneity in the neighbouring landscape would also increase diversity at 84 patch scale (alpha diversity). These results suggest that it is difficult to predict a priori the impact of 85 habitat isolation on local (alpha) species diversity and that this impact depends on the ecosystem under 86 investigation. Here, we compare the effect of patch isolation in two broad habitat types, open vs. 87 closed vegetation, within the same landscape. 88

Most empirical studies on metacommunity dynamics assume that local communities have 89 reached equilibrium at sampling time. However some authors suggested that the time elapsed, since 90 the first species successfully colonized a patch of habitat, is essential for the understanding of 91 observed diversity patterns [START_REF] Mouquet | Community assembly time and the 790 relationship between local and regional species richness[END_REF]. These authors assume that communities at the first 92 stages of the assembly process are unsaturated because only a subset of the regional species pool has 93 yet been able to colonize the patch. Besides spatial structure, patch temporal structure may thus also 94 influence collembolan alpha diversity. Ponge et al. (2006) showed that landscape heterogeneity may 95 come with a more dynamic patch temporal structure. They suggest that regions that include more 96 diverse habitat types may also include more patches of habitat that have experienced a recent change 97 in land use (e.g. patches that switched from forest to agriculture or the reverse, and thus are not 98 continuous through time). This may have subsequently reduced collembolan diversity at patch scale 99 (alpha diversity). In this sense, the lack of diversity observed in most heterogeneous landscape might 100 be due to patch history, i.e. to temporal discontinuity, rather than to patch spatial structure, i.e. 101

fragmentation. 102

Another source of complexity for understanding the influence of habitat structure on diversity 103 patterns is that patch characteristics (age, spatial isolation, land use type) may influence local 104 communities either directly or indirectly. They directly impact local communities through their effect 105 on meta-community dynamics [START_REF] Driscoll | Spatial dynamics of the knob-tailed gecko 706 Nephrurus stellatus in a fragmented agricultural landscape[END_REF]. Patch characteristics may also impact 106 communities through complex links between landscape dynamics and local environmental properties 107 [START_REF] Wu | From balance of nature to hierarchical patch dynamics: a paradigm shift 886 in ecology[END_REF]. For example, isolation and age of a patch can impact local microclimatic 108 conditions [START_REF] Saunders | Biological consequences of ecosystem 836 fragmentation: a review[END_REF][START_REF] Magura | Diversity and composition of carabids during a forestry 782 cycle[END_REF], and increased edge effects in isolated patches 109 can be responsible for changes in soil properties. In this case, patch spatial structure would be 110 responsible for changes in local conditions which would consequently affect local (alpha) diversity 111 (e.g. indirect effect). Conversely, pre-existing local conditions may impact land use changes (e.g. if the 112 forest soil is fertile, the forest is more likely to be turned into a field). Such direct and indirect effects 113 must be disentangled to determine the effects of landscape structure on local communities. 114

In the present study, we intend to disentangle the relative effects of spatial vs. temporal 115 continuity of habitats on collembolan alpha diversity in both agricultural and forest habitats. We will 116 assess the effect on diversity of 1) temporal continuity of habitats (temporal structure), 2) spatial 117 isolation of habitats (spatial structure), 3) interaction of temporal and spatial habitat structures, 4) local 118 environmental conditions (land use and soil) and whether they depend on habitat spatiotemporal 119 structure (indirect effect), and 5) forest and agricultural habitats. 120

According to the rationale above (Ponge et al., 2006), we expect (H1) stable habitats (i.e. old 121 or temporally continuous patches) to support a higher alpha diversity than habitats that have been 122 disturbed in the past decades (i.e. recent or temporally discontinuous patches). Besides being 123 considered as stable habitats, forests display a wider variety of niches than agricultural land due to the 124 quality of their soils and humus: forests have a well-developed humus layer (often including 125 fragmented OF horizons and sometimes humified OH horizons) that is absent in open or agricultural 126 habitat [START_REF] Hågvar | Collembola in Norwegian coniferous forest soils. II. Vertical distribution[END_REF][START_REF] Ponge | Vertical dsitribution of Collembola (Hexapoda) and their food resources in organic 800 horizons of beech forests[END_REF]. Additionally, soil carbon content and moisture are higher in 127 forest than in agricultural habitats [START_REF] Batlle-Aguilar | Modelling soil carbon and nitrogen 651 cycles during land use change. A review[END_REF], thereby favouring Collembola given 128 the well-known requirements of these animals in water and organic matter [START_REF] Hopkin | Biology of the Springtails (Insecta: Collembola)[END_REF]. We thus 129 expect (H2) to find a higher diversity and a higher abundance of Collembola in forested habitats. We 130 think that vegetation structure in agricultural habitats makes dispersal easier than in forests because 131 passive dispersal vectors such as wind are more efficient in open than in closed vegetation (Morecroft 132 et al., 1998). We thus expect (H3) that spatiotemporal continuity will have a lower effect in 133 agricultural habitats when compared to forests. 134

Material and methods 135

Study site 136

Sampling took place in the northern part of the Morvan Regional Natural Park (Burgundy,137 Center-East France). The study area is located in the northern part of the Park (523 6000 -525 2000 138 N, 573 800 -588 800 E ; WGS84, UTM 31N) and represents an area of 16 x 15 km. The climate is 139 submontane-atlantic with continental influence (mean annual rainfall 1000 mm and mean temperature 140 9°C). The bedrock is made of granite and soils are mostly acidic (Cambisols, IUSS Working Group 141 WRB 2006). We selected this region because it displays diverse habitat spatiotemporal structures and 142 relatively homogeneous soil conditions among all habitat of the same type. The region is rural, with 143 intensive to extensive agriculture (55%) and forestry (45%). From the beginning of the twentieth 144 century Douglas fir [Pseudotsuga menziesii Mirbel (Franco)] and Norway spruce [Picea abies (L.) 145

Karst.] have been intensely planted for saw-wood production and coniferous stands have progressively 146 replaced the formerly dominant deciduous stands. However, large areas of oak [Quercus petraea 147 (Matt.) Liebl.] and beech (Fagus sylvatica L.) forest still subsist. Nowadays, agricultural areas consist 148 of permanent pastures (40%), hay meadows (40%) and crops (20%). Forested areas are comprised of 149 planted coniferous stands (45%) and deciduous stands (mostly Ilici-Fagenion) (55%). In this region, 150 the landscape has experienced a dynamic period (1962 to present) due to agricultural abandonment 151 and European subsidies that encouraged farmers to convert meadows into plantation forests. This 152 afforestation created many recent forest patches. 153

Sampling design 154

Our sampling design was comprised of 60 sites (28 forested and 32 agricultural) classified in 155 12 combinations of three habitat descriptors: habitat type (HT), temporal continuity (TC) and spatial 156 isolation (SI). For each spatiotemporal combination we sampled 3 to 9 replicates (Appendix A). 157

Habitat type 158

Collembolan communities are likely to depend on the dichotomy between open and closed 159 vegetation [START_REF] Ponge | Collembolan 811 communities as bioindicators of land use intensification[END_REF][START_REF] Vanbergen | Scale-specific correlations between habitat heterogeneity and 874 soil fauna diversity along a landscape structure gradient[END_REF]. Hence we decided to split the landscape into 160 two major habitat types: forest and agricultural land. Thus, sampled sites can either be meadows, 161 pastures, crops, or Christmas tree plantations for agricultural habitats and coniferous or deciduous 162 stands for forest habitats (Appendix A). Christmas tree plantations might at first be thought as forest 163 habitats. However, they display many characteristics of agricultural habitats: absence of litter and 164 developed humus profiles (due to low stature and density of Christmas trees), use of ploughing and 165 pesticides, i.e. same characteristics as agricultural land. They are generally constituted by no more 166 than five-year-old trees and have been shown to support collembolan communities typical of 167 agricultural habitats [START_REF] Ponge | Collembolan 811 communities as bioindicators of land use intensification[END_REF]. It is well known that the transition from deciduous to 168 coniferous stands implies an abrupt change in soil physicochemical properties (pH, humus form, etc.) 169 [START_REF] Gauquelin | Physico-chemical heterogeneity of superficial soil 725 layers in conifer plantations versus original broad leaf forests in Ariege (Pyrenees, France)[END_REF][START_REF] Augusto | Effects of tree species on understory vegetation and 647 environmental conditions in temperate forests[END_REF]. However, [START_REF] Ponge | Collembolan 811 communities as bioindicators of land use intensification[END_REF] showed that in the 170 Morvan region, collembolan communities do not differ between coniferous and deciduous stands, 171 contrary to often-reported detrimental effects of coniferous plantations, mostly ascribed to changes in 172 humus form and soil acidity [START_REF] Cassagne | Changes in humus properties and 676 collembolan communities following the replanting of beech forests with spruce[END_REF][START_REF] Hasegawa | Collembolan community in broad-leaved forests and in conifer stands of 743 Cryptomeria japonica in Central Japan[END_REF]. In any case, collembolan 173 communities of both forest types differ less from each other than they differ from agricultural 174 communities. The absence of pronounced reaction of collembolan communities to tree species 175 composition was also observed in similar acidic soil conditions in Germany (Salamon and Alphei, 176 2009). This is explained by the fact that on acidic bedrocks of the studied region, similar humus forms 177 with thick litter layers and strong soil acidity (moder) develop under both stand types (Ponge et al. 178 1993). It has been shown that Collembola mostly feed on microorganisms and animal faeces and 179 rarely consume directly leaves or needles [START_REF] Ponge | Food resources and diets of soil animals in a small area of Scots pine litter[END_REF][START_REF] Caner | Origin of the 673 nitrogen assimilated by soil fauna living in decomposing beech litter[END_REF]. As such, they are most of 180 all influenced by humus forms whatever the composition of forest canopies [START_REF] Ponge | Biocenoses of Collembola in atlantic temperate grass-woodland ecosystems[END_REF]. 181

Additionally, coniferous tree species planted in the Morvan region (Douglas fir, silver fir and more 182 rarely Norway spruce) have a more nutrient rich litter and do not acidify the soil to the same extent as 183 pines [START_REF] Augusto | Effects of tree species on understory vegetation and 647 environmental conditions in temperate forests[END_REF]. This allowed us to group both forest types into a single broader category. 184

We avoided sampling in special habitats such as humid areas or clear-cuts so as to minimize the 185 influence of particular environmental conditions within forests and agricultural land. 186

Habitat temporal continuity 187

In order to assess the temporal continuity of each habitat within the focus area, we 188 implemented a dynamic cartography (i.e. picturing both spatial and temporal continuity) using aerial 189 photographs. In total, about two hundred aerial photographs (IGN, France) Using the previously mentioned cartography, we selected sampling points in both habitat types 201 (agriculture and forest) and habitat temporal continuity classes (recent and old) and then categorized 202 the landscape mosaic in a buffer zone of 300 m radius around sampling points (Appendix A). Two 203 parameters were considered to define habitat spatial isolation: edge contrast and dominant age of the 204 matrix. Edge contrast measures the magnitude of the difference between adjacent habitat types. It is 205 calculated as the percent edge of the habitat (containing the sampling point) shared with an opposite 206 habitat within a 300 m radius. Opposite habitat was forest for agricultural land and vice versa. Of 207 course, edge contrast is nil or close to nil for isolation class 0. The matrix was defined by the 208 proportion of the dominant habitat type of a given age which occupies the matrix around the sampling 209 point. 210

Isolation class 0 was comprised of large continuous habitats, i.e. larger than the scale of 211 observation around the sampling point (the 300 m buffer zone). Thus sampling points of isolation class 212 0 (whether in recent or old habitat) were entirely included in a matrix made of the same type of habitat 213 300 m around it (except for one recent forest patch that shared 11% of its edge with an old agricultural 214 patch). The matrix surrounding sampling points of isolation class 0 was mostly old (continuous or 215 non-isolated spatial structure). 216

For isolation classes 1, criteria of spatial isolation slightly differed between forest and 217 agricultural habitats. Agricultural patches of isolation class 1 shared a single edge with an old forest. 218

The matrix surrounding them was mostly comprised of old (and less frequently recent) forest habitats. 219 Forest patches of isolation class 1 corresponded to a particular situation that we repeatedly found in 220 the studied region, e.g. some remnant forest patches in place since 1948 (i.e. old) that have been 221

reconnected by a (recent) forest patch to another old forest patch since the last 30-40 years. Old forests 222 of isolation class 1 shared 25 to 83 % of their edge with an old agricultural land and the rest with a 223 recent forest. Recent forests of isolation class 1 were the "reconnecting patches", sharing 19 to 69% of 224 their edge with an old agricultural land and the rest with an old forest. The matrix surrounding 225 sampling points of isolation class 1 was comprised of old and recent habitats. 226

For isolation class 2, spatial isolation also slightly differed between forest and agricultural 227 habitats. Forest patches of isolation class 2 were remnant patches, entirely surrounded by an old 228 agricultural matrix. They have been completely isolated since they are in place. Old and recent 229 agricultural patches of isolation class 2 shared respectively 60 to 100 % and 45 to 80% of their edge 230 with a forest. The matrix surrounding agricultural patches of isolation class 2 was mostly old. Isolation 231 class 1 was considered to be less isolated than isolation class 2 because with the appearance of recent 232 habitats in the surrounding matrix of isolation class 1, some newly created habitats were of the same 233 type as the one located at the sampling point, originating in a less isolated context. 234

In forests as well as in agricultural land, patches of isolation classes 1 and 2 were sampled at 235 least 10 m (but no more than 50 m) away from the opposite habitat type edge. 236

Collection of fauna and soil data 237

Sampling took place from June 27 to July 9, 2010. Each site was sampled for litter/soil 238 mesofauna using a cylindrical soil corer (5 cm diameter x 7 cm depth, one sample at each sampling 239 site). We thus sampled exactly the same volume of soil at each site, meaning that values of species 240 density, i.e. the number of species per unit area sensu [START_REF] Gotelli | Quantifying biodiversity: procedures and pitfalls in the 734 measurement and comparison of species richness[END_REF] here presented 241 correspond to the number of species found over 0.2 dm². Litter/soil were brought back to the 242 laboratory within a week and placed in a Berlese dry-funnel extractor for 10 days. Animals were 243 collected and stored in 70% ethyl alcohol until identification. Collembola were mounted, cleared in 244 chloral-lactophenol and identified to species level under a light microscope (400x magnification), 245 according to [START_REF] Hopkin | A Key to Collembola (Springtails) of Britain and Ireland[END_REF]), Potapow (2001), Thibaud et al. (2004) and [START_REF] Bretfeld | Synopses on Palaearctic Collembola, II Symphypleona[END_REF]. A list of 246 species is given in Appendix B. 247 We also sampled soils (organo mineral horizon, between 0 and 10 cm) in each site in order to 248 characterize soil physicochemical properties at each sampling site. Three samples were taken around 249 soil fauna samples and were pooled together. Soils were air-dried and sieved to 2 mm before 250 measuring total carbon (Ctot) and total nitrogen (Ntot) contents (gas chromatography), pH (H 2 O), 251 bioavailable phosphorus (Olsen method) and cation exchange capacity (CEC). Additionally, the top 252 five soil centimetres were sampled using a Burger cylinder (0.1 L volume) and immediately packed in 253 waterproof bags in order to determine soil moisture and bulk density. The humus form was 254 characterized according to [START_REF] Brêthes | Classification of forest humus forms: 669 a french proposal[END_REF] and the Humus index was calculated according to 255 [START_REF] Ponge | Humus index: an integrated tool for the assessment of 806 forest floor and topsoil properties[END_REF], and was used as a proxy of litter amount and recalcitrance to decay (Ponge et al., 256 1997;[START_REF] Ponge | Humus Index as an indicator of forest stand and soil properties[END_REF]. 257

Statistical analyses 258

The following diversity indicators were calculated for each site: species density (sensu Gotelli 259 and Colwell, 2001), i.e. the actual number of species found in each sample, species richness (sensu 260 [START_REF] Gotelli | Quantifying biodiversity: procedures and pitfalls in the 734 measurement and comparison of species richness[END_REF] i.e. the local number of species estimated to be found in a smaller sample 261 containing 25 % of the mean individual density (i.e. 57 individuals), Shannon index, dominance 262 (relative frequency of the most abundant species), and abundance (total number of individuals). 263

These diversity indicators were analysed using linear models (type III sums of squares used 264 for unbalanced design and because significant interactions were expected, see Appendix B), testing for 265 habitat type (HT), spatial isolation (SI), and temporal continuity (TC) effects as well as effects of all 266 interactions between these factors. To fulfil linear model assumptions, dominance had to be log-267 transformed. In order to detect possible effects of habitat spatiotemporal structure (regional factors) on 268 its soil quality that could influence diversity indicators, we tested the effect of habitat descriptors on 269 soil physicochemical properties. Most of natural or log-transformed data fulfilled the assumptions of 270 linear models. When this was not the case, we used generalized linear models with a Gamma link 271 function or a Poisson link function. All possible correlations (Pearson) between diversity indicators 272 and soil properties were calculated and tested. We also calculated and tested these correlations in both 273 habitat types separately. 274

Finally, we constructed complete linear models, testing the effects of the three habitat 275 descriptors on diversity indicators and including most important soil parameters as covariates, together 276 with all their interactions. Since there are many combinations of habitat descriptors and many soil 277 parameters it was not possible to include all of them and their interactions in a single model. Therefore 278 we focussed our analysis on the two soil parameters that were the most correlated with diversity and/or 279 that were significantly affected by habitat descriptors, i.e. Ctot and pH. These two variables can be 280 considered as proxies for two main physico-chemical factors which impact collembolan communities 281 at two different scales (species or community): Ctot is a proxy for general habitat and resource 282 availability and thus determines the total abundance; and pH is a proxy for local environmental filter 283 which selects species within communities, since several collembolan species are only adapted to low 284 or high soil acidity [START_REF] Ponge | Biocenoses of Collembola in atlantic temperate grass-woodland ecosystems[END_REF][START_REF] Salmon | The impact of earthworms on the abundance of Collembola: improvement of food 832 resources or of habitat?[END_REF]. We analysed two models testing separately for the 285 effect of these two variables, the three habitat descriptors and all their interactions (two-, three-and 286 four-way interactions). Simple effects of variables and interactions that were kept in each final model 287 were selected using an automatic selection procedure based on AIC (procedure step, with backward 288 direction, [START_REF] Bodzogan | Model selection and Akaike's Information Criterion (AIC)! The general theory 661 and its analytical extensions[END_REF][START_REF] Posada | Model selection and model averaging in phylogenetics: advantages 816 of Akaike Information Criterion and Bayesian approaches over likelihood ratio tests[END_REF]. Combinations of habitat descriptors were 289 compared using least square means and associated multiple comparisons of means (Tukey). All 290 statistical analyses were performed using Mass, car, vegan and Lsmeans packages of R software (R 291 Development Core Team, 2010). 292

Altogether, these analyses enabled us to discriminate between direct and indirect effects. The 293 first type of models (testing the effect of the three habitat descriptors on diversity indicators) includes 294 both direct and indirect effects of spatiotemporal structure. If the second type of models (testing the 295 effect of the three habitat descriptors on soil properties) reveals significant effects, it means that 296 indirect effects are likely to occur. Even if they do not, little differences in soil properties between 297 habitat spatiotemporal structures could still slightly influence collembolan diversity. This is why we 298 constructed a third type of models, testing for the effect of the three habitat descriptors on diversity 299 and including an influential soil property in the same model. If simple effects of habitat descriptors are 300 significant, it means that they have a direct effect on diversity. However, if simple effects of soil 301 properties are significant, indirect effects are occurring. The comparison of the first and third types of 302 models enabled us to assess whether direct or indirect effects were occurring or if both effects were 303 present at the same time (Fig. 1). 304

Results 305

Effects of the three habitat descriptors on collembolan diversity 306

In total, 6339 individuals were identified to 70 species. We found 3639 from 57 species in 307 forest and 2700 individuals from 39 species in agricultural habitats. In forests, 44 species were found 308 in old sites and 42 in recent sites. In agricultural land, 36 species were found in old sites and 24 309 species in recent sites. Thirteen species were present in recent forests but not in old forests and 15 310 species were present in old forests and not in recent forest. In agricultural sites, 15 species were 311 present in old but not in recent sites and only 3 species not present in old sites were found in recent 312 sites. Rarefaction curves (Fig. 2) showed that our sampling was nearly exhaustive for both habitat 313 types whatever old or recent, and that forests (both recent and old) harbored more species in total 314 (gamma diversity) than agricultural land (old > recent). Statistical models implemented on diversity 315 indicators (Model type 1 in Fig. 1, Table 1) showed that habitat type (HT) exerted an effect on species 316 density, species richness and total abundance. Species density, species richness as well as abundance 317 of Collembola were higher in forest compared to agricultural habitats (on average respectively 11.4 318 versus 8.6 for species density and 9.1 versus 7.9 for species richness). However, no effect of HT was 319 detected either on Shannon index or on dominance. Furthermore, only Shannon index, species richness 320 and species density responded to habitat temporal continuity (TC), old habitats showing higher values 321 than recent habitats (on average 10.8 versus 9.3 for species density, 1.8 versus 1.6 for Shannon index, 322 and 9.1 versus 7.5 for species richness). Multiple comparisons among means (Tukey) showed that this 323 effect was mainly due to differences between old and recent forests (on average respectively 13.1 and 324 9.4 for species density, 1.9 and 1.5 for Shannon index, and 10.2 versus 7.9 for species richness), 325 whereas old and recent agricultural lands showed closer values (on average respectively 9.1 versus 7.7 326 for species density, 1.7 versus 1.5 for Shannon index, and 8.3 versus 7.1 for species richness) (Fig. 3). 327

Both coniferous and deciduous forests displayed significantly lower values for species density, species 328 richness and Shannon index in the recent age class compared to the old one (data not shown). We did 329 not detect any effects of spatial isolation (SI) on diversity indicators, either in forest or in agricultural 330 habitats, and no interaction between habitat descriptors (Fig. 4). 331

Effects of the three habitat descriptors on soil characteristics 332

Most soil properties were significantly different according to HT. Models testing the effect of 333 HT on soil properties showed that CEC, Ctot, C:N and Humus index had significantly higher values in 334 forest than in agricultural habitats, whereas soil density, soil moisture and pH showed opposite trends 335 (Model type 2 in Fig. 1, Tables 2 and3). On the other hand, only a few of them, i.e. pH, P and C:N, 336 responded to the two other habitat descriptors (SI and TC). Soil pH, bioavailable phosphorus, and 337 carbon to nitrogen ratio (C:N) showed differences between isolation classes. Soil pH was higher in 338 isolation class 1 (on average 4.3) than in isolation classes 0 and 2 (on average respectively 3.7 and 339 3.8), but only in forest patches, resulting in a significant interaction between HT and SI. Bioavailable 340 phosphorus content was higher in isolation class 2 than in isolation classes 0 and 1 (on average 341 respectively 74, 55 and 44 mg/kg). Only C:N was significantly impacted by TC and was higher in old 342 habitats than in recent ones. Moreover, for C:N, many interactions between habitat descriptors were 343 significant (Table 3). Multiple mean comparisons showed that these effects were mostly due to non-344 isolated old forest habitats (isolation class 0) that showed significantly higher values (on average 20.6) 345 than every other forest habitats whatever their SI or TC (in old habitats: isolation 1, 15.8; isolation 2, 346 16; in recent habitats: isolation 0, 14.5; isolation 1, 14.3; isolation 2, 13.8). In agricultural land, no 347 effect of the spatiotemporal descriptors on C:N was detected.

Effects of the three habitat descriptors and soil characteristics on collembolan diversity 349

When implemented on data from both forest and agricultural habitats, no correlations between 350 Shannon index and soil properties were significant (Fig 5). On the other hand, many correlations 351 between species density and soil properties were significant at 5% level. Species density was 352 positively correlated with CEC, Ctot, C:N and Humus Index (0.37; 0.38; 0.43 and 0.44, respectively) 353 and negatively correlated with bulk density and pH (-0.3 and -0.38, respectively) (Fig 5). Only 354 positive correlations between species richness and Ctot, C:N, CEC and Humus index (respectively 355 0.30, 0.27, 0.28 and 0.33) were observed. However, most of these correlations reflected the above-356 mentioned differences in soil properties between forest and agricultural habitats. When implemented 357 separately in the two HTs no correlations with species density, species richness or Shannon index were 358 significant in agricultural habitats. In forests, only Ctot, C:N (0.4 and 0.44, respectively) and pH (-359 0.39) were significantly correlated to species density and only C:N was significantly correlated to 360 species richness (0.40), but none were correlated to the Shannon index (Fig. 5). 361

As C:N was highly correlated with both Ctot and pH (0.61, p<0.0001 and -0.69, p<0.0001 362 respectively), while Ctot and pH were also correlated (0.43, p < 0.001) but to a lesser extent than to 363 C:N, we decided to include only Ctot and pH as covariates in two distinct global linear models testing 364 their effect and that of habitat descriptors on species density, species richness and Shannon index and 365 we implemented a procedure of automatic selection based on AIC. Both models (Ctot and pH) did not 366 detect any significant effect of any variable on the Shannon index. Table 4 displays the results of 367 models analyzing the effects of habitat descriptors and either Ctot or pH on species density and species 368 richness. The Ctot models showed that there was no simple effect of habitat descriptors either on 369 species density or on species richness, whereas pH models showed significant effects of HT and TC 370 on species density and of TC on species richness. Additionally, pH and Ctot models revealed the effect 371 of several significant interactions. The pH model showed significant effects of the interactions 372 between HT and TC, between HT and SI and between TC and SI on species density. The Ctot models 373 showed the effect of interactions between HT and SI on species density, and between TC and SI on 374 both species density and species richness. Indeed, least square means for species density comparison 375 (Fig. 6a) obtained with the Ctot model showed no difference between both HTs in non-isolated 376 habitats (isolated class 0) whereas it showed significantly higher values in forest than in agriculture in 377 isolation classes 1 and 2. Moreover, comparisons of least square means for species density showed 378 significantly higher values in old than in recent patches for the isolation classes 1 and 2, while it 379 showed no difference between age classes for the continuous habitats (Fig. 6b). Similarly, least square 380 means for species richness comparison showed significantly higher values in old than in recent patches 381 for the isolation class 2, while it showed no difference between age classes for habitats of isolation 382 class 0 and 1 (Fig. 6c). Soil pH and Ctot did not have a significant effect on their own, neither on 383 species density nor on species richness. The Ctot had significant effects in interaction with HT, and 384 TC on species density. According to estimated model parameters, species density increased more with 385

Ctot in old than in recent habitats. It also increased more with Ctot in forest than in agricultural land. 386

The soil pH had significant effects in interaction with HT, TC and SI on species density and in 387 interaction with TC on species richness. Species density decreased with the pH in forests whereas it 388 increased with the pH in agricultural habitats. Species density and species richness also decreased with 389 the pH in old habitats whereas it did not change according to pH in recent habitats. 390

Discussion 391

Effects of habitat temporal continuity on collembolan diversity 392

The total number of species (gamma diversity) was higher in old than in recent forests. 393 Species present in recent forests and not in old ones were all rare species (i.e. found in less than 10% 394 of the records), except for 3 species (Isotoma viridis, Lepidocyrtus cyaneus and Lepidocyrtus 395 lignorum). These species are known as agricultural-preferring species in the studied region (Ponge et 396 al., 2003(Ponge et 396 al., , 2006)). Furthermore, they were found exclusively in isolation classes 1 and 2. Thus it is 397 difficult to know whether they were present as relics of the past HT (i.e. agricultural land) or if they 398 colonized forest patches from the neighboring agricultural matrix. However, the fact they were not 399 present in the equivalent isolation class of old forests suggests that they beneficiated from the presence 400 of a non-saturated community in recent forests. Indeed, the fact that all niches were not necessarily 401 occupied in recent forests was certainly in favor of the persistence of agricultural-preferring species: 402 these species might colonize spatially isolated patches but would not be able to persist in the more 403 diverse communities present in old forests of comparable spatial isolation. In agricultural land, the 404 total number of species was also higher in old than in recent sites. Only three species present in recent 405 sites were absent in old ones. Among the 15 species that were present in old but not in recent sites, 406 only three were common species (i.e. present in more than 10% of the records) and no common 407 species were found in recent but not in old agricultural sites. This shows that even in open habitats 408 such as agricultural land, the total number of species was reduced in recently created habitats. It is still 409 difficult to draw any conclusion on differences in the number of rare species, but the fact that some 410 common species were lacking in recent sites only, allows us to conclude that this absence is due to the 411 temporal continuity of the habitat and not to some random mechanism. 412

Our results show that habitat temporal discontinuity impacts negatively species density, 413 species richness and Shannon index but not the total abundance of Collembola. For a similar number 414 of individuals, recent habitats showed fewer species than old habitats whatever the habitat type or the 415 spatial continuity. This suggests that resources not taken by species still lacking in recent habitats are 416 used by larger populations of existing species. Among the variables under study, only the carbon to 417 nitrogen ratio reacted to temporal continuity, but this was due to the particular situation of spatially 418 continuous (non-isolated) old forests that displayed higher values than every other forest patches 419 whatever their spatiotemporal structure. All other soil properties (humus type, a proxy of litter amount 420 and quality, pH, C, N contents and P availability) were similar in old and recent habitats of the same 421 type, suggesting that habitat temporal continuity has a direct effect on collembolan diversity that does 422 not depend on soil properties. Within the limits of our analytical protocol (we did not study all 423 parameters known to influence Collembola, such as for instance the composition of litter and that of 424 soil microbial communities, nor did we study interactions between Collembola and higher trophic 425 levels) this confirms our first hypothesis (H1) predicting a lower collembolan diversity in recently 426 created habitats. 427

The direct effect of habitat temporal continuity on collembolan diversity is also supported by 428 the fact that both species density and species richness were impacted by temporal continuity in the pH 429 model. This means that habitat temporal discontinuity impacts diversity not only by decreasing the 430 size of the local pool of species (species density) but also by decreasing the number of species that 431 would be present if local soil conditions were strictly similar among all spatiotemporal situations 432 (species richness). This is supported by the fact that the impact of temporal continuity on Shannon 433 index must be considered as a direct effect because this index did not show any significant correlation 434 with soil physicochemical properties. 435 However, the temporal discontinuity of habitat could also be viewed as an index of 436 disturbance. According to the intermediate disturbance hypothesis we could expect recent habitats to 437 host low collembolan diversity, habitats of intermediate age to host a higher biodiversity, and 438 biodiversity to decrease in older habitats because of exclusive competition [START_REF] Connell | Diversity in tropical rain forests and coral reefs[END_REF]Molino and 439 Sabatier, 2001; but see [START_REF] Fox | The intermediate disturbance hypothesis should be abandoned[END_REF]. Our results did not support this general scheme. This might be due 440 to the fact that our study focuses on the landscape scale, so that studied habitat were not homogeneous 441 and host a high diversity of local niches at scales ranging from units to tens square meters (Ponge and 442 Salmon, 2013). Nevertheless, we cannot exclude that habitats older than the ones we studied, might 443 display a decrease in collembolan biodiversity, thus supporting the intermediate disturbance 444 hypothesis. We did not expect old most isolated habitats to display the lowest alpha diversity predicted 445 by metacommunity theories [START_REF] Tilman | Resource Competition and Community Structure[END_REF][START_REF] Hubbell | The Unified Neutral Theory of Biodiversity and Biogeography[END_REF] because the oldest habitats we studied 446 were certainly not old enough to support such patterns. Additionally, within-patch heterogeneity is 447 most likely to prevent collembolan alpha diversity from decreasing to such low levels. 448

Most empirical studies testing the effect of landscape structure on diversity patterns do not 449 take habitat temporal structure into account [START_REF] Mouquet | Community assembly time and the 790 relationship between local and regional species richness[END_REF]. We do not have knowledge of any 450 other study on Collembola that is strictly comparable to ours although collembolan species have been 451

shown to be affected by habitat successional stage [START_REF] Setälä | Influence of micro-habitat and macro-habitat 845 factors on collembolan communities in Douglas-fir Stumps during forest succession[END_REF][START_REF] Loranger | Does soil acidity explain altitudinal 780 sequences in collembolan communities?[END_REF]Scheu et 452 al., 2003;[START_REF] Chauvat | Response of collembolan communities to land-use change 683 and grassland succession[END_REF][START_REF] Salamon | The Collembola community of pure and mixed stands of 830 beech (Fagus sylvatica) and spruce (Picea abies) of different age[END_REF][START_REF] Chauvat | Changes in soil faunal assemblages during 681 conversion from pure to mixed forest stands[END_REF]. While in these studies the 453 observed effects were due both to change in habitat type (succession) and to habitat age (time since the 454 habitat is in place) our results allow us to focus on the effect of habitat age within the same habitat 455 type. Temporally discontinuous (recent) habitats displayed lower diversities due to the poor 456 colonization/dispersal abilities of Collembola: some species were absent from recent habitats not 457 because the habitat was not suitable for them but because they did not have enough time to colonize it. 458

Higher values of the Shannon index in old than in recent habitats support this hypothesis: communities 459 in recent habitats are dominated by fewer species. Coined as colonization credit, this process has been 460 suggested to occur in plant communities (Cristofoli et al., 2010), but has so far been documented by 461 only a few empirical studies on plants [START_REF] Gijbels | An orchid colonization credit in restored calcareous 728 grasslands[END_REF] and butterflies (Cristofoli and Mahy, 462 2010). All these studies showed that specialist species are more affected than generalist species. 463

Effect of habitat spatial isolation on collembolan diversity 464

In this study, we tested two main possible effects of spatial isolation on diversity: the indirect 465 effect of isolation through its effect on environmental conditions and its direct effect through its 466 influence on species likelihood to colonize and persist in a patch. We detected no consistent effect, 467 either direct or indirect, of habitat spatial structure on collembolan diversity, among the two habitat 468 types and the two age classes here compared. 469

Habitat fragmentation is thought to decrease the local diversity of macroorganisms because 470 isolated patches (i) are too small to fulfill ecological and demographic requirements of populations 471 [START_REF] Allouche | Area-heterogeneity 638 tradeoff and the diversity of ecological communities[END_REF], and (ii) are more difficult to colonize [START_REF] Wamser | Trait-specific effects of habitat 879 isolation on carabid species richness and community composition in managed grasslands[END_REF]. We did not find 472 such effect in Collembola. This is probably because our habitat patches were always large enough to 473 fulfill ecological and demographic requirements of all potentially present collembolan species due to 474 the small size of these organisms. [START_REF] Schneider | Microarthropod density and diversity repond little to 841 spatial isolation[END_REF] showed indeed that collembolan populations 475 in patches as small as 50 cm² did not change both in diversity and density within 16 months of 476 isolation. Given that our smallest patch was much larger than this restricted surface, this may explain 477 why spatial discontinuity did not affect collembolan populations in our study. Thus, even if the 478 colonization of isolated patches might be a problem for them (see section 4.3), fragmentation has 479 probably not led to local extinctions, so that colonization is not necessary to maintain diversity. Of 480 course, the connectivity and the size of micro-habitats inside the patches may influence collembolan 481 diversity at micro-site scale [START_REF] Hertzberg | Migration of Collembola in a patchy environment[END_REF]Åstrom and Bengtsson, 2011) but our sampling design 482 does not allow testing this hypothesis. 483

Interacting effects of habitat temporal and spatial structure on diversity 484

Our results showed that spatial and temporal structures of habitats had an interactive effect on 485 local diversity patterns. In the studied region, we showed that species diversity increased with spatial 486 isolation in old habitats whereas it decreased with spatial isolation in recent habitats. This resulted in 487 differences of diversity in isolated habitats while recent and old continuous habitats showed similar 488 values. This suggests that when in place for a long time, isolated habitats supported more colonization 489 events than spatially continuous (i.e. non-isolated) habitats, without concomitant extinction events. 490

This can be due to species from the opposite habitat type being present locally, if they do not have 491 strict habitat preferences, because of increased edge effects in isolated patches (Slawski and Slawska, 492 2000;[START_REF] Östman | Edge or dispersal effects -Their relative importance 792 on arthropod densities on small islands[END_REF]. This also means that the negative effect of spatial isolation on collembolan 493 diversity can only be unravelled if we take the habitat temporal structure into account. Our results 494 suggests that Collembola species need time to colonize recently created habitat that are isolated from 495 other habitats of the same type. This effect should be especially strong for specialist species that do not 496 survive in a matrix of the opposite habitat type. To our knowledge, it is the first time that such 497 interacting effects are empirically unravelled. 498

The interaction between habitat spatial and temporal continuity was not strictly similar for 499 species density and species richness. Indeed, species density was lower in recent than in old habitat of 500 isolation classes 1 and 2, whereas species richness was lower in recent than in old habitat of isolation 2 501 only. By definition, species density is affected by the number of individuals present in a sample, while 502 species richness is not. Species density should thus be sensitive to both local factors and landscape 503 characteristics (regional factors). Local factors determine locally the carrying capacity of the 504 environment while the number of species that can reach a local patch should be mostly determined by 505 landscape characteristics. This difference in sensitivity between both diversity indicators reveals that 506 old habitat of isolation class 1 should benefit from the contribution of many poorly abundant species 507

(not taken into account in the calculation of species richness) in addition to a few abundant species. 508

This results in similar values of species richness in old and recent habitats of isolation class 1, but still 509 different values for species density. In the other hand, old habitats of isolation class 2 benefit from an 510 20 increase in the number of species that are also more evenly distributed, which results in an increase in 511 both species richness and species density compared to recent habitat of the same isolation class. 512

These results support the novel idea that habitat fragmentation constrains diversity not only 513 through spatial but also through temporal continuity: there is a strong positive impact of temporal 514 continuity on the total number of species, in addition to the distribution of individual numbers within 515 each species. Thus, in the case of soil organisms, which probably disperse slowly at landscape scale, 516 regional processes shaping communities must be slow. That is why habitat age has to be taken into 517 account to better predict soil biodiversity in the context of habitat fragmentation. 518

Effect of soil properties in interaction with habitat spatiotemporal structure on diversity 519

Few soil characteristics responded to the spatial and /or temporal structure of habitats, 520 suggesting that indirect effect on diversity should be weak. Additionally, our results showed that both 521 species density and species richness were submitted to direct effects of habitat descriptors and their 522 interactions, whereas no indirect effects were detected since neither the Ctot nor the soil pH had 523 simple effect on diversity. However, the two parameters that were most correlated with species density 524 (soil pH and total carbon Ctot) interacted with habitat descriptors to affect diversity. Collembolan 525 diversity was more influenced by Ctot and soil pH in old than in recent patches. This result 526 corroborates the study of [START_REF] Dzwonko | Assessment of light and soil conditions in ancient and recent woodlands by 708 Ellenberg indicator values[END_REF], who showed that plant species indicator values for several 527 environmental factors (Ellenberg indicators) were more reliable in old than in recent forests. Species 528 can be good indicators of environmental conditions only if communities have had enough time to 529 reach equilibrium. Before equilibrium, a bias can occur because some indicator species are lacking due 530 to dispersal limitation [START_REF] Seabloom | Plant diversity, composition, and invasion of restored and 843 natural prairie pothole wetlands: implications for restoration[END_REF] or because some species reflecting previous 531 habitat type still persist [START_REF] French | Ground flora communities in temperate oceanic plantation forests and the influence 720 of silvicultural, geographic and edaphic factors[END_REF]. 532

The introduction of Ctot in the model suppressed the significant effect of temporal continuity 533 on species density. Likewise, the introduction of the pH in the model suppressed the significant effect 534 of habitat type on species richness. This means that a part of the variability explained by habitat 535 descriptors is in fact due to a difference in soil properties. Ctot was lower (although not significantly) 536 in recent than in old habitats, especially in forest and soil pH was significantly lower in forest than in 537 agricultural land. Since the carbon content and the soil pH may influence collembolan diversity 538 [START_REF] Chagnon | Relationships between soil chemistry, microbial biomass and 679 the collembolan fauna of southern Quebec sugar maple stands[END_REF], we cannot totally reject that a part of the observed difference in diversity 539 according to habitat descriptors is due to slightly different environmental conditions. This shows that 540 discriminating between direct and indirect effects is not straightforward, confirming that when 541 studying the impact of landscape structure on soil animals, soil properties should be taken into 542

account. 543

We also showed that effects of habitat descriptors on species density and species richness were 544 not strictly similar when taking into account soil properties. Fewer effects were detected on species 545 richness than on species density, but all factors impacting species richness also impacted species 546 density. This suggests that some factors impacting species density also impact species relative 547 abundances in a subtle way and that removing this effect on abundances through the use of species 548 richness suppresses the effects detected on diversity. This confirms that using an abundance-free index 549 of biodiversity using rarefaction curves allows a better analysis of the impact of local and regional 550 factors on local pools of species [START_REF] Gotelli | Quantifying biodiversity: procedures and pitfalls in the 734 measurement and comparison of species richness[END_REF]. 551

Differences in diversity patterns between habitat types 552

We defined habitat types as two very broad categories: agriculture or forest without taking the 553 precise habitat type (e.g. coniferous and deciduous forests) into account. Nevertheless, we were able to 554 reveal some significant effects of landscape characteristics on diversity and differences in patterns 555 between the two habitat types. This confirms that for Collembola, the land use is a fundamental factor 556 that determines which species can persist locally [START_REF] Ponge | Biocenoses of Collembola in atlantic temperate grass-woodland ecosystems[END_REF][START_REF] Hopkin | Biology of the Springtails (Insecta: Collembola)[END_REF]Birkhofer et al., 2012). 557

As hypothesized (H2), local diversity in terms of species density and species richness were higher in 558 forest than in agricultural habitats. This is likely to be due to differences in soil properties between 559 these two contrasted habitat types. (1) Forests display well developed humus profiles and a higher soil 560 carbon content, which provide resources for many collembolan species [START_REF] Chagnon | Relationships between soil chemistry, microbial biomass and 679 the collembolan fauna of southern Quebec sugar maple stands[END_REF]. The 561 absence of tree cover and the exportation of organic matter and associated nutrients in agricultural 562 land result in a reduced soil organic layer and soil moisture [START_REF] Batlle-Aguilar | Modelling soil carbon and nitrogen 651 cycles during land use change. A review[END_REF] which will 563 consequently negatively affect diversity and abundance of soil biota. Additionally, higher soil density 564 in agricultural habitats may also reduce collembolan abundance because it provides little pore space 565 for soil-dwelling populations [START_REF] Vreeken-Buijs | Relationships of soil microarthropod biomass 876 with organic matter and pore size distribution in soils under different land use[END_REF]. It is not excluded that other biotic factors 566 such as predation contributed to drive observed diversity patterns. However, our field study did not 567 allow assessing the impact of such factor. Surprisingly, in our study, habitat type had no effect on the 568 Shannon index. Based on the mathematical expression of Shannon"s diversity, which associates a 569 probability of occurrence to each species, this discrepancy suggests that even though the number of 570 species differed, less frequent species were most affected by change in habitat type [START_REF] Gorelick | Combining richness and abundance into a single diversity index using matrix 732 analogues of Shannon's and Simpson's indices[END_REF]. 571

The effect of temporal discontinuity was stronger in forest than in agricultural land. This 572 finding supports our third hypothesis (H3) that predicted a stronger effect of habitat spatiotemporal 573 structure on collembolan diversity in forest than in agricultural habitats. This could arise because open 574 habitats lead to more efficient dispersal either through passive or active mechanisms. First, if 575

Collembola have a preponderant passive dispersal and are directly or indirectly transported by wind, 576 as suggested for some species by [START_REF] Dunger | Colonization behaviour of Collembola under different 710 conditions of dispersal[END_REF] and [START_REF] Coulson | The role of glacier mice in the invertebrate colonisation of glacial 686 surfaces: the moss balls of the Falljokull, Iceland[END_REF], their 577 colonization rate might be higher in agricultural habitats since air flow is stronger in the absence of 578 tree cover [START_REF] Wright | Edge microclimate of temperate woodlands as 884 affected by adjoining land use[END_REF]. This result is in accordance with other findings on Collembola in 579 deglaciated land [START_REF] Ingimarsdottir | 758 Primary assembly of soil communities: disentangling the effect of dispersal and local 759 environment[END_REF]. Indeed these authors showed that in such extremely open 580 habitat (i.e. with reduced to nil vegetation cover) collembolan dispersal rate was potentially high. 581

Another explanation could be that collembolan communities in agricultural land are comprised of 582 more epigeic species than in forests [START_REF] Sousa | Effects of land-use on Collembola diversity patterns in a Mediterranean 857 landscape[END_REF], with morphological traits (e.g. long legs, long 583 furcula) supposed to allow higher mobility in open habitats [START_REF] Salmon | Species traits and habitats in springtail communities: a regional 834 scale study[END_REF]. This result 584 suggests that dispersal rates and modes are habitat-dependent as shown in other microarthropod 585 groups [START_REF] Lindo | Spatial and environmental factors contributing to patterns in 778 arboreal and terrestrial oribatid mite diversity across spatial scales[END_REF]. 586

Our results also showed a significant interaction between spatial isolation and habitat type. 587

With spatial isolation, species density increased in forest but decreased in agricultural habitats. This 588 could be due to better mobility and less strict habitat preferences of species found in agricultural 589 communities [START_REF] Lauga-Reyrel | Diversity within the Collembola community in fragmented 767 coppice forests in south-western France[END_REF]Ponge et al., 2006), likely to be present in remnant 590 forest patches. In contrast, many species from the forest communities show strict habitat preferences 591 and a reduced mobility [START_REF] Auclerc | Experimental assessment of habitat preference and 645 dispersal ability of soil springtails[END_REF] and are thus less prone to colonize remnant agricultural 592 patches. Our results also suggest that the forest matrix surrounding agricultural patches is more 593 difficult to cross for species than the agricultural matrix surrounding forests. Since passive dispersal 594 by wind is likely to be more efficient in agricultural lands than in forests, this suggests that largely 595 overlooked passive dispersal mechanisms might be influential for collembolan communities and meta-596 community dynamics. 597

Conclusion 598

Our study contributes to some extent to disentangle complex effects of habitat characteristics 599 (i.e. spatiotemporal structure and local physicochemical conditions) on collembolan diversity. Most 600 importantly, we showed that habitat temporal continuity is a key factor shaping collembolan diversity 601 and that we must take it into account if we want to understand the effects of habitat spatial structure. 602

We also showed that using both species richness and species density as indicators of biodiversity 603 allows refining the analysis of the factors influencing collembolan diversity at different scales. 604 Unfortunately, it is rather impossible to experiment at landscape scale, and the limits of our study must 605 be clearly defined. We controlled only partly the factors thought to influence collembolan diversity: 606 climate and litter quality could not be controlled, as they can be in experimental conditions (Åström 607 and Bengtsson, 2011;[START_REF] Bokhorst | 663 Extreme winter warming events more negatively impact small rather than large soil fauna: 664 shift in community composition explained by traits not taxa[END_REF]. Similarly, the different levels of isolation and age were 608 broadly defined and not totally equivalent in forest and agricultural habitats. However, we were able to 609 detect several effects of our treatments (habitat type, isolation and patch age), using landscape past 610 dynamics as a surrogate for a strict experimental approach. Some theoretical models predicted such 611 patterns [START_REF] Green | Interactions matter: complexity in landscapes and ecosystems[END_REF][START_REF] Gardner | Spatial processes that maintain biodiversity in plant 723 communities[END_REF], but empirical corroborating 612 studies are still scarce [START_REF] Lemaître | Multiscale assessment of the influence of habitat 775 structure and composition on bird assemblages in boreal forest[END_REF]. Nevertheless, we showed that habitat fragmentation 613 constrains diversity not only in space but also in time. The temporal continuity of habitats is one of the 614 factors that have a positive effect on diversity. Soil organisms disperse slowly compared to above-615 ground biota and it hence takes longer for a recent habitat to build up soil diversity especially if the 616 patch is very isolated. 617

Assembly theory is now well recognized in community ecology but still little applied in soil 618 ecology. This metacommunity framework predicts four models that could explain species distribution 619 at local scale [START_REF] Leibold | The metacommunity 773 concept: a framework for multi-scale community ecology[END_REF]. These models essentially differ in the importance given to dispersal 620 process in explaining metacommunity dynamics. Two of them, "species sorting" (environmental 621 constraints control species distribution) and "mass effect" (dispersal redistributes species among 622 habitats independently of environmental constraints) were found relevant to collembolan communities 623 by da [START_REF] Da Silva | Environmental factors at 694 different spatial scales governing soil fauna community patterns in fragmented forests[END_REF] and [START_REF] Ingimarsdottir | 758 Primary assembly of soil communities: disentangling the effect of dispersal and local 759 environment[END_REF]. This study also supports the idea that 624 dispersal plays an important role in structuring collembolan metacommunities and that the magnitude 625 and direction of its effect depend on the type of habitat considered. 626

Acknowledgments 627

This study was sponsored by the R2DS program of the Conseil Régional d"Ile-de-France. We would 628 like to thank the public and private owners of the sampling sites for allowing the study to be carried 629 out on their land. We would like to tank the IRD (Centre Fance Nord) and the MNHN (Brunoy) for the 630 access to their facilities and material; the Laboratoire des Moyens Analytiques (IRD, Dakar) for 631 performing the soil analysis; the IGN (France) for providing aerial photographs; Joshua Lobe for 632 correction of the English language; Thibaud Decaëns for useful advices about the use of species 633 rarefaction curves; anonymous reviewers for their useful comments which have helped us to increase 634 the quality of the manuscript. 635

FIGURE CAPTIONS

Figure 1 :

 1 Figure 1: Statistical diagram picturing steps of data analyses. Arrows represent effects of factors on

Figure 2 :

 2 Figure 2: Individual based rarefaction curves old forests (F_old), recent forests (F_rec), old

Figure 3 :

 3 Figure 3: Mean species density (3a), Shannon index (3b) and species richness (3c) of old (grey) and

Figure 4 :

 4 Figure 4: Mean species density (4a) and species richness (4b) according to Habitat Type, Temporal

Figure 5 :

 5 Figure 5: Correlation coefficients (Pearson) between species density (grey bars), species richness

Figure 6 :

 6 Figure 6: Least square means for species density and species richness obtained using the model

  Figure Caption

Table 2 .

 2 Soil characteristics (mean values and standard deviations) showing differences between agricultural and forest habitats. Total carbon content (Ctot), soil pH (pH), carbon to nitrogen ratio

	F value

Table 3 .

 3 Effect of habitat descriptors (Habitat Type HT, Temporal Continuity TC and Spatial Isolation SI) and all their interactions on soil properties. Soil pH (pH), total carbon content (Ctot), total nitrogen content (Ntot), carbon to nitrogen ratio (C/N), bioavailable phosphorus (Phosphorus), cation exchange capacity (CEC), soil moisture (Moisture), bulk density (Density) and Humus index (Humus).Transformation, model type (distribution) and results of linear or generalized linear models (F value/Chi square and degrees of freedom df). Significance levels: p<0.05*; p<0.01**; p<0.001***.

	F / Chi square

Table 4 .

 4 Effect of habitat descriptors (Habitat Type HT, Temporal Continuity TC and Spatial Isolation 31 SI), total soil carbon content (Ctot) (left hand side), soil pH (right hand side) and all their interactions 32 on species density and species richness. Transformation and results of linear models (F values and 33 degrees of freedom df), tested after variable selection based on AIC criterion).

	Significance levels:

Appendix A. List of study sites with their classification according to habitat type (agriculture vs forest), temporal continuity (oldt vs recent) and spatial isolation (three isolation classes), followed by % edge contrast with opposite habitat type, matrice type (old or recent or mixed), station code, land use, humus form according to [START_REF] Brêthes | Classification of forest humus forms: 669 a french proposal[END_REF] and main community indices of Collembola (total abundance per sample, species density, species richness, Shannon index and dominance). The edge contrast is the % borderline which the patch with the sampling point shares with the opposite habitat in the circle of 300 m arround the sampling point. The matrix type is the dominant age of the habitat surrounding the patch with the sampling point. The combinaison of both defines the level of isolation.