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Patten NN, Gaynor ML, Soltis DE, Soltis PS. Geographic And Taxonomic Occurrence R-based Scrubbing (gatoRs): An R package and workflow for processing biodiversity data. APPLICATIONS IN PLANT SCIENCES 2024; 12:e11575. [PMID: 38638614 PMCID: PMC11022233 DOI: 10.1002/aps3.11575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 01/07/2024] [Accepted: 01/14/2024] [Indexed: 04/20/2024]
Abstract
Premise Digitized biodiversity data offer extensive information; however, obtaining and processing biodiversity data can be daunting. Complexities arise during data cleaning, such as identifying and removing problematic records. To address these issues, we created the R package Geographic And Taxonomic Occurrence R-based Scrubbing (gatoRs). Methods and Results The gatoRs workflow includes functions that streamline downloading records from the Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio). We also created functions to clean downloaded specimen records. Unlike previous R packages, gatoRs accounts for differences in download structure between GBIF and iDigBio and allows for user control via interactive cleaning steps. Conclusions Our pipeline enables the scientific community to process biodiversity data efficiently and is accessible to the R coding novice. We anticipate that gatoRs will be useful for both established and beginning users. Furthermore, we expect our package will facilitate the introduction of biodiversity-related concepts into the classroom via the use of herbarium specimens.
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Affiliation(s)
- Natalie N. Patten
- Department of MathematicsUniversity of FloridaGainesville32611FloridaUSA
- Present address:
Department of MathematicsThe Ohio State UniversityColumbus43210OhioUSA
| | - Michelle L. Gaynor
- Florida Museum of Natural HistoryUniversity of FloridaGainesville32611FloridaUSA
- Department of BiologyUniversity of FloridaGainesville32611FloridaUSA
| | - Douglas E. Soltis
- Florida Museum of Natural HistoryUniversity of FloridaGainesville32611FloridaUSA
- Department of BiologyUniversity of FloridaGainesville32611FloridaUSA
| | - Pamela S. Soltis
- Florida Museum of Natural HistoryUniversity of FloridaGainesville32611FloridaUSA
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Cazalis V, Santini L, Lucas PM, González-Suárez M, Hoffmann M, Benítez-López A, Pacifici M, Schipper AM, Böhm M, Zizka A, Clausnitzer V, Meyer C, Jung M, Butchart SHM, Cardoso P, Mancini G, Akçakaya HR, Young BE, Patoine G, Di Marco M. Prioritizing the reassessment of data-deficient species on the IUCN Red List. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2023; 37:e14139. [PMID: 37394972 DOI: 10.1111/cobi.14139] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 06/05/2023] [Accepted: 06/08/2023] [Indexed: 07/04/2023]
Abstract
Despite being central to the implementation of conservation policies, the usefulness of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species is hampered by the 14% of species classified as data-deficient (DD) because information to evaluate these species' extinction risk was lacking when they were last assessed or because assessors did not appropriately account for uncertainty. Robust methods are needed to identify which DD species are more likely to be reclassified in one of the data-sufficient IUCN Red List categories. We devised a reproducible method to help red-list assessors prioritize reassessment of DD species and tested it with 6887 DD species of mammals, reptiles, amphibians, fishes, and Odonata (dragonflies and damselflies). For each DD species in these groups, we calculated its probability of being classified in a data-sufficient category if reassessed today from covariates measuring available knowledge (e.g., number of occurrence records or published articles available), knowledge proxies (e.g., remoteness of the range), and species characteristics (e.g., nocturnality); calculated change in such probability since last assessment from the increase in available knowledge (e.g., new occurrence records); and determined whether the species might qualify as threatened based on recent rate of habitat loss determined from global land-cover maps. We identified 1907 species with a probability of being reassessed in a data-sufficient category of >0.5; 624 species for which this probability increased by >0.25 since last assessment; and 77 species that could be reassessed as near threatened or threatened based on habitat loss. Combining these 3 elements, our results provided a list of species likely to be data-sufficient such that the comprehensiveness and representativeness of the IUCN Red List can be improved.
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Affiliation(s)
- Victor Cazalis
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Leipzig University, Leipzig, Germany
| | - Luca Santini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
| | - Pablo M Lucas
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
| | - Manuela González-Suárez
- Ecology and Evolutionary Biology, School of Biological Sciences, University of Reading, Reading, UK
| | | | - Ana Benítez-López
- Integrative Ecology Group, Estación Biológica de Doñana (EBD-CSIC), Sevilla, Spain
- Department of Zoology, Faculty of Science, University of Granada, Granada, Spain
| | - Michela Pacifici
- Global Mammal Assessment Programme, Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
| | - Aafke M Schipper
- Department of Environmental Science, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, Nijmegen, The Netherlands
- PBL Netherlands Environmental Assessment Agency, The Hague, The Netherlands
| | - Monika Böhm
- Global Center for Species Survival, Indianapolis Zoological Society, Indianapolis, Indiana, USA
| | - Alexander Zizka
- Department of Biology, Philipps-University Marburg, Marburg, Germany
| | | | - Carsten Meyer
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Institute of Geosciences and Geography, Martin Luther University Halle-Wittenberg, Halle, Germany
- Institute of Biology, Leipzig University, Leipzig, Germany
| | - Martin Jung
- Biodiversity, Ecology and Conservation Group, Biodiversity and Natural Resources Management Programme, International Institute for Applied Systems Analysis, Laxenburg, Austria
| | - Stuart H M Butchart
- BirdLife International, David Attenborough Building, Cambridge, UK
- Department of Zoology, University of Cambridge, Cambridge, UK
| | - Pedro Cardoso
- Laboratory for Integrative Biodiversity Research (LIBRe), Finnish Museum of Natural History Luomus, University of Helsinki, Helsinki, Finland
| | - Giordano Mancini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
| | - H Reşit Akçakaya
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York, USA
- IUCN Species Survival Commission (SSC), Gland, Switzerland
| | | | - Guillaume Patoine
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Institute of Biology, Leipzig University, Leipzig, Germany
| | - Moreno Di Marco
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
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Coca-De-La-Iglesia M, Valcárcel V, Medina NG. A Protocol to Retrieve and Curate Spatial and Climatic Data from Online Biodiversity Databases Using R. Bio Protoc 2023; 13:e4847. [PMID: 37900105 PMCID: PMC10603197 DOI: 10.21769/bioprotoc.4847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 08/11/2023] [Accepted: 08/11/2023] [Indexed: 10/31/2023] Open
Abstract
Ecological and evolutionary studies often require high quality biodiversity data. This information is readily available through the many online databases that have compiled biodiversity data from herbaria, museums, and human observations. However, the process of preparing this information for analysis is complex and time consuming. In this study, we have developed a protocol in R language to process spatial data (download, merge, clean, and correct) and extract climatic data, using some genera of the ginseng family (Araliaceae) as an example. The protocol provides an automated way to process spatial and climatic data for numerous taxa independently and from multiple online databases. The script uses GBIF, BIEN, and WorldClim as the online data sources, but can be easily adapted to include other online databases. The script also uses genera as the sampling unit but provides a way to use species as the target. The cleaning process includes a filter to remove occurrences outside the natural range of the taxa, gardens, and other human environments, as well as erroneous locations and a spatial correction for misplaced occurrences (i.e., occurrences within a distance buffer from the coastal boundary). Additionally, each step of the protocol can be run independently. Thus, the protocol can begin with data cleaning, if the database has already been compiled, or with climatic data extraction, if the database has already been parsed. Each line of the R script is commented so that it can also be run by users with little knowledge of R.
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Affiliation(s)
- Marina Coca-De-La-Iglesia
- Departamento de Biología, Universidad Autónoma de Madrid (UAM), Madrid, Spain
- TRAGSATEC, Madrid, Spain
| | - Virginia Valcárcel
- Departamento de Biología, Universidad Autónoma de Madrid (UAM), Madrid, Spain
- Centro de Investigación en Biodiversidad y Cambio Global (CIBC-UAM), Madrid, Spain
| | - Nagore G. Medina
- Departamento de Biología, Universidad Autónoma de Madrid (UAM), Madrid, Spain
- Centro de Investigación en Biodiversidad y Cambio Global (CIBC-UAM), Madrid, Spain
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Karger DN, Saladin B, Wüest RO, Graham CH, Zurell D, Mo L, Zimmermann NE. Interannual climate variability improves niche estimates for ectothermic but not endothermic species. Sci Rep 2023; 13:12538. [PMID: 37532828 PMCID: PMC10397316 DOI: 10.1038/s41598-023-39637-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 07/28/2023] [Indexed: 08/04/2023] Open
Abstract
Climate is an important limiting factor of species' niches and it is therefore regularly included in ecological applications such as species distribution models (SDMs). Climate predictors are often used in the form of long-term mean values, yet many species experience wide climatic variation over their lifespan and within their geographical range which is unlikely captured by long-term means. Further, depending on their physiology, distinct groups of species cope with climate variability differently. Ectothermic species, which are directly dependent on the thermal environment are expected to show a different response to temporal or spatial variability in temperature than endothermic groups that can decouple their internal temperature from that of their surroundings. Here, we explore the degree to which spatial variability and long-term temporal variability in temperature and precipitation change niche estimates for ectothermic (730 amphibian, 1276 reptile), and endothermic (1961 mammal) species globally. We use three different species distribution modelling (SDM) algorithms to quantify the effect of spatial and temporal climate variability, based on global range maps of all species and climate data from 1979 to 2013. All SDMs were cross-validated and accessed for their performance using the Area under the Curve (AUC) and the True Skill Statistic (TSS). The mean performance of SDMs using only climatic means as predictors was TSS = 0.71 and AUC = 0.90. The inclusion of spatial variability offers a significant gain in SDM performance (mean TSS = 0.74, mean AUC = 0.92), as does the inclusion of temporal variability (mean TSS = 0.80, mean AUC = 0.94). Including both spatial and temporal variability in SDMs shows the highest scores in AUC and TSS. Accounting for temporal rather than spatial variability in climate improved the SDM prediction especially in ectotherm groups such as amphibians and reptiles, while for endothermic mammals no such improvement was observed. These results indicate that including long term climate interannual climate variability into niche estimations matters most for ectothermic species that cannot decouple their physiology from the surrounding environment as endothermic species can.
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Affiliation(s)
- Dirk Nikolaus Karger
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland.
| | - Bianca Saladin
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
| | - Rafael O Wüest
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
| | - Catherine H Graham
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
| | - Damaris Zurell
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
- University of Potsdam, Maulbeerallee 3, 14469, Potsdam, Germany
| | - Lidong Mo
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
- ETH Zurich, Universitätstrasse 16, 8092, Zürich, Switzerland
| | - Niklaus E Zimmermann
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
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Vicente JR, Vaz AS, Roige M, Winter M, Lenzner B, Clarke DA, McGeoch MA. Existing indicators do not adequately monitor progress toward meeting invasive alien species targets. Conserv Lett 2022. [DOI: 10.1111/conl.12918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Affiliation(s)
- Joana R. Vicente
- CIBIO‐InBIO, Research Center in Biodiversity and Genetic Resources University of Porto Vila do Conde Portugal
- Faculty of Sciences, Department of Biology University of Porto Porto Portugal
- BIOPOLIS Program in Genomics Biodiversity and Land Planning, CIBIO Campus de Vairão Vairão Portugal
| | - A. Sofia Vaz
- CIBIO‐InBIO, Research Center in Biodiversity and Genetic Resources University of Porto Vila do Conde Portugal
- Faculty of Sciences, Department of Biology University of Porto Porto Portugal
- BIOPOLIS Program in Genomics Biodiversity and Land Planning, CIBIO Campus de Vairão Vairão Portugal
| | - Mariona Roige
- AgResearch, Lincoln Research Centre Lincoln New Zealand
| | - Marten Winter
- German Centre for Integrative Biodiversity Research (iDiv), Halle‐Jena‐Leipzig Deutscher Platz 5e Leipzig Germany
| | - Bernd Lenzner
- Bioinvasions, Global Change, Macroecology Group, Department of Botany and Biodiversity Research University of Vienna Vienna Austria
| | - David A. Clarke
- Department of Environment and Genetics La Trobe University Melbourne Victoria Australia
| | - Melodie A. McGeoch
- Department of Environment and Genetics La Trobe University Melbourne Victoria Australia
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