497
Scenarios and Models of the Intergovernmental Platform on Biodiversity and
Ecosystem Services (Kim et al. 2018). Species distribution, community composition,
ecosystem function variables, and ecosystem services variables were reconstructed
since 1900 and projected to 2050 globally, at a 0.5° resolution, using harmonized
land-use data sets developed for the shared-socioeconomic pathways and climate
data sets for the relative concentration pathway scenarios. In this exercise, a spacefor-time substitution was used in the biodiversity models. In other words, no explicit
time series biodiversity data were used to calibrate the models. Instead, current
spatial patterns of biodiversity and drivers were used to infer how biodiversity
changes over time when driver variables change. A future challenge for biodiversity
modelers is to use biodiversity time series to fully model biodiversity across space
and time (Ferrier et al. 2017).
18.5 Concluding Remarks
Since EBVs were first defined, there have been significant advances in the consolidation of the framework, substantial conceptual work on implementation, and increasing enthusiasm about their many potential applications in biodiversity science and
policy. Now the scientific community needs to face the challenge of delivering EBV
products and workflows that provide estimates of changes for the main facets of
biodiversity and support our understanding of the driving mechanisms and the consequences of such changes. There are important opportunities for mobilizing primary data offered by the open-access movement, which continue to permeate the
biodiversity community. These include public institutions responsible for promoting
scientific and technological advancement. Data gaps will be covered by combining
technological development with appropriate biodiversity models. For example,
spaceborne sensors such as the Global Ecosystem Dynamics Investigation (GEDI)
Lidar launched in 2018 are providing unprecedented global coverage in vertical
measurements of vegetation and topography and will most likely support modelbased integration of information for biodiversity variables in unforeseen ways.
Fulfilling the EBV vision requires renewed efforts, first, in continued scientific
and technological support for the mobilization of in-situ data and for designing
more comprehensive and better coordinated monitoring schemes and, second, in the
implementation of workflows and interoperable infrastructures that support wall-towall integration of biodiversity data. GEO BON as a network defined at multiple
levels, from scientific to institutional and infrastructure support, is instrumental for
this endeavor (Hugo et al. 2017; Navarro et al. 2017). Key priorities are the implementation of mechanisms that enhance data mobilization as exemplified by the
Darwin Event Core; a common understanding between the biodiversity research
community and the space agencies of the processes to develop the technology
required for detecting biodiversity change (Paganini et al. 2016); global informatics
infrastructure support that meets the requirements for operationalizing EBVs
(Hardisty et al. 2019); and broad scientific cooperation in implementing and enhancing biodiversity models that integrate all types of Earth observations.
18 Essential Biodiversity Variables: Integrating In-Situ Observations and Remote…
Scenarios and Models of the Intergovernmental Platform on Biodiversity and
Ecosystem Services (Kim et al. 2018). Species distribution, community composition,
ecosystem function variables, and ecosystem services variables were reconstructed
since 1900 and projected to 2050 globally, at a 0.5° resolution, using harmonized
land-use data sets developed for the shared-socioeconomic pathways and climate
data sets for the relative concentration pathway scenarios. In this exercise, a spacefor-time substitution was used in the biodiversity models. In other words, no explicit
time series biodiversity data were used to calibrate the models. Instead, current
spatial patterns of biodiversity and drivers were used to infer how biodiversity
changes over time when driver variables change. A future challenge for biodiversity
modelers is to use biodiversity time series to fully model biodiversity across space
and time (Ferrier et al. 2017).
18.5 Concluding Remarks
Since EBVs were first defined, there have been significant advances in the consolidation of the framework, substantial conceptual work on implementation, and increasing enthusiasm about their many potential applications in biodiversity science and
policy. Now the scientific community needs to face the challenge of delivering EBV
products and workflows that provide estimates of changes for the main facets of
biodiversity and support our understanding of the driving mechanisms and the consequences of such changes. There are important opportunities for mobilizing primary data offered by the open-access movement, which continue to permeate the
biodiversity community. These include public institutions responsible for promoting
scientific and technological advancement. Data gaps will be covered by combining
technological development with appropriate biodiversity models. For example,
spaceborne sensors such as the Global Ecosystem Dynamics Investigation (GEDI)
Lidar launched in 2018 are providing unprecedented global coverage in vertical
measurements of vegetation and topography and will most likely support modelbased integration of information for biodiversity variables in unforeseen ways.
Fulfilling the EBV vision requires renewed efforts, first, in continued scientific
and technological support for the mobilization of in-situ data and for designing
more comprehensive and better coordinated monitoring schemes and, second, in the
implementation of workflows and interoperable infrastructures that support wall-towall integration of biodiversity data. GEO BON as a network defined at multiple
levels, from scientific to institutional and infrastructure support, is instrumental for
this endeavor (Hugo et al. 2017; Navarro et al. 2017). Key priorities are the implementation of mechanisms that enhance data mobilization as exemplified by the
Darwin Event Core; a common understanding between the biodiversity research
community and the space agencies of the processes to develop the technology
required for detecting biodiversity change (Paganini et al. 2016); global informatics
infrastructure support that meets the requirements for operationalizing EBVs
(Hardisty et al. 2019); and broad scientific cooperation in implementing and enhancing biodiversity models that integrate all types of Earth observations.
18 Essential Biodiversity Variables: Integrating In-Situ Observations and Remote…