Root hairs and mycorrhiza represent alternative phylogenetically conserved strategies for belowground absorptive surface maximization

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incl. Conclusion: 1860 words 24 Supplementary Information: 4 figures in colour, 5 tables 25 26 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 2 Summary 27 • Plants take up nutrients from the soil while investing in absorptive root surface or 28 mycorrhizal partners. Root hairs - a major structure for nutrient uptake and cheap to build - 29 increase the absorptive root surface. As such they are an important component of plant 30 resource economics but largely neglected in root economic concepts so far. 31 • This is mainly due to data scarcity, which we set out to overcome by measuring root-hair 32 traits on 82 European grassland species in a greenhouse experiment. Using fluorescence and 33 light microscopy, root-hair length and incidence was measured along with mycorrhizal 34 colonization. 35 • We found a phylogenetically conserved trade-off between plant investment into root hairs 36 and mycorrhiza. A similar trade-off between root-hair incidence and mycorrhiza occurred at 37 the intraspecific level, while patterns were heterogeneous among species. Plant species with 38 high colonization rates showed the highest variability in root-hair incidence. 39 • We conclude that plants vary along a gradient ranging from investment into root hairs as 40 part of a “do-it-yourself” strategy to collaboration with mycorrhizal fungi while showing 41 intraspecific variation in root-hair incidence. These findings demonstrate that root hairs play 42 a fundamental role in fine-root trait variation and need to be considered when studying 43 belowground plant economic strategies. 44 45

46 Collaboration, fine roots, outsourcing, root economics space, functional strategy, belowground traits 47 48 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 3

49 The resource economy of plants has been a focal area of studies investigating plant functional traits 50 (Wright et al., 2004; Freschet et al., 2013a,b; Reich, 2014; Kong et al., 2017; Bergmann et al., 2020; 51 Weigelt et al., 2021, Carmona 2021, Matthus 2025). The general idea is that plants invest carbon in 52 construction and conservation of tissue to ensure the uptake and transport of resources. For 53 aboveground organs - mainly leaves - an economic spectrum of plant strategies has been described 54 and confirmed on a global basis (Wright et al., 2004; Reich, 2014; Díaz et al., 2016). This spectrum 55 ranges from fast growth and resource acquisition of short-lived organs to slow but steady resource 56 acquisition of organs constructed for longevity. An analogue pattern is found in belowground fine-57 roots and called the conservation gradient (Bergmann et al., 2020; Weigelt et al., 2021; Matthus et 58 al., 2025). 59 The concept of a collaboration gradient in root-trait variation that is independent of the conservation 60 gradient and unique to belowground economy has been proposed (Bergmann et al., 2020) and found 61 to be a solid pattern across organizational levels and study systems (Matthus et al., 2025). This 62 collaboration gradient describes plant strategies in soil exploration ranging gradually from do-it-63 yourself investment in specific root length (SRL) to outsourcing to mycorrhizal fungal partners with 64 the consequence of larger fine root diameter (AD) and cortex fraction (CF). 65 Arbuscular mycorrhizal (AM) fungi, which associate with almost 80% of all land plants (Brundrett & 66 Tedersoo, 2018), colonize the root’s cortex and explore the soil with extraradical hyphae (Smith & 67 Read, 2008). AM fungi can take up limiting nutrients like phosphorus and nitrogen, supplying them to 68 the roots in exchange for carbon synthesized by the plant partner´s aboveground photosynthesis 69 (Bolan et al., 1987; Smith & Read, 2008). Besides the exploration of a certain volume of soil, the 70 actual surface and the soil contact of an absorptive plant or fungal structure determines the rate of 71 return on investment of a plant (McCormack & Iversen, 2019). Little is known about traits of fungal 72 extraradical hyphae, but a large body of literature reveals that for the plant itself an effective way to 73 maximize a bsorptive surface and soil exploration is the production of root hairs (Bhat & Nye, 1973; 74 Gahoonia et al., 1997; Bates & Lynch, 2000a,b; Haling et al., 2013; Brown et al., 2013b). Yet, most 75 likely because of the effort involved in data collection, the coverage of root-hair traits in databases is 76 poor (Iversen et al., 2017; Guerrero-Ramirez, 2020; Kattge et al., 2020), and their integration into 77 broader plant economics concepts is inconclusive (Zhao et al., 2024; Matthus et al., 2025). 78 Root hairs are unicellular epidermal extensions on living fine roots of most land plants (Farquhar, 79 1996). They enhance nutrient and water uptake of fine roots (Bhat & Nye, 1973; Gilroy & Jones, 80 2000; Haling et al., 2013; Carminati et al., 2017; Freschet et al., 2021b) contributing to >60% of the 81 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 4 plant´s phosphorus-demand (Gahoonia & Nielsen, 1998). Root-hair traits are known to widely vary 82 among species and along environmental gradients of soil fertility (Lambers et al., 2008; Holdaway et 83 al., 2011), while a large root-hair surface can be realized with long (Yang et al., 2015; Haling et al., 84 2016) and/or many (Brown et al., 2013a; Marzec et al., 2015) root hairs. Furthermore, they have 85 been described to be comparably responsive to soil P availability, in part because of their dynamic 86 growth and life-span (Bates & Lynch, 1996; Zhu et al., 2010; Nestler & Wissuwa, 2016). Carbon-87 cheap, metabolically active (Ma et al., 2018) and dynamic in construction compared to fine roots, 88 root hairs might therefore resemble a ‘fast’ economic strategy component within the conservation 89 gradient. So far, no study could provide empirical data to support this link (Matthus et al., 2025). 90 Empirical evidence suggests that the plant species specific beneficial effect of being mycorrhizal is 91 related to root-hair length (Bolan et al., 1987; Schweiger et al., 1995). Therefore, it has been 92 hypothesized that the carbon investment into root hairs might be an alternative strategy to the 93 mycorrhizal symbiosis on an interspecific (Maherali, 2017) and intraspecific level (Kumar et al., 2019) 94 for acquiring soil resources. If this pattern were to be verified for a larger set of species, it would 95 imply that root hairs represent another aspect of a do-it-yourself strategy of plant economics within 96 the collaboration gradient. To date, this hypothesis has not been tested for a larger species set. For 97 four monocotylous families, Betekhtina et al. (2023) provide evidence for root hair length to trade-98 off with AMF colonization levels. Contrary, Guilbeault-Mayers et al. (2024) reported a root-hair index 99 (encompassing length and density) to increase with AMF colonization in trees. Parasquive et al. 100 (2023) found opposing intraspecific trends of root hair index loadings along the collaboration 101 gradient, depending on tree species. Another study found root hair traits to be independent of the 102 collaboration gradient (Guilbeault-Mayers et al., 2024), as has also been proposed by Dallstream & 103 Soper (2024). 104 It has long been known that non-mycorrhizal plants typically have many and long root hairs while 105 mycorrhizal plants often lack them ( Kelley, 1950; Schweiger et al., 1995; Jakobsen et al., 2005; 106 Brundrett, 2021). Most of these studies only worked with mycorrhizal status as a categorical 107 classification to classify plant functioning. Brundrett & Tedersoo (2018) already noted though, that 108 plant species with many root hairs normally have low mycorrhization and can typically be found in 109 stressful habitats. Still, the current data available originate from different studies conducted under 110 various conditions and measuring different traits and categories, which makes it hard to test for 111 gradual functional trade-offs. 112 To fill this knowledge gap, we measured root-hair length (HL) and root-hair incidence (HI) as well as 113 mycorrhizal colonization on a large set of grassland species grown under common conditions. We 1) 114 tested for phylogenetic patterns and differences between functional groups and mycorrhizal status. 115 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 5 We were interested in whether root hair traits differ between these widely used categories, or 116 whether they gradually change with mycorrhizal colonization. We further aimed to 2) test the 117 hypothesis of an interspecific trade-off between the investment in root hairs and the mycorrhizal 118 partner and to 3) explore the intraspecific variation of root hair traits. Finally, we aimed to 4) 119 integrate interspecific variation of HL and HI into the concept of the root economics space, 120 hypothesizing that root hair investment represents a do-it-yourself strategy additional to the overall 121 increase of SRL. 122 123 124 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. 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125 126 Species set 127 The experiment was conducted in the framework of the Biodiversity Exploratories (Fischer et al., 128 2010), a large scale and long term land-use experiment with 150 grassland plots located in three 129 areas in northern, central and southern Germany. From the vegetation records of the Exploratories, 130 we chose a set of 94 grassland species which could be purchased from the commercial seed supplier 131 Rieger-Hofmann GmbH (Blaufelden-Raboldshausen, Germany). This species set encompasses 132 Fabaceae (legumes), non-leguminous dicotyledons (subsequently called forbs) and monocotyledons 133 (subsequently called grasses, but note that Allium schoenoprasum is attached here as a 134 monocotyledonous plant). 135 136 Greenhouse experiment 137 All data presented here originate from one pot experiment conducted under controlled greenhouse 138 conditions, at the facilities of Freie Universität Berlin, between February and June 2018 (16 h day at 139 22°C, 8 h night at 15°C). We set up the experiment with 94 initial species, two treatments (with and 140 without mycorrhizal inoculation), and 8 replicates distributed over 4 overlapping time blocks of 6 141 weeks growing time each. The entire experiment therefore consisted of 4 time blocks x 94 species x 2 142 treatments x 2 replicates = 1504 experimental units. Whenever a replicate did not survive, we tried 143 to substitute it in the next time block. Nevertheless, some species did not reach a replication of 8 per 144 treatment and some did not germinate at all. In the final analysis, we only included species with a 145 minimum of 3 successful replicates per treatment leading to a total of 1151 experimental units of 82 146 species from 20 families. 147 Prior to the first time block, all seeds were surface sterilized in paper tea bags for 3 min in 7% bleach 148 followed by washing in de-ionized (DI) water until the smell of bleach was gone. The seeds were 149 dried at 20°C and stored until sowing for subsequent time blocks. Seeds germinated in plastic boxes 150 filled with 1:1 steamed sand and vermiculite (1-3 mm, ISOLA Vermiculite GmbH; Sprockhövel, 151 Germany). Based on germination times recorded in pre-experiments, we sowed the seeds to assure 152 that all seedlings were in the cotyledon stage or had their first leaves developed at time of 153 transplanting. Seedlings were transplanted into plastic cones (410 ml 0.41 L; Stueve & Sons; USA) 154 filled with the same substrate as for germination. 155 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 7 The mycorrhizal treatment was realized as follows: after filling the cone to c. ¾ we added a 30 ml 156 horizon of a 1:1 mixture of steamed sand and mycorrhizal inoculum in vermiculite (INOQ Agri, Inoq 157 GmbH, Schnega, Germany). According to the supplier, the inoculum contains 145 spores/ml of 158 Rhizophagus irregularis propagated on vermiculite (1-2 mm) under non-sterile greenhouse 159 conditions. Rhizophagus irregularis is a generalist AM fungus associating with almost all mycorrhizal 160 plants (van der Heijden et al., 2015). To account for other soil microbes that might be present in AM 161 inoculum produced under non-sterile conditions, we prepared a microbial wash from the 162 Rhizophagus inoculum (20 µm mesh, soil:water-ratio: 1:2) for the non-mycorrhizal treatment. We 163 carefully adjusted the amount of inoculum as well as the amount of DI water used to prepare the 164 microbial wash to make sure that each pot received the approximate same number of microbial units 165 irrespective of the treatment. To control for nutrients and physical structure of the AM inoculum, we 166 autoclaved the solid inoculum used to prepare the microbial wash and added a 1:1 mixture with 167 steamed sand as a horizon to the non-mycorrhizal treatment. For both treatments the added 168 horizons were covered with another layer of ~30 ml substrate to avoid cross contamination. During 169 transplanting, seedlings of the non-mycorrhizal treatment received 30 ml of the microbial wash, 170 while seedlings of the mycorrhizal treatment received 30 ml of DI water. We replaced seedlings that 171 died shortly after transplanting during the first week. 172 Within each time block, plants grew for 6 weeks in the cones before harvest. All cones were fully 173 randomized at time of transplanting and were rearranged every two weeks. Plants received 25 ml of 174 DI water 3 times a week; two weeks and four weeks after transplanting, they received 25 ml of a ¼ 175 strength Hoagland solution (recipe available in Lachaise et al., 2021) instead. 176 At time of harvest, aboveground and belowground biomass of the plants were separated. Roots were 177 first rinsed with water. Three first order roots per plant were carefully cut, transferred to 10% 178 formalin at pH 7 (ROTI Histofix, Carl Roth, Karlsruhe, Germany) in Phosphate Buffered Saline (PBS) 179 buffer and kept at 4 °C for overnight fixation. The next day, the formalin solution was first replaced 180 by PBS buffer twice for approx. 2 hours each and finally by a solution of 70% ethanol, 5% glycerin and 181 25% DI water for long term preservation. The remaining roots were carefully washed by hand during 182 harvest, transferred to cold DI water and kept at 4°C. Within a week they were scanned in water-183 fille d plastic trays using an Epson perfection 800 Photo scanner at a resolution of 800 dpi. As root 184 systems were small and young, we decided to measure traits on the entire root system. This included 185 mainly first to third order roots and a small fraction of higher order roots. 99.98 % of root length 186 within the entire experiment belonged to roots with a diameter < 2 mm. 187 188 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 8 Trait measurements 189 Total root length and volume as well as the average root diameter (D [mm]) were measured using 190 WinRhizo 2017 software (Regent Instruments Inc., Québec, Canada). Aboveground and belowground 191 dry biomass was determined after drying at 60°C for at least three days. The mycorrhizal growth 192 response (MGR) of each plant species was calculated as MGR= ln[total dry biomass inoculated / total 193 dry biomass non-inoculated] (Hoeksema et al., 2010; Maherali, 2014). All other root traits were 194 measured within the mycorrhizal treatment assuming that this resembles the natural soil biotic 195 condition. Root dry biomass was used to calculate the specific root length (SRL – root length/dry 196 biomass [m/g]) and root tissue density (RTD – dry biomass/root volume [g/cm³]) by calculating the 197 volume as the sum of 0.2 mm diameter size classes according to Rose (2017). 198 Root-hair length (HL [µm]), cortex fraction (CF [%]) and first order root diameter (Dfirst [mm]) were 199 measured on the preserved first order root tips of three randomly chosen replicates per species from 200 the mycorrhizal treatment using a fluorescence microscope (Zeiss Axio Imager 2, Carl Zeiss AG, 201 Oberkochen, Germany). One root per replicate was randomly picked and dyed in 0.01% Calcofluor-202 white (Thermo Fisher Scientific, Waltham, USA) for 5-10 seconds. Subsequently, it was rinsed in DI 203 water for a few seconds, mounted on a slide and carefully covered with a cover slip without applying 204 pressure. As Calcofluor-white binds to cellulose, it helps distinguish plant cell walls including those of 205 fine root hairs. As all roots were small and translucent there was no need for cross sectioning to 206 measure stele and cortex diameter (Fig. S1). Microscopic images were taken with a Zeiss AxioCam at 207 a magnification of x50 using a 430 nm fluorescence filter. For each replicate, several images were 208 taken using the functions “Z-Stacks” and “Tiles” to display a continuous segment of 5 mm within the 209 mature root hair zone. The “Tiles” function merges several images along the root while the “Z-210 Stacks” function combines images vertically, thereby producing an in-focus image throughout the 211 entire range of depths. We defined the Z-Stacks to range from the middle of the stele to the upper 212 epidermal layer of the root just beneath the cover slip. The first order root diameter (Dfirst) as well as 213 the stele diameter were measured at three positions along the image. We calculated the cortex 214 frac tion (CF) as the percent area of a first order root cross section that is occupied by tissue outside 215 the stele (Freschet et al., 2021a). Mean values of Dfirst and CF were first calculated at replicate level 216 and subsequently at the species level. HL was measured according to Delhaize et al. (2012). In brief, 217 we divided the 5 mm root segments into 5 sub-segments of 1 mm each and measured the length of 218 the longest root hair on each side of the root in each sub-segment (i.e. 2 root hairs per sub-segment). 219 All 10 measurements per 5 mm root segment were averaged to calculate the mean HL per replicate. 220 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 9 Mycorrhizal status (obligate mycorrhizal, facultative mycorrhizal, non-mycorrhizal) was assigned on 221 species level according to the FungalRoot database (Soudzilovskaia et al., 2020). In case of conflicting 222 status reports within the database, we followed the provided expert recommendations. 223 224 For the determination of the percentage of mycorrhizal colonization (%M) and the root-hair 225 incidence (HI [%]), we used representative subsamples of the dried root systems of the three 226 replicates from the mycorrhizal treatment of each species (Freschet et al., 2021a). Furthermore, one 227 replicate per species in the non-mycorrhizal treatment was randomly chosen and checked for AM 228 colonization. Roots were first cleared in 10% (w/v) KOH for 15 min at 80°C and then stained in 0.05% 229 (w/v) Trypan Blue in lactoglycerol for another 15 min at 80°C. Mycorrhizal colonization was 230 determined with the magnified intersection method (McGonigle et al., 1990) at a magnification of 231 x200, using a minimum of 30 root pieces on a slide to count presence or absence of mycorrhizal 232 structures in general (colonization rate) and of arbuscules in specific (rate of arbuscular colonization) 233 in 50-100 intersects. Mycorrhizal hyphae were identified based on their staining, their growing habit 234 (intraradical between cortical cells) and their missing of irregular septation. Due to the commercial 235 inoculum, there was very little contamination with other fungi. For the non-mycorrhizal treatment, 236 mycorrhizal colonization rates between 1% and 6% were detected for 6 out of 82 replicates 237 suggesting very limited contamination. Within the mycorrhizal treatment colonization rates of up to 238 86% and rates of arbuscular colonization up to 72% clearly confirmed a successful inoculation. HI was 239 determined simultaneously and analogously to %M, recorded as presence or absence at each 240 intersect (Siqueira & Saggin-Júnior, 2001), giving a proxy of how much percent of the root length was 241 covered by root hairs. 242 The coefficients of variation of HI and HL (cvHI, cvHL) were calculated by using the general R function 243 cv(x) that computes the sample coefficient of variation as (SD/mean)*100. To display the within-244 species correlation between %M and HI of all species while accounting for overall between-species 245 differences in both traits, we normalized the data by coding the intraspecific median of the three 246 trait records per species as 0, the lower value as = lower value – median value and the higher value 247 as = h igher value – median value. 248 Root nitrogen concentration (N [%]) was measured on the three replicates, after drying and milling 249 the roots, using an Elemental Analyzer (Euro EA, HEKAtech, Wegberg, Germany). 250 251 252 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 10 Analysis 253 All analyses were carried out in R version 3.6.3 (R Core Team, 2020). To explore phylogenetic 254 patterns in the root hair data we used the function drop.tip() from the package ape (Paradis et al., 255 2004) to prune the DaPhnE phylogeny (Durka & Michalski, 2012) for our species set and the function 256 phylosig() as well as phylo.heatmap() from the package phytools (Revell, 2012) to calculate the 257 phylogenetic signal of all traits and to display trait variation along the tree by using color palettes 258 from the package viridis (Garnier, 2018). The package ggplot2 (Wickham, 2010) was used to display 259 violin plots, the pairwise correlation heatmap and the correlation between %M and HI at intraspecific 260 level and the package cowplot (Wilke, 2024) was used for multipanel figures. 261 Prior to the calculation of pairwise correlations and principal component analyses (PCA), we 262 improved data distribution by applying log transformation for all traits except CF, HI and %M, which 263 we transformed using the function logit() from the gtools (Warnes et al., 2020) package, since these 264 traits varied between 0 and 1. The function rcorr() from the package Hmisc (Harrell, 2020) was used 265 to calculate Pearson’s correlations of all trait pairs, and the functions comparative.data() and pgls() 266 from the package caper (Orme et al., 2018) were used to calculate phylogenetically corrected 267 pairwise correlations. We determined the phylogenetically corrected correlation coefficient by taking 268 the square root from the adjusted r² of the model multiplied by -1 in case of a negative regression 269 coefficient while assigning r=0 in case of negative adjusted r² values. The phylogenetically informed 270 PCAs were calculated using phyl.pca() from the package phytools (Revell, 2012) and displayed using 271 functions from the package shape (Soetaert, 2014). Ellipsoids were plotted using the package ellipse 272 (Murdoch & Chow, 2024). Permanova based on euclidean pairwise distances in PCA space among 273 groups were performed using the pairwise.adonis() function from the package pairwiseAdonis 274 (Martinez Arbizu, 2019). 275 We further used the packages dplyr (Wickham et al., 2020a), Rmisc (Hope, 2013), raster (Hijmans, 276 2020), data.table (Dowle & Srinivasan, 2020) and devtools (Wickham et al., 2020b) for general data 277 handling and exploration. 278 279

280 Root hair traits show a phylogenetically conserved pattern 281 R oot-hair length and incidence showed strong phylogenetic signals (Fig. 1, Table S1) and were highly 282 positively correlated (Fig. S2). Monocotyledons showed many long root hairs, with the hairless Allium 283 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 11 schoenoprasum being the only exception, while legumes (Fabaceae) had few and short root hairs 284 (Fig. 1). Within the other dicotyledonous families, Asteraceae showed low values while 285 Polygonaceae, Caryophyllaceae and Brassicaceae showed high values for both root-hair length and 286 incidence. Throughout the entire set of species, mycorrhizal colonization showed a completely 287 inverted pattern which was strongly phylogenetically conserved as well (Fig. 1, Table S1). Clades with 288 long root hairs and high root-hair incidence were poorly colonized by mycorrhizal fungi, while clades 289 with short and few root hairs showed high colonization rates. Root-hair length and incidence were 290 both negatively correlated with mycorrhizal colonization. This pattern disappeared for root-hair 291 length after phylogenetic correction (Fig. S2). 292 Examining plant functional types, root-hair length was lower in legumes than in grasses and forbs, 293 with grasses having the longest root hairs overall (Fig. 2a). The coefficient of variation in root-hair 294 length did not differ significantly among these plant functional groups, even though grasses tended 295 to have the least variation (Fig. 2e). Root-hair incidence was higher and its coefficient of variation 296 was lower in grasses than in both legumes and forbs (Fig. 2b,f). 297 298 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 12 299 Fig. 1: The phylogenetically conserved trade-off between the investment in root hairs and 300 mycorrhization. Colour-coded are the species mean values of root-hair length and incidence as well 301 as percent mycorrhizal colonization to the right and the corresponding phylogenetic tree with 302 broader taxonomic groups to the left. Trait values are standardized to the same range, colour-coded 303 from yellow (low) via green (medium) to blue (high). Phylogenetic signal of each trait is displayed as 304 Pagel´s lambda. Grasses are shaded in medium grey, non-leguminous forbs in light grey and 305 leguminous forbs in dark grey. Allium schoenoprasum L. with the lowest hair incidence had no root 306 hairs in the samples for determination of hair length leading to a missing value. 307 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 13 308 Fig. 2: Variation in root hair traits according to plant functional type and mycorrhizal status. 309 Displayed are raw data (upper panels) of species mean root-hair length (HL, panel a, c) and incidence 310 (HI, panel b, d) as well as the coefficient of variation (lower panels) in root-hair length (cvHL, panel e, 311 g) and incidence (cvHI, panel f, h). Displayed are kernel density distributions and group means (black 312 dots) with 95% confidence intervals. Non-overlapping confidence intervals are highlighted by a 313 coloured ribbon to visualize group differences. Plant functional types: grasses, forbs, legumes; 314 mycorrhizal status: obligate mycorrhizal (AM), facultative mycorrhizal (AM-NM), non-mycorrhizal 315 (NM). 316 317 Mycorrhizal status is not a strong predictor of root-hair traits 318 Of the 82 grassland species tested in the experiment, 64 were obligate mycorrhizal, 9 facultative 319 mycorrhizal and 9 non-mycorrhizal, as classified according to the FungalRoot database. Mycorrhizal 320 status did not predict species root-hair length or its coefficient of variation well, even though 321 obligate mycorrhizal species tended to have shorter root hairs (Fig. 2c). Root-hair incidence instead 322 was lower in obligate mycorrhizal species than in non-mycorrhizal species, while facultative 323 mycorrhizal species had intermediate values (Fig. 2d). The coefficient of variation of root-hair 324 incidence showed the opposite pattern with obligate mycorrhizal species being more variable than 325 non-mycorrhizal species, and facultative mycorrhizal species showing intermediate values again (Fig. 326 2h). 327 328 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 14 An ecological trade-off between root hairs and mycorrhization 329 The phylogenetically informed PCA revealed a strong trade-off (PC 1 = 45%) between high root-hair 330 incidence and length on one end, and high mycorrhizal colonization rates on the other, accompanied 331 by an increase in variation in root-hair incidence (Fig. 3, Table S2). PC 2 explained 23% of variation, 332 with the coefficient of variation of root-hair length influencing this axis most strongly. 333 Mycorrhizal status as well as plant functional types affected species locations within the PCA (Table 334 S3). Non-mycorrhizal species differed from obligate mycorrhizal species by being closely aggregated 335 at high values of root-hair incidence on PC 1. Grasses differed from both forbs and legumes by 336 showing high root-hair incidence as well, even though considerable variation occurred within each of 337 the functional types. Legumes were located at high values of mycorrhizal colonization and variation 338 in root-hair incidence on PC 1 while spanning the entire range of PC 2. 339 340 341 342 Fig. 3: Phylogenetically informed principal component analysis of root hair traits and mycorrhizal 343 colonization rate. Panel a displays species based on their mycorrhizal status (obligate mycorrhizal - 344 AM, facultative mycorrhizal - AM-NM, non-mycorrhizal - NM) while panel b displays species based on 345 their plant functional group (grasses, forbs, legumes). Ellipsoids and large dots display 95% 346 confidence intervals and centroids. PCA results can be found in table S2. HL – hair length, HI – hair 347 incidence, cvHL – coefficient of variation in hair length, cvHI – coefficient of variation in hair 348 incidence, %M - percent mycorrhizal colonization. 349 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 15 350 At the intraspecific level, root-hair incidence correlates with mycorrhizal colonization rate but 351 species show strong heterogeneity 352 Despite low within-species replication (n = 3 individual plants per species scored for root hair traits), 353 we could detect an overall association between root-hair incidence and mycorrhizal colonization rate 354 (Fig. 4). Individual plants with higher colonization rates had lower root-hair incidence than less-355 colonized individuals within the same species. Overall, we found a slight negative correlation (slope = 356 -0.29, p<0.001) with small confidence intervals. However, there was considerable variation among 357 species. No intraspecific correlation was found between the mycorrhizal colonization rate and root-358 hair length. 359 360 361 Fig. 4: Intraspecific correlation of root-hair incidence and mycorrhizal colonization. Displayed is the 362 relative difference in mycorrhizal colonization (%M) and root-hair incidence (HI) within each species 363 as well as the overall correlation with 95% confidence interval. 364 365 Root-hair traits add to the root economics space 366 The inclusion of root-hair traits introduced a new dimension to the root economics space. The first 367 axis (22%) of the extended PCA (Fig. 5, Fig. S3, Table S4) was dominated by specific root length on 368 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 16 one end and root average diameter and diameter of first order roots on the other, accompanied by 369 variation in cortex fraction but also root-tissue density. The trade-off between the investment in 370 root-hair length and incidence on one end and the coefficient of variation of root-hair incidence on 371 the other dominated the second axis (20%). Mycorrhizal colonization intensity and mycorrhizal 372 growth response were associated with variation in root-hair incidence. Root-tissue density loaded 373 strongest on the third axis (14%) together with the coefficient of variation of root-hair length and 374 antagonistically to root-nitrogen concentration and cortex fraction. 375 Plants of different mycorrhizal status as well as different plant functional types differed in their root 376 economic strategies within the space (Table S5). Non-mycorrhizal and facultative mycorrhizal plants 377 differed from obligate mycorrhizal plants, while non-mycorrhizal plants showed the highest specific 378 root length on PC1 and highest root-hair length and incidence on PC2, and there was no general 379 pattern along PC3. Obligate mycorrhizal plants spanned the entire space but clearly showed the 380 highest values for root diameter on PC1, lowest root-hair incidence and highest colonization rate on 381 PC2 and highest root-nitrogen concentration on PC3. Legumes were located at high root diameter, 382 cortex fraction and colonization rate as well as high root-nitrogen concentration. Grasses showed a 383 clear trend towards high root-hair length and incidence as well as specific root length. As such, 384 grasses and legumes formed distinct groups almost without overlap, while forbs spanned the entire 385 root economics space. 386 387 388 389 Fig. 5: Extended phylogenetically informed principal component analysis. Displayed are species 390 based on their mycorrhizal type (obligate mycorrhizal - AM, facultative mycorrhizal – AM-NM, non-391 mycorrhizal - NM). Ellipsoids and large dots display 95% confidence intervals and centroids. PCA 392

can be found in Table S4. HL – hair length, HI – hair incidence, cvHL – coefficient of variation 393 in hair length, cvHI – coefficient of variation in hair incidence, %M - % mycorrhizal colonization, SRL – 394 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 17 specific root length, AD – average diameter, Dfirst – diameter of first order roots, CF – cortex fraction, 395 RTD – root tissue density, N – root nitrogen concentration, MGR – mycorrhizal growth response. 396 397

398 Plants can either invest in root hairs or rely on mycorrhizal partners while maintaining variation in 399 root-hair incidence 400 We found a striking pattern of an evolutionarily conserved trade-off between plant investment in 401 root hairs – specifically their incidence – and mycorrhizal symbiosis. The phylogenetic conservation 402 occurred at high taxonomic levels; grasses showing high root-hair incidence and length, paired with 403 low mycorrhizal colonization rates, while legumes exhibited the opposite pattern (Fig. 1 and 2). This 404 supports existing knowledge on grasses and legumes (Hill et al., 2006). Non-leguminous forbs 405 exhibited a range of strategies along the entire gradient of variation. This is an expectable result, 406 given that forbs are not monophyletic and comprise all forms of mycorrhizal status. An evolutionarily 407 deep-rooted phylogenetic signal might be the reason why many correlations between raw trait data 408 disappeared after phylogenetic correction. 409 In contrast to the level of mycorrhizal colonization, we found mycorrhizal status to be a weak 410 predictor of root-hair traits. The traditional mycorrhizal status classification of species as being 411 obligate, facultative or non-mycorrhizal and the respective definitions have been discussed lately 412 (Cosme et al., 2018; Brundrett & Tedersoo, 2019). Cosme et al. (2018) argue that species classified as 413 being non-mycorrhizal can have low levels of colonization and even a few arbuscules. We found the 414 same pattern in our species classified as non-mycorrhizal with low colonization rates and no or very 415 few arbuscules. Moreover, we found that these species had high root-hair length and incidence, 416 hence resembling an extreme do-it-yourself trait syndrome. 417 Non-mycorrhizal plants can be subdivided based on their phosphorus (P) acquisition strategy as P-418 scavengers, which rely on dissolved P, and P-miners, which exude organic compounds that release 419 fixed P (Lambers et al., 2008; Lambers & Teste, 2013; Yu et al., 2020). Carex vulpina, as the only non-420 mycorrhizal species with a P-mining strategy in our dataset showed the highest HI but only an 421 av erage HL within the non-mycorrhizal status. A larger number of Proteaceae type species (P-miners) 422 would be needed to draw general conclusions about HL and HI patterns of the different non-423 mycorrhizal P acquisitions strategies. Hence, our results can be considered representative only for P 424 scavenging species. 425 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 18 The classification of facultative mycorrhizal species includes both species that are mycorrhizal only 426 under specific circumstances (like nutrient deficiencies) and species that always have low 427 colonization rates; hence plants with different ecological strategies (Brundrett & Tedersoo, 2019; 428 Soudzilovskaia et al., 2020). Furthermore, the status ‘facultative’ can be misleading in case of 429 conflicting observations for species with an overall low data record. Accordingly, we found strong 430 overlap in root-hair traits between obligate and facultative mycorrhizal species, even though the 431 latter tended to have more and longer root hairs as we would have expected given the fact that they 432 have lower colonization rates (Fig. S4). The categories of facultative and obligate mycorrhizal species 433 seem to not be informative for root hair patterns. However, non-mycorrhizal plants differed strongly 434 from obligate mycorrhizal plants by having higher root-hair incidence and lower variation therein. 435 This pattern also dominated the overall gradual trade-off between the investment in root hairs and 436 mycorrhiza: a strong investment in root-hair incidence was accompanied by low variation of the 437 same trait. Species with high mycorrhizal colonization rates produce fewer root hairs but encompass 438 more intraspecific variation. The coefficient of variation provided us with a scale-independent 439 measure of variation. It should be noted though that at a given standard deviation, it is inversely 440 related to the mean value, hence mathematically favoring high mean trait values to coincide with low 441 variation of the same trait. Given the fact that being mycorrhizal can be a competitive advantage in 442 many though not all terrestrial habitats (Brundrett & Tedersoo, 2018), it remains to be studied how 443 root hair traits add to the filtering of environmental variation for species occurrence (Laughlin et al., 444 2021). 445 446 Intraspecific variation in root-hair incidence and mycorrhizal colonization mirrors the interspecific 447 pattern 448 Although this experiment was not designed to test for intraspecific variation, we could show that 449 overall, the within-species root-hair incidence was higher at lower colonization rates. We cannot 450 determine if this variation originates from a plastic response of the plant to different colonization 451 levels of the AM fungus or from genetic variation between plant individuals. Further research is 452 needed to evaluate this question and to determine cause and effect. Plasticity in both root-hair 453 length and incidence has been reported in response to soil P (Bates & Lynch, 1996, 2000b; Zhu et al., 454 2010) as well as mycorrhizal inoculation (Price et al., 1989; Sun & Tang, 2013; Wu et al., 2016). 455 Suggestions about the resource costs of root hairs being higher (Price et al., 1989) or lower (Brown et 456 al., 2013a) than those of the mycorrhizal symbiosis differ widely, while soil moisture and P availability 457 (Brown e t al. , 2013a; Fort et al., 2015; Ma et al., 2021) further mediate the effects. Given the design 458 of our study with homogeneous soil fertilization, we cannot test the effect of soil P on root hair traits 459 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 19 and their variability. Specifically, it remains to be studied if facultative mycorrhizal species show 460 higher coefficients of variation in root-hair incidence and length under different levels of soil P. 461 Furthermore, patterns might change over time, given the fact that we analyzed young plants. 462 Nevertheless, our results suggest an overall intraspecific trade-off between root-hair incidence and 463 mycorrhizal colonization mirroring the interspecific pattern and leading to stronger variation in root-464 hair incidence in obligate mycorrhizal species with high colonization rates. 465 466 Root hairs add to the do-it-yourself strategy of plants 467 The trade-off between root hairs and mycorrhizal colonization rate defined the second axis of the 468 principal component analysis on all traits, with the root traits of the collaboration gradient 469 dominating the first and those of the conservation gradient the third axis. The first axis resembled 470 the collaboration gradient with a trade-off between ‘do-it-yourself’ with high SRL and ‘outsourcing’ 471 with high root diameter and cortex fraction as expected within the framework of the root economics 472 space (Bergmann et al., 2020; Ding et al., 2020; Wen et al., 2022). RTD also loaded on axis 1 – though 473 less than on axis 3 - with a considerable amount of variation, being negatively correlated to SRL. This 474 correlation has been reported before (Eissenstat, 1992; Reich, 2014) and might originate from the 475 fact that, for a given diameter SRL, has to increase with decreasing RTD (Ostonen et al., 2007). This 476 might be the most important driver behind former detection of a one dimensional root economics 477 spectrum that parallels leaf economics (Freschet et al., 2010; Reich, 2014). 478 On axis 2, root-hair length and incidence behaved antagonistically to the degree of variation in root-479 hair incidence accompanied by mycorrhizal colonization rate and growth response. With 20% 480 variance, the trade-off explained a considerable amount of variation within the entire trait space. 481 Mycorrhizal colonization was less strongly associated with the first axis than with the root-hair 482 dominated second axis, though the bivariate correlation with cortex fraction was strong as expected 483 in the concept of the collaboration gradient. Since mycorrhizal colonization was measured on the 484 same microscopy slides as root-hair incidence, while root-hair length and cortex fraction were 485 measured separately, we do not expect a methodological bias here. As for the correlation with %M, 486 both traits of the first and the second axis link to the functional concept of collaboration. This is in 487 line with the scheme proposed by Wen et al. (2019) who found species to either rely on a root 488 morphology of high absorptive surface, which can be achieved in different ways (in their case by high 489 SRL or branching) or on mycorrhizal symbiosis and a high root diameter for P-scavenging. Root hairs, 490 as another absorptive structure added to the concept, are also involved in P-mining by exudation 491 (Wen et al., 2022) but the respective impact on their association with the collaboration gradient is 492 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 20 yet to be explored as P-mobilizing exudates were not measured in the current study. Taken together, 493 it remains to be tested on a larger set of species, if the inclusion of root hair traits widens the 494 collaboration gradient to a plane encompassing different strategies for do-it-yourself resource 495 acquisition. 496 The third axis resembled the conservation gradient proposed as the belowground analogue of the 497 fast-slow economic spectrum in leaves (Weigelt et al., 2021), with RTD representing the ‘slow’ and 498 root-N concentration representing the ‘fast’ strategy. The degree of variation in root-hair length was 499 also associated with the ‘slow’ strategy on axis three. We can only speculate that this might be 500 related to the fact that slow growing species invest in fine roots with a longer lifespan. Hence those 501 species might keep the ability to alter the length of the comparably more short-lived root hairs given 502 the fact that their surface provides the main absorptive structure for those species (Fort et al., 2015). 503 Cortex fraction loaded on the ‘fast’ side of axis three. We hypothesize that this unexpected link might 504 occur because AMF also enhance species N uptake under limiting conditions (Govindarajulu et al., 505 2005; Hodge & Fitter, 2010). As root-N concentration, cortex fraction and colonization rate were 506 measured on the same replicates, the effect of mycorrhizal colonization rate on root-N concentration 507 and a resulting positive correlation (r=0.3) might be overestimated by our data, which were 508 measured on plants growing under relatively low nutrient conditions. Furthermore, our experiment 509 was restricted to a single AMF species and excluded plant mycorrhizal types other than arbuscular 510 mycorrhiza. Ectomycorrhizal species tend to occupy areas of the ‘slow’ strategy in the root 511 economics space (Bergmann et al., 2020), hence adding variation to the conservation gradient that is 512 not covered in the present experiment. It is also important to notice that, due to the nature of the 513 ectomycorrhizal symbiosis with fungal hyphae covering entire fine roots and leading to fast 514 degradation of root hairs (Farquhar, 1996) the importance of root-hair traits might change in a global 515 dataset. 516 517

518 We can support the hypothesis that investment into root hairs and mycorrhizal partnerships are 519 alternative ecological strategies for soil exploration and resource uptake with a strong evolutionary 520 history. This interspecific ecological trade-off is mirrored at the intraspecific level with plants showing 521 more root hairs at lower mycorrhizal colonization rates. Strong heterogeneity between species calls 522 for further investigations of intraspecific patterns. A high degree of variation in root-hair incidence is 523 a ssociated with high mycorrhizal colonization rates and growth response at the species level. The 524 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 21 ecological trade-off between the investment in root hairs and the degree of variation in incidence 525 being intraspecifically correlated with mycorrhizal colonization rates dominates the second axis of 526 the root economics space. We conclude that variation in root-hair patterns is neither fully aligned 527 with the conservation gradient nor the existing concept of the collaboration gradient but rather 528 introduces a new dimension of variation into the picture. Still, regarding the strong trade-off with 529 mycorrhizal colonization, we consider root hairs, and specifically their incidence, to add to the 530 ecological strategy of ‘do-it-yourself’. Hence, we find the concept of collaboration to span the first 531 and second and the conservation gradient to represent the third axis of variation in the root 532 economics space. These results present strong evidence that root hairs are a considerable source of 533 variation in fine root morphology that should be considered when studying belowground plant 534 functioning. 535 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 22

536 We thank Erik Faltin, Cathrin Schierenbeck, Anja Wulf, Max Fussan, Maxi Bergmann and many others 537 for help with root washing and scanning. We further thank Julien Bachelier for use of the 538 fluorescence microscope and in particular Maria Schauer for sharing her knowledge about fixation 539 and microscopy of plant material. 540 We also thank the managers of the three Biodiversity Exploratories, Konstanz Wells, Swen Renner, 541 Kirsten Reichel-Jung, Sonja Gockel, Kerstin Wiesner, Katrin Lorenzen, Andreas Hemp, Martin Gorke 542 and Miriam Teuscher, and all former managers for their work in maintaining the plot and project 543 infrastructure; Christiane Fischer for giving support through the central office, Andreas Ostrowski for 544 managing the central data base, and Markus Fischer, Eduard Linsenmair, Dominik Hessenmöller, 545 Daniel Prati, Ingo Schöning, François Buscot, Ernst-Detlef Schulze, Wolfgang W. Weisser and the late 546 Elisabeth Kalko for their role in setting up the Biodiversity Exploratories project. The work has been 547 funded by the DFG Priority Program 1374 "Infrastructure-Biodiversity-Exploratories". Field work 548 permits were issued by the responsible state environmental offices of Baden-Württemberg, 549 Thüringen, and Brandenburg. We acknowledge funding from the German Research Foundation (DFG, 550 grants 432975993 to JB, KL 1866/12-1 to MvK and 323522591 to MR). 551 552 Author contribution 553 JB designed and performed the experiment, ran the analyses and wrote the paper. TL contributed to 554 the analysis and the conceptual development of the study and revised the paper. KB and EB 555 participated in the experiment and data exploration. EM revised the paper. MvK and MR contributed 556 to the study design and revised the paper. 557 558 Data availability 559 This work is based on data elaborated by the RootFun project (323522591) and further analyzed 560 within the HAIRphae project (432975993) of the Biodiversity Exploratories program (DFG Priority 561 Program 1374). All data used is publicly available in the Biodiversity Exploratories Information System 562 (http://doi.org/10.17616/R32P9Q) under dataset ID ##### (will be linked upon acceptance) or in 563 databases referenced. The authors explicitly encourage appropriate usage and database 564 implementation of the data. 565 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint 23

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DOMORT., Poaceae, 790 obligate mycorrhizal. 791 Fig. S2: Pairwise correlations of all measured traits. 792 Fig. S3: Extended phylogenetically informed principal component analysis. 793 Fig. S4: Variation in mycorrhizal colonization (%M) between plants of different mycorrhizal status. 794 Table S1: Phylogenetic signal of all measured traits. 795 Table S2: Phylogenetically informed principal component analysis of root hair traits and %M. 796 Table S3: Permanova based on pairwise dissimilarities of plant functional types and mycorrhizal 797 types within the principal component analysis displayed in Table S2. 798 Table S4: Extended phylogenetically informed principal component analysis. 799 Table S5: Permanova based on pairwise dissimilarities of plant functional types and mycorrhizal 800 types within the extended principal component analysis displayed in Table S4. 801 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted May 14, 2026. ; https://doi.org/10.64898/2026.05.13.723781doi: bioRxiv preprint