Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale

W. Daniel Kissling (Corresponding Author), Jorge A. Ahumada, Anne Bowser, Miguel Fernandez, Néstor Fernández, Enrique Alonso García, Robert P. Guralnick, Nick J. B. Isaac, Steve Kelling, Wouter Los, Louise Mcrae, Jean-baptiste Mihoub, Matthias Obst, Monica Santamaria, A.K. Skidmore, Kristen J. Williams, Donat Agosti, Daniel Amariles, Christos Arvanitidis, Lucy Bastin & 16 others Francesca De Leo, Willi Egloff, Jane Elith, Donald Hobern, David Martin, Henrique M. Pereira, Graziano Pesole, Johannes Peterseil, Hannu Saarenmaa, Dmitry Schigel, Dirk S. Schmeller, Nicola Segata, Eren Turak, Paul F. Uhlir, Brian Wee, Alex R. Hardisty

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Abstract

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.

Original languageEnglish
Pages (from-to)600-625
Number of pages26
JournalBiological reviews
Volume93
Issue number1
Early online date2 Aug 2017
DOIs
Publication statusPublished - 16 Jan 2018

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Biodiversity
biogeography
biodiversity
Workflow
Information Storage and Retrieval
Metadata
Interoperability
Monitoring
monitoring
Sampling
infrastructure
Research
Zooplankton
Population
Planets
application coverage
Spatial Analysis
Units of measurement
Policy Making
Conservation of Natural Resources

Keywords

  • ITC-ISI-JOURNAL-ARTICLE
  • ITC-HYBRID
  • UT-Hybrid-D

Cite this

Kissling, W. D., Ahumada, J. A., Bowser, A., Fernandez, M., Fernández, N., García, E. A., ... Hardisty, A. R. (2018). Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale. Biological reviews, 93(1), 600-625. https://doi.org/10.1111/brv.12359
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, A.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. / Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale. In: Biological reviews. 2018 ; Vol. 93, No. 1. pp. 600-625.
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abstract = "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.",
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Kissling, WD, Ahumada, JA, Bowser, A, Fernandez, M, Fernández, N, García, EA, Guralnick, RP, Isaac, NJB, Kelling, S, Los, W, Mcrae, L, Mihoub, J, Obst, M, Santamaria, M, Skidmore, AK, Williams, KJ, Agosti, D, Amariles, D, Arvanitidis, C, Bastin, L, De Leo, F, Egloff, W, Elith, J, Hobern, D, Martin, D, Pereira, HM, Pesole, G, Peterseil, J, Saarenmaa, H, Schigel, D, Schmeller, DS, Segata, N, Turak, E, Uhlir, PF, Wee, B & Hardisty, AR 2018, 'Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale' Biological reviews, vol. 93, no. 1, pp. 600-625. https://doi.org/10.1111/brv.12359

Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale. / Kissling, W. Daniel (Corresponding Author); 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, A.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.

In: Biological reviews, Vol. 93, No. 1, 16.01.2018, p. 600-625.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale

AU - Kissling, W. Daniel

AU - Ahumada, Jorge A.

AU - Bowser, Anne

AU - Fernandez, Miguel

AU - Fernández, Néstor

AU - García, Enrique Alonso

AU - Guralnick, Robert P.

AU - Isaac, Nick J. B.

AU - Kelling, Steve

AU - Los, Wouter

AU - Mcrae, Louise

AU - Mihoub, Jean-baptiste

AU - Obst, Matthias

AU - Santamaria, Monica

AU - Skidmore, A.K.

AU - Williams, Kristen J.

AU - Agosti, Donat

AU - Amariles, Daniel

AU - Arvanitidis, Christos

AU - Bastin, Lucy

AU - De Leo, Francesca

AU - Egloff, Willi

AU - Elith, Jane

AU - Hobern, Donald

AU - Martin, David

AU - Pereira, Henrique M.

AU - Pesole, Graziano

AU - Peterseil, Johannes

AU - Saarenmaa, Hannu

AU - Schigel, Dmitry

AU - Schmeller, Dirk S.

AU - Segata, Nicola

AU - Turak, Eren

AU - Uhlir, Paul F.

AU - Wee, Brian

AU - Hardisty, Alex R.

PY - 2018/1/16

Y1 - 2018/1/16

N2 - 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.

AB - 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.

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Kissling WD, Ahumada JA, Bowser A, Fernandez M, Fernández N, García EA et al. Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale. Biological reviews. 2018 Jan 16;93(1):600-625. https://doi.org/10.1111/brv.12359