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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%",
eval = FALSE
)
```
## [fruclimadapt](https://github.com/Carm1r/fruclimadapt): Evaluation tools for assessing climate adaptation of fruit tree species in [R](https://www.r-project.org).
[](https://www.gnu.org/licenses/gpl-3.0)
This package is a compilation of functions for the assessment of climate adaptation and the identification of potential risks for grapevines and fruit trees. Procedures in the package allow to:
* Downscale daily meteorological variables to hourly values
* Estimate chilling and forcing heat accumulation
* Estimate plant phenology
* Calculate bioclimatic indices to evaluate fruit tree and grapevine adaptation
* Estimate the indicence of weather-related disorders in fruits
* Estimate plant water requirements.
<div id="menu" />
---------------------------------------------
## Resources
* [Installation](#Instal)
* [1. Required packages](#P1)
* [2. Example: Estimate the phenology of a peach cultivar](#P2)
* [3. Example: Estimate the number and damage caused by spring frosts](#P3)
<div id="Instal" />
---------------------------------------------
## Installation
You can install the released version of fruclimadapt from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("fruclimadapt")
```
And the development version from [GitHub](https://github.com/) with:
``` r
install.packages("devtools")
library(devtools)
devtools::install_github("Carm1r/fruclimadapt")
```
[Menu](#menu)
<div id="P1" />
---------------------------------------------
## Using fruclimadapt
### 1. Required packages
> * **[data.table](https://CRAN.R-project.org/package=data.table)**
> * **[lubridate](https://CRAN.R-project.org/package=lubridate)**
> * **[tidyverse](https://CRAN.R-project.org/package=tidyverse)**
> * **[zoo](https://CRAN.R-project.org/package=zoo)**
```r
install.packages("data.table")
install.packages("lubridate")
install.packages("tidyverse")
install.packages("zoo")
library(fruclimadapt)
library(data.table)
library(tidyverse)
library(zoo)
```
[Menu](#menu)
<div id="P2" />
---------------------------------------------
### 2. Example. Estimate the phenology of a peach cultivar
This example shows how to use the functions *hourly_temps*, *chill_portions*, *GDH_linear* and *phenology_sequential* to estimate the date of occurrence of the phenological stages for a nectarine cultivar, using daily weather data.
```{r example1}
library(fruclimadapt)
# Generate a dataset with hourly temperatures from the dataset with daily values (Tudela_DW, included in the package)
data(Tudela_DW)
Tudela_HT <- hourly_temps(Tudela_DW,42.13132)
# Use the hourly dataset to calculate chill as chill portions and growing degree hours
# Calculate chill as chill portions, starting on DOY 305
Chill <- chill_portions(Tudela_HT,305)
# Calculate forcing heat as growing degree hours (GDH) with the linear model using base temperature 4.7 C and no upper thresholds
GDH <- GDH_linear(Tudela_HT,4.7,999,999)
# Combine the datasets Chill and GDH in a dataframe with a format compatible with the function phenology_sequential
Tudela_CH <- merge(Chill,GDH) %>%
select(Date, Year, Month, Day, DOY, Chill,GDH) %>%
arrange(Date) %>%
rename(GD=GDH)
# Obtain the predicted dates for the cultivar "Big Top" using the requirement dataset included in the package (Bigtop_reqs)
data(Bigtop_reqs)
Phenology_BT <- phenology_sequential(Tudela_CH, Bigtop_reqs, 305)
```
[Menu](#menu)
<div id="P3" />
---------------------------------------------
### 3. Estimate the number and damage caused by spring frosts
This example shows how to use the function *spring_frost* to estimate the number and accumulated damage caused by spring frosts from budbreaking for the same nectarine cultivar used to estimate the phenology in the previous example.
```{r example2}
library(fruclimadapt)
# Use the dataframe with the phenological dates obtained with phenology_sequential to generate a new one with the format required by the function spring_frost
Phenology_frost <- Phenology_BT %>%
select(Freq_Year,Freq_DOY) %>%
rename(Year=Freq_Year,Pheno_date=Freq_DOY)
# Extract a dataframe with daily minimum temperatures from the daily climate example dataset with the format required by spring_frost
Tmin_Tudela <- Tudela_DW %>%
mutate(Date=make_date(Year,Month,Day), DOY=yday(Date)) %>%
select(Year, DOY, Tmin)
# Predict the number and accumulated damage of the spring frosts using the critical values contained in the example dataset Tcrits_peach and extract the dataframe with the total results for each year
data(Tcrits_peach)
Frost_BT <- spring_frost(Tmin_Tudela, Phenology_frost, Tcrits_peach, 181)
Frost_results <- as.data.frame(Frost_BT[['Damage_frosts']])
```
[Menu](#menu)
## Licenses
The R/fruclimadapt package as a whole is distributed under [GPL-3 (GNU General Public License version 3)](https://www.gnu.org/licenses/gpl-3.0).
## Author
[Carlos Miranda](https://github.com/Carm1r)