50 Years of Cumulative Open-Source Data Confirm Stable and Robust Biodiversity Distribution Patterns for Macrofungi
Fungi are a hyper-diverse kingdom that contributes significantly to the regulation of the global carbon and nutrient cycle. However, our understanding of the distribution of fungal diversity is often hindered by a lack of data, especially on a large spatial scale. Open biodiversity data may provide...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Journal of Fungi |
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| Online Access: | https://www.mdpi.com/2309-608X/8/9/981 |
| _version_ | 1827659871560925184 |
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| author | Haili Yu Tiejun Wang Andrew Skidmore Marco Heurich Claus Bässler |
| author_facet | Haili Yu Tiejun Wang Andrew Skidmore Marco Heurich Claus Bässler |
| author_sort | Haili Yu |
| collection | DOAJ |
| description | Fungi are a hyper-diverse kingdom that contributes significantly to the regulation of the global carbon and nutrient cycle. However, our understanding of the distribution of fungal diversity is often hindered by a lack of data, especially on a large spatial scale. Open biodiversity data may provide a solution, but concerns about the potential spatial and temporal bias in species occurrence data arising from different observers and sampling protocols challenge their utility. The theory of species accumulation curves predicts that the cumulative number of species reaches an asymptote when the sampling effort is sufficiently large. Thus, we hypothesize that open biodiversity data could be used to reveal large-scale macrofungal diversity patterns if these datasets are accumulated long enough. Here, we tested our hypothesis with 50 years of macrofungal occurrence records in Norway and Sweden that were downloaded from the Global Biodiversity Information Facility (GBIF). We first grouped the data into five temporal subsamples with different cumulative sampling efforts (i.e., accumulation of data for 10, 20, 30, 40 and 50 years). We then predicted the macrofungal diversity and distribution at each subsample using the maximum entropy (MaxEnt) species distribution model. The results revealed that the cumulative number of macrofungal species stabilized into distinct distribution patterns with localized hotspots of predicted macrofungal diversity with sampling efforts greater than approximately 30 years. Our research demonstrates the utility and importance of the long-term accumulated open biodiversity data in studying macrofungal diversity and distribution at the national level. |
| first_indexed | 2024-03-09T23:30:22Z |
| format | Article |
| id | doaj.art-92543054916a4eda8ba42e3e25742cbb |
| institution | Directory Open Access Journal |
| issn | 2309-608X |
| language | English |
| last_indexed | 2024-03-09T23:30:22Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Fungi |
| spelling | doaj.art-92543054916a4eda8ba42e3e25742cbb2023-11-23T17:10:17ZengMDPI AGJournal of Fungi2309-608X2022-09-018998110.3390/jof809098150 Years of Cumulative Open-Source Data Confirm Stable and Robust Biodiversity Distribution Patterns for MacrofungiHaili Yu0Tiejun Wang1Andrew Skidmore2Marco Heurich3Claus Bässler4Faculty of Geo-Information Science and Earth Observation, University of Twente, 7514 AE Enschede, The NetherlandsFaculty of Geo-Information Science and Earth Observation, University of Twente, 7514 AE Enschede, The NetherlandsFaculty of Geo-Information Science and Earth Observation, University of Twente, 7514 AE Enschede, The NetherlandsChair of Wildlife Ecology and Wildlife Management, University of Freiburg, 79105 Freiburg, GermanyBavarian Forest National Park, 94481 Grafenau, GermanyFungi are a hyper-diverse kingdom that contributes significantly to the regulation of the global carbon and nutrient cycle. However, our understanding of the distribution of fungal diversity is often hindered by a lack of data, especially on a large spatial scale. Open biodiversity data may provide a solution, but concerns about the potential spatial and temporal bias in species occurrence data arising from different observers and sampling protocols challenge their utility. The theory of species accumulation curves predicts that the cumulative number of species reaches an asymptote when the sampling effort is sufficiently large. Thus, we hypothesize that open biodiversity data could be used to reveal large-scale macrofungal diversity patterns if these datasets are accumulated long enough. Here, we tested our hypothesis with 50 years of macrofungal occurrence records in Norway and Sweden that were downloaded from the Global Biodiversity Information Facility (GBIF). We first grouped the data into five temporal subsamples with different cumulative sampling efforts (i.e., accumulation of data for 10, 20, 30, 40 and 50 years). We then predicted the macrofungal diversity and distribution at each subsample using the maximum entropy (MaxEnt) species distribution model. The results revealed that the cumulative number of macrofungal species stabilized into distinct distribution patterns with localized hotspots of predicted macrofungal diversity with sampling efforts greater than approximately 30 years. Our research demonstrates the utility and importance of the long-term accumulated open biodiversity data in studying macrofungal diversity and distribution at the national level.https://www.mdpi.com/2309-608X/8/9/981species distribution modelspecies discovery curvespecies richnesshotspot |
| spellingShingle | Haili Yu Tiejun Wang Andrew Skidmore Marco Heurich Claus Bässler 50 Years of Cumulative Open-Source Data Confirm Stable and Robust Biodiversity Distribution Patterns for Macrofungi Journal of Fungi species distribution model species discovery curve species richness hotspot |
| title | 50 Years of Cumulative Open-Source Data Confirm Stable and Robust Biodiversity Distribution Patterns for Macrofungi |
| title_full | 50 Years of Cumulative Open-Source Data Confirm Stable and Robust Biodiversity Distribution Patterns for Macrofungi |
| title_fullStr | 50 Years of Cumulative Open-Source Data Confirm Stable and Robust Biodiversity Distribution Patterns for Macrofungi |
| title_full_unstemmed | 50 Years of Cumulative Open-Source Data Confirm Stable and Robust Biodiversity Distribution Patterns for Macrofungi |
| title_short | 50 Years of Cumulative Open-Source Data Confirm Stable and Robust Biodiversity Distribution Patterns for Macrofungi |
| title_sort | 50 years of cumulative open source data confirm stable and robust biodiversity distribution patterns for macrofungi |
| topic | species distribution model species discovery curve species richness hotspot |
| url | https://www.mdpi.com/2309-608X/8/9/981 |
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