DOI: 10.5061/dryad.vmcvdnd31
title: Reconsidering warming effects on seedling recruitment in Tibetan plateau's alpine meadows via Open-Top chamber experiments

description: Open-Top Chambers (OTCs), widely used as field warming facilities, not
 only generate warming effects but also reduce water availability through
 rain interception effect. While OTCs are extensively applied to explore
 the effects of warming on seedling recruitment which act as a fundamental
 driver of population dynamics, the potential experimental biases
 introduced by the rain interception effect remains largely unexplored.
 This knowledge gap raises concerns about the interpretation of warming
 experiments using OTC facilities. We conducted warming experiments in
 alpine meadows on the Tibetan Plateau using OTCs. Three treatments were
 applied: control (no OTC), warming alone (W, +2 °C without OTC
 precipitation interception), and warming with decreased precipitation
 (WDP, +2 °C with OTC precipitation interception). Focusing on 50 plant
 species across various functional groups, we disentangled the independent
 effects of warming and decreased precipitation caused by OTC interception
 on seedling emergence, survival, and establishment. We applied structural
 equation modeling (SEM) to analyze the relationships between emergence
 timing, rate, survival, and establishment success. Our study
 demonstrates that warming (W) and warming with decreased precipitation
 (WDP) treatments accelerated seedling emergence but decreased survival and
 establishment rates at the community level. The WDP reduced survival by
 20% compared to W. The SEM analysis revealed that earlier emergence and
 higher emergence rates under W indirectly reduced establishment success,
 while WDP directly suppressed survival by limiting water availability.
 Furthermore, W increased the biomass of grasses and perennials, whereas
 WDP significantly reduced their biomass. In contrast, annuals and
 non-grasses showed no significant response to either treatment. Synthesis
 and applications: The OTC-induced precipitation reduction can overestimate
 the impacts of warming on seedling establishment success, with species and
 functional group-specific responses. Therefore, interpreting data from OTC
 warming experiments requires careful consideration of precipitation
 interception effects. To mitigate this issue, future studies should
 optimize experimental designs to minimize precipitation interception,
 incorporating methods such as collecting and redistributing precipitation
 to better support seedling water availability. Furthermore, to enhance
 ecosystem resilience and support biodiversity in the context of climate
 change, conservation strategies should prioritize species and functional
 groups that are especially vulnerable to changes in warming and
 precipitation.
description: <strong>Seedling emergence
 monitoring</strong> Seedling recruitment was
 monitored from March 2022 until October 2022 in all experimental plots.
 Seedling emergence was recorded every two days, with time of seedling
 exposure to the soil surface defined as the initial emergence time. Each
 emergent seedling was labeled with a colored label and inserted into the
 soil beside the seedling. Different colored labels were used each month to
 allow seedling survival to be monitored. Seedlings began to appear in May
 and continued to emerge until July, with very few emergences afterward. We
 recorded the seedling mortality rate each month. Additionally, we
 calculated the seedling emergence rate, mean emergence time , emergence
 index, survival rate, and establishment rate.
 <strong>Seedling growth trait
 measurements</strong> Seedlings were manually
 thinned out three months after the first emergence. Five healthy, pest-
 and disease-free, well-grown seedlings of each species were retained for
 seedling trait measurements. Leaf and root traits were measured before
 drying. Two weeks after thinning, five fully expanded young leaves from
 each species were selected, and their leaf area was measured using a leaf
 area meter (Li-300, Li-COR, Lincoln, USA). Leaves were then dried for 72
 hours at 60 °C and weighed. Specific leaf area (SLA, cm²/g) was calculated
 as the ratio of fresh leaf area to dry weight. At the end of the growing
 season, the aboveground parts and roots of all plants were harvested. The
 entire root system of each plant was obtained using a root scanning system
 (WinRHIZO Pro 2009b), and root traits were measured, including total root
 length (TRL) and root average diameter (RAD). Specific root area (SRA,
 root surface area/root weight), specific root length (SRL, total length of
 absorbing roots/total dry weight), and root tissue density (RTD, total dry
 weight of absorbing roots/volume) were calculated using the respective
 formulas. We excluded coarse roots (&gt; 2 mm in diameter). Finally,
 aboveground biomass and root biomass were measured after drying to a
 constant weight and total biomass was calculated.
description: # Reconsidering warming effects on seedling recruitment in Tibetan
 plateau's alpine meadows via Open-Top chamber experiments
 [https://doi.org/10.5061/dryad.vmcvdnd31](https://doi.org/10.5061/dryad.vmcvdnd31) ## Description of the data and file structure We conducted warming experiments in alpine meadows on the Tibetan Plateau using OTCs. Three treatments were applied: control (no OTC), warming alone (W, +2 °C without OTC precipitation interception), and warming with decreased precipitation (WDP, +2 °C with OTC precipitation interception). Focusing on 50 plant species across various functional groups, we disentangled the independent effects of warming and decreased precipitation caused by OTC interception on seedling emergence, survival, and establishment. We applied structural equation modeling (SEM) to analyze the relationships between emergence timing, rate, survival, and establishment success. ### Files and variables #### File: data.xlsx **Description:**  ##### Variables * W：warming * DP: decreased precipitation * WDP: warming with decreased precipitation Explanation for 'null': Some seeds did not germination, therefore, the subsequent germination traits (germination time, survival rate, establishment rate), as well as seedling growth traits (specific leaf area, biomass, root traits, etc.) are all recorded as null. ##### Seedling\_emergence\_and\_growth\_traits.csv |Number| Trait |Trait Abbreviations| Unit | Ecological functions | \| 1 | Emergence rate | ER | % | Seed quality, growth potential | \| 2 | Emergence index | EI | | Seed quality, growth potential | \| 3 | Survival rate | SR | % | Survivability; adaptability | \| 4 |Seedling establishment rate| SER | % | Survivability; adaptability | \| 5 | Initial emergence time | IT | d | Seed quality; growth potential | \| 6 | Mean emergence time | MT | d | Seed quality; growth potential | \| 7 | Specific leaf area | SLA | cm2 g-1| Potential relative growth, light capt | \| 8 | Aboveground biomass | ANPP | g | Carbon storage capacity; ecosystem productivity | \| 9 | Root biomass | BNPP | g | Organic matter storage; soil ecosystem productivity| |10 | Total biomass | TB | g | Ecosystem productivity | |11 | Root average diameter | RAD | mm | Nutrient and water uptake, plant economics | |12 | Specific root length | SRL | cm g-1 | Nutrient and water uptake, plant economics | |13 | Root tissue density | RTD | g cm-3 | Nutrient acquisition strategy | |14 | Specific root surface area | SRA | cm2 g-1| Nutrient and water uptake, plant economics | ## Code/software data &lt;- read_excel("data.xlsx",sheet=2) View(data) \#SEM model1 =' ER~ w EI~ w+ER IT~ w +ER+EI SR~ w +EI+IT+ER SER~ w +EI+IT+ER+SR' fit1 = sem(model1, data = data,check.gradient = FALSE) summary(fit1, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE) semPaths(fit1,"std",curveAdjacent = TRUE) fitMeasures(fit1,c("chisq","df","pvalue","cfi","nfi","ifi","rmsea","EVCI")) \#Hedges*' d* library(esc) data&lt;- read.csv("data.csv") results &lt;- list() for (i in 1:nrow(data)) { result &lt;- esc_mean_sd( ``` grp1m = data$grp1m[i], grp1sd = data$grp1sd[i], grp1n = data$grp1n[i], grp2m = data$grp2m[i], grp2sd = data$grp2sd[i], grp2n = data$grp2n[i], es.type = "d" ``` ) results[[i]] &lt;- result } print(results) write.csv(results, "output.csv") Explanation for “ ‘SEM_and_d.R‘ file ”: the R code for calculating the structural equation model and effect sizes in the study. ## Access information Data was derived from the following sources: * **Reconsidering warming effects on seedling recruitment in Tibetan Plateau's Alpine Meadows via Open-Top Chamber experiments**