Package 'epicrop'

Description

Extracts Area Under Disease Progress Curve (AUDPC) values along with location and emergence date information from an epicrop.sim object.

Usage

audpc_dt(x)

Arguments

Value

A data.table::data.table() with columns:

• lat: Latitude (if available)

• lon: Longitude (if available)

• AUDPC: Area under disease progress curve

• emergence: Emergence date (as character)

Description

Construct a vector of emergence dates by combining a set of years with a set of month-day strings (e.g., "-06-01"), returning a sorted IDate vector tagged with class epicrop.emerge for downstream use with run_epicrop_model().

Usage

build_epicrop_emergence(years, month_day)

Arguments

Value

A sorted vector of data.table::IDate emergence dates with class epicrop.emerge (i.e., inherits(x, "epicrop.emerge") will be TRUE).

Author(s)

Adam H. Sparks, [email protected]

See Also

run_epicrop_model(), fetch_epicrop_weather_list()

Examples

# Basic usage: combine years with multiple month-day patterns
years <- 2001:2002
month_day <- c("-06-01", "-06-14", "-06-30")

em <- build_epicrop_emergence(years, month_day)
em

# Check class and structure
inherits(em, "epicrop.emerge")   # TRUE
head(em)                         # First few dates (IDate)
length(em)                       # 6 (2 years × 3 month-days)

# Typical downstream: pass to run_epicrop_model(...)
# run_epicrop_model(bacterial_blight, em, wth_list, output = "audpc")

Description

Helper functions with pre-loaded parameter tables for optimal performance. Custom parameter tables can be provided to override defaults.

Usage

bacterial_blight(
  wth,
  emergence,
  RcA = NULL,
  RcT = NULL,
  RRS = NULL,
  RRG = NULL,
  ...
)

brown_spot(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

leaf_blast(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

sheath_blight(
  wth,
  emergence,
  RcA = NULL,
  RcT = NULL,
  RRS = NULL,
  RRG = NULL,
  ...
)

tungro(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

modified_kim_leaf_blast(
  wth,
  emergence,
  RcA = NULL,
  RcT = NULL,
  RRS = NULL,
  RRG = NULL,
  ...
)

modified_kim_sheath_blight(
  wth,
  emergence,
  RcA = NULL,
  RcT = NULL,
  RRS = NULL,
  RRG = NULL,
  ...
)

leaf_rust(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

s_tritici_blotch(
  wth,
  emergence,
  RcA = NULL,
  RcT = NULL,
  RRS = NULL,
  RRG = NULL,
  ...
)

bb(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

bs(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

lb(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

sb(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

tg(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

mk_lb(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

mk_sb(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

lr(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

brown_rust(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

stb(wth, emergence, RcA = NULL, RcT = NULL, RRS = NULL, RRG = NULL, ...)

Arguments

 Details

Author(s)

Adam H. Sparks, [email protected]

References

Savary, S., Nelson, A., Willocquet, L., Pangga, I., and Aunario, J. (2012). Modeling and mapping potential epidemics of rice diseases globally. Crop Protection, 34: 6-17. doi:10.1016/j.cropro.2011.11.009

Kim, K. H., Cho, J., Lee, Y. H., & Lee, W. S. (2015). Predicting potential epidemics of rice leaf blast and sheath blight in South Korea. Agricultural and Forest Meteorology, 203: 191-207. doi:10.1016/j.agrformet.2015.01.011

Savary, S., Stetkiewicz, S., Brun, F., & Willocquet, L. (2015). Modelling and mapping potential epidemics of wheat diseases. European Journal of Plant Pathology, 142: 771-790. doi:10.1007/s10658-015-0650-7

Description

Retrieve one or more continuous blocks of weather for one or more locations from given start dates and durations, then split each result into a named list of per‑year tables. Each (location, start, duration) result is an epicrop.wth.list. The top-level return is an epicrop.wth.bundle when multiple requests are processed, otherwise a single epicrop.wth.list.

Usage

fetch_epicrop_weather_list(
  lonlat,
  start_date,
  duration,
  years = NULL,
  mode = "pairwise",
  location_names = NULL
)

Arguments

Details

Flexible inputs

• lonlat: a single numeric vector, c(lon, lat); or multiple locations as a numeric vector of length ⁠2n⁠, or a 2‑column matrix/data.frame, or a list of list(c(lon, lat)).

• start_date: a single "YYYY-MM-DD" (or Date/IDate), or a vector of the same; or a month–day string like "06-30" or "6-30" (leading "-" optional) provided together with years.

• duration: single integer or a vector (recycled); interpreted as inclusive days to fetch (end = start + duration - 1).

• years: only used when start_date lacks a year. We compute a cover window per distinct month–day: start = min(paste(years, md)), end = max(paste(years, md)) + (duration - 1).

Value

• If only one (location, start, duration) is requested: an epicrop.wth.list.

• Otherwise: an epicrop.wth.bundle (a named list of epicrop.wth.list).

Author(s)

Adam H. Sparks, [email protected]

Examples

# Single location, month-day start date (any of "6/30", "-06-30", "06-30")
w1 <- fetch_epicrop_weather_list(
  lonlat     = c(121.255669, 14.16742),
  start_date = "6/30",
  duration   = 120L,
  years      = 2000:2001
)

# ISO start date
w2 <- fetch_epicrop_weather_list(
  lonlat     = c(121.255669, 14.16742),
  start_date = "2000-06-30",
  duration   = 120L
)

# Multiple locations × multiple dates (cross mode), mixed inputs
locations <- rbind(
  "IRRI_ZES" = c(121.255669, 14.16742),
  "Metro_Manila" = c(120.985, 14.6042)
)
w3 <- fetch_epicrop_weather_list(
  lonlat     = locations,
  start_date = c("2000-06-30", "6-30"),
  duration   = 120L,
  years      = 2000:2001,
  mode       = "cross"
)

# Multiple start dates for same location across years (efficient API calls)
w4 <- fetch_epicrop_weather_list(
  lonlat     = c(121.255669, 14.16742),
  start_date = c("-06-01", "-06-14", "-06-30"),
  duration   = 90L,
  years      = 2001:2003
)
# This makes only 3 API calls (one per year), fetching from earliest to
# latest start date + duration

Description

Formats an existing data.frame() of weather data for use in epicrop. Only the data necessary for use in the model is returned and the columns are renamed to values expected by the model. The data are assumed to be on a daily time-step. For converting sub-daily weather data to daily, see cropgrowdays::daily_mean().

Usage

format_wth(wth, date, temp, rhum, rain, tmin, tmax, lat, lon)

Arguments

Details

Required values

Weather data must be a daily time-step and contain the following values,

• full date including year, month and day,

• average daily temperature,

• average daily relative humidity,

• total daily rainfall

Optional values

The following values are optional and the model can be run by default without them.

• average minimum daily temperature (only used if simple_wetness == FALSE)

• average maximum daily temperature (only used if simple_wetness == FALSE)

• Latitude (only used if simple_wetness == FALSE and for mapping outputs)

• Longitude (only used for mapping outputs)

  Field Name	Value
  YYYYMMDD	Date as Year Month Day (ISO8601)
  DOY	Consecutive day of year, commonly called "Julian date"
  TEMP	Mean daily temperature (°C)
  TMIN	Daily minimum temperature (°C)
  TMAX	Daily maximum temperature (°C)
  RHUM	Mean daily relative humidity (%)
  RAIN	Mean daily rainfall (mm)
  LAT	Latitude of area of interest
  LON	Longitude of area of interest.

Value

An epicrop.wth object, a data frame compatible with a data.table::data.table(), suitable for use in epicrop.

Author(s)

Adam H. Sparks, [email protected]

Examples

# Get weather data from the POWER API, using the `get_wth()` function,
# this is for example purposes only as it is NOT necessary to reformat
# the data provided by `get_wth()`.

library(nasapower)
w <- get_power(
  lonlat = c(121.25562, 14.6674),
  dates = c("2000-06-30", "2000-12-31"),
  community = "AG",
  pars = c(
    "T2M",
    "T2M_MIN",
    "T2M_MAX",
    "RH2M",
    "PRECTOTCORR"
  ),
  temporal_api = "DAILY"
)

format_wth(
  wth = w,
  date = "YYYYMMDD",
  temp = "T2M",
  rhum = "RH2M",
  rain = "PRECTOTCORR",
  tmin = "T2M_MIN",
  tmax = "T2M_MAX",
  lat = "LAT",
  lon = "LON"
)

Description

Get the AUDPC value from an epicrop model run object's attributes for use in analysis, mapping, or reporting.

Usage

get_audpc(x)

Arguments

Value

Numeric AUDPC value

Description

This function is a wrapper for the nasapower::get_power() with predefined parameters suitable for use in epicrop.

Usage

get_wth(lonlat, dates, duration = NULL)

Arguments

Value

A epicrop.wth, a data frame based on a data.table::data.table(), object suitable for use in epicrop containing weather data, dates and geolocation information (LAT/LON values) with the following columns:

Author(s)

Adam H. Sparks, [email protected]

Examples

# get weather for IRRI Zeigler Experiment Station in wet season 2000 from the
# default NASA POWER data.
power <- get_wth(
  lonlat = c(121.25562, 14.6774),
  dates = c("2000-06-30", "2000-12-31")
)

# get 120 days of weather for IRRI Zeigler Experiment Station in wet season
# 2000 by specifying the duration but not the end-date and specifying to use
# POWER data.
power <- get_wth(
  lonlat = c(121.25562, 14.6774),
  dates = "2000-06-30",
  duration = 120
)

Description

A unified helper that executes any epicrop model (e.g., bacterial_blight(), brown_spot(), leaf_blast(), sheath_blight(), tungro(), modified_kim_leaf_blast(), modified_kim_sheath_blight(), leaf_rust(), or s_tritici_blotch()) over a set of emergence dates, using a list of per-year weather data.tables. Handles within-year and cross-year windows without globally binding weather.

Usage

run_epicrop_model(
  model_fun,
  emergence_dates,
  wth_list,
  window_days = 120L,
  output = "audpc",
  ...
)

Arguments

Value

A data.table::data.table. When output = "audpc": columns emergence (IDate) and AUDPC (numeric). When output = "full": full model output columns plus emergence, and an AUDPC column preserved per emergence date.

Author(s)

Adam H. Sparks, [email protected]

See Also

fetch_epicrop_weather_list, build_epicrop_emergence

Examples

years <- 2001:2003
month_day <- c("-06-01", "-06-14", "-06-30")
lonlat <- c(121.255669, 14.16742)
duration <- 120L
emergence <- build_epicrop_emergence(years, month_day)

wth_list <- fetch_epicrop_weather_list(years,
                                       lonlat,
                                       start_date = month_day,
                                       duration = duration)
run_epicrop_model(bacterial_blight, emergence, wth_list)

Description

This function is originally used by specific disease models in ‘EPIRICE’ and ‘EPIWHEAT’ to model disease intensity of several rice diseases and two wheat diseases respectively. Given proper values it can be used with other pathosystems as well.

Usage

seir(
  wth,
  emergence,
  onset,
  duration,
  H0,
  I0,
  RcA,
  RcT,
  RcOpt,
  p,
  i,
  Sx,
  a = 1,
  rhlim = 90,
  rainlim = 5,
  RRS = NULL,
  RRG = NULL,
  RcW = NULL,
  RRLEX = NULL,
  simple_wetness = TRUE,
  weighted_wetness = FALSE,
  age_driver = c("day", "dvs"),
  thermal_time = NULL,
  infection_window = NULL
)

Arguments

 Details

Value

A data.table::data.table() object containing the following columns:

simday

Day of simulation (1-indexed, where 1 is the emergence date)

dates

Date of simulation (Date class)

sites

Total number of healthy sites present on day "x"

latent

Number of latent sites present on day "x"

infectious

Number of infectious sites present on day "x"

removed

Number of removed sites present on day "x"

senesced

Number of senesced sites present on day "x"

rateinf

Rate of infection (new infections on day "x")

rlex

Rate of lesion expansion (healthy sites converted to infectious via direct expansion on day "x")

rtransfer

Rate of transfer from latent to infectious sites on day "x"

rremoved

Rate of removal from infectious to removed sites on day "x"

rgrowth

Rate of growth of healthy sites on day "x"

rsenesced

Rate of senescence of healthy sites on day "x"

diseased

Number of diseased (latent + infectious + removed) sites on day "x"

intensity

Proportion of diseased sites (latent + infectious) per total living sites (excludes removed and senesced) on day "x"

lat

Latitude value if provided by the wth object

lon

Longitude value if provided by the wth object

The returned object also has an attribute AUDPC (accessed via attr(result, "AUDPC")) containing the area under the disease progress curve for the entire simulation, calculated using the trapezoidal rule.

Output Structure

The output is organized into three categories:

State Variables (stocks at end of each day):

• sites, latent, infectious, removed, senesced

Flow Variables (rates/changes during each day):

• rateinf, rlex, rtransfer, rremoved, rgrowth, rsenesced

Derived Variables (calculated from states):

• diseased, intensity

Mass Balance: At any day: sites + latent + infectious + removed + senesced should equal initial sites (H0) plus cumulative growth minus cumulative senescence (accounting for numerical precision).

a – Aggregation Details

When a is set to 1 the assumption is that that there is no disease aggregation with new infections occurring at random among the healthy sites. When a is greater than 1 there is aggregation in the disease occurrence, the pathogen is unable to access the entire population of healthy sites, which results in disease aggregation. Refer to Savary et al. (2012) for greater detail.

TMIN/TMAX Details

If simple_wetness is set to FALSE, the function will use the TMIN and TMAX columns in the wth object to calculate the leaf wetness value for 24 hours of the day using the rhlim and rainlim values and then uses RcW to calculate a value between 0 and 1 for the whole day. When simple_wetness is set to TRUE, the function only sets the leaf wetness to 0 or 1 for the day based on the rhlim and rainlim values.

LAT/LON Details

If the wth object provides LAT and LON columns, these will be included in the output for mapping purposes. Both values must be present. These columns are provided by default when using get_wth().

Author(s)

Adam H. Sparks, [email protected] from original by Robert J. Hijmans, Rene Pangga and Jorrel Aunario.

References

Sparks, A. H., P. D. Esker, M. Bates, W. Dall' Acqua, Z. Guo, V. Segovia, S.D. Silwal, S. Tolos, and K. A. Garrett, 2008. Ecology and Epidemiology in R: Disease Progress over Time. The Plant Health Instructor. doi:10.1094/PHI-A-2008-0129-02.

Madden, L. V., G. Hughes, and F. van den Bosch. 2007. The Study of Plant Disease Epidemics. American Phytopathological Society, St. Paul, MN. doi:10.1094/9780890545058.

Savary, S., Nelson, A., Willocquet, L., Pangga, I., and Aunario, J. Modeling and mapping potential epidemics of rice diseases globally. Crop Protection, Volume 34, 2012, Pages 6-17, ISSN 0261-2194 doi:10.1016/j.cropro.2011.11.009.

See Also

Disease-specific helper functions:

• bacterial_blight(),

• brown_spot(),

• leaf_blast(),

• sheath_blight(),

• tungro(),

• modified_kim_leaf_blast(),

• modified_kim_sheath_blight(),

• leaf_rust(), and

• s_tritici_blotch().