Cargando…
Trends and gaps in biodiversity and ecosystem services research: A text mining approach
Understanding the relationship between biodiversity conservation and ecosystem services concepts is essential for evidence-based policy development. We used text mining augmented by topic modelling to analyse abstracts of 15 310 peer-reviewed papers (from 2000 to 2020). We identified nine major topi...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9666618/ https://www.ncbi.nlm.nih.gov/pubmed/36057041 http://dx.doi.org/10.1007/s13280-022-01776-2 |
_version_ | 1784831550199693312 |
---|---|
author | Takacs, Viktoria O’Brien, C. David |
author_facet | Takacs, Viktoria O’Brien, C. David |
author_sort | Takacs, Viktoria |
collection | PubMed |
description | Understanding the relationship between biodiversity conservation and ecosystem services concepts is essential for evidence-based policy development. We used text mining augmented by topic modelling to analyse abstracts of 15 310 peer-reviewed papers (from 2000 to 2020). We identified nine major topics; “Research & Policy”, “Urban and Spatial Planning”, “Economics & Conservation”, “Diversity & Plants”, “Species & Climate change”, “Agriculture”, “Conservation and Distribution”, “Carbon & Soil & Forestry”, “Hydro-& Microbiology”. The topic “Research & Policy” performed highly, considering number of publications and citation rate, while in the case of other topics, the “best” performances varied, depending on the indicator applied. Topics with human, policy or economic dimensions had higher performances than the ones with ‘pure’ biodiversity and science. Agriculture dominated over forestry and fishery sectors, while some elements of biodiversity and ecosystem services were under-represented. Text mining is a powerful tool to identify relations between research supply and policy demand. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13280-022-01776-2. |
format | Online Article Text |
id | pubmed-9666618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-96666182022-11-30 Trends and gaps in biodiversity and ecosystem services research: A text mining approach Takacs, Viktoria O’Brien, C. David Ambio Review Understanding the relationship between biodiversity conservation and ecosystem services concepts is essential for evidence-based policy development. We used text mining augmented by topic modelling to analyse abstracts of 15 310 peer-reviewed papers (from 2000 to 2020). We identified nine major topics; “Research & Policy”, “Urban and Spatial Planning”, “Economics & Conservation”, “Diversity & Plants”, “Species & Climate change”, “Agriculture”, “Conservation and Distribution”, “Carbon & Soil & Forestry”, “Hydro-& Microbiology”. The topic “Research & Policy” performed highly, considering number of publications and citation rate, while in the case of other topics, the “best” performances varied, depending on the indicator applied. Topics with human, policy or economic dimensions had higher performances than the ones with ‘pure’ biodiversity and science. Agriculture dominated over forestry and fishery sectors, while some elements of biodiversity and ecosystem services were under-represented. Text mining is a powerful tool to identify relations between research supply and policy demand. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13280-022-01776-2. Springer Netherlands 2022-09-03 2023-01 /pmc/articles/PMC9666618/ /pubmed/36057041 http://dx.doi.org/10.1007/s13280-022-01776-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Takacs, Viktoria O’Brien, C. David Trends and gaps in biodiversity and ecosystem services research: A text mining approach |
title | Trends and gaps in biodiversity and ecosystem services research: A text mining approach |
title_full | Trends and gaps in biodiversity and ecosystem services research: A text mining approach |
title_fullStr | Trends and gaps in biodiversity and ecosystem services research: A text mining approach |
title_full_unstemmed | Trends and gaps in biodiversity and ecosystem services research: A text mining approach |
title_short | Trends and gaps in biodiversity and ecosystem services research: A text mining approach |
title_sort | trends and gaps in biodiversity and ecosystem services research: a text mining approach |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9666618/ https://www.ncbi.nlm.nih.gov/pubmed/36057041 http://dx.doi.org/10.1007/s13280-022-01776-2 |
work_keys_str_mv | AT takacsviktoria trendsandgapsinbiodiversityandecosystemservicesresearchatextminingapproach AT obriencdavid trendsandgapsinbiodiversityandecosystemservicesresearchatextminingapproach |