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Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data
This research aims to establish the possible habitat suitability of Heracleum sosnowskyi (HS), one of the most aggressive invasive plants, in current and future climate conditions across the territory of the European part of Russia. We utilised a species distribution modelling framework using public...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9005721/ https://www.ncbi.nlm.nih.gov/pubmed/35414080 http://dx.doi.org/10.1038/s41598-022-09953-9 |
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author | Koldasbayeva, Diana Tregubova, Polina Shadrin, Dmitrii Gasanov, Mikhail Pukalchik, Maria |
author_facet | Koldasbayeva, Diana Tregubova, Polina Shadrin, Dmitrii Gasanov, Mikhail Pukalchik, Maria |
author_sort | Koldasbayeva, Diana |
collection | PubMed |
description | This research aims to establish the possible habitat suitability of Heracleum sosnowskyi (HS), one of the most aggressive invasive plants, in current and future climate conditions across the territory of the European part of Russia. We utilised a species distribution modelling framework using publicly available data of plant occurrence collected in citizen science projects (CSP). Climatic variables and soil characteristics were considered to follow possible dependencies with environmental factors. We applied Random Forest to classify the study area. We addressed the problem of sampling bias in CSP data by optimising the sampling size and implementing a spatial cross-validation scheme. According to the Random Forest model built on the finally selected data shape, more than half of the studied territory in the current climate corresponds to a suitability prediction score higher than 0.25. The forecast of habitat suitability in future climate was highly similar for all climate models. Almost the whole studied territory showed the possibility for spread with an average suitability score of 0.4. The mean temperature of the wettest quarter and precipitation of wettest month demonstrated the highest influence on the HS distribution. Thus, currently, the whole study area, excluding the north, may be considered as s territory with a high risk of HS spreading, while in the future suitable locations for the HS habitat will include high latitudes. We showed that chosen geodata pre-processing, and cross-validation based on geospatial blocks reduced significantly the sampling bias. Obtained predictions could help to assess the risks accompanying the studied plant invasion capturing the patterns of the spread, and can be used for the conservation actions planning. |
format | Online Article Text |
id | pubmed-9005721 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-90057212022-04-15 Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data Koldasbayeva, Diana Tregubova, Polina Shadrin, Dmitrii Gasanov, Mikhail Pukalchik, Maria Sci Rep Article This research aims to establish the possible habitat suitability of Heracleum sosnowskyi (HS), one of the most aggressive invasive plants, in current and future climate conditions across the territory of the European part of Russia. We utilised a species distribution modelling framework using publicly available data of plant occurrence collected in citizen science projects (CSP). Climatic variables and soil characteristics were considered to follow possible dependencies with environmental factors. We applied Random Forest to classify the study area. We addressed the problem of sampling bias in CSP data by optimising the sampling size and implementing a spatial cross-validation scheme. According to the Random Forest model built on the finally selected data shape, more than half of the studied territory in the current climate corresponds to a suitability prediction score higher than 0.25. The forecast of habitat suitability in future climate was highly similar for all climate models. Almost the whole studied territory showed the possibility for spread with an average suitability score of 0.4. The mean temperature of the wettest quarter and precipitation of wettest month demonstrated the highest influence on the HS distribution. Thus, currently, the whole study area, excluding the north, may be considered as s territory with a high risk of HS spreading, while in the future suitable locations for the HS habitat will include high latitudes. We showed that chosen geodata pre-processing, and cross-validation based on geospatial blocks reduced significantly the sampling bias. Obtained predictions could help to assess the risks accompanying the studied plant invasion capturing the patterns of the spread, and can be used for the conservation actions planning. Nature Publishing Group UK 2022-04-12 /pmc/articles/PMC9005721/ /pubmed/35414080 http://dx.doi.org/10.1038/s41598-022-09953-9 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 | Article Koldasbayeva, Diana Tregubova, Polina Shadrin, Dmitrii Gasanov, Mikhail Pukalchik, Maria Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data |
title | Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data |
title_full | Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data |
title_fullStr | Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data |
title_full_unstemmed | Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data |
title_short | Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data |
title_sort | large-scale forecasting of heracleum sosnowskyi habitat suitability under the climate change on publicly available data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9005721/ https://www.ncbi.nlm.nih.gov/pubmed/35414080 http://dx.doi.org/10.1038/s41598-022-09953-9 |
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