Locally rare species influence grassland ecosystem multifunctionality

Species diversity promotes the delivery of multiple ecosystem functions (multifunctionality). However, the relative functional importance of rare and common species in driving the biodiversity–multifunctionality relationship remains unknown. We studied the relationship between the diversity of rare and common species (according to their local abundances and across nine different trophic groups), and multifunctionality indices derived from 14 ecosystem functions on 150 grasslands across a land-use intensity (LUI) gradient. The diversity of above- and below-ground rare species had opposite effects, with rare above-ground species being associated with high levels of multifunctionality, probably because their effects on different functions did not trade off against each other. Conversely, common species were only related to average, not high, levels of multifunctionality, and their functional effects declined with LUI. Apart from the community-level effects of diversity, we found significant positive associations between the abundance of individual species and multifunctionality in 6% of the species tested. Species-specific functional effects were best predicted by their response to LUI: species that declined in abundance with land use intensification were those associated with higher levels of multifunctionality. Our results highlight the importance of rare species for ecosystem multifunctionality and help guiding future conservation priorities.


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Many studies have demonstrated that high species diversity enhances ecosystem functioning 82 both in experimental and natural assemblages (1-4; reviewed in [5] this issue). However, it 83 has been argued elsewhere that it is not the total number of species per se, but the functional 84 properties of the most locally abundant ones (hereafter common species) that drive ecosystem 85 functioning (mass-ratio hypothesis; [6]). Other work has shown that each common species 86 can only provide a limited number of functions [1,[7][8]. Extending the mass-ratio hypothesis 87 to the simultaneous provision of multiple ecosystem functions at high levels 88 (multifunctionality), we might therefore predict that several common species would be needed 89 to maintain multifunctionality and that the diversity of common species, rather than overall 90 diversity, would be its main biotic driver. In contrast to this argument, less locally abundant 91 (hereafter rare) species have been shown to play a crucial role in affecting several ecosystem 92 functions [9][10][11]. Rare species comprise the vast majority of the species in any natural 93 community and are more sensitive to anthropogenic disturbances [12,13]. Thus quantifying 94 the functional consequences of their loss is of particular importance to predict the provision of 95 ecosystem services in the future. The functional importance of common vs. rare species could 96 depend on the ecosystem functions under scrutiny. Studies focused on productivity and 97 pollination have found common species to be the main driver (e.g., [9, [14][15][16][17]) while those 98 focusing on functions associated with some regulating (e.g., invasion resistance) or 99 recreational (e.g., bird watching) services highlight the importance of rare species [18][19][20]. 100 Due to their contrasting effects depending on the function considered, studies measuring 101 multifunctionality are required to comprehensively assess the relative functional importance 102 of rare and common species [8,11]. 103 Studies across large temporal or spatial scales have shown that the relationship 104 between diversity and ecosystem functioning may change with abiotic conditions or land-use 105 intensification [21][22][23][24][25], the level of multifunctionality desired [8,26] or the type of organism 106 6 being considered [23]. Land-use intensification promotes shifts in the functional composition 107 of multiple taxa (e.g., 27), potentially dampening the generally positive relationship between 108 diversity and ecosystem multifunctionality (25). The effects of biodiversity might also depend 109 on the level of multifunctionality considered [26,28]. High levels of many functions can be 110 difficult to achieve if there are strong trade-offs between functions or between diversity 111 effects on these functions. Finally, different components of biodiversity may differ in their 112 functional effects. Above-and belowground organisms differ in their sensitivity to climate or 113 anthropogenic disturbances, with rare aboveground species being the most sensitive (e.g., [13, 114 29]), and can also have different effects on ecosystem multifunctionality, with stronger effects 115 found for aboveground organisms [23,30]. The context-dependencies of the biodiversity-116 functioning relationship are poorly understood, particularly in terms of how they might 117 modify effects of rare and common species. Existing comparisons of the functional role of 118 rare vs. common species have seldom been extended beyond single taxa, individual 119 ecosystem functions or a particular study site (but see [11]). In order to understand the 120 response of natural and semi-natural ecosystems to ongoing global change, we therefore need 121 to examine the relationships between different components of diversity (above-vs. 122 belowground, common vs. rare) and ecosystem multifunctionality across environmental 123 gradients [23] (see also [31]; this issue). 124 It has also been hypothesized that the presence of certain species can be of particular 125 importance for ecosystem functioning, regardless of their abundance or whether they are 126 above-or belowground organisms (identity hypothesis; [32,33]). This hypothesis has 127 received empirical support from studies focusing on individual functions such as litter 128 decomposition, parasitism or predation [34][35][36]. However, studies have not yet tested whether 129 there are species that can drive overall ecosystem multifunctionality, which would require 130 lack of trade-offs in their effects on different functions. If there are influential species, it is 131 important to understand the characteristics that they possess and how they respond to land-use 132 7 intensification. If such species decline in abundance as land use intensifies then, in addition to 133 effects of biodiversity loss, compositional change driven by land use may have large effects 134 on ecosystem multifunctionality. 135 Here, we assess the functional role of the diversity of rare and common species (based 136 on their local abundance), both above-and belowground, on several multifunctionality indices 137 derived from 14 ecosystem functions, related to the delivery of supporting, provisioning, 138 regulating and cultural services (sensu [37]). Our hypotheses are: i) the diversity of common 139 species is a more important driver of ecosystem multifunctionality than the diversity of rare 140 species, ii) the positive effect of diversity on multifunctionality will decline with land-use 141 intensity due to the associated changes in functional composition, iii) the diversity of 142 aboveground organisms is the strongest biotic predictor for ecosystem multifunctionality [23], 143 iv) there are particular species, across multiple trophic levels, that can promote high 144 multifunctionality and land-use intensification changes the abundance of these species.  Schorfheide-Chorin (in the Northeast), and the area in and around the National Park Hainich-151 Dün (in central Germany; [38]). The 50 grassland plots per region were selected to span a 152 gradient of the full range of land-use practices and intensities found in Central European 153 grasslands. Information about land-use intensity was obtained directly from the land owners 154 via questionnaires [38]. We used this information to calculate a compound measure of land-155 use intensity (LUI) which summarizes the three major components of land-use in these 156 grasslands -intensity of fertilization, mowing and grazing-with the following formula: LUI = 157 sqrt((F i /F R ) + (M i /M R ) + (G i /G R )), where F i , M i and R i are the amount of fertilizer applied, site per year, respectively. All three components were standardized by the average across the 160 50 grassland plots within each region (F R , M R and G R ; see [39] for full methodological 161 details). We averaged LUI across 2006-2010, the period when most diversity and functioning 162 data was collected. At each site, we measured the abundance and richness of nine trophic groups using standard 167 methodology (see Table S1 for details). Overall, our sampling included ~4300 taxa (the 168 taxonomic unit varied between groups [ Table S1] but we refer to all as species, for 169 simplicity). The groups were: autotrophs (plants and bryophytes), belowground herbivores 170 (insect larvae), belowground predators (insect larvae), detritivores (insects and millipedes),  Using data for each of these nine trophic groups we calculated multidiversity, i.e., a 176 measure of overall diversity at the community level obtained by averaging standardized 177 diversity measures across trophic groups [13]. To calculate multidiversity we first classified 178 the species into two groups according to their abundance (which was measured differently for 179 the various groups [ Table S1]): common (the top 10% species in terms of total abundance) 180 and rare species (the bottom 90% of species). Abundance is widely accepted as a measure of 181 rarity (e.g., [40]); therefore, we chose abundance across all study sites to be the most 182 representative measure of the overall rarity of our target species. The top 10% species 183 (common species hereafter) accounted for 80% of the total abundance sampled, whereas the 184 9 bottom 90% of species (rare species hereafter) made on average 20% of the total abundance 185 (ranging from 6% in bacteria to 30% in belowground herbivores; Fig. S1). A second step in 186 the calculation of our multidiversity metric was to standardize all variables to a common scale 187 (between 0 and 1) by subtracting the minimum value and dividing by the maximum value 188 found across the 150 sites to avoid the influence of different ranges in diversity characterizing 189 each group. Third, we classified the trophic groups into above-and belowground organisms  control, pollinator abundance, bird diversity and flower cover (see [25] and Table S2 for 200 detailed methodology). These ecosystem functions are related to nutrient cycling, food 201 provision, sustainable soil use, pest resistance, or cultural and recreational services. We 202 calculated three ecosystem multifunctionality metrics using these 14 functions and following 203 the multiple threshold approach of Byrnes et al. [26], which sum up the number of measured 204 functions that exceeds a given threshold. These thresholds are defined as a given percentage 205 of the maximum level found for each function, and we used three thresholds (50%, 75% and 206 90%) to represent a wide spectrum. In order to reduce the influence of outliers the maximum 207 was defined as an average of the top five values for each function across our study sites.  211 We used multi-model inference based on information theory [41] to analyze the response of 212 ecosystem multifunctionality to the multidiversity of above-and belowground common and 213 rare species. We performed a different analysis for each of the three multifunctionality which is related to the accumulation of soil material and water availability; [42, 43]) and LUI. 223 We removed elevation from the set of environmental predictors because it was highly 224 correlated with soil depth (Spearman´s rank correlation ρ = -0.91). We also accounted for 225 potential context-dependencies in the diversity-multifunctionality relationship by including 226 the interactions between LUI, region, and the four multidiversity predictors.

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To analyze the relative importance of environmental conditions, the multidiversity of 228 above-and belowground common and rare species, and the interactions between them, as 229 drivers of ecosystem multifunctionality, we built a set of competing models including either: 230 environmental variables only, environmental + diversity variables, or environmental + 231 diversity variables and the interactions between diversity and region and/or land-use intensity; 232 see Table S3 for the full list of models). From these competing models we selected those that 233 best fit our data according to the Akaike Information Criterion (AICc, corrected for small 234 sample sizes). Thus, those models differing less than 2 AICc units from the most 235 parsimonious model (ΔAICc < 2) were included in the set of best-fitting models. We also  As a sensitivity analysis, we repeated our multi-model selection but used the 243 multidiversity of the bottom 50% species, instead of the bottom 90%, as an alternative 244 measure of rarity. These bottom 50% species made up on average 3% of the total abundance 245 (ranging from 0.04% in bacteria to 6% in belowground herbivores; Fig. S1; see Table S4 for 246 detailed results). We also repeated our analyses using the abundance, instead of the species 247 richness, of above-and belowground common and rare species (Table S5)  (i) Selection of species 253 We selected a subset of individual species that occurred in all three study areas, and in at least 254 10 of the 150 sites to obtain reliable parameter estimates (see Estimation of the functional role 255 of each species below). Some of the trophic groups measured (detritivores, and belowground 256 herbivores and predators) were not included in these species-level analyses as they contained 257 too few species fulfilling our selection criteria. Of those that did, soil microbial decomposers 258 and bacterivorous protists were overrepresented. Thus, in order to obtain a balanced sampling 259 size for each trophic group, we only selected the most and least abundant 25 species within 260 each trophic group that met the criteria. These species roughly corresponded to those 261 classified as common and rare in the community-level analyses (Table S6). Thereby, we

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(a) Community level 328 Between 10% and 18% of the variation in multifunctionality was explained by study region, 329 environmental variables, land-use intensity (LUI) and our multidiversity metrics (Fig. 1). All 330 the best models (those with ΔAIC < 2) included at least one of the four multidiversity metrics, 331 with models only including environment and LUI performing less well (ΔAIC between 2.6 332 and 7.1; Table S3). The effects of multidiversity on multifunctionality differed depending on 333 the metrics considered. Aboveground multidiversity of common species was not significantly 334 related to any of the multifunctionality measures, whereas the multidiversity of common 335 species belowground was positively related to multifunctionality at the 50% threshold, but not 336 to the other multifunctionality measures (Table S3). The multidiversity of rare species both 337 above-and belowground was significantly, but oppositely (positive for above-and negative 338 15 for belowground), related to multifunctionality at the highest thresholds (75% and 90%; Figs. 339 1 and 2).

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The relationships found between multidiversity (both above-and belowground) and 341 multifunctionality at the highest thresholds did not depend on LUI or study region (Fig. 1).

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The best models for both the 75% and 90% thresholds did not include interactions between 343 region and/or LUI and multidiversity (Table S3). The best models for the 50% 344 multifunctionality threshold, however, included interactions between region, and/or LUI, and 345 one or more multidiversity metrics ( Fig. 1; Table S3), thus demonstrating that multidiversity-346 multifunctionality relationships were context-dependent for the low threshold measure.

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Indeed, for multifunctionality at the 50% threshold the interactions were as important as the 348 main effects (Fig. 1), and not including them increased the AICc by more than 3 units in all 349 cases, suggesting a strong decline in model performance (Table S3). Interactions with region 350 or LUI affected the associations between belowground, but not aboveground, multidiversity  (Fig. S2). Regardless of the interactions with region and LUI, we found a higher importance 357 of aboveground multidiversity for the 75% and 90% thresholds, which shifted towards a 358 higher importance of belowground multidiversity components at the 50% thresholds ( Fig. 1; 359 Table S3). associations between the abundance of individual species and multifunctionality in 6% of the 364 species tested, whereas we found negative relationships for 4% of the species (Table S7). 365 Aboveground rare species had significantly more positive, and fewer negative, relationships 366 with multifunctionality than the aboveground common species did (Fig. 3), a trend not found 367 in belowground organisms. The ratio between positive and negative relationships differed 368 substantially depending on the trophic group studied. Microbial decomposers had more 369 positive than negative relationships with multifunctionality (11% vs. 1%), with the opposite 370 pattern observed in symbionts (4% vs. 10%, Table S7). The remaining trophic groups showed 371 slightly more positive than negative relationships.

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Including the abundance, functional traits and response to LUI of the individual 373 species allowed us to predict 13-16% of the variance in the strength of species -374 multifunctionality associations. The multiple regressions performed revealed that response to 375 LUI was the strongest predictor of the associations between individual species abundance and 376 multifunctionality. Species that increased in abundance in response to LUI were negatively 377 correlated with multifunctionality at the 75% and 90% thresholds ( Fig. 4; Table S8). The important role that rare species play in maintaining individual ecosystem functions and, 384 to some extent, multifunctionality has been highlighted previously [8,11,[18][19][20]. Here, we 385 extend those results to multitrophic assemblages in realistic landscapes, and show that: i) the 386 relative importance of rare species increases when multifunctionality is defined using higher 387 thresholds for the functions and ii) that this relationship remains relatively consistent across 388 study regions and land-use intensities (Fig. 2). Our results show that the ability of ecosystems 389 to maintain a large number of functions at average levels (50% threshold) is mainly driven by 390 the diversity of common species and, intuitively, by the prevailing environmental conditions 391 (as shown by the significant interactions found in our models). However, the delivery of a 392 smaller number of functions, but at very high levels (75% and 90% thresholds), was mainly 393 related to the multidiversity of rare species. The level of multifunctionality required will 394 depend on stakeholder preferences, but the performance of many functions at their highest 395 potential (high multifunctionality values at high thresholds) can be generally interpreted as a 396 more desirable state of natural ecosystems. Overall, our study shows that the diversity of rare 397 species is consistently and positively related to multifunctionality at the highest levels, thus 398 implying the existence of "win-win" scenarios between biodiversity conservation and 399 ecosystem service provision.

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A high diversity of rare species might be more beneficial for multifunctionality than a 401 high diversity of common species if rare species are less likely to negatively affect ecosystem 402 functions. We found that functional trade-offs between species, where some species have 403 positive effects on multifunctionality and others negative effects, were less common amongst 404 rare than common species (Fig. 3). This could explain the stronger positive effect of rare 405 species diversity on multifunctionality. Our correlative study does not allow us to investigate 406 the mechanisms behind the lower incidence of such functional trade-offs in rare species.

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However, we speculate that if functional effects are driven by the presence of a given species, 408 rather than by its abundance, they are much less likely to be negative. In the case of presence-409 based functional effects the species is either there, and promotes a given function, or is absent 410 and has no effect. For example, the presence of certain species can promote recreational 411 services such as birdwatching [20], or prevent plant invasions [18,19]). Such presence-based 412 effects are likely to be the dominant ones amongst rare species. In contrast, functional effects 413 that are proportional to a species' abundance [6] may also be negative. Abundant species can 414 reduce, instead of promote a given function, e.g., species with low specific leaf area can 415 reduce rates of nutrient cycling. Common species are more likely than rare species to have 416 such abundance-related effects. Therefore, even if the common species are functionally 417 relevant, they may have opposing functional effects (e.g., the positive effects of a common 418 productive plant on forage production might be balanced by negative effects of a common 419 herbivorous insect that feeds upon it). Such strong functional trade-offs between common 420 species could therefore result in a small effect of common species diversity on 421 multifunctionality and a greater importance of rare species diversity in promoting 422 multifunctionality. A complementary explanation for the higher functional importance of rare 423 species is that they tend to be less redundant than common species in the functional traits they  Belowground and aboveground biotic components are known to respond differently to 445 anthropogenic disturbances and are likely to differ in their effects on ecosystem functioning 446 (e.g., [13,30]); however, very few studies have explored their separate functional roles [23]. 447 We found that aboveground multidiversity, particularly of rare species, was often positively 448 related to multifunctionality at the highest levels, whereas belowground multidiversity was 449 negatively associated with it. Aboveground rare species are highly sensitive to anthropogenic 450 disturbances [13,29] and these findings suggest that they are also amongst the most 451 functionally important species. Our results support the crucial role of the diversity of 452 aboveground organisms, e.g., plants [1][2][3][4]8], but also herbivores [28] or predators [58] in 453 determining ecosystem multifunctionality.

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The stronger positive relationship between above-than belowground diversity with 455 multifunctionality concurs with the only previous study including these two groups separately 456 [23]. It may be argued that the higher importance of above-than belowground components is 457 dictated by the selection of ecosystem functions studied; however, this is unlikely as both our 458 study and Jing et al. [23] included a high proportion of soil-related variables. It seems that, 459 when considered alone, belowground diversity explains variation in multifunctionality that 460 could be mainly due to its correlation with aboveground diversity [23,58], but further studies 461 are required to test whether the pattern we observed holds across a wide variety of ecosystems 462 and environments. Importantly, our snap-shot sampling design may have reduced our capacity 463 to compare the effects of both above-and belowground multidiversity, as belowground 464 organisms are less sensitive to anthropogenic disturbances [13] and thus they could increase 465 the stability in ecosystem functioning by increasing response diversity [59]. 466 The negative relationship between belowground diversity and ecosystem 467 multifunctionality, however, is surprising and contrasts with previous research (e.g., [23, 60, 468 20 61]). Soil biota effects are often driven more by functional composition than by species 469 richness per se (see [60] for a review). Hence, the negative relationship between belowground 470 multidiversity and ecosystem functioning could reflect compositional changes rather than 471 diversity effects [23,24]. Another potential explanation for these results is that the functional 472 effects of belowground diversity are context-dependent and change with climate or soil 473 (regional differences in our study sites [62]), or with land-use intensification ( Fig. S2; see also 474 [23]). The latter could obscure the overall effect of belowground multidiversity on ecosystem 475 functioning, when it is investigated across wide environmental gradients. In this regard, we 476 found strong context-dependency for low (50%) levels of multifunctionality, as the 477 relationship between belowground multidiversity and multifunctionality changed both with 478 study region and land-use intensity (Fig. S2). Regardless of the underlying mechanisms, the 479 contrasting relationships between above-and belowground biotic components and   [32,33], extending it to multiple functions and trophic levels. An example of one 497 of these particularly influential species is Hieracium pilosella, plant native to central Europe 498 and locally rare in our study sites. This species was positively associated with 499 multifunctionality according to our method and has previously been shown to increase soil 500 organic C, litter decomposition and microbial biomass in comparison to other grassland 501 species [63], to attract a variety of pollinators [64] and to have a relatively high resistance to 502 pathogenic fungal infections [65]. We found a similar number of influential species for both 503 common and rare species, and for both above-and belowground organisms; indicating that 504 individual species within these biotic components are equally important for 505 multifunctionality. Understanding the attributes of these particularly influential species, and 506 their effects on multifunctionality should be a research priority if we are to predict the 507 consequences of biodiversity loss and compositional changes for ecosystem service provision.

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The direction of the relationship between the abundance of individual species and 509 multifunctionality was best predicted by their response to land-use intensification, even after 510 accounting for the range in abundance across the plots and important functional traits.

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Previous studies have shown that land-use intensification shifts plant functional composition 512 and leads to an increase in the abundance of productive species, which enhance some 513 provisioning services but compromise regulating and cultural services such as carbon storage 514 or aesthetic value, therefore reducing overall multifunctionality [25]. Similarly, changes in the 515 ratio between soil fungi and bacteria with land-use intensification may speed-up nutrient 516 recycling but reduce ecosystem recovery after disturbances [24]. We show here that,  approach also supports the identity hypothesis, and extends it to multiple trophic groups and 534 functions by showing, for the first time, that ~10% of the species tested can be particularly 535 associated to overall ecosystem functioning. We also found that the effect of an individual 536 species on multifunctionality is related to its response to land-use intensity, which will help to 537 anticipate the functional consequences of compositional changes across multiple trophic 538 groups caused by land-use intensification.     Figure S1. Abundance distribution of common and rare species within each trophic group. indicates the interaction term between study region and a given multidiversity metric. LUI × 778 indicates the interaction term between land-use intensity and a given multidiversity metric.

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The R 2 of the best model for each multifunctionality metric (first row in Table S3) is  Table S3; Fig. S2). Note that dots are residuals of both multidiversity and 786 multifunctionality metrics after filtering by study region, LUI, soil pH and depth and the 787 topographic wetness index.