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том 14 издание 9 страницы 2308-2320

myClim: Microclimate data handling and standardised analyses in R

Тип публикацииJournal Article
Дата публикации2023-08-08
scimago Q1
wos Q1
БС1
SJR2.945
CiteScore13.3
Impact factor6.2
ISSN2041210X, 20412096
Ecology, Evolution, Behavior and Systematics
Ecological Modeling
Краткое описание

  • Microclimates have been recognised as one of the key drivers in global change biology. Durable microclimate loggers, detailed in‐situ measurements and sophisticated modelling tools are increasingly available, but a lack of standardised workflows for microclimate data handling hinders synthesis across the studies and thus progress in the global change biology. To overcome these limitations, we developed an R package myClim for microclimate data processing, storage and analyses. The myClim package supports complete workflow for microclimate data handling, including reading raw logger data files, their preprocessing and cleaning, time‐series' aggregation, calculation of ecologically relevant microclimatic variables, data export and storage.

  • The myClim package stores data in a size‐efficient, hierarchical structure which respects the hierarchy of field microclimate measurement (locality > loggers > sensors). For imported microclimatic data, myClim provides an informative summary and automatically detects and corrects common issues like duplicated and wrongly ordered measurements. The myClim package also provides advanced functions for microclimate data aggregation to various timescales (e.g. days, months, years or growing seasons) as well as tools for sensor calibration, data conversion and joining of multiple microclimatic time series.

  • The myClim package provides advanced functions for standardised calculation of ecologically relevant microclimatic variables like freezing and growing degree days, snow cover period, soil volumetric water content and atmospheric vapour pressure deficit. Calculated microclimatic variables are stored efficiently in myClim data format and can be easily exported to long or wide tables for further analyses and visualisations.

  • Adopting myClim can facilitate large‐scale syntheses, boost data sharing and increase the comparability and reproducibility of microclimatic studies. The stable version of myClim is available on CRAN (https://cran.r‐project.org/web/packages/myClim) and the development version is available on GitHub (https://github.com/ibot‐geoecology/myClim).

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ГОСТ |
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Man M. et al. myClim: Microclimate data handling and standardised analyses in R // Methods in Ecology and Evolution. 2023. Vol. 14. No. 9. pp. 2308-2320.
ГОСТ со всеми авторами (до 50) Скопировать
Man M., Kalčík V., MACEK M., BRŮNA J., Hederová L., Wild J., KOPECKÝ M. myClim: Microclimate data handling and standardised analyses in R // Methods in Ecology and Evolution. 2023. Vol. 14. No. 9. pp. 2308-2320.
RIS |
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TY - JOUR
DO - 10.1111/2041-210x.14192
UR - https://doi.org/10.1111/2041-210x.14192
TI - myClim: Microclimate data handling and standardised analyses in R
T2 - Methods in Ecology and Evolution
AU - Man, Matěj
AU - Kalčík, Vojtěch
AU - MACEK, MARTIN
AU - BRŮNA, JOSEF
AU - Hederová, Lucia
AU - Wild, Jan
AU - KOPECKÝ, MARTIN
PY - 2023
DA - 2023/08/08
PB - Wiley
SP - 2308-2320
IS - 9
VL - 14
SN - 2041-210X
SN - 2041-2096
ER -
BibTex |
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BibTex (до 50 авторов) Скопировать
@article{2023_Man,
author = {Matěj Man and Vojtěch Kalčík and MARTIN MACEK and JOSEF BRŮNA and Lucia Hederová and Jan Wild and MARTIN KOPECKÝ},
title = {myClim: Microclimate data handling and standardised analyses in R},
journal = {Methods in Ecology and Evolution},
year = {2023},
volume = {14},
publisher = {Wiley},
month = {aug},
url = {https://doi.org/10.1111/2041-210x.14192},
number = {9},
pages = {2308--2320},
doi = {10.1111/2041-210x.14192}
}
MLA
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Man, Matěj, et al. “myClim: Microclimate data handling and standardised analyses in R.” Methods in Ecology and Evolution, vol. 14, no. 9, Aug. 2023, pp. 2308-2320. https://doi.org/10.1111/2041-210x.14192.