Metadata Catalogue
Vulnerability Workflow - Risk assessment of NIS introduction and establishment, habitat vulnerability to NIS and estimation of the impact on Biotopes
Background
Information about the incidence and impact of Non-indigenous and Invasive Species (NIS) are often scattered across different spatial, temporal and taxonomic scales and, therefore, it can be difficult to draw any comprehensive conclusion about the most vulnerable ecosystems or map the areas more at risk of biological invasion. Occurrence data are usually collected using a variety of sampling approaches and the impact of NIS can affect ecosystems at any biological scale (e.g., individuals, populations, communities, etc.) and with different degrees of severity. The heterogeneity of species occurrence data and the complexity of multiple effects acting at different biological scales and determining ecosystem-dependent changes make estimations of NIS incidence and impact difficult on large geographical scales.
Introduction
Comprehensive, standardised and modular methods to assess both incidence and impact of NIS at different spatial scale (e.g., continental, regional, local) are required to support management and conservation actions and to prioritise areas of intervention. To achieve this objective, researchers have developed two standardised approaches to quantify the incidence and the impact of NIS on ecosystems respectively by means of: occurrence cubes and analysis of the Cumulative IMPacts of invasive ALien species (CIMPAL). Occurrence cubes consist of species occurrence data aggregated on a three-dimensional space (cube) whereby the three dimensions considered are taxonomic, temporal and spatial. Data cubes allow the homogenisation and aggregation of heterogeneous data collected using different methods and standards. The CIMPAL model allows the mapping of cumulative negative impacts of NIS on different ecosystems (marine, freshwater, terrestrial) on the basis of existing evidence. NIS impacts can be additionally mapped according to the main associated pathways of introduction and the relative importance of species on cumulative impacts can be inferred. Using these two standardised methodologies, vulnerability map of biotopes can be produced in order to identify hot spots particularly threatened by NIS and that, in turn, would require special protection and maintenance.
Aims
This validation case aims at using the occurrence cube approach and the CIMPAL model to map ecosystem and habitat type vulnerability at continental scale, inferring the relevance of key risk factors (e.g. vectors of invasion) and intrinsic resistance/resilience components (e.g. native biodiversity, food web structure, etc…) and design scenarios of change, in the context of expected climate changes, for ecosystem and habitat types found highly vulnerable to NIS.
The workflow developed offers a valuable tool that may assist policy makers and managers in their efforts to develop strategies for mitigating the impacts of invasive species and improving the environmental status of marine waters. The method, although tested on the the marine environment, can easily be transferred to the terrestrial environment as well.
Default
- Date ( Creation)
- 2019-07-04
- Date ( Publication)
- 2021-03-18
- Status
- Under development / Pre operational
- Keywords
-
Biotope
- Keywords
-
IJI
- Access constraints
- License
- Use limitation
-
The final license will be available soon.
- OnLine resource
-
Info page
(
WWW:LINK-1.0-http--link
)
- OnLine resource
-
Workflow
(
WWW:LINK-1.0-http--link
)
- Service Name
-
Biotope GBIF extractor
- Service Description
-
The service aims at harvesting species occurrences from GBIF based on a keyword for the geographic region (two letter country code) and a time interval, both entered by the user.
It represents the Step 1a.
- Service Reference (id)
- Service Name
-
Occurrences Dataset Uploader
- Service Description
-
This service aims at enabling the dataset uploading from the user.
It represents the Step 1b.
- Service Reference (id)
- Service Name
-
Biotope GRISS Extractor
- Service Description
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The service aims at harvesting all the alien taxonomy files from GRIIS based on the country, a parameter set by the user. GRIIS downloads all available files (with an upper hard limit of 500) and zips them to be consumed by Step 3 (Occurrence Syntax Normalizer).
It represents Step 2a.
- Service Reference (id)
- Service Name
-
Alien Taxonomy Dataset Uploader
- Service Description
-
This service aims at enabling the dataset uploading from the user.
It represents the Step 2b.
- Service Reference (id)
- Service Name
-
Occurrences Syntax Normalizer
- Service Description
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This service aims at normalizing the user datasets to be consistent with the accepted formats.
It represents the Step 3.
- Service Reference (id)
- Service Name
-
Occurrences DataCube Builder
- Service Description
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This service aims at building two datacubes based on the occurrences. The datacube aggregates (=counts) occurrences on a regular grid. This count has a stochastic component that takes the uncertainty field into account. All this process has been developed in R in the frame of the TrIAS project.
It represents the Step 4.
- Service Reference (id)
- Service Name
-
Occurrences DataCube Analyst
- Service Description
-
This service aims at crossing the datacube with a geographic layer in order to compute incidence information per zone. This information is extracted based on the geolocation code. It includes a tool to visualize the outputs rasters.
It represents the Step 5.
- Service Reference (id)
- Service Name
-
CIMPAL Calculator (Cumulative IMPacts of invasive ALien species calculator)
- Service Description
-
This service aims at calculating a spatialized cumulative impact index, generating vulnerability maps. It represents the Step 6.
- Service Reference (id)
- Service Name
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Zonal Statistics Producer
- Service Description
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This service aims at producing the zonal statistics. The Python and C++ codes provides a generic tool to extract the statistics from a geographic layer with quantitative values for each patch of a categorical map. It represents the Step 7.
Metadata
- File identifier
- 30d404c5-eba4-4ca0-a273-983413960868 XML
- Metadata language
- en
- Hierarchy level
- Workflow
- Metadata Schema Version
-
1.0