This layer provides a transformation of environmental layer to best predict fern compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and to classify New Zealand into areas of similar biotic composition. The biotic data used for this model include all fern taxa from NVS recce data and estimated community compositions from pollen data.

Layer ID 238
Data type Grid
Resolution 100.000m
Services Raster Query API, data.govt.nz Atom Feed

This layer provides a transformation of environmental layer to best predict tree and shrub compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and to classify New Zealand into areas of similar biotic composition. The biotic data used for this model include all non-fern tree and shrub taxa from NVS recce data and estimated community compositions from pollen data.

Layer ID 257
Data type Grid
Resolution 100.000m
Services Raster Query API, data.govt.nz Atom Feed

This layer provides a classification of New Zealand ecosystems according to fern composition. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relation ship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. The transformed environmental layers were then used to classify New Zealand into areas of similar biotic composition. The biotic data used for this model include all fern taxa from NVS recce data and estimated community compositions from pollen data.

Layer ID 219
Data type Grid
Resolution 100.000m
Services Raster Query API, data.govt.nz Atom Feed

This layer provides a transformation of environmental layer to best predict fern compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and to classify New Zealand into areas of similar biotic composition. The biotic data used for this model include all fern taxa from NVS recce data and estimated community compositions from pollen data.

Layer ID 249
Data type Grid
Resolution 100.000m
Services Raster Query API, data.govt.nz Atom Feed

This layer provides a transformation of environmental layer to best predict plant compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and to classify New Zealand into areas of similar biotic composition. The biotic data used for this model include all vascular plant taxa from NVS recce data and estimated community compositions from pollen data.

Layer ID 232
Data type Grid
Resolution 100.000m
Services Raster Query API, data.govt.nz Atom Feed

This layer provides a transformation of environmental layer to best predict plant compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and to classify New Zealand into areas of similar biotic composition. The biotic data used for this model include all vascular plant taxa from NVS recce data and estimated community compositions from pollen data.

Layer ID 235
Data type Grid
Resolution 100.000m
Services Raster Query API, data.govt.nz Atom Feed

This layer provides a transformation of environmental layer to best predict fern compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and to classify New Zealand into areas of similar biotic composition. The biotic data used for this model include all fern taxa from NVS recce data and estimated community compositions from pollen data.

Layer ID 237
Data type Grid
Resolution 100.000m
Services Raster Query API, data.govt.nz Atom Feed

This layer provides a transformation of environmental layer to best predict tree and shrub compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and to classify New Zealand into areas of similar biotic composition. The biotic data used for this model include all non-fern tree and shrub taxa from NVS recce data and estimated community compositions from pollen data.

Layer ID 260
Data type Grid
Resolution 100.000m
Services Raster Query API, data.govt.nz Atom Feed

Zero BASE mask (Fmask)

Licence

Creative Commons Attribution 3.0 New Zealand

You may use this work for commercial purposes.

You must attribute the creator in your own works.

38
0
Added
02 Oct 2012

This is a binary mask layer identifying all areas that by definition (e.g., forested or water body) should have BASE carrying capacity set to zero (0 stock units/ha). All other areas are set to one (unity). The final BASE carrying capacity is derived by multiplying the result of the regression models by this binary mask leaving model values either unchanged or reset to zero. For use with both Model 1 and Model 2.

Layer ID 314
Data type Image/Raster
Resolution 25.000m
Services data.govt.nz Atom Feed

This layer provides a transformation of environmental layer to best predict tree and shrub compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and to classify New Zealand into areas of similar biotic composition. The biotic data used for this model include all non-fern tree and shrub taxa from NVS recce data and estimated community compositions from pollen data.

Layer ID 256
Data type Grid
Resolution 100.000m
Services Raster Query API, data.govt.nz Atom Feed
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