DOI: 10.5061/dryad.dbrv15fc4
title: Water level drawdown and perennial vegetation impact litter decomposition in the sediment of a eutrophic wetland in the Netherlands

description: Managed wetlands often lack natural dynamics, such as water level
 fluctuations that normally cause dry-wet cycles. Several dry years result
 in a (partial) water level drawdown, after which an excess of rainfall
 creates the wet phase. To mimic these natural cycles, a water level
 drawdown can be manually induced. However, this will have major
 consequences for the cycling of carbon and nutrients. Yet, it is hereto
 unknown how water level drawdown, and the associated changes in vegetation
 composition and environmental conditions, affect plant litter
 decomposition. In the sediment of a eutrophic wetland, we buried green and
 rooibos tea bags, and local reed litter within a full-factorial design of
 water level drawdown (yes or no) and perennial vegetation (yes or no)
 (n=9). Inundated conditions had lower temperature and higher 
 conductivity and moisture content in the sediment.  We found
 lower tea decay in the water level drawdown area, indicating more tea mass
 remaining after 90 days. The decomposition rate of tea was higher in the
 areas with perennial vegetation, pointing towards faster breakdown of
 organic matter. Results on remaining reed litter mass were in line with
 those from the tea-bags; increasing with a water level drawdown. Our
 results suggest that a multi-year water level drawdown reduces the
 decomposition rate in the sediment, while increasing the potential for
 more carbon sequestration. After a drawdown, establishment of perennial
 vegetation and re-inundation could speed up decomposition rates in the
 sediment, showing the importance of allowing water level dynamics to
 maintain high productivity.  
description: To study the impact of changing environmental conditions during a
 water level drawdown on organic matter breakdown, tea bags and reed litter
 bags were buried in a full-factorial design, covering the water level
 drawdown management conditions (yes or no) and the presence of perennial
 reed vegetation (yes or no), resulting in four location types. The use of
 both tea bags and reed litter bags allows for the comparison with other
 areas that have used the tea bag index and for a standardized comparison
 between the drawdown and non-drawdown area. The added value of the reed
 litter bags is that this is area-specific material and may thus respond
 differently to the local conditions. Discrepancies between the two methods
 may indicate that material from the area itself is more adapted to the
 disturbances that occur. Exclosures were built to protect the buried
 litter bags against herbivory and bioturbation at the locations with no
 perennial vegetation, that are prone to disturbance. In the water level
 drawdown area the exclosures are 1.5 meter in diameter and 2 meter in
 height to protect against herbivory by red deer (<em>Cervus
 elaphus</em>) and geese (<em>Anser spp.</em>). In the
 non-water level drawdown area – under inundated conditions – we employed
 small wire cages of 1 meter in diameter and 1.5 meter in height to prevent
 fish from disturbing the study. Since the litter bags in the perennial
 vegetation were less visible and less prone to disturbance by grazers, no
 exclosures were used for these locations. Each of the four environmental
 conditions consisted of 9 locations distributed over the area, resulting
 in a total of 36 locations. For two locations in the area with a water
 level drawdown and with perennial vegetation, we were unable to relocate
 the tea bags and the reed litter bags (n=7).
 <em>Environmental conditions</em>
 The environmental conditions were measured for all four location
 types at the start (day 0), after 44 days and at the end (day 90) of the
 study. At each location, the vegetation community was monitored in a plot
 of 1x1 meter at the start of the study (day 0) by identifying each plant
 to species level and estimating the cover of each species. To quantify the
 abiotic conditions, two sediment samples of 10 centimeters depth (d = 3.5
 cm) were taken to determine organic matter content at the start of the
 study and after 44 and 90 days. The two cores were taken opposite of each
 other and in between the buried tea- and reed litter bags. Per location,
 the sediment samples were pooled in one bag and stored at 5 ⁰C until
 analysis. After thoroughly mixing the sediment sample, a subsample of 20
 mL was taken and weighted. The subsample was dried at 70 ⁰C for 48 hours
 and weighted, after which the subsample was combusted at 550 ⁰C for 4
 hours and weighted again. These weights were used to calculate moisture
 content (%) and loss of ignition, that we used as a proxy for organic
 matter content (%). In addition to the sediment samples, we used the
 W.E.T. sensor kit (Delta-T Devices Ltd) to measure sediment temperature
 (⁰C) and sediment conductivity (mS/m) in triplo at each location at day 0,
 day 44 and day 90. At inundated locations (no water level drawdown, no
 perennial vegetation), probes were used to measure water temperature (⁰C)
 and water conductivity (mS/m) at day 44 and day 90 (Hach HQ40D). Some data
 on temperature and conductivity in the non-drawdown area is missing on
 either the locations with perennial vegetation (Day 44, 90) or without
 perennial vegetation (Day 0). We dealt with these missing data by testing
 for overall differences (irrespective of measurement time). The average
 water depth was 24.7 ± 11.7 cm with pH of 8.8 ± 0.3 and oxygen
 concentration of 10.8 ± 0.7 mg/L (pH and oxygen measured with Hach HQ40D).
 During the study period the average air temperature was 17.8 ⁰C with a
 maximum temperature of 31.8 ⁰C and a minimum temperature of 4.9 ⁰C
 (measurements KNMI; weather station in Lelystad). The average amount of
 sun per day was 8.3 hours and there was rainfall on 57% of the days with
 on average 2.3 mm rain per day and a maximum of 20.2 mm rain on the
 31<sup>st</sup> of July 2024. 
 <em>Tea bag study</em> The tea-bag
 index (TBI) (www.teatime4science.org) was used to determine the ability to break down organic matter in a standardized way. The TBI allows the calculation of the relative decomposition rate (<em>k</em>) and an organic matter stabilization factor (<em>S</em>) using two types of tea, green tea (higher portion of labile litter) and rooibos tea (high portion of recalcitrant litter), as organic matter substitutes (Keuskamp et al., 2013). The difference in decomposition rate between the two types, fast for green tea and slow for rooibos, allows a single measurement effort in time. At the end of May 2023, thee replicates of a paired green tea bag and rooibos tea bag were buried at each location, resulting in a total of 216 buried tea bags. Tea bags were buried at a depth of 8 cm and a distance of ± 1 meter was adhered between pairs of bags. After approximately 90 days, following Keuskamp et al. (2013), the tea bags were retrieved from the sediment. The possible organic material adhering to the tea bags was removed and the tea bags were dried in the oven at 70⁰C for 48 hours and weighted (precision scale: 0.001g). To correct for the small clay particles adhering to the tea bags, ash-free dry mass was determined through combustion of the tea bags at 550 ⁰C for four hours  Ash-free dry weight of the green tea and rooibos tea was used to calculate the decomposition rate (<em>k</em>), the weight of the green tea was used to calculate the stabilization factor (<em>S</em>) (Keuskamp et al., 2013). The stabilization factor quantifies to which degree the labile fraction is not broken down but stabilizes. A negative <em>s</em> indicates that also part of the recalcitrant fraction was decomposed. <em>Reed litter bags</em> In addition to the TBI, local plant litter consisting of dry reed (<em>Phragmites australis</em>)<em> </em>leaves (3.1 ± 0.1 g) was buried to get a better understanding of area-specific decomposition rates. In April 2023, dry reed leaves were collected from both locations with and without water level drawdown in the field, mixed and airdried for 48 hours in the lab before use in the litter bags. PVC-coated glass-fiber mesh was used to create non-decomposable bags of 14.6 cm by 7.3 cm by sowing them with a nylon wire. The mesh size was 1.2 x 1.2 mm to also allow the entering of microfauna. At the end of May 2023, three reed litter bags were buried at each location in the Oostvaardersplassen, resulting in a total of 108 buried reed bags. At three points in time (after 44, 70 and 90 days), one of the bags was removed from each location. This allowed the construction of a decomposition curve over time for each location type. In the water level drawdown area with perennial vegetation, we lost 5, 5 and 4 litter bags respectively at each collection point in time, either, due to the inability to relocate the litter bags in the dense vegetation or because the litter bags were uprooted, possibly by red deer.  After collecting the reed litter bags, the protocol was similar to that described in <em>section 2.4</em> on the analysis of the tea bags. Ash-free dry weight was additionally corrected for the amount of reed remaining after combusting reed leaves, to avoid an overestimation of the amount of reed mass remaining.
description: # Water level drawdown and perennial vegetation impact litter
 decomposition in the sediment of a eutrophic wetland in the Netherlands
 [https://doi.org/10.5061/dryad.dbrv15fc4](https://doi.org/10.5061/dryad.dbrv15fc4) ## Description of the data and file structure There are four data files in this dataset. The first dataset contains the environmental conditions that were measured ("Soil properties"). This was done in the inundated locations using probes (Hach) and in the dry locations and in the reed vegetated locations this was done using a W.E.T. Sensor kit at three points in time.  The second dataset contains the vegetation recordings that were made at the start of the experiment (Day 0 of burial). It contains the cover of the found plant species that were measured in a plot of 1x1 meter.  The third dataset is the data for working with the tea bag index (TBI). This consists of the weights of the bags before and after burying them in the sediment and their weight after ashing. For the calculations done with regard to the Tea bag index I refer to Keuskamp et al. 2013. The last dataset is the data on the reed litter bags, containing the retrieval dates and the weights of each of the litter bags including the correction after ashing.  ### Files and variables #### File: Soil\_properties.xlsx **Description:** Measurements of the sediment properties at each location in the field, containing both measurements done in the field as lab analysis after taking sediment from the field. Empty spaces in the dataset are quite abundant and indicate missing data. The columns on variables measured in dry areas (sediment) and in wet areas (water) results in some n/a values as they are not both applicable to all locations. Additionally, the data on dry matter or organic material content of the sediment was only done once (in contrast to the triplo measurements of the field variables, therefore two rows also here remain empty.  ##### Variables | Variables | Unit | Description | | :-------------------- | :----------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Location | # | Location ID, unique for each location that was measured multiple times (Retrieved) | | Treatment | Dry, Reed\_dry, Reed\_wet, Wet | Factor with four levels describing the four location types. Dry refers to the drawdown area, Reed refers to the reed-vegetated areas and Wet to thte non-drawdown area.  | | Retrieved | 0,1,3 | Retrieval moment in the field (0 = start of experiment (end of May 2023), 1 = first retrieval for reed bags (beginning of July 2023), 3 = third retrieval for reed (end of August 2023)). Second retrieval was not measured for soil properties.  | | Soil\_temperature | °C | Sediment temperature measured using the W\.E.T. sensor in the non-inundated locations (measured in triplo at each location) | | Soil\_conductivity | mS/m | Sediment conductivity measured using the W\.E.T. sensor in the non-inundated locations (measured in triplo at each location) | | Soil\_Moisture | % | Sediment moisture measured using the W\.E.T. sensor in the non-inundated locations (measured in triplo at each location) | | Water\_level | cm | The water level at the time of measuring (only for the Wet treatment) | | Water\_temperature | °C | Water temperature measured using Hach probe (only for the Wet treatment) | | Water\_conductivity | mS/m | Water conductivity measured using Hach probe (only for the Wet treatment) | | Water\_O2 | mg/L | Water oxygen concentrations measured using the Hach probe (only for the Wet treatment) | | Water\_pH | - | Water pH measured using the Hach probe (only for the Wet treatment) | | Weight\_tray | g | The weight of the tray used for determining sediment characteristics of each location | | Wet\_weight\_soil | g | Wet weight of the sediment from each location  | | Dry\_weight\_soil | g | Dry weight of the sediment from each location after drying the sediment for 48 hours at 70 °C | | Ash | g | Ash weight of the sediment from each location after ahsing the sediment for 4 hours at 770 °C | | Dry\_matter\_perc | % | Percentage of dry matter in the sediment (calculated using wet and dry weight of the soil) | | Organic\_matter\_prec | % | Percentage of organic matter (LOI) in the sediment (calculated using dry and ahs weight of the soil) | | Ash\_perc | % | Percentage of ash that remains in the sediment after ashing | #### File: Vegetatie.xlsx **Description:** Dataset containing the vegetation recordings (cover and height of vegetation) at each location (except the wet locations).  ##### Variables | Variables | Unit | Description | | :-------- | :----------------------------- | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Location | # | Location ID, unique for each location | | Treatment | Dry, Reed\_dry, Reed\_wet, Wet | Factor with four levels describing the four location types. Dry refers to the drawdown area, Reed refers to the reed-vegetated areas and Wet to the non-drawdown area (not present in this dataset since there is no vegetation at these locations).  | | Date | dd-mm-yyyy | Date of making the vegetation recordings | | Species | txt | The species name of each of the species present in the plot | | Cover | % | The cover of the indicated species (total per location can exceed 100% due to undergrowth) | | Length1 | cm | Length of the vegetation that was measured in triplo (1/3) | | Length2 | cm | Length of the vegetation that was measured in triplo (2/3) | | Length3 | cm | Length of the vegetation that was measured in triplo (3/3) | #### File: TBI.xlsx **Description:** Data of the tea bags that were buried in the sediment for +/- 90 days. Empty cells correspond to missing data due to e.g. missing tea bags. All the start weights of the tea bags are present, but by leaving the cells of the final weights empty it is possible to see which tea bags were lost and at which location. This also results in some empty cells for S or k, since this needs the weight data of the tea bags.  ##### Variables | Variables | Unit | Description | | :------------------------ | :----------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Location | # | Location ID, unique for each location | | Treatment | Dry, Reed\_dry, Reed\_wet, Wet | Factor with four levels describing the four location types. Dry refers to the drawdown area, Reed refers to the reed-vegetated areas and Wet to the non-drawdown area | | Replicate | 1,2,3 | Replicate of the tea bags of the reed bags | | Start\_Date | dd-mm-yyyy | Date the litter or tea bags were buried in the sediment | | End\_Date | dd-mm-yyyy | Retrieval data of the litter or tea bags from the sediment | | S\_corr | - | Stabilisation factor, calculated following Keuskamp et al. 2013 | | k\_corr | - | Decomposition rate constant, calculated following Keuskamp et al. 2013 | | Inbubation time | Days | Number of days the bags were in the sediment.  | | Start\_weight\_Green\_Tea | g | Start weight of the green tea bags | | Start\_Weight\_Red\_Tea | g | Start weight of the red tea bags | | Final\_weight\_Green\_Tea | g | Final weight of the green tea bags after incubation time | | Final\_weight\_Red\_tea | g | Final weight of the red tea bags after incubation time | #### File: Reed\_litter.xlsx **Description:** Data of the reed litter bags that were buried in the sediment and retrieved on three moments in time (1 litter bag per location per retrieval time). Empty cells are only there to be able to reconstruct our graph where the start "fraction of mass remaining" is 1 (Day 0).  ##### Variables | Variables | Unit | Description | | :------------------------------ | :----------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Location | # | Location ID, unique for each location | | Treatment | Dry, Reed\_dry, Reed\_wet, Wet | Factor with four levels describing the four location types. Dry refers to the drawdown area, Reed refers to the reed-vegetated areas and Wet to the non-drawdown area | | Set | 1,2,3 | Replicate of the tea bags of the reed bags | | Retrieval | 0,1,3 | Retrieval moment in the field (0 = start of experiment (end of May 2023), 1 = first retrieval for reed bags (beginning of July 2023), 3 = third retrieval for reed (end of August 2023)). Second retrieval was not measured for soil properties.  | | Time\_in\_ground | Days | Number of days the bags were in the sediment.  | | Weight\_bag\_reed\_(g) | g | Weight of the bag without the reed leaves | | Initial\_weight\_reed\_(g) | g | Weight of the reed leaves without the bag before burial | | Dry\_weight\_reed | g | Weight of the reed after burial and after drying at 48 hours at 70 °C | | Handling\_constant | - | Handling constant to correct for the reed loss during handling of the bags | | Ash\_weight\_together\_(g) | g | Ash weight of the reed leaves after burial and after ashing for 4 hours at 550 °C | | Ash\_initial\_reed (g) | g | Ashing of unburied reed leaves was used to give us an estimate of how much ash there would be in the reed leaves (without additional sediment particles that adhere during burial), to calculate the excess of ash that we measrued in "Ash\_weight\_together", this excess is removed form the weight since this is probably due to adhering sediment particles | | Excess\_ash\_(g) | g | Excess ash as described in Ash\_inital\_reed, that is due to adhering sediment particles | | Reed\_mass\_remaining | g | The mass of reed remaining after burial for a certain amount of days and after correction for the ashing.  | | Fraction\_reed\_mass\_remaining | Fraction | Fraction of reed mass remaining after burial for a certain amount of days using the initial weight of reed and the reed mass remaining.  | ## Code/software The data can be viewed in Microsoft Office.  **Statistical analysis:** To determine differences in environmental conditions across water level drawdown management and the presence of perennial vegetation (independent variables), linear mixed effect models (package lmerTest in R; Kuznetsova et al., 2017) were used. Sediment or water temperature, sediment or water conductivity, sediment moisture and sediment organic matter (log transformed) content were used as dependent variables. Location and measurement time (0, 44 and 90 days) were inserted as random effect, to be able to correct for missing data. The four location types were tested for distinct vegetation communities using Permanova analysis (function adonis2) in combination with non-metric multidimensional scaling (NMDS) from the function metaMDS with Bray-Curtis distances for 2 dimensions (k=2) (package “vegan”; Oksanen et al., 2022). Additionally, total vegetation cover was tested for water level drawdown and perennial vegetation using linear models (package “stats”; R Core Team, 2023). To determine the effect of water level drawdown management (yes or no) and presence of perennial vegetation (yes or no) on the stabilization factor (s), the decomposition rate (k) and the remaining mass of green and rooibos tea, we used general linear mixed models (package “lmerTest” (Kuznetsova et al., 2017)). Water level drawdown management and presence of perennial vegetation were used as independent variables in each model, including an interaction and location was inserted as random effect. To determine the effect of location type (interaction water level drawdown management and perennial vegetation) on the reed mass remaining over time non-linear models were fitted with and without location type allowing different slopes per location type. To test for model improvement the anova function (package “stats” (R Core Team, 2023)) was used. To test for differences within treatments of the response variable, an ANCOVA analysis was used on the ln transformed reed mass remaining (dependent variable), with time as a covariate and location type as the independent variable.  The function emmeans was used to evaluate Tukey adjustment pairwise comparisons in case of two or more levels or interaction effects (package “emmeans” (Russell, 2022)). To check for main effects the function anova (package “stats” (R Core Team, 2023)) was used for all models. To assess relations between environmental conditions and decomposition properties, spearman regression coefficients were calculated by the function “cor” (stats package (R Core Team, 2023)) with pairwise complete observations for the covariance matrix to optimize the use of data despite NA values. The sediment properties were normalized per retrieval time and subsequently averaged over retrieval times before calculating regression coefficients. In this way, there was one value for each environmental condition per treatment to cope with missing environmental conditions at certain retrieval points. All analyses have been done in R version 4.3.0 using R Studio (R Core Team, 2023). To visualize the data, we used the function “ggplot” (ggplot2 package (Wickham, 2016) in combination with editing in Adobe Illustrator. All models were fitted with a Gaussian-error distribution. Normality of the residuals of the models were assessed using histograms, and were transformed if necessary  All significant levels were set at alpha = 0.05 and all values are given in mean ± sd.