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Date of publication: April 8, 2022

Version 1

Date of publication: April 8, 2022

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Global trends in biodiversity (BES-SIM cSAR-iDiv)

by Inês Martins

Projections from the cSAR-iDiv model from 1900-2050 using LUH2 and SSPs-RCPs, done in the BES-SIM inter-model comparison for IPBES. ...(continue reading)

DOI 10.25829/5zmy41
Citation
Martins, I., Pereira, H. (2022). Global trends in biodiversity (BES-SIM cSAR-iDiv) (Version 1) [Dataset]. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. https://doi.org/10.25829/5zmy41

BES-SIMSSP scenariosRCP scenariosIPBES

30
The title of the dataset. Global trends in biodiversity (BES-SIM cSAR-iDiv)
The date on which this version of the data was created in YYYY-MM-DD format.
A paragraph describing the dataset.
Hover to see a suggestion for a good description. Allowed:
Projections from the cSAR-iDiv model from 1900-2050 using LUH2 and SSPs-RCPs, done in the BES-SIM inter-model comparison for IPBES.
Provide the DOI number of associated publications. Click Plus to add DOIs.
https://doi.org/
10.1101/2020.04.14.031716
The method of production of the original data.
Hover to see a suggestion for a minimum description. cSAR-iDiv model team, 14 December 2018
The coverage content type describes the general content type of the resource (multiple selection possible).
The name of the Project.
The URL from the project website. https://ipbes.net/scenarios-models/expert-group-activities
The name of the person or other creator type principally responsible for creating this data.
The email of the person or other creator type principally responsible for creating this data. istmartins@gmail.com

N/A

hpereira@idiv.de

N/A

The names of the co-creators responsible for creating this data. Click Plus to add co-creators.
Select between Creative Commons (CC) or Non-CC license.
Please select the CC license from the list. We recommend the use of CC BY 4.0

Essential Biodiversity Variables

Select the EBV class and the EBV name for the dataset. For cross-cutting use the comment at the bottom of the page for further information.
Genetic composition
Intraspecific genetic diversity
Genetic differentiation
Effective population size
Inbreeding
Other
Species populations
Species distributions
Species abundances
Other
Species traits
Morphology
Physiology
Phenology
Movement
Other
Community composition
Community abundance
Taxonomic and phylogenetic diversity
Trait diversity
Interaction diversity
Other
Ecosystem functioning
Primary productivity
Ecosystem phenology
Ecosystem disturbances
Other
Ecosystem structure
Live cover fraction
Ecosystem distribution
Ecosystem Vertical Profile
Other
Ecosystem services
Pollination
Other
Cross-cutting

Entity

Select the entity type of the dataset.
Species
Communities
Ecosystems
Other
None
A description of the range of taxa or ecosystem types addressed in the dataset. E.g. "300 species of mammals”, “Forests”, etc.
The reference as a URL. N/A

Metric

Provide the name, description, units of minimum 1 metric. Click Plus to add metrics.

Scenario

If applicable, name the scenario's exercise, the version and provide a URL to the reference. https://en.wikipedia.org/wiki/Shared_Socioeconomic_Pathways

Spatial domain

Global
Continental/Regional
National
Sub-national/Local
degree
southWest lat: -90, lon: -180
northEast lat: 90, lon: 180

Temporal domain

The targeted time period between each value in the dataset.
decadal
annually
monthly
weekly
daily
Other
Irregular
Single time
Select the temporal extent of the dataset.
When the dataset represents a Single time, then use the same start and end date.
__

Environmental domain *

Terrestrial
Marine
Freshwater
Miscellaneous information about the data, not captured elsewhere. Delta_S (original name: CC-DC) for the two time periods and S for 2015 (original name: Sp) were provided by cSAR team. Delta_SS and values of S for 1900 and 2050 calculated by H.M. Pereira on 20.3.2022.
Entities
All birds
Forest birds
Non-forest birds