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Ten best practices for effective phenological research
The number and diversity of phenological studies has increased rapidly in recent years. Innovative experiments, field studies, citizen science projects, and analyses of newly available historical data are contributing insights that advance our understanding of ecological and evolutionary responses t...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10457241/ https://www.ncbi.nlm.nih.gov/pubmed/37507579 http://dx.doi.org/10.1007/s00484-023-02502-7 |
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author | Primack, Richard B. Gallinat, Amanda S. Ellwood, Elizabeth R. Crimmins, Theresa M. Schwartz, Mark D. Staudinger, Michelle D. Miller-Rushing, Abraham J. |
author_facet | Primack, Richard B. Gallinat, Amanda S. Ellwood, Elizabeth R. Crimmins, Theresa M. Schwartz, Mark D. Staudinger, Michelle D. Miller-Rushing, Abraham J. |
author_sort | Primack, Richard B. |
collection | PubMed |
description | The number and diversity of phenological studies has increased rapidly in recent years. Innovative experiments, field studies, citizen science projects, and analyses of newly available historical data are contributing insights that advance our understanding of ecological and evolutionary responses to the environment, particularly climate change. However, many phenological data sets have peculiarities that are not immediately obvious and can lead to mistakes in analyses and interpretation of results. This paper aims to help researchers, especially those new to the field of phenology, understand challenges and practices that are crucial for effective studies. For example, researchers may fail to account for sampling biases in phenological data, struggle to choose or design a volunteer data collection strategy that adequately fits their project’s needs, or combine data sets in inappropriate ways. We describe ten best practices for designing studies of plant and animal phenology, evaluating data quality, and analyzing data. Practices include accounting for common biases in data, using effective citizen or community science methods, and employing appropriate data when investigating phenological mismatches. We present these best practices to help researchers entering the field take full advantage of the wealth of available data and approaches to advance our understanding of phenology and its implications for ecology. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00484-023-02502-7. |
format | Online Article Text |
id | pubmed-10457241 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-104572412023-08-27 Ten best practices for effective phenological research Primack, Richard B. Gallinat, Amanda S. Ellwood, Elizabeth R. Crimmins, Theresa M. Schwartz, Mark D. Staudinger, Michelle D. Miller-Rushing, Abraham J. Int J Biometeorol Review Paper The number and diversity of phenological studies has increased rapidly in recent years. Innovative experiments, field studies, citizen science projects, and analyses of newly available historical data are contributing insights that advance our understanding of ecological and evolutionary responses to the environment, particularly climate change. However, many phenological data sets have peculiarities that are not immediately obvious and can lead to mistakes in analyses and interpretation of results. This paper aims to help researchers, especially those new to the field of phenology, understand challenges and practices that are crucial for effective studies. For example, researchers may fail to account for sampling biases in phenological data, struggle to choose or design a volunteer data collection strategy that adequately fits their project’s needs, or combine data sets in inappropriate ways. We describe ten best practices for designing studies of plant and animal phenology, evaluating data quality, and analyzing data. Practices include accounting for common biases in data, using effective citizen or community science methods, and employing appropriate data when investigating phenological mismatches. We present these best practices to help researchers entering the field take full advantage of the wealth of available data and approaches to advance our understanding of phenology and its implications for ecology. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00484-023-02502-7. Springer Berlin Heidelberg 2023-07-29 2023 /pmc/articles/PMC10457241/ /pubmed/37507579 http://dx.doi.org/10.1007/s00484-023-02502-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Paper Primack, Richard B. Gallinat, Amanda S. Ellwood, Elizabeth R. Crimmins, Theresa M. Schwartz, Mark D. Staudinger, Michelle D. Miller-Rushing, Abraham J. Ten best practices for effective phenological research |
title | Ten best practices for effective phenological research |
title_full | Ten best practices for effective phenological research |
title_fullStr | Ten best practices for effective phenological research |
title_full_unstemmed | Ten best practices for effective phenological research |
title_short | Ten best practices for effective phenological research |
title_sort | ten best practices for effective phenological research |
topic | Review Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10457241/ https://www.ncbi.nlm.nih.gov/pubmed/37507579 http://dx.doi.org/10.1007/s00484-023-02502-7 |
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