Experimental dataset for the effect of chilling on budburst
Data files
May 07, 2024 version files 68.70 MB
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data.zip
68.60 MB
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README.md
10.12 KB
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supplementary_data.xlsx
95.09 KB
Abstract
We obtained available information from 23 experimental studies about chilling effects in budburst and established an experimental database of budburst date for 50 temperate and boreal species from 33 provenance origins (94 species-provenance combinations).
README: Experimental dataset for the effect of chilling on budburst
The explanations to the headers of the supplementary_data
Source original reference (see Table S1)
genus: genus name
species: species name
BBCH: BBCH code of phenological event in the experiment
Prov_code: The code to distinguish different provenances
prov_lat: latitude of provenance origin
prov_lon: longitude of provenance origin
sam_lat: latitude of the sampling site
sam_lon: longitude of the sampling site
sampleyear: the year to sample the plant material; 999 represent unknown
sampleday: the day of year to sample the plant material
chilling_T: the temperature the plant materials were chilled ("natural " represent that the plant materials were chillled in natural conditions )
chilling_day: number of days from 1 Nov to the date when plant materials were moved to forcing condition
forcing_T: the temperaure of the forcing treatments ("natural " represent that the plant materials were forced in natural conditions )
forcing_photoperiod: the daylength of the forcing treatments ("natural " represent that the plant materials were forced in natural conditions )
forcing_day: number of days to budburst since the date when plant materials were moved to forcing condition
CA5: chilling accumulation calculated by chilling algorithm with Tc=5C
CA7: chilling accumulation calculated by chilling algorithm with Tc=7C
GDD5Jan1: forcing requirement calculated by forcing algorithm with Tb=5C and t1=1 January
GDD0Jan1: forcing requirement calculated by forcing algorithm with Tb=0 C and t1=1 January
GDD5Feb1: forcing requirement calculated by forcing algorithm with Tb=5C and t1=1 February
leaf morphology: 1, broadleaved species; 2 conifers
Experimental materials: 1, twig; 2, seedling
chilling treatments: 1, natural; 2, artifical
forcing treatments: 1, diurnal temperature range (DTR)>0; 2 DTR=0
The description of each file and the explanations to the headers in data.zip:
all_data.xlsx: The chilling accumulation and forcing requirements in observational and experimental dataset for each species.
CA_obs: chilling accumulation in the observational dataset based on the optimal combination of chilling and forcing algorithm
FR_obs: forcing requirement in the observational dataset based on the optimal combination of chilling and forcing algorithm
CA_exp: chilling accumulation in the experimental dataset based on the optimal combination of chilling and forcing algorithm
FR_exp: forcing requirement in the experimental dataset based on the optimal combination of chilling and forcing algorithm
sheet name: genus name + species name + Prov_code
all_station.xlsx: The latitude and longitude of observational and experimental sites and their sample size.
lat_obs: latitude of stations in the observational dataset
lon_obs: longitude of stations in the observational dataset
lat_exp: latitude of provenance origin in the experimental dataset
lon_exp: longitude of provenance origin in the experimental dataset
N_obs: the sample size of the observational dataset
N_exp: the sample size of the experimental dataset
results_eu+mat.csv/results_US+mat.csv: The parameters of CA-FR curves according to experimental and observational dataset.
genus: genus name
species: species name
BBCH: BBCH code of phenological event in the experiment
prov: The code to distinguish different provenances
lat: mean latitude of provenance origin
lon: mean longitude of provenance origin
phylum: 1, angiosperm; 2, gymnosperm
material: 1, twig; 2, seedling
chilling_type: 1, natural; 2, artifical
forcing_type: 1, diurnal temperature range (DTR)>0; 2 DTR=0
distance: Geographical distance between provenance origins in the experimental datasets and stations in the observational datasets (km)
a_exp: parameter a of CA-FR curve fitted from experimental data
b_exp: parameter b of CA-FR curve fitted from experimental data
c_exp: parameter c of CA-FR curve fitted from experimental data
RMSE_exp: root-mean-square error (RMSE) of CA-FR curve fitted from experimental data
R2_exp: Coefficient of determination of CA-FR curve fitted from experimental data
a_obs: parameter a of CA-FR curve fitted from all observational data
b_obs: parameter b of CA-FR curve fitted from all observational data
c_obs: parameter c of CA-FR curve fitted from all observational data
RMSE_obs: root-mean-square error (RMSE) of CA-FR curve fitted from all observational data
R2_obs: Coefficient of determination of CA-FR curve fitted from all observational data
miniFR_exp: the minimum FR in the experimental dataset
CR_exp: chilling requirement in experimental data, chilling requirement is defined as the amount of chilling required for endodormancy release
CS_exp: chilling sensitivity in experimental data, chilling sensitivity is defined as the sensitivity of FR to CA under intermediate chilling conditions
miniFR_obs: the minimum FR in the observational dataset
CR_obs: chilling requirement in observational data, chilling requirement is defined as the amount of chilling required for endodormancy release
CS_obs: chilling sensitivity in observational data, chilling sensitivity is defined as the sensitivity of FR to CA under intermediate chilling conditions
Similarity: Absolute difference in the CA-FR curves between observations and experiments, defined as the mean absolute relative difference in FR under different chilling conditions
ca_method: 1, CA5; 2, CA7
fr_method: 1, GDD5Jan1; 2, GDD0Jan1; 3, GDD5Feb1
MATexp: mean annual temperature in experimental stations
MATobs: mean annual temperature in observational stations
heatstress: difference in mean temperature between the chilling treatment and forcing treatment averaged from all sampling dates
results_eu_20231129.csv/results_US_20231129.csv: The parameters of CA-FR curves and the indictors of chilling effects according to experimental and observational dataset, which can be directly used to draw figures by 2_visualization.R
The explaination of duplicate headers are the same as those in results_eu+mat.csv/results_US+mat.csv
minCA_obs: the minimum CA in the observational dataset
maxCA_obs: the maximum CA in the observational dataset
MATdiff: MATexp minus MATobs
similarity_dir: Directional difference in the CA-FR curves fitted from experimental data and all observational data
similarity_sample: Absolute difference in the CA-FR curves fitted from experimental data and 1000 random samples in observational data
similarity_sample_dir: Directional difference in the CA-FR curves fitted from experimental data and 1000 random samples in observational data
CR_sample: chilling requirement in observational data (averaged from 1000 random samples)
CS_sample: chilling sensitivity in observational data (averaged from 1000 random samples)
SD_similarity_sample: standard derivation of absolute difference in the CA-FR curves fitted from experimental data and 1000 random samples in observational data
SD_similarity_sample_dir: standard derivation of directional difference in the CA-FR curves fitted from experimental data and 1000 random samples in observational data
SD_CR_sample: standard derivation of chilling requirement in 1000 random samples
SD_CS_sample: standard derivation of chilling sensitivity in 1000 random samples
RMSE_sample: mean root-mean-square error (RMSE) of CA-FR curve fitted from 1000 random samples
R2_sample: Coefficient of determination of CA-FR curve fitted from 1000 random samples
SD_RMSE_sample: standard derivation of root-mean-square error (RMSE) of CA-FR curve fitted from 1000 random samples
SD_R2_sample: standard derivation of coefficient of determination of CA-FR curve fitted from 1000 random samples
.csv files in par_EU and par_USA folders: the parameters of CA_FR curves fitted from 1000 random samples in observational dataset.
filename: genus name + species name + Prov_code
a_obs: parameter a of CA-FR curve fitted from each random sample
b_obs: parameter b of CA-FR curve fitted from each random sample
c_obs: parameter c of CA-FR curve fitted from each random sample
R2_obs: coefficient of determination of CA-FR curve fitted from each random sample
RMSE_obs: root-mean-square error (RMSE) of CA-FR curve fitted from each random sample
lifefrom_data.csv: the lifefrom of investigated species. DBS: deciduous broadleaf shrub; DBT: deciduous broadleaf tree; ECT: evergreen conifer tree. Rows 1-64 correspond to species-provenance in results_eu_20231129.csv, and rows 65-94 correspond to species-provenance in results_US_20231129.csv.
The description of each Matlab .m file:
(1) a_extract_phedata: extract all phenological data from the original PEP725 dataset.
(2) b_a_selectdata: select the phenological events investigated.
(3) b_b_eobosdata: extract temperature data from the meteorological datasets.
(4) c_a_selectspecies: select the species investiagted in the observational datasets based on the experimental datasets.
(5) c_b_calculateCDGDD: calculate chilling accumulation and forcing requirements of obervational data
(6) c_c_compareBBCH: compare the forcing requirement of different phenological events so as to calibrate the experimental data when different spring events were recorded between experiments and observations
(7) d_compareCDGDD1: compare the chilling and forcing curves between obervations and experiments
The description of each R software .R file:
(1) 1_data: compare the chilling effects between observations and experiments
(2) 2_visualization: Code for drawing figures in manuscript and supplementary materials.
Methods
To identify phenological experiments that manipulated chilling and forcing, we searched both ISI Web of Science and Google Scholar with TOPIC = (budburst OR leaf out OR flowering OR phenology) AND chilling. The initial searches yielded more than 200 papers. Subsequently, we reviewed and assessed each paper strictly. The papers that were included in the analyses needed to meet the following criteria: (1) focusing on plant species existing in the ground phenological dataset; (2) testing for the effects of chilling on budburst, leaf-out or flowering; (3) having at least 3 chilling treatments. As a result, only 23 papers were included in the analyses.
These papers first exposed dormant twigs or seedlings to different periods of natural low temperatures in the field or artificial low temperatures in the refrigerator and then to different forcing temperature and photoperiod regimes in growth chambers. The most important response data in these papers are days to budburst and duration of chilling treatments (i.e., starting and ending date of chilling treatments). We used GetData Graph Digitizer (http://www.getdata-graph-digitizer.com/index.php) to scrape these response data from the figures of each paper or directly extract the data from the tables of each paper whenever possible. For studies simultaneously testing the effects of photoperiod on budburst timing, we only retained the results under long photoperiod treatment (removing the data under short photoperiod), so as to mirror the photoperiod in natural conditions. Many papers reported the degree days to budburst rather than the days to budburst. In these cases, we converted the degree days to budburst to days to budburst according to the forcing treatments in the experiments and algorithms of degree-day (i.e., starting date and temperature threshold). Meanwhile, we added relevant information to the response data according to the contents of each paper, including the sampling site of plant materials, sampling year and date, provenance origin of plant materials, chilling temperature (natural chilling or experimental chilling), forcing temperature, and forcing photoperiod.
Following the above processes, we constructed an experimental dataset involving 50 temperate woody species. Because different provenances of the same species may vary in their phenological response to chilling (Alberto, et al., 2013; Guo, et al., 2020; Thibault, et al., 2020), we compared the experimental data with the observation data at the provenance level. As a result, 94 species/provenances (64 in Europe and 30 in North America) were analyzed For each species/provenance in the experimental data, we determined the leaf morphology (coniferous or broadleaved species), plant material (twig or seedling), types of chilling treatment (natural chilling or artificial chilling), types of forcing treatment (different day/night temperature or constant temperature).
Usage notes
Microsoft Excel is required to open the data files.