| 1. |
- Zizka, Alexander, 1986, et al.
(författare)
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CoordinateCleaner: Standardized cleaning of occurrence records from biological collection databases
- 2019
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Ingår i: Methods in Ecology and Evolution. - : Wiley. - 2041-210X. ; 10:5, s. 744-751
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Tidskriftsartikel (refereegranskat)abstract
- Species occurrence records from online databases are an indispensable resource in ecological, biogeographical and palaeontological research. However, issues with data quality, especially incorrect geo-referencing or dating, can diminish their usefulness. Manual cleaning is time-consuming, error prone, difficult to reproduce and limited to known geographical areas and taxonomic groups, making it impractical for datasets with thousands or millions of records. Here, we present CoordinateCleaner, an r-package to scan datasets of species occurrence records for geo-referencing and dating imprecisions and data entry errors in a standardized and reproducible way. CoordinateCleaner is tailored to problems common in biological and palaeontological databases and can handle datasets with millions of records. The software includes (a) functions to flag potentially problematic coordinate records based on geographical gazetteers, (b) a global database of 9,691 geo-referenced biodiversity institutions to identify records that are likely from horticulture or captivity, (c) novel algorithms to identify datasets with rasterized data, conversion errors and strong decimal rounding and (d) spatio-temporal tests for fossils. We describe the individual functions available in CoordinateCleaner and demonstrate them on more than 90million occurrences of flowering plants from the Global Biodiversity Information Facility (GBIF) and 19,000 fossil occurrences from the Palaeobiology Database (PBDB). We find that in GBIF more than 3.4 million records (3.7%) are potentially problematic and that 179 of the tested contributing datasets (18.5%) might be biased by rasterized coordinates. In PBDB, 1205 records (6.3%) are potentially problematic. All cleaning functions and the biodiversity institution database are open-source and available within the CoordinateCleaner r-package.
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| 2. |
- Edler, Daniel, et al.
(författare)
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raxmlGUI 2.0: A graphical interface and toolkit for phylogenetic analyses using RAxML
- 2021
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Ingår i: Methods in Ecology and Evolution. - : John Wiley & Sons. - 2041-210X. ; 12:2, s. 373-377
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Tidskriftsartikel (refereegranskat)abstract
- raxmlGUI is a graphical user interface to RAxML, one of the most popular and widely used softwares for phylogenetic inference using maximum likelihood. Here we present raxmlGUI 2.0, a complete rewrite of the GUI which seamlessly integrates RAxML binaries for all major operating systems with an intuitive graphical front-end to setup and run phylogenetic analyses. Our program offers automated pipelines for analyses that require multiple successive calls of RAxML, built-in functions to concatenate alignment files while automatically specifying the appropriate partition settings, and one-click model testing to select the best substitution models using ModelTest-NG. In addition to RAxML 8.x, raxmlGUI 2.0 also supports the new RAxML-NG, which provides new functionality and higher performance on large datasets. raxmlGUI 2.0 facilitates phylogenetic analyses by coupling an intuitive interface with the unmatched performance of RAxML. © 2020 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society
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| 3. |
- Farage, C., et al.
(författare)
-
Identifying flow modules in ecological networks using Infomap
- 2021
-
Ingår i: Methods in Ecology and Evolution. - : Wiley. - 2041-210X. ; 12:5, s. 778-786
-
Tidskriftsartikel (refereegranskat)abstract
- Analysing how species interact in modules is a fundamental problem in network ecology. Theory shows that a modular network structure can reveal underlying dynamic ecological and evolutionary processes, influence dynamics that operate on the network and affect the stability of the ecological system. Although many ecological networks describe flows, such as biomass flows in food webs or disease transmission, most modularity analyses have ignored network flows, which can hinder our understanding of the interplay between structure and dynamics. Here we present Infomap, an established method based on network flows to the field of ecological networks. Infomap is a flexible tool that can identify modules in virtually any type of ecological network and is particularly useful for directed, weighted and multilayer networks. We illustrate how Infomap works on all these network types. We also provide a fully documented repository with additional ecological examples. Finally, to help researchers to analyse their networks with Infomap, we introduce the open-source R package infomapecology. Analysing flow-based modularity is useful across ecology and transcends to other biological and non-biological disciplines. A dynamic approach for detecting modular structure has strong potential to provide new insights into the organisation of ecological networks.
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| 4. |
- Farage, Carmel, et al.
(författare)
-
Identifying flow modules in ecological networks using Infomap
- 2021
-
Ingår i: Methods in Ecology and Evolution. - London : British Ecology Society. - 2041-210X. ; 12:5, s. 778-786
-
Tidskriftsartikel (refereegranskat)abstract
- Analysing how species interact in modules is a fundamental problem in network ecology. Theory shows that a modular network structure can reveal underlying dynamic ecological and evolutionary processes, influence dynamics that operate on the network and affect the stability of the ecological system. Although many ecological networks describe flows, such as biomass flows in food webs or disease transmission, most modularity analyses have ignored network flows, which can hinder our understanding of the interplay between structure and dynamics. Here we present Infomap, an established method based on network flows to the field of ecological networks. Infomap is a flexible tool that can identify modules in virtually any type of ecological network and is particularly useful for directed, weighted and multilayer networks. We illustrate how Infomap works on all these network types. We also provide a fully documented repository with additional ecological examples. Finally, to help researchers to analyse their networks with Infomap, we introduce the open-source R package infomapecology. Analysing flow-based modularity is useful across ecology and transcends to other biological and non-biological disciplines. A dynamic approach for detecting modular structure has strong potential to provide new insights into the organisation of ecological networks.
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| 5. |
- Zizka, Alexander, et al.
(författare)
-
CoordinateCleaner : Standardized cleaning of occurrence records from biological collection databases
- 2019
-
Ingår i: Methods in Ecology and Evolution. - : Wiley-Blackwell. - 2041-210X. ; 10:5, s. 744-751
-
Tidskriftsartikel (refereegranskat)abstract
- Species occurrence records from online databases are an indispensable resource in ecological, biogeographical and palaeontological research. However, issues with data quality, especially incorrect geo-referencing or dating, can diminish their usefulness. Manual cleaning is time-consuming, error prone, difficult to reproduce and limited to known geographical areas and taxonomic groups, making it impractical for datasets with thousands or millions of records.Here, we present CoordinateCleaner, an r-package to scan datasets of species occurrence records for geo-referencing and dating imprecisions and data entry errors in a standardized and reproducible way. CoordinateCleaner is tailored to problems common in biological and palaeontological databases and can handle datasets with millions of records. The software includes (a) functions to flag potentially problematic coordinate records based on geographical gazetteers, (b) a global database of 9,691 geo-referenced biodiversity institutions to identify records that are likely from horticulture or captivity, (c) novel algorithms to identify datasets with rasterized data, conversion errors and strong decimal rounding and (d) spatio-temporal tests for fossils.We describe the individual functions available in CoordinateCleaner and demonstrate them on more than 90million occurrences of flowering plants from the Global Biodiversity Information Facility (GBIF) and 19,000 fossil occurrences from the Palaeobiology Database (PBDB). We find that in GBIF more than 3.4 million records (3.7%) are potentially problematic and that 179 of the tested contributing datasets (18.5%) might be biased by rasterized coordinates. In PBDB, 1205 records (6.3%) are potentially problematic.All cleaning functions and the biodiversity institution database are open-source and available within the CoordinateCleaner r-package.
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