Research applications of primary biodiversity databases in the digital age.

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

Research applications of primary biodiversity databases in the digital age

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

California dragonfly and damselfly (Odonata) database: temporal and spatial distribution of species records collected over the past century

The recently completed Odonata database for California consists of specimen records from the major entomology collections of the state, large Odonata collections outside of the state, previous literature, historical and recent field surveys, and from enthusiast group observations. The database includes 32,025 total records and 19,000 unique records for 106 species of dragonflies and damselflies, with records spanning 1879–2013. Records have been geographically referenced using the point-radius method to assign coordinates and an uncertainty radius to specimen locations. In addition to describing techniques used in data acquisition, georeferencing, and quality control, we present assessments of the temporal, spatial, and taxonomic distribution of records. We use this information to identify biases in the data, and to determine changes in species prevalence, latitudinal ranges, and elevation ranges when comparing records before 1976 and after 1979. The average latitude of where records occurred increased by 78 km over these time periods. While average elevation did not change significantly, the average minimum elevation across species declined by 108 m. Odonata distribution may be generally shifting northwards as temperature warms and to lower minimum elevations in response to increased summer water availability in low-elevation agricultural regions. The unexpected decline in elevation may also be partially the result of bias in recent collections towards centers of human population, which tend to occur at lower elevations. This study emphasizes the need to address temporal, spatial, and taxonomic biases in museum and observational records in order to produce reliable conclusions from such data

California dragonfly and damselfly (Odonata) database: temporal and spatial distribution of species records collected over the past century.

The recently completed Odonata database for California consists of specimen records from the major entomology collections of the state, large Odonata collections outside of the state, previous literature, historical and recent field surveys, and from enthusiast group observations. The database includes 32,025 total records and 19,000 unique records for 106 species of dragonflies and damselflies, with records spanning 1879-2013. Records have been geographically referenced using the point-radius method to assign coordinates and an uncertainty radius to specimen locations. In addition to describing techniques used in data acquisition, georeferencing, and quality control, we present assessments of the temporal, spatial, and taxonomic distribution of records. We use this information to identify biases in the data, and to determine changes in species prevalence, latitudinal ranges, and elevation ranges when comparing records before 1976 and after 1979. The average latitude of where records occurred increased by 78 km over these time periods. While average elevation did not change significantly, the average minimum elevation across species declined by 108 m. Odonata distribution may be generally shifting northwards as temperature warms and to lower minimum elevations in response to increased summer water availability in low-elevation agricultural regions. The unexpected decline in elevation may also be partially the result of bias in recent collections towards centers of human population, which tend to occur at lower elevations. This study emphasizes the need to address temporal, spatial, and taxonomic biases in museum and observational records in order to produce reliable conclusions from such data

Use of Online Species Occurrence Databases in Published Research since 2010

Museums and funding agencies have invested considerable resources in recent years to digitize information from natural history specimens and contribute to online species occurrence databases. Such efforts are necessary to reap the full benefits of irreplaceable historical data by making them openly accessible and allowing the integration of collections data with other datasets. However, recent estimates suggest that still only 10% of biocollections are available in digital form. The biocollections community must therefore continue to justify and promote digitization efforts, particularly for high-diversity groups with large numbers of specimens, such as invertebrates.  Our overarching goal is to determine how uses of biodiversity databases have developed in recent years, as more data has come online. To this end, we present a bibliometric analysis of published research to characterize uses of online species occurrence databases since 2010. Relevant papers for this analysis include those that use online and openly accessible primary occurrence records, or those that add data to an online database. Google Scholar (GS) provides full-text indexing, which was important to identify data sources that often appear buried in the methods section of a paper. Our search was therefore restricted to GS. We drew a list of relevant search terms and downloaded all records returned by each search (or the first 500 if there were more) into a Zotero reference management database. About one third of the 2500 papers in the final dataset were relevant. Three of the authors with specialized knowledge of the field characterized relevant papers using a standardized tagging protocol based on a series of key topics of interest. We developed a list of potential tags and descriptions for each topic, including: database(s) used, database accessibility, scale of study, region of study, taxa addressed, general use of data, other data types linked to species occurrence data, data quality issues addressed, authors, institutions, and funding sources. Each tagged paper was thoroughly checked by a second tagger. The final dataset of tagged papers allow us to quantify general areas of research made possible by the expansion of online species occurrence databases, and trends over time. For example, preliminary results on a subset of the papers indicate that the most common uses of online species occurrence databases have been: (a) to determine trends in species richness or distribution; (b) to describe a new database; and (c) to assist in developing species checklists or taxonomic studies. Studies addressing plants have generally been more prevalent than those concerning both vertebrates and invertebrates. However, while the number of plant and vertebrate studies have remained relatively constant in recent years, invertebrate studies are increasing.  We also address the importance of both proper citation of databases and use of approaches to improve data quality issues involving errors and biases. The most common aspects of data quality addressed were to check for currently valid names, spatial errors, and to exclude certain unsuitable records. Finally, we identify more integrative studies that incorporate multiple data types, and determine whether these uses are enabled by collaborations. Overall, our presentation demonstrates initial trend results for over 100 specific tags associated with 13 topics of interest, and network analyses of authors and institutions for relevant papers. We also outline the downstream utility of our dense tagging approach for understanding domain-wide trends, and the potential for developing machine-learning approaches to more efficiently characterize certain aspects of published research

Use of Online Species Occurrence Databases in Published Research since 2010

Museums and funding agencies have invested considerable resources in recent years to digitize information from natural history specimens and contribute to online species occurrence databases. Such efforts are necessary to reap the full benefits of irreplaceable historical data by making them openly accessible and allowing the integration of collections data with other datasets. However, recent estimates suggest that still only 10% of biocollections are available in digital form. The biocollections community must therefore continue to justify and promote digitization efforts, particularly for high-diversity groups with large numbers of specimens, such as invertebrates.  Our overarching goal is to determine how uses of biodiversity databases have developed in recent years, as more data has come online. To this end, we present a bibliometric analysis of published research to characterize uses of online species occurrence databases since 2010. Relevant papers for this analysis include those that use online and openly accessible primary occurrence records, or those that add data to an online database. Google Scholar (GS) provides full-text indexing, which was important to identify data sources that often appear buried in the methods section of a paper. Our search was therefore restricted to GS. We drew a list of relevant search terms and downloaded all records returned by each search (or the first 500 if there were more) into a Zotero reference management database. About one third of the 2500 papers in the final dataset were relevant. Three of the authors with specialized knowledge of the field characterized relevant papers using a standardized tagging protocol based on a series of key topics of interest. We developed a list of potential tags and descriptions for each topic, including: database(s) used, database accessibility, scale of study, region of study, taxa addressed, general use of data, other data types linked to species occurrence data, data quality issues addressed, authors, institutions, and funding sources. Each tagged paper was thoroughly checked by a second tagger. The final dataset of tagged papers allow us to quantify general areas of research made possible by the expansion of online species occurrence databases, and trends over time. For example, preliminary results on a subset of the papers indicate that the most common uses of online species occurrence databases have been: (a) to determine trends in species richness or distribution; (b) to describe a new database; and (c) to assist in developing species checklists or taxonomic studies. Studies addressing plants have generally been more prevalent than those concerning both vertebrates and invertebrates. However, while the number of plant and vertebrate studies have remained relatively constant in recent years, invertebrate studies are increasing.  We also address the importance of both proper citation of databases and use of approaches to improve data quality issues involving errors and biases. The most common aspects of data quality addressed were to check for currently valid names, spatial errors, and to exclude certain unsuitable records. Finally, we identify more integrative studies that incorporate multiple data types, and determine whether these uses are enabled by collaborations. Overall, our presentation demonstrates initial trend results for over 100 specific tags associated with 13 topics of interest, and network analyses of authors and institutions for relevant papers. We also outline the downstream utility of our dense tagging approach for understanding domain-wide trends, and the potential for developing machine-learning approaches to more efficiently characterize certain aspects of published research

Research applications of primary biodiversity databases in the digital age.

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