1
|
Wang Q, Wang H, Chang R, Zeng H, Bai X. Dynamic simulation patterns and spatiotemporal analysis of land-use/land-cover changes in the Wuhan metropolitan area, China. Ecol Modell 2022. [DOI: 10.1016/j.ecolmodel.2021.109850] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
|
2
|
Sigler K, Warren D, Tracy B, Forrestel E, Hogue G, Dornburg A. Assessing temporal biases across aggregated historical spatial data: a case study of North Carolina’s freshwater fishes. Ecosphere 2021. [DOI: 10.1002/ecs2.3878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Affiliation(s)
- Kyra Sigler
- North Carolina Museum of Natural Sciences Raleigh North Carolina 27601 USA
- Department of Biological and Agricultural Engineering North Carolina State University Raleigh North Carolina 27695 USA
| | - Dan Warren
- Biodiversity and Biocomplexity Unit Okinawa Institute of Science and Technology Okinawa Japan
| | - Bryn Tracy
- North Carolina Museum of Natural Sciences Raleigh North Carolina 27601 USA
| | - Elisabeth Forrestel
- Department of Viticulture and Enology University of California Davis California 95616 USA
| | - Gabriela Hogue
- North Carolina Museum of Natural Sciences Raleigh North Carolina 27601 USA
| | - Alex Dornburg
- Department of Bioinformatics and Genomics University of North Carolina Charlotte Charlotte North Carolina 28223 USA
| |
Collapse
|
3
|
Mandeville CP, Koch W, Nilsen EB, Finstad AG. Open Data Practices among Users of Primary Biodiversity Data. Bioscience 2021; 71:1128-1147. [PMID: 34733117 PMCID: PMC8560312 DOI: 10.1093/biosci/biab072] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Presence-only biodiversity data are increasingly relied on in biodiversity, ecology, and conservation research, driven by growing digital infrastructures that support open data sharing and reuse. Recent reviews of open biodiversity data have clearly documented the value of data sharing, but the extent to which the biodiversity research community has adopted open data practices remains unclear. We address this question by reviewing applications of presence-only primary biodiversity data, drawn from a variety of sources beyond open databases, in the indexed literature. We characterize how frequently researchers access open data relative to data from other sources, how often they share newly generated or collated data, and trends in metadata documentation and data citation. Our results indicate that biodiversity research commonly relies on presence-only data that are not openly available and neglects to make such data available. Improved data sharing and documentation will increase the value, reusability, and reproducibility of biodiversity research.
Collapse
Affiliation(s)
- Caitlin P Mandeville
- Department of Natural History, Norwegian University of Science and Technology, Trondheim, Norway
| | - Wouter Koch
- Department of Natural History, Norwegian University of Science and Technology, Trondheim, Norway
| | - Erlend B Nilsen
- Faculty of Biosciences and Aquaculture, Nord University, Steinkjer, Norway
| | - Anders G Finstad
- Department of Natural History, Norwegian University of Science and Technology, Trondheim, Norway
| |
Collapse
|
4
|
Vihotogbé R, Idohou R, Vianou A, Spies P, Salako V, Assogbadjo A, Glèlè Kakaï R. Abundance and effects of climate change on geographical distribution of
Mondia whitei
(Hook.f.) Skeels (Apocynaceae) in the Dahomey Gap (West Africa). Afr J Ecol 2021. [DOI: 10.1111/aje.12914] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Affiliation(s)
- Romaric Vihotogbé
- Ecole de Foresterie Tropicale Université Nationale d’Agriculture Kétou Benin
- Laboratory of Applied Ecology Faculty of Agronomic Sciences University of Abomey–Calavi Cotonou Benin
- Laboratoire de Biomathématiques et d’Estimations Forestières Faculty of Agronomic Sciences University of Abomey–Calavi Cotonou Benin
| | - Rodrigue Idohou
- Laboratoire de Biomathématiques et d’Estimations Forestières Faculty of Agronomic Sciences University of Abomey–Calavi Cotonou Benin
- Ecole de Gestion et de Production Végétale et Semencière Université Nationale d’Agriculture Kétou Benin
| | - Aldrich Vianou
- Laboratory of Applied Ecology Faculty of Agronomic Sciences University of Abomey–Calavi Cotonou Benin
- Laboratoire de Biomathématiques et d’Estimations Forestières Faculty of Agronomic Sciences University of Abomey–Calavi Cotonou Benin
| | - Paula Spies
- Department of Genetics University of Free State Bloemfontein South Africa
| | - Valère Salako
- Laboratoire de Biomathématiques et d’Estimations Forestières Faculty of Agronomic Sciences University of Abomey–Calavi Cotonou Benin
| | - Achille Assogbadjo
- Laboratory of Applied Ecology Faculty of Agronomic Sciences University of Abomey–Calavi Cotonou Benin
| | - Romain Glèlè Kakaï
- Laboratoire de Biomathématiques et d’Estimations Forestières Faculty of Agronomic Sciences University of Abomey–Calavi Cotonou Benin
| |
Collapse
|
5
|
Suárez-Tangil BD, Rodríguez A. Estimates of Species Richness and Composition Depend on Detection Method in Assemblages of Terrestrial Mammals. Animals (Basel) 2021; 11:ani11010186. [PMID: 33466807 PMCID: PMC7830977 DOI: 10.3390/ani11010186] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 01/04/2021] [Accepted: 01/11/2021] [Indexed: 11/16/2022] Open
Abstract
Detecting rapid changes in mammal composition at large spatial scales requires efficient detection methods. Many studies estimate species composition with a single survey method without asking whether that particular method optimises detection for all occurring species and yields reliable community-level indices. We explore the implications of between-method differences in efficiency, consistency, and sampling effort for the basic characterisation of assemblages of medium to large mammals in a region with three contrasted Mediterranean landscapes. We assessed differences between camera traps, scent stations, scat surveys, and track surveys. Using track surveys, we detected all species present in the regional pool (13) and obtained the most accurate description of local species richness and composition with the lowest sampling effort (16 sampling units and 2 survey sessions at most). Had we chosen camera traps, scent stations, or scat surveys as the only survey method, we would have underestimated species richness (9, 11, and 12 species, respectively) and misrepresented species composition in varying degrees. Preliminary studies of method performance inform whether single or multiple survey methods are needed and eventually which single method might be most appropriate. Without such a formal assessment current practices may produce unreliable and incomplete species inventories, ultimately leading to incorrect conclusions about the impact of human activity on mammal communities.
Collapse
|
6
|
Ball-Damerow JE, Brenskelle L, Barve N, Soltis PS, Sierwald P, Bieler R, LaFrance R, Ariño AH, Guralnick RP. Research applications of primary biodiversity databases in the digital age. PLoS One 2019; 14:e0215794. [PMID: 31509534 PMCID: PMC6738577 DOI: 10.1371/journal.pone.0215794] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Accepted: 07/13/2019] [Indexed: 01/21/2023] Open
Abstract
Our world is in the midst of unprecedented change-climate shifts and sustained, widespread habitat degradation have led to dramatic declines in biodiversity rivaling historical extinction events. At the same time, new approaches to publishing and integrating previously disconnected data resources promise to help provide the evidence needed for more efficient and effective conservation and management. Stakeholders have invested considerable resources to contribute to online databases of species occurrences. However, estimates suggest that only 10% of biocollections are available in digital form. The biocollections community must therefore continue to promote digitization efforts, which in part requires demonstrating compelling applications of the data. Our overarching goal is therefore to determine trends in use of mobilized species occurrence data since 2010, as online systems have grown and now provide over one billion records. To do this, we characterized 501 papers that use openly accessible biodiversity databases. Our standardized tagging protocol was based on key topics of interest, including: database(s) used, taxa addressed, general uses of data, other data types linked to species occurrence data, and data quality issues addressed. We found that the most common uses of online biodiversity databases have been to estimate species distribution and richness, to outline data compilation and publication, and to assist in developing species checklists or describing new species. Only 69% of papers in our dataset addressed one or more aspects of data quality, which is low considering common errors and biases known to exist in opportunistic datasets. Globally, we find that biodiversity databases are still in the initial stages of data compilation. Novel and integrative applications are restricted to certain taxonomic groups and regions with higher numbers of quality records. Continued data digitization, publication, enhancement, and quality control efforts are necessary to make biodiversity science more efficient and relevant in our fast-changing environment.
Collapse
Affiliation(s)
| | - Laura Brenskelle
- Florida Museum of Natural History, University of Florida, Gainesville, FL, United States of America
| | - Narayani Barve
- Florida Museum of Natural History, University of Florida, Gainesville, FL, United States of America
| | - Pamela S. Soltis
- Florida Museum of Natural History, University of Florida, Gainesville, FL, United States of America
| | - Petra Sierwald
- Field Museum of Natural History, Chicago, IL, United States of America
| | - Rüdiger Bieler
- Field Museum of Natural History, Chicago, IL, United States of America
| | - Raphael LaFrance
- Florida Museum of Natural History, University of Florida, Gainesville, FL, United States of America
| | - Arturo H. Ariño
- Department of Environmental Biology, Universidad de Navarra, Pamplona, Spain
| | - Robert P. Guralnick
- Florida Museum of Natural History, University of Florida, Gainesville, FL, United States of America
| |
Collapse
|
7
|
Mancini MC, Roth PRO, Brennand PG, Ruiz-Esparza Aguilar JM, Rocha PA. Tyto furcata (Tytonidae: Strigiformes) pellets: tools to access the richness of small mammals of a poorly known Caatinga area in northeast Brazil. MAMMALIA 2019. [DOI: 10.1515/mammalia-2018-0017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
Owls are efficient predators and are widely distributed around the globe. Remains of undigested prey is regurgitated by these birds in the form of pellets, and these are a valuable source of information about prey communities and the diet of owls. In this study, the composition of mammals present in the diet of owls that inhabit different caves was evaluated through the analysis of their pellets. We found 373 pellets from seven caves, and small mammals composed at least 80% of the diet of these birds in all caves. The mammal composition found in the pellets showed a richness of 26 distinct taxa including 12 rodents, three marsupials and 11 bats. In this work, we highlight the richness of small mammals in a poorly known Caatinga area. We also highlight the importance of morphology and taxonomy in supporting this kind of research, which relies upon vertebrate parts as its source of information for identification. Finally, we reiterate the efficiency of the study of owl pellets as a rapid approach for assessing local mammal richness and as a complementary method in studies of diversity and conservation.
Collapse
|
8
|
Escribano N, Galicia D, Ariño AH. Completeness of Digital Accessible Knowledge (DAK) about terrestrial mammals in the Iberian Peninsula. PLoS One 2019; 14:e0213542. [PMID: 30849112 PMCID: PMC6407841 DOI: 10.1371/journal.pone.0213542] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 02/22/2019] [Indexed: 11/22/2022] Open
Abstract
The advent of online data aggregator infrastructures has facilitated the accumulation of Digital Accessible Knowledge (DAK) about biodiversity. Despite the vast amount of freely available data records, their usefulness for research depends on completeness of each body of data regarding their spatial, temporal and taxonomic coverage. In this paper, we assess the completeness of DAK about terrestrial mammals distributed across the Iberian Peninsula. We compiled a dataset with all records about mammals occurring in the Iberian Peninsula available in the Global Biodiversity Information Facility and in the national atlases from Portugal and Spain. After cleaning the dataset of errors as well as records lacking collection dates or not determined to species level, we assigned all occurrences to a 10-km grid. We assessed inventory completeness by calculating the ratio between observed and expected richness (based on the Chao2 richness index) in each grid cell and classified cells as well-sampled or under-sampled. We evaluated survey coverage of well-sampled cells along four environmental gradients and temporal coverage. Out of 796,283 retrieved records, quality issues led us to remove 616,141 records unfit for this use. The main reason for discarding records was missing collection dates. Only 25.95% cells contained enough records to robustly estimate completeness. The DAK about terrestrial mammals from the Iberian Peninsula was low, and spatially and temporally biased. Out of 5,874 cells holding data, only 620 (9.95%) were classified as well-sampled. Moreover, well-sampled cells were geographically aggregated and reached inventory completeness over the same temporal range. Despite the increasing availability of DAK, its usefulness is still compromised by quality issues and gaps in data. Future work should therefore focus on increasing data quality, in addition to mobilizing unpublished data.
Collapse
Affiliation(s)
- Nora Escribano
- Universidad de Navarra, Department of Environmental Biology, Pamplona, Spain
- * E-mail:
| | - David Galicia
- Universidad de Navarra, Department of Environmental Biology, Pamplona, Spain
| | - Arturo Hugo Ariño
- Universidad de Navarra, Department of Environmental Biology, Pamplona, Spain
| |
Collapse
|
9
|
Peterson AT, Asase A, Canhos DAL, de Souza S, Wieczorek J. Data Leakage and Loss in Biodiversity Informatics. Biodivers Data J 2018:e26826. [PMID: 30473617 PMCID: PMC6235996 DOI: 10.3897/bdj.6.e26826] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Accepted: 10/17/2018] [Indexed: 11/12/2022] Open
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.
Collapse
Affiliation(s)
- A Townsend Peterson
- Biodiversity Institute, University of Kansas, Lawrence, United States of America Biodiversity Institute, University of Kansas Lawrence United States of America
| | - Alex Asase
- University of Ghana, Accra, Ghana University of Ghana Accra Ghana
| | | | | | - John Wieczorek
- Museum of Vertebrate Zoology, University of California, Berkeley, United States of America Museum of Vertebrate Zoology, University of California Berkeley United States of America
| |
Collapse
|
10
|
Hengl T, Walsh MG, Sanderman J, Wheeler I, Harrison SP, Prentice IC. Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potential. PeerJ 2018; 6:e5457. [PMID: 30155360 PMCID: PMC6109375 DOI: 10.7717/peerj.5457] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2018] [Accepted: 07/27/2018] [Indexed: 11/20/2022] Open
Abstract
Potential natural vegetation (PNV) is the vegetation cover in equilibrium with climate, that would exist at a given location if not impacted by human activities. PNV is useful for raising public awareness about land degradation and for estimating land potential. This paper presents results of assessing machine learning algorithms-neural networks (nnet package), random forest (ranger), gradient boosting (gbm), K-nearest neighborhood (class) and Cubist-for operational mapping of PNV. Three case studies were considered: (1) global distribution of biomes based on the BIOME 6000 data set (8,057 modern pollen-based site reconstructions), (2) distribution of forest tree taxa in Europe based on detailed occurrence records (1,546,435 ground observations), and (3) global monthly fraction of absorbed photosynthetically active radiation (FAPAR) values (30,301 randomly-sampled points). A stack of 160 global maps representing biophysical conditions over land, including atmospheric, climatic, relief, and lithologic variables, were used as explanatory variables. The overall results indicate that random forest gives the overall best performance. The highest accuracy for predicting BIOME 6000 classes (20) was estimated to be between 33% (with spatial cross-validation) and 68% (simple random sub-setting), with the most important predictors being total annual precipitation, monthly temperatures, and bioclimatic layers. Predicting forest tree species (73) resulted in mapping accuracy of 25%, with the most important predictors being monthly cloud fraction, mean annual and monthly temperatures, and elevation. Regression models for FAPAR (monthly images) gave an R-square of 90% with the most important predictors being total annual precipitation, monthly cloud fraction, CHELSA bioclimatic layers, and month of the year, respectively. Further developments of PNV mapping could include using all GBIF records to map the global distribution of plant species at different taxonomic levels. This methodology could also be extended to dynamic modeling of PNV, so that future climate scenarios can be incorporated. Global maps of biomes, FAPAR and tree species at one km spatial resolution are available for download via http://dx.doi.org/10.7910/DVN/QQHCIK.
Collapse
Affiliation(s)
| | - Markus G Walsh
- The Earth Institute, Columbia University, New York, NY, USA.,Selian Agricultural Research Institute, Arusha, Tanzania
| | | | | | - Sandy P Harrison
- School of Archeology, Geography and Environmental Science, University of Reading, Reading, UK
| | - Iain C Prentice
- Department of Life Sciences and Grantham Institute-Climate Change and the Environment, Imperial College London, London, UK
| |
Collapse
|
11
|
Abstract
Studying and protecting each and every living species on Earth is a major challenge of the 21st century. Yet, most species remain unknown or unstudied, while others attract most of the public, scientific and government attention. Although known to be detrimental, this taxonomic bias continues to be pervasive in the scientific literature, but is still poorly studied and understood. Here, we used 626 million occurrences from the Global Biodiversity Information Facility (GBIF), the biggest biodiversity data portal, to characterize the taxonomic bias in biodiversity data. We also investigated how societal preferences and taxonomic research relate to biodiversity data gathering. For each species belonging to 24 taxonomic classes, we used the number of publications from Web of Science and the number of web pages from Bing searches to approximate research activity and societal preferences. Our results show that societal preferences, rather than research activity, strongly correlate with taxonomic bias, which lead us to assert that scientists should advertise less charismatic species and develop societal initiatives (e.g. citizen science) that specifically target neglected organisms. Ensuring that biodiversity is representatively sampled while this is still possible is an urgent prerequisite for achieving efficient conservation plans and a global understanding of our surrounding environment.
Collapse
|
12
|
Tessarolo G, Ladle R, Rangel T, Hortal J. Temporal degradation of data limits biodiversity research. Ecol Evol 2017; 7:6863-6870. [PMID: 28904766 PMCID: PMC5587493 DOI: 10.1002/ece3.3259] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2017] [Revised: 06/14/2017] [Accepted: 06/25/2017] [Indexed: 11/09/2022] Open
Abstract
Spatial and/or temporal biases in biodiversity data can directly influence the utility, comparability, and reliability of ecological and evolutionary studies. While the effects of biased spatial coverage of biodiversity data are relatively well known, temporal variation in data quality (i.e., the congruence between recorded and actual information) has received much less attention. Here, we develop a conceptual framework for understanding the influence of time on biodiversity data quality based on three main processes: (1) the natural dynamics of ecological systems—such as species turnover or local extinction; (2) periodic taxonomic revisions, and; (3) the loss of physical and metadata due to inefficient curation, accidents, or funding shortfalls. Temporal decay in data quality driven by these three processes has fundamental consequences for the usage and comparability of data collected in different time periods. Data decay can be partly ameliorated by adopting standard protocols for generation, storage, and sharing data and metadata. However, some data degradation is unavoidable due to natural variations in ecological systems. Consequently, changes in biodiversity data quality over time need be carefully assessed and, if possible, taken into account when analyzing aging datasets.
Collapse
Affiliation(s)
- Geiziane Tessarolo
- Departamento de Ecologia Instituto de Ciências Biológicas Universidade Federal de Goiás Goiânia Brazil.,Programa de Pós-graduação em Recursos Naturais do Cerrado Universidade Estadual de Goiás Anápolis Brazil
| | - Richard Ladle
- ICBS Universidade Federal de Alagoas Maceió Brazil.,School of Geography and the Environment University of Oxford Oxford UK
| | - Thiago Rangel
- Departamento de Ecologia Instituto de Ciências Biológicas Universidade Federal de Goiás Goiânia Brazil
| | - Joaquin Hortal
- Departamento de Ecologia Instituto de Ciências Biológicas Universidade Federal de Goiás Goiânia Brazil.,Departamento de Biogeografía y Cambio Global Museo Nacional de Ciencias Naturales (MNCN-CSIC) Madrid Spain
| |
Collapse
|