DOI: 10.5061/dryad.0gb5mkmdg
title: Data from: Ectomycorrhizal fungi and root water uptake respond independently to water availability

description: Temperate forests on their warm and dry distribution limits are expected
 to be most vulnerable to reductions in water availability. This prediction
 is mostly based on studies assessing single forest functions, mainly
 growth. Water and nutrient cycling are functions that rely on tree roots
 and their symbiotic association with ectomycorrhizal (ECM) fungi. Trees
 can compensate for seasonal reductions in water availability by shifting
 root water-uptake (RWU) towards deeper soil layers, but ECM fungi mostly
 dwell in the topsoil, thus suffering from desiccation and compromising
 nutrient uptake. We hypothesised that drier sites should depict larger
 seasonal shifts in RWU, but at the expense of lower ECM fungal diversity
 and colonization of fine roots by ECM fungi. We selected three beech
 (Fagus sylvatica) forests in their warm distribution limit with
 contrasting geographic locations and mean annual precipitation: northern
 Atlantic (2500mm), intermediate transitional (1150mm), and southern
 Mediterranean (780mm). We collected soil, stem, and root samples in spring
 (wet) and summer (dry) to: (1) quantify fine-root density and colonization
 by ECM fungi, (2) infer RWU from isotopic composition of plant and soil
 water, and (3) characterize ECM communities through DNA-metabarcoding.
 Generalized and linear mixed models revealed that high topsoil moisture
 benefited ECM diversity, but higher diversity and ECM colonization did not
 imply larger contributions of the topsoil to RWU. The prevailing climate
 and abiotic conditions determined how ECM communities were structured,
 more than seasonal climatic variability. Across sites, communities
 differed in their functional diversity: ECM fungi with long hyphae, more
 vulnerable to water scarcity, dominated at the southernmost site, where
 water availability was the highest. Our results suggest that, in a climate
 change scenario, increasing drought might not compromise RWU, but it would
 still be detrimental for ECM communities, compromising key ecosystem
 services such as nutrient cycling and productivity.
description: # Data from: Ectomycorrhizal fungi and root water uptake respond
 independently to water availability Dataset DOI:
 [10.5061/dryad.0gb5mkmdg](10.5061/dryad.0gb5mkmdg) ## Description of the
 data and file structure This dataset includes ten datafiles and one script
 used in this publication: Title: Ectomycorrhizal fungi and root water
 uptake respond independently to water availability Authors list: Asun
 Rodríguez-Uña, David Moreno-Mateos, Silvia Matesanz, Lisa Wingate, Adrià
 Barbeta, Javier Porras-Gómez , Teresa E. Gimeno Accepted for publication
 in Oikos on the 28th June 2025 Corresponding author: Asun Rodríguez-Uña
 ([ar2190@cam.ac.uk](mailto:ar2190@cam.ac.uk),
 [asun.rodez@gmail.com](mailto:asun.rodez@gmail.com)) Data corresponds to
 soil, stem and root samples collected in spring (wet) and summer (dry)
 from three beech forests in their warm distribution limit with contrasting
 geographic locations and mean annual precipitation. Data analyses enable
 to (1) quantify fine-root density and colonization by ECM fungi, (2) infer
 RWU from isotopic composition of plant and soil water, and (3)
 characterize ECM communities through DNA-metabarcoding.  ### Files and
 variables #### File: wi_sample_list.csv This file contains the list of
 samples collected for analyses of water isotopic composition and
 volumetric water content. In each sampling campaign, three soil samples
 were collected at different depths in each selected tree, plus one
 lignified branch segment. One groundwater sample was also collected on
 each study site in each sampling campaign. * Sample -&gt; character
 variable. Unique identifier of each sample * Site -&gt; factor variable
 with three levels. Name of the site (Artikutza, Northern site; Iturrieta,
 Intermediate site; Diustes, Southern site) * Tree -&gt; character
 variable. Unique identifier of the sampled tree for wood samples (see
 variable “Type”) or the tree next to the sampling point for soil samples
 (see variable “Type”). * Campaign -&gt; factor variable with two levels
 (Jun and Aug). Sampling campaign (spring/June 2020 or summer/August 2020)
 * Date -&gt; numerical variable. Sampling collection date in YYYYMMDD *
 Type -&gt; factor variable with three levels (soil, wood and water). Type
 of sampled material. * Description -&gt; character variable. Sampling
 depth for soil samples, type of material collected (branch vs. wood core)
 for wood samples and location of source for water samples. #### File:
 water_extraction_data.csv This file contains the list of samples collected
 for analysing relative water content. In each sampling campaign, three
 soil samples were collected at different depths in each selected tree,
 plus one lignified branch segment. * Sample -&gt; character variable.
 Unique identifier of each sample * Type -&gt; factor variable with two
 levels (SOIL TOP, STEM TISSUE). Source of each sample * Weight_sample_soil
 -&gt; numerical variable. Weight of the soil sample transferred to the
 extraction vessel in g. * Fresh_sample_soil -&gt; numerical variable.
 Fresh weight of the sample and the extraction vessel in g.   *
 Water_volume_in_sample -&gt; numerical variable. Weight difference between
 fresh and dry samples corresponding to the volume (or mass) of water in g.
 #### File: soilProperties.csv This file contains soil physical and
 chemical properties measured on three locations per study site. At each
 location, three samples were collected at different depths. The variables
 included in this file are: * Sample -&gt; character variable. Unique
 identifier of each sample * site -&gt; factor variable with three levels.
 Name of the site (Artikutza, Northern site; Iturrieta, Intermediate site;
 Diustes, Southern site) * closest_tree: character variable. The unique
 identifier of the closest tree to the location of sample collection *
 up_depth -&gt; numerical variable. Upper depth of sample collection in cm
 * lw_depth -&gt; numerical variable. Lower depth of sample collection in
 cm * collection date -&gt; numerical variable. Sampling collection date in
 YYYYMMDD * clay_perc -&gt; numerical variable. Percentage of clay *
 fine_sand_perc -&gt; numerical variable. Percentage of fine sand *
 coarse_sand_perc -&gt; numerical variable. Percentage of coarse sand *
 loam_perc -&gt; numerical variable. Percentage of fine sand * K -&gt;
 numerical variable. Potassium concentration in mg kg-1 * NO3. -&gt;
 numerical variable. Nitrate concentration in mg kg-1 * NH4. -&gt;
 numerical variable. Ammonium concentration in mg kg-1 * total_C -&gt;
 numerical variable. Percentage of total carbon * total_N -&gt; numerical
 variable. Percentage of total nitrogen * total_P -&gt; numerical variable.
 Total phosphorous content in g kg-1 * pH -&gt; numerical variable. Soil pH
 (unitless) * Conductivity -&gt; numerical variable. Soil conductivity in
 microS cm-1 * Psi_sub_e -&gt; Parameter derived from the soil texture
 classification describing the air entry water potential in J kg-1.
 Obtained from:
 [https://doi.org/10.1007/978-1-4612-1626-1](https://doi.org/10.1007/978-1-4612-1626-1) * b\_ -&gt; Parameter from the soil moisture release equation (unitless) derived from the soil texture classification. Obtained from: [https://doi.org/10.1007/978-1-4612-1626-1](https://doi.org/10.1007/978-1-4612-1626-1) * theta_sub_s -&gt; Parameter derived from the soil texture classification describing the soil saturation water content in m3 m-3. Obtained from: [https://doi.org/10.1007/978-1-4612-1626-1](https://doi.org/10.1007/978-1-4612-1626-1) * sand_total_perc -&gt; numerical variable. Total percentage of sand, that is the sum of fine_sand_perc and coarse_sand_perc. #### File: rwcSoil.csv This file contains soil gravimetric and volumetric water content measured next to each one of the study trees. Next to each tree, three samples were collected at different depths. The variables included in this file are: * site -&gt; factor variable with three levels. Name of the site (Artikutza, Northern site; Iturrieta, Intermediate site; Diustes, Southern site) * season -&gt; factor variable with two levels (Jun and Aug). Sampling campaing (spring/June 2020 or summer/August 2020) * tree -&gt; character variable. Unique identifier of the tree next to the sampling point * soilDepth -&gt; factor variable with three levels (Upper, Shallow, Deep). Sampling depth (0-5 cm, upper; 20-25 cm, shallow; 40-45 cm, deep) * gwc -&gt; numerical variable. Gravimetric water content, unitless * vwc -&gt; numerical variable. Volumetric water content, unitless #### File: treeWI.csv This file contains water isotopic composition of wood samples collected from the studied trees. The variables included in this file are: * Tree-&gt; character variable. Unique identifier of the sampled tree * Site -&gt; factor variable with three levels. Name of the site (Artikutza, Northern site; Iturrieta, Intermediate site; Diustes, Southern site) * Campaign -&gt; factor variable with two levels (Jun and Aug). Sampling campaing (spring/June 2020 or summer/August 2020) * rwc -&gt; numerical variable. Sample relative water content, unitless * dD_cont_corr -&gt; numerical variable. Hydrogen isotopic composition of the extracted tree water expressed in permil using the delta notation. This values has been custom-corrected for instrument drift and potential contamination (see methods of the associated paper for further details). * d18O_cont_corr -&gt; numerical variable. Oxygen isotopic composition of the extracted tree water expressed in permil using the delta notation. This values has been custom-corrected for instrument drift and potential contamination (see methods of the associated paper for further details). * d2H_sap -&gt; numerical variable. Estimated hydrogen isotopic composition of tree sap water expressed in permil using the delta notation. See methods in the associated paper for further details. * d18O_sap -&gt; numerical variable. Estimated oxygen isotopic composition of tree sap water expressed in permil using the delta notation. See methods in the associated paper for further details. #### File: soilWI.csv This file contains water isotopic composition of soil samples collected next to the studied trees. The variables included in this file are: * Tree -&gt; character variable. Unique identifier of the sampled tree * Site -&gt; factor variable with three levels. Name of the site (Artikutza, Northern site; Iturrieta, Intermediate site; Diustes, Southern site) * Campaign -&gt; factor variable with two levels (Jun and Aug). Sampling campaing (spring/June 2020 or summer/August 2020) * soilDepth -&gt; factor variable with three levels (Upper, Shallow, Deep). Sampling depth (0-5 cm, upper; 20-25 cm, shallow; 40-45 cm, deep) * dD_cont_corr -&gt; numerical variable. Hydrogen isotopic composition of the extracted soil water expressed in permil using the delta notation. This values have been custom-corrected for instrument drift and potential contamination (see methods of the associated paper for further details). * d18O_cont_corr -&gt; numerical variable. Oxygen isotopic composition of the extracted soil water expressed in permil using the delta notation. This values have been custom-corrected for instrument drift and potential contamination (see methods of the associated paper for further details). * d2H_soil_text_corr -&gt; numerical variable. Estimated hydrogen isotopic composition of unbound soil water expressed in permil using the delta notation. See methods in the associated paper for further details. * d18O_soil_text_corr -&gt; numerical variable. Estimated oxygen isotopic composition of unbound water expressed in permil using the delta notation. See methods in the associated paper for further details. #### File: OTU_database.csv This file contains the number of reads of each ectomycorrhizal fungal OTU identified in each sample and the corresponding taxonomy and hyphal exploration type assigned to each OTU. At each tree, three fine root samples were collected at different orientations. The variables included in this file are: * otu_code -&gt; character variable. Unique identifier of each ectomycorrhizal fungal OTU * otu_id -&gt; character variable. Shorter unique identifier to each ectomycorrhizal fungal OTU * final_taxonomy -&gt; character variable. Final taxonomy assigned to each ectomycorrhizal fungal OTU * mycelium -&gt; factor variable with three levels (contact-short, medium-long, unknown). Exploration type of the hyphae of each ectomycorrhizal fungal OTU rest of the columns -&gt; numerical variables. Number of reads of each ectomycorrhizal fungal OTU identified in each sample, unitless #### File: ECM_colonization.csv This file contains the ectomycorrhizal fungal colonization rates for each sample. From each sample, three 5cm segments were measured. The variables included in this file are: * site -&gt; factor variable with three levels. Name of the site (ART=Artikutza, Northern site; ITU = Iturrieta, Intermediate site; DIU=Diustes, Southern site) * season -&gt; factor variable with two levels (JUN and AUG). Sampling campaing (spring/June 2020 or summer/August 2020) * date -&gt; numerical variable. Sampling collection date in YYYYMMDD * tree -&gt; character variable. Unique identifier for each sampled tree * id -&gt; character variable indicating the code assigned to each sample * Segment1 -&gt; numerical variable. Number of live ECM root tips identified in fine root segment 1 of 5cm length, unitless * Segment2 -&gt; numerical variable. Number of live ECM root tips identified in fine root segment 2 of 5cm length, unitless * Segment3 -&gt; numerical variable. Number of live ECM root tips identified in fine root segment 3 of 5cm length, unitless #### File: length_vol_roots.csv This file contains the total length of fine roots per unit of soil volume for each sample. The variables included in this file are: * site -&gt; factor variable with three levels. Name of the site (ART=Artikutza, Northern site; ITUIturrieta, Intermediate site; DIU=Diustes, Southern site) * season -&gt; factor variable with two levels (JUN=June, AUG=August). Sampling campaign (spring/June 2020 or summer/August 2020) * tree -&gt; character variable. Unique identifier of the sampled tree * sample -&gt; character variable. Unique identifier of each sample * leng_vol -&gt; numerical variable. Total length of fine roots per unit of soil volume (in cm m-3) ## Code/software #### File: RodriguezUna_et_al_Oikos.R The R code enables to run all the analysis with the files provided, showing that prevailing climate and abiotic conditions determined how ECM communities were structured, more than seasonal climatic variability. Across sites, communities differed in their functional diversity: ECM fungi with long hyphae, more vulnerable to water scarcity, dominated at the southernmost site, where water availability was the highest.