Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale
Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standa...
| Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2018
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/83289 |
| _version_ | 1855522844180480000 |
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| author | Kissling, W. Daniel Ahumada, Jorge A. Bowser, Anne Fernández, Miguel Fernández, Néstor García, Enrique Alonso Guralnick, Robert P. Isaac, Nick J. B. Kelling, Steve Los, Wouter McRae, Louise Mihoub, Jean-Baptiste Obst, Matthias Santamaria, Monica Skidmore, Andrew K. Williams, Kristen J. Agosti, Donat Amariles, Daniel Arvanitidis, Christos Bastin, Lucy Leo, Francesca de Egloff, Willi Elith, Jane Hobern, Donald Martin, David Pereira, Henrique M. Pesole, Graziano Peterseil, Johannes Saarenmaa, Hannu Schigel, Dmitry Schmeller, Dirk S. Segata, Nicola Turak, Eren Uhlir, Paul F. Wee, Brian Hardisty, Alex R. |
| author_browse | Agosti, Donat Ahumada, Jorge A. Amariles, Daniel Arvanitidis, Christos Bastin, Lucy Bowser, Anne Egloff, Willi Elith, Jane Fernández, Miguel Fernández, Néstor García, Enrique Alonso Guralnick, Robert P. Hardisty, Alex R. Hobern, Donald Isaac, Nick J. B. Kelling, Steve Kissling, W. Daniel Leo, Francesca de Los, Wouter Martin, David McRae, Louise Mihoub, Jean-Baptiste Obst, Matthias Pereira, Henrique M. Pesole, Graziano Peterseil, Johannes Saarenmaa, Hannu Santamaria, Monica Schigel, Dmitry Schmeller, Dirk S. Segata, Nicola Skidmore, Andrew K. Turak, Eren Uhlir, Paul F. Wee, Brian Williams, Kristen J. |
| author_facet | Kissling, W. Daniel Ahumada, Jorge A. Bowser, Anne Fernández, Miguel Fernández, Néstor García, Enrique Alonso Guralnick, Robert P. Isaac, Nick J. B. Kelling, Steve Los, Wouter McRae, Louise Mihoub, Jean-Baptiste Obst, Matthias Santamaria, Monica Skidmore, Andrew K. Williams, Kristen J. Agosti, Donat Amariles, Daniel Arvanitidis, Christos Bastin, Lucy Leo, Francesca de Egloff, Willi Elith, Jane Hobern, Donald Martin, David Pereira, Henrique M. Pesole, Graziano Peterseil, Johannes Saarenmaa, Hannu Schigel, Dmitry Schmeller, Dirk S. Segata, Nicola Turak, Eren Uhlir, Paul F. Wee, Brian Hardisty, Alex R. |
| author_sort | Kissling, W. Daniel |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a ‘Big Data’ approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence-only or presence–absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi-source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter- or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi-source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA-based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals. |
| format | Journal Article |
| id | CGSpace83289 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace832892025-03-13T09:44:10Z Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale Kissling, W. Daniel Ahumada, Jorge A. Bowser, Anne Fernández, Miguel Fernández, Néstor García, Enrique Alonso Guralnick, Robert P. Isaac, Nick J. B. Kelling, Steve Los, Wouter McRae, Louise Mihoub, Jean-Baptiste Obst, Matthias Santamaria, Monica Skidmore, Andrew K. Williams, Kristen J. Agosti, Donat Amariles, Daniel Arvanitidis, Christos Bastin, Lucy Leo, Francesca de Egloff, Willi Elith, Jane Hobern, Donald Martin, David Pereira, Henrique M. Pesole, Graziano Peterseil, Johannes Saarenmaa, Hannu Schigel, Dmitry Schmeller, Dirk S. Segata, Nicola Turak, Eren Uhlir, Paul F. Wee, Brian Hardisty, Alex R. biodiversity big data data open data data sets interoperability sustainable development biodiversidad interoperabilidad Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a ‘Big Data’ approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence-only or presence–absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi-source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter- or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi-source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA-based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals. 2018-02 2017-08-29T15:51:30Z 2017-08-29T15:51:30Z Journal Article https://hdl.handle.net/10568/83289 en Open Access Wiley Kissling, W. Daniel; Ahumada, Jorge A.; Bowser, Anne; Fernandez, Miguel; Fernández, Néstor; García, Enrique Alonso; Guralnick, Robert P.; Isaac, Nick J. B.; Kelling, Steve; Los, Wouter; McRae, Louise; Mihoub, Jean-Baptiste; Obst, Matthias; Santamaria, Monica; Skidmore, Andrew K.; Williams, Kristen J.; Agosti, Donat; Amariles, Daniel; Arvanitidis, Christos; Bastin, Lucy; De Leo, Francesca; Egloff, Willi; Elith, Jane; Hobern, Donald; Martin, David; Pereira, Henrique M.; Pesole, Graziano; Peterseil, Johannes; Saarenmaa, Hannu; Schigel, Dmitry; Schmeller, Dirk S.; Segata, Nicola; Turak, Eren; Uhlir, Paul F.; Wee, Brian; Hardisty, Alex R.. 2017. Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale . Biological Reviews. 93(1): 600-625 |
| spellingShingle | biodiversity big data data open data data sets interoperability sustainable development biodiversidad interoperabilidad Kissling, W. Daniel Ahumada, Jorge A. Bowser, Anne Fernández, Miguel Fernández, Néstor García, Enrique Alonso Guralnick, Robert P. Isaac, Nick J. B. Kelling, Steve Los, Wouter McRae, Louise Mihoub, Jean-Baptiste Obst, Matthias Santamaria, Monica Skidmore, Andrew K. Williams, Kristen J. Agosti, Donat Amariles, Daniel Arvanitidis, Christos Bastin, Lucy Leo, Francesca de Egloff, Willi Elith, Jane Hobern, Donald Martin, David Pereira, Henrique M. Pesole, Graziano Peterseil, Johannes Saarenmaa, Hannu Schigel, Dmitry Schmeller, Dirk S. Segata, Nicola Turak, Eren Uhlir, Paul F. Wee, Brian Hardisty, Alex R. Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale |
| title | Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale |
| title_full | Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale |
| title_fullStr | Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale |
| title_full_unstemmed | Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale |
| title_short | Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale |
| title_sort | building essential biodiversity variables ebvs of species distribution and abundance at a global scale |
| topic | biodiversity big data data open data data sets interoperability sustainable development biodiversidad interoperabilidad |
| url | https://hdl.handle.net/10568/83289 |
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