course_natal.bib

@article{Rivers2011,
abstract = {The distribution, ecology and conservation status of the majority of plant species are poorly known. One of the challenges ahead is to address this knowledge gap and give more emphasis to this important group of species that represents a critical component of earth's biodiversity. Full conservation assessments require expert knowledge of the group concerned, but for the majority of plant species, especially those from the tropics, the best source of knowledge is specimens housed within herbaria. Digitisation projects are underway to render information from this important global biodiversity resource more accessible; the next step is to assemble and utilise these data to make better informed conservation decisions. One crucial question is: how many herbarium specimens are needed to detect threatened species? Such information would inform and help to prioritise digitisation efforts. Using 11,461 herbarium records we assessed species geographic range to determine a preliminary conservation status of 661 endemic species of Leguminosae and Orchidaceae from Madagascar, following the IUCN criteria. By capturing 15 georeferenced specimens per species we produced range estimates for use in conservation assessments consistent with estimates based on all known specimens, for more than 95{\%} of species. None of the threatened species were misclassified as not threatened, and less than 3{\%} of species would receive conservation support as a result of being falsely identified as threatened. This approach can therefore help progress towards the Global Strategy for Plant Conservation target of a conservation assessment for each plant species, while reducing digitisation effort by up to half. {\textcopyright} 2011 Elsevier Ltd.},
author = {Rivers, Malin C. and Taylor, Lin and Brummitt, Neil A. and Meagher, Thomas R. and Roberts, David L. and Lughadha, Eimear Nic},
doi = {10.1016/j.biocon.2011.07.014},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2011 - Rivers et al. - Biological Conservation.pdf:pdf;:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2011 - Rivers et al. - Biological Conservation(2).pdf:pdf},
issn = {00063207},
journal = {Biological Conservation},
keywords = {Conservation assessment,Herbarium specimen,Leguminosae,Madagascar,Orchidaceae,Threatened species,conservation assessment},
month = {oct},
number = {10},
pages = {2541--2547},
title = {{How many herbarium specimens are needed to detect threatened species?}},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0006320711002679 https://linkinghub.elsevier.com/retrieve/pii/S0006320711002679 http://dx.doi.org/10.1016/j.biocon.2011.07.014},
volume = {144},
year = {2011}
}
@article{Topel2017,
abstract = {{\textcopyright} The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. Understanding the patterns and processes underlying the uneven distribution of biodiversity across space constitutes a major scientific challenge in systematic biology and biogeography, which largely relies on effectively mapping and making sense of rapidly increasing species occurrence data. There is thus an urgent need for making the process of coding species into spatial units faster, automated, transparent, and reproducible. Here we present SpeciesGeoCoder, an open-source software package written in Python and R, that allows for easy coding of species into user-defined operational units. These units may be of any size and be purely spatial (i.e., polygons) such as countries and states, conservation areas, biomes, islands, biodiversity hotspots, and areas of endemism, but may also include elevation ranges. This flexibility allows scoring species into complex categories, such as those encountered in topographically and ecologically heterogeneous landscapes. In addition, SpeciesGeoCoder can be used to facilitate sorting and cleaning of occurrence data obtained from online databases, and for testing the impact of incorrect identification of specimens on the spatial coding of species. The various outputs of SpeciesGeoCoder include quantitative biodiversity statistics, global and local distribution maps, and files that can be used directly in many phylogeny-based applications for ancestral range reconstruction, investigations of biome evolution, and other comparative methods. Our simulations indicate that even datasets containing hundreds of millions of records can be analyzed in relatively short time using a standard computer. We exemplify the use of SpeciesGeoCoder by inferring the historical dispersal of birds across the Isthmus of Panama, showing that lowland species crossed the Isthmus about twice as frequently as montane species with a marked increase in the number of dispersals during the last 10 million years.},
author = {T{\"{o}}pel, Mats and Zizka, Alexander and Cali{\'{o}}, M.F. Maria Fernanda and Scharn, Ruud and Silvestro, Daniele and Antonelli, Alexandre},
doi = {10.1093/sysbio/syw064},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (Antonelli Lab)/Arbeit/Literature/Archive//2016 - T{\"{o}}pel et al. - Systematic Biology.pdf:pdf},
issn = {1063-5157},
journal = {Systematic Biology},
keywords = {Ancestral area reconstruction,Biodiversity patterns,Ecology,Evolution,Point in polygon,Species distribution data},
month = {aug},
number = {2},
pages = {145--151},
title = {{SpeciesGeoCoder: Fast categorization of species occurrences for analyses of biodiversity, biogeography, ecology, and evolution}},
url = {https://academic.oup.com/sysbio/article-lookup/doi/10.1093/sysbio/syw064},
volume = {66},
year = {2017}
}
@misc{GBIForg2020,
author = {GBIF.org},
doi = {10.15468/dl.qazjh4},
title = {{Diogenidae (25 February 2020) GBIF Occurrence Download}},
year = {2020}
}
@misc{GBIForg2020a,
author = {GBIF.org},
doi = {10.15468/dl.ixq7wh},
title = {{Entomobryidae (25 February 2020) GBIF Occurrence Download}},
year = {2020}
}
@misc{GBIForg2019c,
author = {GBIF.org},
doi = {10.15468/dl.uutyb6},
title = {{Arhynchobatidae (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019b,
author = {GBIF.org},
doi = {10.15468/dl.zv6kuq},
title = {{Tityus (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019d,
author = {GBIF.org},
doi = {10.15468/dl.8hnzfo},
title = {{Dipsadidae (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019a,
author = {GBIF.org},
doi = {10.15468/dl.bx0jjw},
title = {{Neanuridae (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@manual{Chamberlain2018,
annote = {R package version 0.5.0},
author = {Chamberlain, Scott},
title = {{rredlist: 'IUCN' Red List Client}},
url = {https://cran.r-project.org/package=rredlist},
year = {2018}
}
@misc{GBIForg2019,
author = {GBIF.org},
doi = {10.15468/dl.sojrfp},
title = {{Diogenidae (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@manual{Ooms2019,
annote = {R package version 1.2},
author = {Ooms, Jeroen},
title = {{writexl: Export Data Frames to Excel 'xlsx' Format}},
url = {https://cran.r-project.org/package=writexl},
year = {2019}
}
@article{NicLughadha2019,
abstract = {Herbarium specimens provide verifiable and citable evidence of the occurrence of particular plants at particular points in space and time, and are vital resources for assessing extinction risk in the tropics, where plant diversity and threats to plants are greatest. We reviewed approaches to assessing extinction risk in response to the Convention on Biological Diversity's Global Strategy for Plant Conservation Target 2: an assessment of the conservation status of all known plant species by 2020. We tested five alternative approaches, using herbarium-derived data for trees, shrubs and herbs in five different plant groups from temperate and tropical regions. All species were previously fully assessed for the IUCN Red List. We found significant variation in the accuracy with which different approaches classified species as threatened or not threatened. Accuracy was highest for the machine learning model (90{\%}) but the least data-intensive approach also performed well (82{\%}). Despite concerns about spatial, temporal and taxonomic biases and uncertainties in herbarium data, when specimens represent the best available evidence for particular species, their use as a basis for extinction risk assessment is appropriate, necessary and urgent. Resourcing herbaria to maintain, increase and disseminate their specimen data is essential to guide and focus conservation action. This article is part of the theme issue ‘Biological collections for understanding biodiversity in the Anthropocene'.},
author = {{Nic Lughadha}, Eimear and Walker, Barnaby E. and Canteiro, C{\'{a}}tia and Chadburn, Helen and Davis, Aaron P. and Hargreaves, Serene and Lucas, Eve J. and Schuiteman, Andr{\'{e}} and Williams, Emma and Bachman, Steven P. and Baines, David and Barker, Amy and Budden, Andrew P. and Carretero, Julia and Clarkson, James J. and Roberts, Alexandra and Rivers, Malin C.},
doi = {10.1098/rstb.2017.0402},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2019 - Nic Lughadha et al. - Philosophical Transactions of the Royal Society B Biological Sciences.pdf:pdf},
isbn = {0000000288064},
issn = {0962-8436},
journal = {Philosophical Transactions of the Royal Society B: Biological Sciences},
keywords = {Conservation assessment,Digitization,Extent of occurrence,IUCN Red List,Machine learning,Natural history collections},
month = {jan},
number = {1763},
pages = {20170402},
title = {{The use and misuse of herbarium specimens in evaluating plant extinction risks}},
url = {https://royalsocietypublishing.org/doi/10.1098/rstb.2017.0402},
volume = {374},
year = {2019}
}
@article{Ooms2014,
author = {Ooms, Jeroen},
journal = {arXiv},
title = {{The jsonlite Package: A Practical and Consistent Mapping Between JSON Data and R Objects}},
url = {https://arxiv.org/abs/1403.2805},
year = {2014}
}
@misc{GBIForg2019e,
author = {GBIF.org},
doi = {10.15468/dl.zznjbv},
title = {{Harengula (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019f,
author = {GBIF.org},
doi = {10.15468/dl.zjjpmh},
title = {{Conchocarpus (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019g,
author = {GBIF.org},
doi = {10.15468/dl.4srw8a},
title = {{Gaylussacia (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019h,
author = {GBIF.org},
doi = {10.15468/dl.rpkjsh},
title = {{Thozetella (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019i,
author = {GBIF.org},
doi = {10.15468/dl.762543},
title = {{Lepismium (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019j,
author = {GBIF.org},
doi = {doi.org/10.15468/dl.nmzgi9},
title = {{Iridaceae (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019k,
author = {GBIF.org},
doi = {10.15468/dl.scmkx5},
title = {{Pilosocereus (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019l,
author = {GBIF.org},
doi = {10.15468/dl.d34gos},
title = {{Tocoyena (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019m,
author = {GBIF.org},
doi = {10.15468/dl.6bzfz4},
title = {{Prosthechea (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019n,
author = {GBIF.org},
doi = {10.15468/dl.wkwque},
title = {{Oocephalus (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@misc{GBIForg2019o,
author = {GBIF.org},
doi = {10.15468/dl.zj2cyj},
title = {{Tillandsia (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@article{Stevart2019,
abstract = {Preserving tropical biodiversity is an urgent challenge when faced with the growing needs of countries. Despite their crucial importance for terrestrial ecosystems, most tropical plant species lack extinction risk assessments, limiting our ability to identify conservation priorities. Using a novel approach aligned with IUCN Red List criteria, we conducted a continental-scale preliminary conservation assessment of 22,036 vascular plant species in tropical Africa. Our results underline the high level of extinction risk of the tropical African flora. Thirty-three percent of the species are potentially threatened with extinction, and another third of species are likely rare, potentially becoming threatened in the near future. Four regions are highlighted with a high proportion ({\textgreater}40{\%}) of potentially threatened species: Ethiopia, West Africa, central Tanzania, and southern Democratic Republic of the Congo. Our approach represents a first step toward data-driven conservation assessments applicable at continental scales providing crucial information for sustainable economic development prioritization.},
author = {St{\'{e}}vart, T. and Dauby, G. and Lowry, P. P. and Blach-Overgaard, A. and Droissart, V. and Harris, D. J. and Mackinder, B. A. and Schatz, G. E. and Sonk{\'{e}}, B. and Sosef, M. S. M. and Svenning, J.-C. and Wieringa, J. J. and Couvreur, T. L. P.},
doi = {10.1126/sciadv.aax9444},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2019 - St{\'{e}}vart et al. - Science Advances.pdf:pdf},
issn = {2375-2548},
journal = {Science Advances},
month = {nov},
number = {11},
pages = {eaax9444},
title = {{A third of the tropical African flora is potentially threatened with extinction}},
url = {http://advances.sciencemag.org/lookup/doi/10.1126/sciadv.aax9444},
volume = {5},
year = {2019}
}
@misc{GBIF.org2019p,
author = {GBIF.org},
doi = {10.15468/dl.8hnzfo},
title = {{Dipsadidae (29 December 2019) GBIF Occurrence Download}},
year = {2019}
}
@article{Zizka2020b,
abstract = {Aim: To provide distribution information and preliminary conservation assessments for all species of the pineapple family (Bromeliaceae), one of the most diverse and ecologically important plant groups of the American tropics—a global biodiversity hotspot. Furthermore, we aim to analyse patterns of diversity, endemism and the conservation status of the Bromeliaceae on the continental level in the light of their evolutionary history. Location: The Americas. Methods: We compiled a dataset of occurrence records for 3,272 bromeliad species (93.4{\%} of the family) and modelled their geographic distribution using either climate‐based species distribution models, convex hulls or geographic buffers dependent on the number of occurrences available. We then combined this data with information on taxonomy and used the ConR software for a preliminary assessment of the conservation status of all species following Criterion B of the International Union for the Conservation of Nature (IUCN). Results: Our results stress the Atlantic Forest in eastern Brazil, the Andean slopes, Central America and the Guiana Highlands as centres of bromeliad diversity and endemism. Phylogenetically ancient subfamilies of bromeliads are centred in the Guiana highlands whereas the large radiations of the group spread across different habitats and large geographic area. A total of 81{\%} of the evaluated bromeliad species are Possibly Threatened with extinction. We provide range polygons for 3,272 species, as well as newly georeferenced point localities for 911 species in the novel “bromeliad” r package, together with functions to generate diversity maps for individual taxonomic or functional groups. Main conclusions:Diversity centres of the Bromeliaceae agreed with macroecological patterns of other plant and animal groups, but show some particular patterns related to the evolutionary origin of the family, especially ancient dispersal corridors. A staggering 2/3rds of Bromeliaceae species might be threatened with extinction, especially so in tropical rain forests, raising concerns about the conservation of the family and bromeliad‐dependent animal species.},
author = {Zizka, Alexander and Azevedo, Josue and Leme, Elton and Neves, Beatriz and Ferreira, Andrea and Caceres, Daniel and Zizka, Georg},
doi = {10.1111/ddi.13004},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2020 - Zizka et al. - Diveristy and Distributions.pdf:pdf},
journal = {Diveristy and Distributions},
number = {2},
pages = {183--195},
title = {{Biogeography and conservation status of the pineapple family (Bromeliaceae)}},
volume = {26},
year = {2020}
}
@article{Jin2020,
abstract = {High-quality data are indispensable for research and management in biodiversity conservation. Nevertheless, errors in biodiversity data must be removed before they can be used with confidence. In this study, we have developed a workflow for cleaning occurrence data archived in various biodiversity databases. The workflow allows researchers and practitioners to identify taxonomic and geographic errors in millions of records in an automatic, reproducible, and transparent manner. It also allows users to correct several types of taxonomic and geographic errors. We applied the workflow to clean global tree occurrence records. The results showed that among the 30,242,556 occurrence records of 58,034 species extracted from eight databases, only 8,624,319 (28.5{\%}) records of 22,766 (39.2{\%}) species were classified as high quality after running through the workflow. Inaccurate and non-standard taxon names appeared as a more severe problem than geographical errors that people are most familiar with. The workflow developed in this study can be easily adapted to clean occurrence records of other taxonomic groups, which allows researchers and practitioners to reduce uncertainties in their findings.},
author = {Jin, Jing and Yang, Jun},
doi = {10.1016/j.gecco.2019.e00852},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2020 - Jin, Yang - Global Ecology and Conservation.pdf:pdf},
issn = {23519894},
journal = {Global Ecology and Conservation},
month = {mar},
pages = {e00852},
publisher = {Elsevier Ltd},
title = {{BDcleaner: A workflow for cleaning taxonomic and geographic errors in occurrence data archived in biodiversity databases}},
url = {https://doi.org/10.1016/j.gecco.2019.e00852 https://linkinghub.elsevier.com/retrieve/pii/S235198941930633X},
volume = {21},
year = {2020}
}
@misc{rcoreteam2019,
address = {Austria, Vienna},
author = {{R Core Team}},
publisher = {R Foundation for Statistical Computing},
title = {{R: A language and environment for statistical computing.}},
url = {https://www.r-project.org/},
year = {2019}
}
@article{Pelletier2018,
abstract = {The conservation status of most plant species is currently unknown, despite the fundamental role of plants in ecosystem health. To facilitate the costly process of conservation assessment, we developed a predictive protocol using a machine-learning approach to predict conservation status of over 150,000 land plant species. Our study uses open-source geographic, environmental, and morphological trait data, making this the largest assessment of conservation risk to date and the only global assessment for plants. Our results indicate that a large number of unassessed species are likely at risk and identify several geographic regions with the highest need of conservation efforts, many of which are not currently recognized as regions of global concern. By providing conservation-relevant predictions at multiple spatial and taxonomic scales, predictive frameworks such as the one developed here fill a pressing need for biodiversity science.},
author = {Pelletier, Tara A. and Carstens, Bryan C. and Tank, David C. and Sullivan, Jack and Esp{\'{i}}ndola, Anah{\'{i}}},
doi = {10.1073/pnas.1804098115},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2018 - Pelletier et al. - Proceedings of the National Academy of Sciences.pdf:pdf},
issn = {0027-8424},
journal = {Proceedings of the National Academy of Sciences},
month = {dec},
number = {51},
pages = {13027--13032},
pmid = {30509998},
title = {{Predicting plant conservation priorities on a global scale}},
url = {http://www.pnas.org/lookup/doi/10.1073/pnas.1804098115},
volume = {115},
year = {2018}
}
@article{Cosiaux2018,
author = {Cosiaux, Ariane and Gardiner, Lauren M. and Stauffer, Fred W. and Bachman, Steven P. and Sonk{\'{e}}, Bonaventure and Baker, William J. and Couvreur, Thomas L.P.},
doi = {10.1016/j.biocon.2018.02.025},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2018 - Cosiaux et al. - Biological Conservation.pdf:pdf},
issn = {00063207},
journal = {Biological Conservation},
month = {may},
pages = {323--333},
title = {{Low extinction risk for an important plant resource: Conservation assessments of continental African palms (Arecaceae/Palmae)}},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0006320717317627},
volume = {221},
year = {2018}
}
@article{Zizka2019,
author = {Zizka, Alexander and Silvestro, Daniele and Andermann, Tobias and Azevedo, Josu{\'{e}} and {Duarte Ritter}, Camila and Edler, Daniel and Farooq, Harith and Herdean, Andrei and Ariza, Mar{\'{i}}a and Scharn, Ruud and Svantesson, Sten and Wengstr{\"{o}}m, Niklas and Zizka, Vera and Antonelli, Alexandre},
doi = {10.1111/2041-210X.13152},
editor = {Quental, Tiago},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2019 - Zizka et al. - Methods in Ecology and Evolution.pdf:pdf},
issn = {2041-210X},
journal = {Methods in Ecology and Evolution},
keywords = {1,biodiversity institutions,c ti o n,data quality,fossils,gbif,geo-referencing,i ntro d u,palaeobiology database,pbdb,r package,species distribution modelling},
month = {may},
number = {5},
pages = {744--751},
title = {{CoordinateCleaner: Standardized cleaning of occurrence records from biological collection databases}},
url = {http://doi.wiley.com/10.1111/2041-210X.13152 https://onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13152},
volume = {10},
year = {2019}
}
@article{Guedes2018,
abstract = {{\textcopyright} 2017 The Authors. Global Ecology and Biogeography Published by John Wiley {\&} Sons Ltd Motivation: We generated a novel database of Neotropical snakes (one of the world's richest herpetofauna) combining the most comprehensive, manually compiled distribution dataset with publicly available data. We assess, for the first time, the diversity patterns for all Neotropical snakes as well as sampling density and sampling biases. Main types of variables contained: We compiled three databases of species occurrences: a dataset downloaded from the Global Biodiversity Information Facility (GBIF), a verified dataset built through taxonomic work and specialized literature, and a combined dataset comprising a cleaned version of the GBIF dataset merged with the verified dataset. Spatial location and grain: Neotropics, Behrmann projection equivalent to 1° × 1°. Time period: Specimens housed in museums during the last 150 years. Major taxa studied: Squamata: Serpentes. Software format: Geographical information system (GIS). Results: The combined dataset provides the most comprehensive distribution database for Neotropical snakes to date. It contains 147,515 records for 886 species across 12 families, representing 74{\%} of all species of snakes, spanning 27 countries in the Americas. Species richness and phylogenetic diversity show overall similar patterns. Amazonia is the least sampled Neotropical region, whereas most well-sampled sites are located near large universities and scientific collections. We provide a list and updated maps of geographical distribution of all snake species surveyed. Main conclusions: The biodiversity metrics of Neotropical snakes reflect patterns previously documented for other vertebrates, suggesting that similar factors may determine the diversity of both ectothermic and endothermic animals. We suggest conservation strategies for high-diversity areas and sampling efforts be directed towards Amazonia and poorly known species.},
author = {Guedes, Tha{\'{i}}s B. and Sawaya, Ricardo J. and Zizka, Alexander and Laffan, Shawn and Faurby, S{\o}ren and Pyron, R. Alexander and B{\'{e}}rnils, Renato S. and Jansen, Martin and Passos, Paulo and Prudente, Ana L. C. and Cisneros-Heredia, Diego F. and Braz, Henrique B. and Nogueira, Cristiano de C. and Antonelli, Alexandre},
doi = {10.1111/geb.12679},
issn = {1466822X},
journal = {Global Ecology and Biogeography},
keywords = {GBIF,Serpentes,conservation,data availability,geographical distribution,phylogenetic diversity,sampling gaps,species richness},
month = {jan},
number = {1},
pages = {14--21},
title = {{Patterns, biases and prospects in the distribution and diversity of Neotropical snakes}},
url = {http://doi.wiley.com/10.1111/geb.12679},
volume = {27},
year = {2018}
}
@manual{Garnier2018,
annote = {R package version 0.5.1},
author = {Garnier, Simon},
title = {{viridis: Default color maps from 'matplotlib'}},
url = {https://cran.r-project.org/package=viridis},
year = {2018}
}
@techreport{IUCN2017,
author = {{IUCN Standards and Petitions Subcommittee}},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2017 - IUCN Standards and Petitions Subcommittee - Unknown.pdf:pdf},
keywords = {IUCN,Kategorien,Rote Liste Kategorien,Rote liste},
pages = {1--60},
title = {{Guidelines for Using the IUCN Red List - Categories and Criteria. Version 13. Prepared by the Standards and Petitions Subcommittee. Downloadable from http://www.iucnredlist.org/documents/RedListGuidelines.pdf}},
year = {2017}
}
@article{Dauby2017,
author = {Dauby, Gilles and St{\'{e}}vart, Tariq and Droissart, Vincent and Cosiaux, Ariane and Deblauwe, Vincent and Simo-Droissart, Murielle and Sosef, Marc S. M. and Lowry, Porter P. and Schatz, George E. and Gereau, Roy E. and Couvreur, Thomas L. P.},
doi = {10.1002/ece3.3704},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2017 - Dauby et al. - Ecology and Evolution.pdf:pdf},
issn = {20457758},
journal = {Ecology and Evolution},
keywords = {IUCN,area of occupancy,criterion B,distribution range,extent of occurrence,location,preliminary status,threatened taxa},
month = {dec},
number = {24},
pages = {11292--11303},
title = {{ConR: An R package to assist large-scale multispecies preliminary conservation assessments using distribution data}},
url = {http://doi.wiley.com/10.1002/ece3.3704},
volume = {7},
year = {2017}
}
@article{Bachman2011,
author = {Bachman, Steven P. and Moat, Justin and Hill, Andrew and de la Torre, Javier and Scott, Ben},
doi = {10.3897/zookeys.150.2109},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2011 - Bachman et al. - ZooKeys.pdf:pdf},
isbn = {1313297013132989},
issn = {1313-2970},
journal = {ZooKeys},
keywords = {AJAX,Biodiversity,Conservation,Flickr,GBIF,Geospatial,Google maps,HTML5,IUCN,JSON,Mapping,Open source,Red list},
month = {nov},
pages = {117--126},
pmid = {22207809},
title = {{Supporting Red List threat assessments with GeoCAT: geospatial conservation assessment tool}},
url = {http://zookeys.pensoft.net/articles.php?id=3037},
volume = {150},
year = {2011}
}
@misc{Hijmans2019,
annote = {R package version 2.6-7},
author = {Hijmans, Robert J.},
title = {{raster: Geographic data analysis and modeling}},
url = {https://cran.r-project.org/package=raster},
year = {2019}
}
@misc{Chamberlain2017,
author = {Chamberlain, Scott A},
title = {{rgbif: Interface to the Global Biodiversity Information Facility API. R package version 0.9.9.}},
url = {https://github.com/ropensci/rgbif},
year = {2017}
}
@article{Antonelli2018,
author = {Antonelli, Alexandre and Zizka, Alexander and Carvalho, Fernanda Antunes and Scharn, Ruud and Bacon, Christine D. and Silvestro, Daniele and Condamine, Fabien L},
doi = {10.1073/pnas.1713819115},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2018 - Antonelli et al. - Proceedings of the National Academy of Sciences.pdf:pdf},
issn = {0027-8424},
journal = {Proceedings of the National Academy of Sciences},
month = {jun},
number = {23},
pages = {6034--6039},
title = {{Amazonia is the primary source of Neotropical biodiversity}},
url = {http://www.pnas.org/lookup/doi/10.1073/pnas.1713819115},
volume = {115},
year = {2018}
}
@misc{Wickham2018,
annote = {R package version 1.2.0},
author = {Wickham, Hadley},
title = {{tidyverse: Easily install and load the 'Tidyverse'}},
url = {https://cran.r-project.org/package=tidyverse},
year = {2018}
}
@article{Yesson2007,
author = {Yesson, Chris and Brewer, Peter W and Sutton, Tim and Caithness, Neil and Pahwa, Jaspreet S and Burgess, Mikhaila and Gray, W Alec and White, Richard J and Jones, Andrew C. and Bisby, Frank A and Culham, Alastair},
doi = {10.1371/journal.pone.0001124},
editor = {Beach, James},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2007 - Yesson et al. - PLoSone.pdf:pdf},
issn = {1932-6203},
journal = {PLoS ONE},
month = {nov},
number = {11},
pages = {e1124},
title = {{How Global Is the Global Biodiversity Information Facility?}},
url = {http://dx.plos.org/10.1371/journal.pone.0001124},
volume = {2},
year = {2007}
}
@techreport{Anderson2016,
address = {Copenhagen, Denmark},
author = {Anderson, Robert P and Ara{\'{u}}jo, Miguel and Guisan, Antoine and Lobo, Jorge M and Mart{\'{i}}nez-Meyer, Enrique and Peterson, Townsend and Sober{\'{o}}n, Jorge},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2016 - Anderson et al. - Unknown.pdf:pdf},
institution = {GBIF},
pages = {27pp},
title = {{Final Report of the Task Group on GBIF Data Fitness for Use in Distribution Modelling - Are species occurrence data in global online repositories fit for modeling species distributions? The case of the Global Biodiversity Information Facility (GBIF)}},
year = {2016}
}
@misc{Chamberlain2016,
annote = {R package version 0.1.1},
author = {Chamberlain, Scott},
title = {{scrubr: Clean Biological Occurrence Records}},
url = {https://cran.r-project.org/package=scrubr},
year = {2016}
}
@article{Robertson2016,
author = {Robertson, Mark P and Visser, Vernon and Hui, Cang},
doi = {10.1111/ecog.02118},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2016 - Robertson, Visser, Hui - Ecography.pdf:pdf},
journal = {Ecography},
pages = {394--401},
title = {{Biogeo: an R package for assessing and improving data quality of occurrence record datasets}},
volume = {39},
year = {2016}
}
@article{Schmidt2017,
author = {Schmidt, Marco and Zizka, Alexander and Traor{\'{e}}, Salifou and Ataholo, Mandingo and Chatelain, Cyrille and Daget, Philippe and Dressler, Stefan and Hahn, Karen and Kirchmair, Ivana and Krohmer, Julia and Mbayngone, Elis{\'{e}}e and M{\"{u}}ller, Jonas V and Nacoulma, Blandine and Ou{\'{e}}draogo, Amad{\'{e}} and Ou{\'{e}}draogo, Oumarou and Sambar{\'{e}}, Oumarou and Schuman, Katharina and Wieringa, Jan J and Zizka, Georg and Thiombiano, Adjima},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2017 - Schmidt et al. - Phytotaxa Monographs.pdf:pdf},
isbn = {9781776701223},
journal = {Phytotaxa Monographs},
number = {1},
pages = {1--215},
title = {{Diversity, distribution and preliminary conservation status of the flora of Burkina Faso}},
volume = {304},
year = {2017}
}
@article{Lowenberg-Neto2014,
author = {Loewenberg-Neto, Peter},
doi = {10.11646/zootaxa.3802.2.12},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2014 - Loewenberg-Neto - Zootaxa.pdf:pdf},
isbn = {1175-5326 (Print)$\backslash$r1175-5326 (Linking)},
issn = {1175-5334},
journal = {Zootaxa},
keywords = {Animal Distribution,Biota,Geographic Information Systems,Geographic Mapping,Latin America,Plant Dispersal},
month = {may},
number = {2},
pages = {300},
pmid = {24871011},
title = {{Neotropical region: a shapefile of Morrone's (2014) biogeographical regionalisation}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/24871011 http://biotaxa.org/Zootaxa/article/view/zootaxa.3802.2.12},
volume = {3802},
year = {2014}
}
@article{Morrone2014,
author = {Morrone, Juan J},
doi = {10.11646/zootaxa.3782.1.1},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2014 - Morrone - Zootaxa.pdf:pdf},
isbn = {9781775573623},
issn = {1175-5334},
journal = {Zootaxa},
keywords = {Antilles,Biogeographical classification,Central america,Mexico,Neotropics,South america},
month = {mar},
number = {1},
pages = {1},
pmid = {24871951},
title = {{Biogeographical regionalisation of the Neotropical region}},
url = {http://biotaxa.org/Zootaxa/article/view/zootaxa.3782.1.1},
volume = {3782},
year = {2014}
}
@article{Maldonado2015,
author = {Maldonado, Carla and Molina, Carlos I. and Zizka, Alexander and Persson, Claes and Taylor, Charlotte M. and Alb{\'{a}}n, Joaquina and Chilquillo, Eder and R{\o}nsted, Nina and Antonelli, Alexandre},
doi = {10.1111/geb.12326},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2015 - Maldonado et al. - Global Ecology and Biogeography.pdf:pdf},
issn = {1466822X},
journal = {Global Ecology and Biogeography},
keywords = {cinchoneae,data quality,gbif,occurrence data,rubiaceae,species richness},
month = {aug},
number = {8},
pages = {973--984},
title = {{Estimating species diversity and distribution in the era of Big Data: to what extent can we trust public databases?}},
url = {http://doi.wiley.com/10.1111/geb.12326},
volume = {24},
year = {2015}
}
@book{iucn2012,
address = {Gland and Cambridge},
author = {IUCN},
edition = {Second edi},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2012 - IUCN - Unknown.pdf:pdf},
isbn = {9782831714356},
pages = {32 pp},
publisher = {IUCN},
title = {{IUCN Red List Categories and Criteria. Version 3.1}},
year = {2012}
}
@book{Goldblatt2008,
address = {Portland, London},
author = {Goldblatt, Peter and Manning, John C},
pages = {1--336},
publisher = {Timber Press},
title = {{The Iris family: Natural history and classification}},
year = {2008}
}
@article{Peterson2018,
abstract = {The field of biodiversity informatics is in a massive, “grow-out” phase of creating and enabling large-scale biodiversity data resources. Because perhaps 90{\%} of existing biodiversity data nonetheless remains unavailable for science and policy applications, the question arises as to how these existing and available data records can be mobilized most efficiently and effectively. This situation led to our analysis of several large-scale biodiversity datasets regarding birds and plants, detecting information gaps and documenting data “leakage” or attrition, in terms of data on taxon, time, and place, in each data record. We documented significant data leakage in each data dimension in each dataset. That is, significant numbers of data records are lacking crucial information in terms of taxon, time, and/or place; information on place was consistently the least complete, such that geographic referencing presently represents the most significant factor in degradation of usability of information from biodiversity information resources. Although the full process of digital capture, quality control, and enrichment is important to developing a complete digital record of existing biodiversity information, payoffs in terms of immediate data usability will be greatest with attention paid to the georeferencing challenge.},
author = {Peterson, A. Townsend and Asase, Alex and Canhos, Dora and de Souza, Sidnei and Wieczorek, John},
doi = {10.3897/BDJ.6.e26826},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2018 - Peterson et al. - Biodiversity Data Journal.pdf:pdf},
issn = {1314-2828},
journal = {Biodiversity Data Journal},
keywords = {Biodiversity data,Digitization,Fitness for use,Geographic referencing,Georeferencing,Informatics,Place,Taxon,Time,Usability},
month = {nov},
pages = {e26826},
title = {{Data Leakage and Loss in Biodiversity Informatics}},
url = {https://bdj.pensoft.net/articles.php?id=26826},
volume = {6},
year = {2018}
}
@article{Gueta2016,
abstract = {The recent availability of species occurrence data from numerous sources, standardized and connected within a single portal, has the potential to answer fundamental ecological questions. These aggregated big biodiversity databases are prone to numerous data errors and biases. The data-user is responsible for identifying these errors and assessing if the data are suitable for a given purpose. Complex technical skills are increasingly required for handling and cleaning biodiversity data, while biodiversity scientists possessing these skills are rare. Here, we estimate the effect of user-level data cleaning on species distribution model (SDM) performance. We implement several simple and easy-to-execute data cleaning procedures, and evaluate the change in SDM performance. Additionally, we examine if a certain group of species is more sensitive to the use of erroneous or unsuitable data. The cleaning procedures used in this research improved SDM performance significantly, across all scales and for all performance measures. The largest improvement in distribution models following data cleaning was for small mammals (1 g-100 g). Data cleaning at the user level is crucial when using aggregated occurrence data, and facilitating its implementation is a key factor in order to advance data-intensive biodiversity studies. Adopting a more comprehensive approach for incorporating data cleaning as part of data analysis, will not only improve the quality of biodiversity data, but will also impose a more appropriate usage of such data.},
author = {Gueta, Tomer and Carmel, Yohay},
doi = {10.1016/j.ecoinf.2016.06.001},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2016 - Gueta, Carmel - Ecological Informatics.pdf:pdf},
issn = {15749541},
journal = {Ecological Informatics},
keywords = {Australian mammals,Big-data,Biodiversity informatics,Data-cleaning,MaxEnt,SDM performance,biodiversity informatics},
pages = {139--145},
publisher = {Elsevier B.V.},
title = {{Quantifying the value of user-level data cleaning for big data: A case study using mammal distribution models}},
volume = {34},
year = {2016}
}
@article{Graham2008,
author = {Graham, Catherine H and Elith, Jane and Hijmans, Robert J and Guisan, Antoine and Peterson, A Townsend and Loiselle, Bette A and {The Nceas Predicting Species Distribution Working Group}},
doi = {10.1111/j.1365-2664.2007.01408.x},
file = {:C$\backslash$:/Users/az64mycy/Dropbox (iDiv)/Literature/2008 - Graham et al. - Journal of Applied Ecology.pdf:pdf},
journal = {Journal of Applied Ecology},
pages = {239--247},
title = {{The influence of spatial errors in species occurrence data used in distribution models}},
volume = {45},
year = {2008}
}