Package: chillR 0.75

chillR: Statistical Methods for Phenology Analysis in Temperate Fruit Trees

The phenology of plants (i.e. the timing of their annual life phases) depends on climatic cues. For temperate trees and many other plants, spring phases, such as leaf emergence and flowering, have been found to result from the effects of both cool (chilling) conditions and heat. Fruit tree scientists (pomologists) have developed some metrics to quantify chilling and heat (e.g. see Luedeling (2012) <doi:10.1016/j.scienta.2012.07.011>). 'chillR' contains functions for processing temperature records into chilling (Chilling Hours, Utah Chill Units and Chill Portions) and heat units (Growing Degree Hours). Regarding chilling metrics, Chill Portions are often considered the most promising, but they are difficult to calculate. This package makes it easy. 'chillR' also contains procedures for conducting a PLS analysis relating phenological dates (e.g. bloom dates) to either mean temperatures or mean chill and heat accumulation rates, based on long-term weather and phenology records (Luedeling and Gassner (2012) <doi:10.1016/j.agrformet.2011.10.020>). As of version 0.65, it also includes functions for generating weather scenarios with a weather generator, for conducting climate change analyses for temperature-based climatic metrics and for plotting results from such analyses. Since version 0.70, 'chillR' contains a function for interpolating hourly temperature records.

Authors:Eike Luedeling [aut, cre], Lars Caspersen [aut], Eduardo Fernandez [aut]

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chillR.pdf |chillR.html✨
chillR/json (API)

# Install 'chillR' in R:
install.packages('chillR', repos = c('https://eikeluedeling.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

106 exports 3 stars 1.64 score 112 dependencies 1 dependents 3 mentions 296 scripts 913 downloads

Last updated 10 months agofrom:7adb7cba36. Checks:OK: 7 NOTE: 2. Indexed: yes.

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Doc / VignettesOKSep 08 2024
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R-4.4-win-x86_64OKSep 08 2024
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R-4.3-win-x86_64OKSep 08 2024
R-4.3-mac-x86_64OKSep 08 2024
R-4.3-mac-aarch64OKSep 08 2024

Exports:add_datebloom_predictionbloom_prediction2bloom_prediction3bootstrap.phenologyFitcheck_temperature_recordcheck_temperature_scenariochile_agromet2chillRchillingChilling_Hourschilling_hourtablecolor_bar_makerconvert_scen_informationdaily_chillDate2YEARMODAdaylengthdownload_baseline_cmip6_ecmwfrdownload_cmip6_ecmwfrDynamic_ModelDynModel_driverEmpirical_daily_temperature_curveEmpirical_hourly_temperaturesextract_cmip6_dataextract_differences_between_charactersextract_temperatures_from_gridsfilter_temperaturesfix_weatherGDDGDHGDH_modelgen_rel_change_scenariogenSeasongenSeasonListget_last_dateget_weathergetClimateWizard_scenariosgetClimateWizardDatahandle_cimishandle_dwdhandle_dwd_oldhandle_gsodhandle_gsod_oldhandle_ucipmidentify_common_stringinterpolate_gapsinterpolate_gaps_hourlyJDay_countJDay_earlierJDay_laterleap_yearload_ClimateWizard_scenariosload_temperature_scenariosmake_all_day_tablemake_california_UCIPM_station_listmake_chill_plotmake_climate_scenariomake_climate_scenario_from_filesmake_daily_chill_figuresmake_daily_chill_plotmake_daily_chill_plot2make_hourly_tempsmake_JDaymake_multi_pheno_trend_plotmake_pheno_trend_plotordered_climate_listpatch_daily_temperaturespatch_daily_tempsPhenoFlexPhenoFlex_fixedDynModelGAUSSwrapperPhenoFlex_fixedDynModelwrapperPhenoFlex_GAUSSwrapperPhenoFlex_GDHwrapperphenologyFitphenologyFitterplot_climate_scenariosplot_phenology_trendsplot_PLSplot_scenariosPLS_chill_forcePLS_phenoread_tabRMSEPRPDRPIQrunn_meanrunn_mean_predsave_temperature_scenariosselect_by_file_extensionstack_hourly_tempsstage_transitionsstep_modelStepChill_Wrappertemperature_generationtemperature_scenario_baseline_adjustmenttemperature_scenario_from_recordstempResponsetempResponse_daily_listtempResponse_hourtabletest_if_equalUniChill_WrapperUnifiedModel_WrapperUniForce_WrapperUtah_ModelVIPweather2chillRYEARMODA2Date

Dependencies:askpassassertthatbackportsbitopsbootcachemcellrangercheckmatechronclassclassIntclicolorspacecpp11crayoncurldata.tabledateDBIdigestdotCall64dplyre1071ecmwfrfansifarverfastmapfieldsfilelockFormulaformula.toolsgenericsGenSAgetPassggplot2gluegtablehmshttrisobandjsonliteKendallKernSmoothkeyringlabelinglatticelifecyclelmtestlubridatemagrittrmapsMASSMatrixmemoisemetRmgcvmimemunsellnlmeopenssloperator.toolspatchworkpillarpkgconfigplsplyrprettyunitsprogressproxypurrrR.methodsS3R.ooR.utilsR6rappdirsrasterRColorBrewerRcppRCurlreadxlrematchreshape2rlangRMAWGENrstudioapis2sandwichscalessfsodiumspspamstringistringrstrucchangesysterratibbletidyrtidyselecttimechangeunitsurcautf8varsvctrsviridisLitewithrwkXMLyamlzoo

PhenoFlex

Carsten Urbach, Eike Luedeling, Katja Schiffers

Rendered fromPhenoFlex.Rmdusingknitr::rmarkdownon Sep 08 2024.

Last update: 2020-12-10
Started: 2020-12-10

Producing hourly temperature records for agroclimatic analysis

Eike Luedeling, University of Bonn, Germany

Rendered fromhourly_temperatures.Rmdusingknitr::rmarkdownon Sep 08 2024.

Last update: 2020-12-10
Started: 2018-01-04

Readme and manuals

Help Manual

Help pageTopics
chillR: statistical methods for phenology analysis in temperate fruit treeschillR-package
Add date/time column to data.frameadd_date
Bloom prediction from chilling and forcing requirements, assumed to be fulfilled strictly in sequencebloom_prediction
Bloom prediction from chilling and forcing requirements, assumed to be fulfilled strictly in sequence - version 2bloom_prediction2
Bloom prediction from chilling and forcing requirements, assumed to be fulfilled strictly in sequence - version 3bloom_prediction3
bootstrap.phenologyFitbootstrap.phenologyFit
Concatenate bootstrap_phenologyfit objectsc.bootstrap_phenologyFit
Weather stations in Californiacalifornia_stations
Check a daily or hourly temperature record for compliance with chillR's standardscheck_temperature_record
Check temperature scenario for consistencycheck_temperature_scenario
chifullchifull
Convert a weather file downloaded from the Chilean Agromet website to chillR formatchile_agromet2chillR
Calculation of chilling and heat from hourly temperature recordschilling
Calculation of cumulative chill according to the Chilling Hours ModelChilling_Hours
Add chilling and heat accumulation to table of hourly temperatureschilling_hourtable
ChuineCFChuineCF
ChuineFstarChuineFstar
Make color scheme for bar plots in outputs of the chillR packagecolor_bar_maker
Converts list of change scenarios to data.frame or vice versaconvert_scen_information
Calculation of daily chill and heat accumulationdaily_chill
Date to YEARMODA conversionDate2YEARMODA
Compute sunrise and sunset times, and daylengthdaylength
Download historical CMIP6 Data via the ecwfr packagedownload_baseline_cmip6_ecmwfr
Download CMIP6 Data via the ecwfr packagedownload_cmip6_ecmwfr
Dynamic_ModelDynamic_Model
DynModel_driverDynModel_driver
Empirical daily temperature curveEmpirical_daily_temperature_curve
Empirical daily temperature predictionEmpirical_hourly_temperatures
Unpacks and formats downloaded CMIP6 dataextract_cmip6_data
Identify shared leading or trailing character stringsextract_differences_between_characters
Extract temperature information from gridded datasetextract_temperatures_from_grids
Quality filter for temperature recordsfilter_temperatures
Weather data fixer and quality checkerfix_weather
Calculation of cumulative heat according to the Growing Degree Day ModelGDD
Calculation of cumulative heat according to the Growing Degree Hours ModelGDH
Calculation of cumulative heat according to the Growing Degree Hours Model (alternative function name)GDH_model
Generates relative climate change scenarios based on extracted CMIP6 datagen_rel_change_scenario
Generate SeasonsgenSeason
genSeasonListgenSeasonList
Get the last date from a phenology recordget_last_date
Download weather data from online databaseget_weather
Extract mutltiple scenarios from the ClimateWizard databasegetClimateWizard_scenarios
Extract climate data from the ClimateWizard databasegetClimateWizardData
List, download or convert to chillR format data from the CIMIS databasehandle_cimis
List, download or convert to chillR format data from the Deutscher Wetterdienst databasehandle_dwd
List, download or convert to chillR format data from the Deutscher Wetterdienst databasehandle_dwd_old
List, download or convert to chillR format data from the Global Summary of the Day databasehandle_gsod
Deprecated version of handle_gsod. List, download or convert to chillR format data from the Global Summary of the Day databasehandle_gsod_old
List, download or convert to chillR format data from the UCIPM databasehandle_ucipm
Identify shared leading or trailing character stringsidentify_common_string
Linear gap interpolationinterpolate_gaps
Interpolate gaps in hourly temperature recordsinterpolate_gaps_hourly
Count days between two Julian datesJDay_count
Check whether a Julian date is before or after another oneJDay_earlier
Check whether a Julian date is after another oneJDay_later
Cherry bloom data for Klein-Altendorf, GermanyKA_bloom
Weather data for Klein-Altendorf, GermanyKA_weather
Leap year finderleap_year
Load climate wizard scenariosload_ClimateWizard_scenarios
Load temperature scenariosload_temperature_scenarios
Fill in missing days in incomplete time seriesmake_all_day_table
Makes a list of the UC IPM weather stationsmake_california_UCIPM_station_list
Plot climate metrics over timemake_chill_plot
Make climate scenariomake_climate_scenario
Make climate scenario from multiple saved csv filesmake_climate_scenario_from_files
Produce image of daily chill and heat accumulationmake_daily_chill_figures
Plot daily climate metric accumulation throughout the yearmake_daily_chill_plot
Plot daily climate metric accumulation throughout the year (2)make_daily_chill_plot2
Make hourly temperature record from daily datamake_hourly_temps
Make Julian Day in dataframemake_JDay
Combine multiple phenology contour plots in one figuremake_multi_pheno_trend_plot
Make image showing phenology response to temperatures during two phasesmake_pheno_trend_plot
Sort files in a folder, so that numbers are in ascending sequenceordered_climate_list
Patch gaps in daily weather recordspatch_daily_temperatures
Patch gaps in daily weather records - updatedpatch_daily_temps
PhenoFlexPhenoFlex
PhenoFlex_fixedDynModelGAUSSwrapperPhenoFlex_fixedDynModelGAUSSwrapper
PhenoFlex_fixedDynModelwrapperPhenoFlex_fixedDynModelwrapper
PhenoFlex_GAUSSwrapperPhenoFlex_GAUSSwrapper
PhenoFlex_GDHwrapperPhenoFlex_GDHwrapper
phenologyFitphenologyFit
phenologyFitterphenologyFitter
Plot multiple chilling scenario groups (or for other metrics)plot_climate_scenarios
Plot mutltiple ClimateWizard scenarios obtained with getClimateWizard_scenariosplot_climateWizard_scenarios
Visualizing phenology responses to temperatures during two phasesplot_phenology_trends
Output of Partial Least Squares analysis results of phenology vs. daily mean temperaturesplot_PLS
Plot historic and future scenarios for climate-related metrics ('ggplot2' version)plot_scenarios
plot bootstrap_phenologyFitplot.bootstrap_phenologyFit
plot phenologyFitplot.phenologyFit
Partial Least Squares analysis of phenology vs. accumulated daily chill and heatPLS_chill_force
Partial Least Squares analysis of phenology vs. daily mean temperaturesPLS_pheno
predict bootstrap_phenologyFitpredict.bootstrap_phenologyFit
predict phenologyFitpredict.phenologyFit
print phenologyFitprint.phenologyFit
Read csv table regardless of whether it is a true csv or the French typeread_tab
Root Mean Square Error of Prediction (RMSEP)RMSEP
Residual Prediction Deviation (RPD)RPD
Ratio of Performance to InterQuartile distance (RPIQ)RPIQ
Running mean of a vectorrunn_mean
Prediction based on a running meanrunn_mean_pred
Save temperature scenarios generated with temperature_generationsave_temperature_scenarios
Select string that end in a particular way (e.g. a certain file extension)select_by_file_extension
Stacking of hourly temperaturesstack_hourly_temps
Compute what it takes to advance through development stagesstage_transitions
Calculation of cumulative temperature metric according to a user-defined stepwise weight functionstep_model
StepChill_WrapperStepChill_Wrapper
summary.bootstrap_phenologyFitsummary.bootstrap_phenologyFit
summary phenologyFitsummary.phenologyFit
Generation of synthetic temperature recordstemperature_generation
Make temperature scenario relative to a particular baselinetemperature_scenario_baseline_adjustment
Make monthly temperature scenario from historic recordstemperature_scenario_from_records
Calculation of climatic metrics from hourly temperature recordstempResponse
Calculation of climatic metrics from lists of daily temperature recordstempResponse_daily_list
Add metric accumulation to table of hourly temperaturestempResponse_hourtable
Test if all character vectors in a string are equaltest_if_equal
UniChill_WrapperUniChill_Wrapper
UnifiedModel_WrapperUnifiedModel_Wrapper
UniForce_WrapperUniForce_Wrapper
Calculation of cumulative chill according to the Utah ModelUtah_Model
Calculate VIP scores for PLS regressionVIP
Convert downloaded weather to chillR formatweather2chillR
Hourly temperature data sampleWinters_hours_gaps
YEARMODA to Date conversionYEARMODA2Date