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EM: Effect of climate change on the habitat suitability of the relict species Zelkova carpinifolia Spach using ensembled species distribution modelling (EM-1037)
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Expand AllEM Identity and Description
EM Identification
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EM ID
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EM-1037 |
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EM Short Name
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BIOMOD, Z. carpinifolia distribution, Middle East |
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EM Full Name
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Effect of climate change on the habitat suitability of the relict species Zelkova carpinifolia Spach using ensembled species distribution modelling |
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EM Source or Collection
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None |
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EM Source Document ID
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492 |
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Document Author
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Koç, D.E., Ustaoğlu, B. and Biltekin, D. |
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Document Year
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2024 |
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Document Title
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Effect of climate change on the habitat suitability of the relict species Zelkova carpinifolia Spach using ensembled species distribution modelling |
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Document Status
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Peer reviewed and published |
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Comments on Status
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Published journal manuscript |
Software and Access
| https://cran.r-project.org/web/packages/biomod2/index.html | |
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Contact Name
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Derya Evrim Koç |
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Contact Address
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Faculty of Humanities and Social Science, Department of Geography, Sakarya University, Serdivan, 54050, Sakarya, Türkiye |
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Contact Email
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dekoc@sakarya.edu.tr |
EM Description
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Summary Description
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Zelkova carpinifolia is a Tertiary relict tree distributed in Hyrcanian and Colchic forests. Most of its habitat has been destroyed in the last century. This study aimed to model potentially suitable habitat areas for Zelkova carpinifolia from the past to the future. The Last Glacial Maximum (LGM) and Future (2061–2080) models include 19 bioclimatic variables from the CCSM4 global circulation model Pearson correlation coefficient was used to assess collinearity between variables and ten variables were selected for distribution modelling. Habitat suitability was estimated using the Biodiversity Modelling (BIOMOD) ensemble modelling method by combining the results of ten algorithm models using the R package “biomod2”. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and true skills statistics (TSS) were calculated to evaluate the performance of the models. The contributions of the environmental variables were calculated separately for each algorithm model. According to the results obtained, the most effective bioclimatic variable in the distribution of the species is temperature seasonality (Bio4). The modelling results revealed that Zelkova carpinifolia survived in suitable refuge areas in western Asia during the LGM. These distribution areas have remained largely unchanged and even expanded. The future model results predict that the suitable habitats of the species will narrow in the Hyrcanian forests south of Caspian Sea and that more suitable conditions will be found around the Caucasus. Given the increasing destruction of these valuable plant species due to human activities and the expected negative impacts of climate change in the future, it is important to develop policies and strategies for the protection of Zelkova carpinifolia's habitat, the creation of nature reserves, and sustainability. |
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Specific Policy or Decision Context Cited
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None provided |
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Biophysical Context
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Middle East region between the Black and Caspian seas as well south of Russia and north of Iraq |
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EM Scenario Drivers
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None identified |
EM Relationship to Other EMs or Applications
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Method Only, Application of Method or Model Run
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Method + Application |
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New or Pre-existing EM?
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Application of existing model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
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Document ID for related EM
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Doc-491 |
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EM ID for related EM
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EM-1036 |
EM Modeling Approach
EM Relationship to Time
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EM Temporal Extent
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Last glacial maximum, present, 2070 |
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EM Time Dependence
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time-dependent |
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EM Time Reference (Future/Past)
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both |
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EM Time Continuity
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discrete |
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EM Temporal Grain Size Value
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NA |
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EM Temporal Grain Size Unit
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Year |
EM Spatial Extent
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Bounding Type
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Physiographic or ecological |
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Spatial Extent Name
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NA |
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Spatial Extent Area (Magnitude)
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>1,000,000 km^2 |
Spatial Distribution of Computations
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EM Spatial Distribution
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spatially distributed (in at least some cases) |
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Spatial Grain Type
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area, for pixel or radial feature |
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Spatial Grain Size
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5 km^2 |
EM Structure and Computation Approach
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EM Computational Approach
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Analytic |
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EM Determinism
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stochastic |
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Statistical Estimation of EM
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Model Checking Procedures Used
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Model Calibration Reported?
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Yes |
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Model Goodness of Fit Reported?
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Yes |
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Goodness of Fit (metric| value | unit)
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Model Operational Validation Reported?
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No |
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Model Uncertainty Analysis Reported?
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Unclear |
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Model Sensitivity Analysis Reported?
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Yes |
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Model Sensitivity Analysis Include Interactions?
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Yes |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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| None |
Centroid Lat/Long (Decimal Degree)
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Centroid Latitude
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40.34 |
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Centroid Longitude
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46.1 |
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Centroid Datum
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WGS84 |
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Centroid Coordinates Status
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Estimated |
Environments and Scales Modeled
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EM Environmental Sub-Class
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Terrestrial Environment (sub-classes not fully specified) |
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Specific Environment Type
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Multiple terrestrial habitats |
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EM Ecological Scale
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Ecological scale is coarser than that of the Environmental Sub-class |
Scale and taxa of organisms modeled
Scale of differentiation of organisms modeled
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EM Organismal Scale
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Species |
Taxonomic level and name of organisms or groups identified
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EnviroAtlas URL
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| GAP Ecological Systems, Average Annual Precipitation |
EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)
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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
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| None |
EM Variable Names (and Units)
Predictor
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Intermediate
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Intermediate (Computed) Variables (and Units)
view details (3 variables)
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Response
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