Data from: Weed management modifies functional properties of both weeds and microbial nitrogen-cycling communities in Mediterranean vineyards
Data files
Nov 13, 2024 version files 52.31 KB
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microbial_data_set_DRYAD.xlsx
41.27 KB
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README.md
11.04 KB
Abstract
Nitrogen (N) availability is crucial to maintaining crop productivity in agroecosystems, driven primarily by soil microbial processes such as nitrification and denitrification. Weeds are an integral part of agroecosystems and are involved in many processes related to the N cycle, but how weed management could shift plant-microbe interactions and thus N-cycling is yet to be determined. Using a network of 15 Mediterranean vineyards, we quantified the effect of five years of different weed management practices (chemical weeding, tillage, mowing) on the aboveground and belowground functional properties of weed communities and soil microbial N-cycling. Specific root length (SRL) of the tilled and mowed weed communities were 30 % and 44 % lower than in the herbicide-treated weed communities. Soil pH and texture were the main drivers of soil microbial activity as quantified by substrate-induced respiration (SIR), potential denitrifying enzyme activities to SIR ratio (PDEA:SIR) and potential nitrifying to denitrifying enzyme activity ratio (PNEA:PDEA). Acidic soils with a low sand content had high SIR while alkaline soils with low sand content had high PDEA:SIR. PNEA:PDEA was negatively related to soil pH. • SIR was also impacted by the management: mowed weed communities had 58 % higher SIR compared to herbicide-treated communities. Weed communities with high SRL were associated with soils with a higher nitrifying enzyme efficiency per unit of respired carbon.
Synthesis and applications: Overall, our findings indicate that vineyard weed management influences the potential nitrifying enzyme activities by modifying the root strategies of weed communities. This study highlights that the design of sustainable weed management strategies should incorporate unintended effects on soil microbial communities and N-cycling.23-Sep-2024 --
https://doi.org/10.5061/dryad.t4b8gtjb1
Description of the data and file structure
The table includes all the explaining variables and response variables necessary to analyses the dataset. Each line corresponds to a sampled quadrat, corresponding to a weed community and associated potential soil microbial activities, in a vineyard plot. The unique identifier is indicated by the “ID_Quadrat” column. Each vineyard was characterized by four quadrats. Thus, ID_Quadrat = “128_3” means that this line is associated with the third quadrat of the vineyard “128”.
The dataset contains all the following information :
- Microbial potential activities (SIR, PDEA, PNEA, PNEA_SIR, PDEA_SIR, PNEA_PDEA)
- Weed management variables (Cov_dur, Ferti_NPK, Vinasse, Nb.Mow.IR, Nb.Till.IR, Nb.Chem.IR, Nb.Chem.R, Dim.1.pra, Dim.2.pra, Dim.3.pra, clust)
- Soil abiotic characteristics (Soil_Organic_Matter, pH, Sab)
- Weed traits and characteristics(SLA.CWM, LDMC.CWM, Height.CWM, C_N.CWM, Biomass, Rich, Annual.tot, Leg.tot, D, C_N_root, Root_dry_biomass_g_total, SRL, RTD, Quadrat_weed_cover, Dim.1, Dim.2, Dim.3, Dim.4)
Files and variables
File: microbial_data_set_DRYAD.xlsx
The table below lists the different variables of the dataset with their description. We did not specify the units as the whole dataset is unitless.
Variable | Description | Unit |
---|---|---|
ID_Quadrat | Unique identifier for each line of the table : quadrats where weed and microbial communities were characterised | - |
SIR | Substrate-induced Respiration | µg C-CO2 .g-1.h-1 |
PDEA | Potential denitrifying enzyme activity | µg N-NO3- .g-1.h-1 |
PNEA | Potential nitrifying enzyme activity | µg N-N2O .g-1.h-1 |
Clust | Three weed management types : | - |
Cov_dur | Number of days with weed cover per year | |
Ferti_NPK | NPK annual inputs | kg.ha-1 |
Vinasse | annual inputs of vinasse (i.e. residuum after wort distillation) | % of amended area |
Nb.Mow.IR | Frequency of mowing of the inter-rows | - |
Nb.Till.IR | Frequency of tillage of the inter-rows | - |
Nb.Chem.IR | Frequency of chemical weeding of the inter-rows | - |
Nb.Chem.R | Frequency of chemical weeding of the vine rows | - |
Dim.1.pra | Coordinates of the vineyards on the first axis of the PCA based on management variables, averaged over the 2015-2020 period (Figure S2 of the paper) | - |
Dim.2.pra | Coordinates of the vineyards on the second axis of the PCA based on management variables, averaged over the 2015-2020 period (Figure S2 of the paper) | - |
Dim.3.pra | Coordinates of the vineyards on the second axis of the PCA based on management variables, averaged over the 2015-2020 period (Figure S2 of the paper) | - |
Soil Organic Matter | Soil organic matter | ‰ |
pH | pH | - |
%Sand | Percentage of sand of the soil | ‰ |
Prec | Annual rainfall | mm |
Temp | Mean annual temperature | °C |
AI | Aridity index | - |
Date_survey | Dates when the quadrats where characterised | - |
Biomass | Above-ground weed biomass | g |
SLA.CWM | Specific leaf area | m².kg-1 |
LDMC.CWM | Lead Dry Matter Content | mg.g-1 |
Height.CWM | Height | cm |
C_N.CWM | Carbon to Nitrogen leaf ratio | - |
Rich | Weed richness | - |
Annual.tot | Percentage of annual weed species covering the quadrats | % |
Leg.tot | Percentage of weed species of the Fabaceae family covering the quadrats | % |
D | Root diameter of weeds | mm |
C_N_root | Carbon to nitrogen ratio of weed roots | - |
Root_dry_biomass_g_total | Root dry biomass of the weed community | g |
SRL | Specific Root Length | g.m-1 |
RTD | Root Tissue Density | g.cm-3 |
Quadrat_weed_cover | Percentage of weed cover over the quadrat | % |
PDEA_SIR | PDEA to SIR ratio | µg N-NO3-. µg-1 C-CO2 |
PNEA_SIR | PNEA to SIR ratio | µg N-N2O. µg-1 C-CO2 |
PNEA_PDEA | PNEA to PDEA ratio | µg N-NO3-. µg-1 N-N2O |
Dim.1 | Coordinates of the weed communities on the first axis of the PCA based on weed aboveground and belowground traits (Figure 4 of the paper) | - |
Dim.2 | Coordinates of the weed communities on the second axis of the PCA based on weed aboveground and belowground traits (Figure 4 of the paper) | - |
Dim.3 | Coordinates of the weed communities on the third axis of the PCA based on weed aboveground and belowground traits (Figure 4 of the paper) | - |
Dim.4 | Coordinates of the weed communities on the fourth axis of the PCA based on weed aboveground and belowground traits (Figure 4 of the paper) | - |
Missing data: NA
Using a network of 15 Mediterranean vineyards, we quantified the effect of five years of different weed management practices (chemical weeding, tillage, mowing) on the aboveground and belowground functional properties of weed communities and soil microbial N-cycling.