Oceania Biota Data - Page 8

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.

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.

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.

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.

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.

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.

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.

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.

Lupin density has been classified within 4 ha (200 x 200 m) tiles as either absent (transparent), low density (< 1 plant/ha = yellow), moderate density (<10 plants/ha = orange) or high density (>10 plants/ha = red).