Data from: Recurrent drought amplifies drought impacts and increases seasonal synchrony in mountain grassland communities
Data files
Oct 20, 2025 version files 335.31 KB
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Canopy_height_Necromass.txt
7.18 KB
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Counts_raw_data_flowers_merged.txt
80.20 KB
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Counts_raw_data.txt
131.58 KB
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Peak_drought_ANPP_data_2020.txt
60.50 KB
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Plant_codes.txt
1.31 KB
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README.md
6.17 KB
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Recovery_ANPP_data_2020.txt
44.61 KB
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seedling_counts_2020.txt
3.76 KB
Abstract
Climate change increases the frequency and severity of drought events with strong repercussions on grassland ecosystems. While the effects of single drought events on ecosystem structure and functioning are well understood, it is largely unknown whether and how drought frequency modifies ecosystem responses to drought. Here, we assessed how the increase in frequency of severe, annual summer drought impacted grassland communities. We examined these effects in a species-rich sub-alpine mountain meadow with drought frequencies of one, three, and 13 years, compared to ambient conditions.
We found that high drought frequency increased seasonal plant community synchrony. This pattern was associated with a reduction in species richness, a shift in plant functional groups, a loss of early-seasonal plant species, and a constrained establishment of seedlings throughout the growing season. Additionally, these changes were accompanied by a decreased fraction of biomass as drought frequency increased. Furthermore, we show that negative drought effects were enhanced with an increasing drought frequency, and that negative drought effects on plant communities outweighed the weak adaptive effects of species.
We conclude that single and low-frequency drought studies may not adequately predict longer-term changes in our rapidly shifting climate. With the ongoing increase in drought frequency due to climate change, we predict that grassland plant communities will increase in seasonal synchrony. We suggest that this increase in synchrony will leave ecosystems vulnerable to future disturbances, because asynchrony is a critical component of stability. Moreover, given the weak adaptive effects of plant species to long-term recurrent drought, we conclude that plant communities are unlikely to be able to adapt to the rapid increase in recurrent drought events.
https://doi.org/10.5061/dryad.4tmpg4fmt
Description of the data and file structure
Four summer drought treatments were established in the enclosed area at the study site: a single year summer drought, three years of recurrent summer drought, 13 years of recurrent summer drought, and ambient conditions (n = 4, respectively). In total, 4 plots for ambient, single, three, and 13 years of drought frequency were installed four weeks before summer drought simulation in 2020, respectively. In all 16 plots, species composition and vegetation height (cm) were measured every two weeks from 22 May to 22 October 2020. Plant species composition was estimated by noting for each species present the number of modules and flowering stems. Seedling composition in the plots was counted separately every three weeks between the 23 June and the 22 October 2020.
Additionally, aboveground biomass (living plant material) and necromass (dead plant material) was sampled destructively in the plots at peak drought on 6 August 2020 and during recovery on 22 October 2020. Samples were split into plant species and separated into leaves, stems, and flowers. This was done for biomass and necromass, respectively. For each species of each plot, the leaf area was determined from thawed leaves that were saturated with water and scanned (V700 Photo, Epson, WinRHIZO Pro 2012, Regent Instruments). Scanned leaves were dried in the subsequent three days at 60 °C and were weighed. Specific leaf area (SLA) was calculated by dividing the scanned leaf area by the dry weight of the leaves for each species and treatment, respectively. Leaf area index (LAI) was calculated from the leaf surface of all leaves divided by the total unit of ground area of the plot.
Files and variables
File: Canopy_height_Necromass.txt
Description: Biweekly measurements of canopy height and visual estimation of plant community necromass
Variables
- Plot: Plot code
- Treatment: Drought treatment
- Date: Date of measurement
- Canopy_mean: Average height of the plant community in cm
- Canopy_max: Maximum height of the plant community in cm
- Necromass: Score for how much necromass was visible. Score of 1 indicates no visible necromass, only alive plants. A score of 10 indicates only necromass, only dead plants.
- Author: Name of the person recording the measurement
File: Counts_raw_data.txt
Description: Number of modules (~leaves) of each plant species in each plot at a biweekly interval
Variables
- Author: Name of researcher taking measurements
- Code: Plot code
- Treatment: Drought treatment
- Replicate: Treatment replicate
- Section: Quadrant of the plot where measurements were performed (A, B, C, or D)
- Time_point_forb: Time point at which forb modules were counted
- Time_point_grass: Time point at which grass modules were counted
- Date: Measurement date
- Columns: plant species names
- Cells: total number of modules counted of a species in a plot at a certain date
File: Counts_raw_data_flowers_merged.txt
Description: Number of flowers (blooming) and seeds (flowering stems with seeds) of each plant species in each plot at a biweekly interval
Variables
- Author: Name of researcher taking measurements
- Code: Plot code
- Treatment: Drought treatment
- Replicate: Treatment replicate
- Section: Quadrant of the plot where measurements were performed (A, B, C, or D)
- Date: Measurement date
- Columns: plant species names
- Cells: total number of flowers or seeds counted of a species in a plot at a certain date
File: Recovery_ANPP_data_2020.txt
Description: Plant species-specific dry weight and leaf traits from the recovery harvest
Variables
- Plot: Plot code
- Treatment: Drought treatment
- Rep: Replicate number
- Time_point: Harvest timepoint (recovery in this case)
- Functional_group: To which functional group the plant species belongs: grass, forb or legume
- Species: Plant species name
- Alive_dead: Plant material was alive (a) or dead (d)
- Organ: Plant material was from leaves, flowering stem or seeds.
- Weight: Dry weight of plant material in g
- Leaf_area: Area of plant leaves in cm2
File: seedling_counts_2020.txt
Description: Number of seedlings at a biweekly interval
Variables
- Date: Date of measurement
- Plot: Plot code
- Herbs: Number of seedlings that were herbs (forbs)
- Legumes: Number of seedlings that were legumes
- Grasses: Number of seedlings that were grasses
- Total: The total number of seedlings
File: Peak_drought_ANPP_data_2020.txt
Description: Plant species-specific dry weight and leaf traits from the peak drought harvest
Variables
- Plot: Plot code
- Treatment: Drought treatment
- Rep: Replicate number
- Time_point: Harvest timepoint (peak drought in this case)
- Functional_group: Functional_group: To which functional group the plant species belongs: grass, forb or legume
- Species: Plant species name
- Alive_dead: Plant material was alive (a) or dead (d)
- Organ: Plant material was from leaves, flowering stem or seeds.
- Weight: Dry weight of plant material in g
- Leaf_area: Area of plant leaves in cm2
File: Plant_codes.txt
Description: Plant species full names and abbreviations
Variables
- Full.name: Plant species full name in latin
- Abbreviation: 5 letter abbreviation of plant species
Code/software
Scripts written using R 4.1.1 (R Core Team 2021). R packages needed per script are detailed in each script at the very top. All scripts labelled '00' are pre-processing scripts to remove errors and noise from raw data. Scripts labelled '1' are to explore general biomass and plant module patterns over time and follow on '00' scripts. Scripts labelled '2' follow and add more detailed calculations on seasonal responses and environmental variables. Scripts labelled '3' relate to plant trait data. Scripts labelled '4' and '5' add temporal patterns of flower and seedling counts.