The Ecosystem Structure EBV class encompasses the condition of the structural components of ecosystems that lead to, and maintain, biodiversity characteristics. The Ecosystem Structure WG focuses on the monitoring of the relevant EBVs, and how they are changing in time.

About Ecosystem Structure WG
Co-Leads
Gary Geller
NASA

Ilaria Palumbo
Joint Research Centre
Key objectives
  1. Identify and agree on a set of EBVs that characterize the structure of ecosystems, its relationship to biodiversity, and that facilitate monitoring change. Develop an explicit definition for each EBV, including any sub-variables.
  2. Identify the in situ and remotely sensed observations needed to generate these EBVs, and facilitate the acquisition of and access to these observations.
  3. Facilitate mechanisms to generate the identified EBVs and sub-variables and make them accessible.
  4. Work with the various BONs to provide guidance on the observation systems and facilitate the acquisition of in situ data pertinent to ecosystem structure.
  5. Relate the Ecosystem Structure EBVs to policy relevant outputs, particularly indicators for the CBD targets and SDGs.
Activities
1. Remote sensing for EBVs
Leads Andrew Skidmore and Brian O’Connor
Development approach Monitoring, Data mobilization, Modelling
EBVs Habitat structure
Description The Remote Sensing for Essential Biodiversity Variables (RS4EBV) project is funded by the European Space Agency (ESA) under Innovators III and aims to establish a monitoring and modelling framework around the use of Sentinel-2 imagery for the retrieval of Essential Biodiversity Variables (EBVs). Direct
RS derives EBVs such as Leaf Area Index (LAI), leaf chlorophyll and vegetation phenology, as well as a higher-level indirect EBV, namely Functional Diversity (FD) (the range and relative abundance of traits within a plant community) will be retrieved.
Timeline 2017 2018 2019 2020
Milestones and/or Deliverables
  1. Final delivery (2nd Q)
  2. Scientific article (3rd Quarter)
Resources ESA funded RS-EBV Innovators project
Link with other WG, BONs, TF This activity will be supported by the Remote Sensing TF.
2. Global monthly vegetation cover (percentage of cover)
Leads Emiliana Valentini and Carlos Guerra
Development approach Monitoring, Data mobilization, Modelling, Application
EBVs Ecosystem Extent and fragmentation
Description We propose to create and validate a global layer of vegetation cover (as percentage of cover) based on MODIS images with monthly variation that can be used as a critical support for several indicators related to hydrologically based environmental modelling.
Timeline 2017 2018 2019 2020
Milestones and/or Deliverables
  • Jan-Jun 2017:
    Validation activities
  • Aug-Nov 2017: Testing
    and assimilation
  • Dec 2017: publication
    of the dataset.
Resources
Link with other activities The output of this activity will feed into the EBV Data TF
3. LandScen: Land Use and Land Cover change scenarios portal
Lead Isabel Rosa
Development Approach Data mobilization
EBVs Ecosystem Extent and fragmentation, Land cover
Description Existing scenarios of land use and land cover change (LULCC) are sparsely distributed amongst the literature with no central platform that facilitates the access to this information. In this activity, a database of existing scenarios of LULCC across the globe will be created. Several characteristics of
these scenarios will be recorded, such as: spatial and temporal resolutions, extent, location, model used, and contact information. Such database of metadata, and whenever possible the data itself, will be the basis of a web portal, to facilitate the access to existing LULCC by policy and decision makers, thus contributing to a more comprehensive view and a greater utility of these scenarios in supporting policy- and decision-makers.
Timeline 2017 2018 2019 2020
Milestones and/or Deliverables
  • 1st Q 2017: Initial setup
  • mid-/end- 2017: Midterm review
1st Q 2018: Final delivery
Resources Marie Sklodowska-Curie grant agreement No 703862 for the LCCMcons project
Link with other activities
4. SilviNat: an automated tool for monitoring natural forest and forest plantations’ dynamics
Leads Isabel M.D. Rosa and Joāo M.B. Carreiras
Development Approach Monitoring, Modelling
EBVs Ecosystem Extent and fragmentation, Land cover
Description Being able to monitor the dynamics of forest plantations (Silviculture), primary forests and natural regeneration (Natural forests) is essential to have a clear picture on the overall forest cover change, and how it impacts the provision of ecosystem services such as timber production and carbon
sequestration, among others. At the global scale, it is very challenging to distinguish natural forests from plantations (see Hansen et al. 2013), due to the great diversity of species used in silviculture which often mix their spectral signal with that of native forests. At the local to regional scales,
however, it is possible to develop tools that are able to i) individualize the spectral signature of the most important tree species used in plantations and ii) evaluate over time the dynamics of forest loss and gain within natural forests (primary and regeneration) and plantations. Such comprehensive
monitoring would allow decision-makers to assess not only the impact of changes in commodity prices (e.g. timber value), but also the success of implemented conservation actions (e.g. promote forest regeneration), and to tackle illegal deforestation activities, thus having a comprehensive picture on the dynamics of forest cover change. In this activity, a fully-automated tool will be developed to track forest dynamics in the Atlantic Forest of Brazil.
Timeline 2017 2018 2019 2020
Milestones and/or Deliverables 1st Q 2017: Initial setup mid-/end- 2017: Midterm review 1st Q 2018: Final delivery
Resources Marie Sklodowska-Curie grant agreement No 703862 for the LCCMcons project
Link with other activities The output of this activity will feed into the EBV Data TF
Data Products
Documents & Publications
Partners
Resources