Package: hatchR 1.0.1.9000

hatchR: Predict Fish Hatch and Emergence Timing

Predict hatch and emergence timing for a wide range of wild fishes using the effective value framework (Sparks et al., (2019) <doi:10.1139/cjfas-2017-0468>). 'hatchR' offers users access to established phenological models and the flexibility to incorporate custom parameterizations using external datasets.

Authors:Bryan M. Maitland [aut, cre], Morgan M. Sparks [aut, cph], Eli Felts [ctb], Allison Swartz [ctb], Paul Frater [ctb]

hatchR_1.0.1.9000.tar.gz
hatchR_1.0.1.9000.zip(r-4.7)hatchR_1.0.1.9000.zip(r-4.6)hatchR_1.0.1.9000.zip(r-4.5)
hatchR_1.0.1.9000.tgz(r-4.6-any)hatchR_1.0.1.9000.tgz(r-4.5-any)
hatchR_1.0.1.9000.tar.gz(r-4.7-any)hatchR_1.0.1.9000.tar.gz(r-4.6-any)
hatchR_1.0.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
hatchR/json (API)

# Install 'hatchR' in R:
install.packages('hatchR', repos = c('https://bmait101.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bmait101/hatchr/issues

Pkgdown/docs site:https://bmait101.github.io

Datasets:

On CRAN:

Conda:

7.06 score 4 stars 41 scripts 235 downloads 8 exports 40 dependencies

Last updated from:efb8c0e8d0. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK158
source / vignettesOK277
linux-release-x86_64OK119
macos-release-arm64OK171
macos-oldrel-arm64OK138
windows-develOK92
windows-releaseOK157
windows-oldrelOK100
wasm-releaseOK124

Exports:check_continuousfit_modelmodel_selectplot_check_tempplot_phenologypredict_phenologypredict_spawnsummarize_temp

Dependencies:clicommonmarkcpp11curldplyrfarvergenericsggplot2ggtextgluegridtextgtableisobandjpeglabelinglifecyclelitedownlubridatemagrittrmarkdownpillarpkgconfigpngR6RColorBrewerRcpprlangS7scalesstringistringrtibbletidyselecttimechangeutf8vctrsviridisLitewithrxfunxml2

Launching Shiny
Introduction | Shiny server | Using Shiny locally | In Rstudio | With internet | Without internet

Last update: 2025-08-13
Started: 2025-04-25

Non-fish examples
A simple example: coastal tailed frogs | Multiple populations: developmental rates of cabbage beetles | Model sources | References

Last update: 2025-07-16
Started: 2025-07-15

Predict fish phenology: basic
Overview | Data checks | Model select | Predict phenology | Understanding your results | Visualizing phenology | A note about negative temperatures | References

Last update: 2025-06-10
Started: 2024-11-20

Predict spawning
Introduction | Workflow | Model selection | Compare to predict_phenology() | Using multiple inputs for predict_spawn()

Last update: 2025-05-05
Started: 2025-05-02

Advanced plotting
Overview | A simple example | Plotting multiple years | Plotting multiple individual spawning events | References

Last update: 2025-04-25
Started: 2024-11-22

Model bibliography
Bibliography

Last update: 2025-04-25
Started: 2025-02-28

Parameterize hatchR Models
Overview | Built-in parameterizations | model_table | model_select() | Creating custom models | fit_model() | Fitting models for other fishes | Important considerations | References

Last update: 2025-04-25
Started: 2024-11-20

Predict fish phenology: advanced
Overview | Multiple spawn dates | Looping | Vectorizing | Mapping | Apply | Iterating over multiple variables | Getting usable output | Naming your lists | References

Last update: 2025-04-25
Started: 2024-11-20

Predict fish phenology: nested
Overview | Example Data | Nested Dataframes | Data Check | Mapping Across Nested Data | References

Last update: 2025-04-25
Started: 2024-11-22

Introduction
Overview | Input Data Requirements | Water Temperature Data | Dates and Times | Reading in dates from a file | From strings | From individual components | Time Zones | Importing water temperature data | Using readr::read_csv() | Using read.csv() | Temperature data checks | Visualize your temperature data | Summarize temperature data | Check for continuous data | Species-specific model parameters | Spawn Dates | Next steps | References

Last update: 2025-02-07
Started: 2024-11-18