Visualizing veg. formation and class data¶

The 17 vegetation formations are determined in large part by bioclimatic conditions. This notebook uses a series of climate/vegetation metrics from global datasets (annotated outside of this notebook) to visualize how these patterns vary by formation.

Reading these files directly from GCS requires installing a couple of packages:

mamba install fsspec gcsfs

In [1]:

import os
import artlo
from artlo import plt
import numpy as np
import pandas as pd
import geopandas as gpd

import os import artlo from artlo import plt import numpy as np import pandas as pd import geopandas as gpd

In [2]:

# paths
base = '/home/cba/src/forestobs-nsw'
plots = os.path.join(base, 'docs', 'img')
sample_path = 'gs://nsw-scratch/vector/nsw-class-samples-200k-annotated.gpkg'
meta_path = 'gs://nsw-scratch/raster/nsw-veg-raw.csv'

# paths base = '/home/cba/src/forestobs-nsw' plots = os.path.join(base, 'docs', 'img') sample_path = 'gs://nsw-scratch/vector/nsw-class-samples-200k-annotated.gpkg' meta_path = 'gs://nsw-scratch/raster/nsw-veg-raw.csv'

In [3]:

# plot settings
artlo.plot.set_style('salo-dark')

# plot settings artlo.plot.set_style('salo-dark')

Reading and formatting the data¶

In [4]:

# read the data into memory
meta = pd.read_csv(meta_path)
samples = gpd.read_file(sample_path)

# read the data into memory meta = pd.read_csv(meta_path) samples = gpd.read_file(sample_path)

In [5]:

# link up the metadata class names to their numerical specs
class_nums = list(meta['ClassNumbe'].unique())
form_nums = list(meta['Formatio_1'].unique())

class_nums.sort()
form_nums.sort()

class_names = [meta['ClassName'][meta['ClassNumbe'] == class_num].iloc[0] for class_num in class_nums]
form_names = [meta['FormationN'][meta['Formatio_1'] == form_num].iloc[0] for form_num in form_nums]

# replace the numbers in the dataframe with names for easier plotting
for class_name, class_num in zip(class_names, class_nums):
    samples['classes'][samples['classes'] == class_num] = class_name
    
for form_name, form_num in zip(form_names, form_nums):
    samples['formations'][samples['formations'] == form_num] = form_name

# link up the metadata class names to their numerical specs class_nums = list(meta['ClassNumbe'].unique()) form_nums = list(meta['Formatio_1'].unique()) class_nums.sort() form_nums.sort() class_names = [meta['ClassName'][meta['ClassNumbe'] == class_num].iloc[0] for class_num in class_nums] form_names = [meta['FormationN'][meta['Formatio_1'] == form_num].iloc[0] for form_num in form_nums] # replace the numbers in the dataframe with names for easier plotting for class_name, class_num in zip(class_names, class_nums): samples['classes'][samples['classes'] == class_num] = class_name for form_name, form_num in zip(form_names, form_nums): samples['formations'][samples['formations'] == form_num] = form_name

/tmp/ipykernel_5197/463801097.py:13: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  samples['classes'][samples['classes'] == class_num] = class_name
/tmp/ipykernel_5197/463801097.py:16: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  samples['formations'][samples['formations'] == form_num] = form_name

Bar charts for each climate/veg pattern¶

In [ ]:

# start plotting
columns = ['land_surface_temperature_mean', 'leaf_area_index_mean', 'cloud_cover_mean']
units = ['$^\circ$C', '$m^2 m^{-2}$', '%']

for column, unit in zip(columns, units):
    bp = samples.boxplot(
        column=column,
        by='formations',
        rot=90,
        grid=False,
        figsize=(5.5,6.5),
        fontsize='small',
        showfliers=False,
        return_type='both',
        patch_artist = True,
    )

    # add patch colors
    #for row_key, (ax,row) in bp.iteritems():
    #    ax.set_xlabel('')
    #    for i, box in enumerate(row['boxes']):
    #        box.set_facecolor(form_colors[i])

    # add labels
    plt.suptitle(None)
    plt.title(column)
    plt.ylabel(units)
    plt.tight_layout()
    plt.savefig(os.path.join(plots, f'{column}.png'), dpi=200)
    plt.close()

# start plotting columns = ['land_surface_temperature_mean', 'leaf_area_index_mean', 'cloud_cover_mean'] units = ['$^\circ$C', '$m^2 m^{-2}$', '%'] for column, unit in zip(columns, units): bp = samples.boxplot( column=column, by='formations', rot=90, grid=False, figsize=(5.5,6.5), fontsize='small', showfliers=False, return_type='both', patch_artist = True, ) # add patch colors #for row_key, (ax,row) in bp.iteritems(): # ax.set_xlabel('') # for i, box in enumerate(row['boxes']): # box.set_facecolor(form_colors[i]) # add labels plt.suptitle(None) plt.title(column) plt.ylabel(units) plt.tight_layout() plt.savefig(os.path.join(plots, f'{column}.png'), dpi=200) plt.close()

In [6]:

# plot all in a grid
subfigsize = (5.5, 6.5)
xsize, ysize = (4, 3)
figsize = (xsize * subfigsize[0], ysize * subfigsize[1])
fig, axs = plt.subplots(ysize, xsize, figsize=figsize)
columns = samples.columns[2:-1]
by='formations'

axs = axs.reshape(np.product((xsize, ysize)))
for idx, column in enumerate(columns):

    if 'temperature' in column:
        units = '$^\circ$C'
    elif 'cloud' in column:
        units = '%'
    elif 'leaf_area' in column:
        units = '$m^2 m^{-2}$'

    bp = samples.boxplot(
        column=column,
        by=by,
        ax=axs[idx],
        rot=90,
        grid=False,
        figsize=subfigsize,
        fontsize='small',
        showfliers=False,
        patch_artist = True,
    )

    # add labels
    axs[idx].set_title(column)
    axs[idx].set_ylabel(units)
    
fig.suptitle(None)
fig.tight_layout()
plt.savefig(os.path.join(plots, f"{by}-env-conditions.png"), dpi=200)

# plot all in a grid subfigsize = (5.5, 6.5) xsize, ysize = (4, 3) figsize = (xsize * subfigsize[0], ysize * subfigsize[1]) fig, axs = plt.subplots(ysize, xsize, figsize=figsize) columns = samples.columns[2:-1] by='formations' axs = axs.reshape(np.product((xsize, ysize))) for idx, column in enumerate(columns): if 'temperature' in column: units = '$^\circ$C' elif 'cloud' in column: units = '%' elif 'leaf_area' in column: units = '$m^2 m^{-2}$' bp = samples.boxplot( column=column, by=by, ax=axs[idx], rot=90, grid=False, figsize=subfigsize, fontsize='small', showfliers=False, patch_artist = True, ) # add labels axs[idx].set_title(column) axs[idx].set_ylabel(units) fig.suptitle(None) fig.tight_layout() plt.savefig(os.path.join(plots, f"{by}-env-conditions.png"), dpi=200)

Listing the class and formation names¶

In [7]:

for name, num in zip(form_names, form_nums):
    print(f"form {int(num):03d}: {name}")

for name, num in zip(form_names, form_nums): print(f"form {int(num):03d}: {name}")

form 000: Cleared
form 001: Rainforests
form 002: Wet sclerophyll forests (Shrubby subformation)
form 003: Wet sclerophyll forests (Grassy subformation)
form 004: Grassy woodlands
form 005: Grasslands
form 006: Dry sclerophyll forests (Shrub/grass subformation)
form 007: Dry sclerophyll forests (Shrubby subformation)
form 008: Heathlands
form 009: Alpine complex
form 010: Freshwater wetlands
form 011: Forested wetlands
form 012: Saline  wetlands
form 013: Semi-arid woodlands (Grassy subformation)
form 014: Semi-arid woodlands (Shrubby subformation)
form 015: Arid shrublands (Chenopod subformation)
form 016: Arid shrublands (Acacia subformation)

In [8]:

for name, num in zip(class_names, class_nums):
    print(f"class {int(num):03d}: {name}")

for name, num in zip(class_names, class_nums): print(f"class {int(num):03d}: {name}")

class 000: Cleared
class 001: Subtropical Rainforests
class 002: Northern Warm Temperate Rainforests
class 003: Cool Temperate Rainforests
class 004: Dry Rainforests
class 005: Littoral Rainforests
class 006: North Coast Wet Sclerophyll Forests
class 007: South Coast Wet Sclerophyll Forests
class 008: Northern Escarpment Wet Sclerophyll Forests
class 009: Southern Escarpment Wet Sclerophyll Forests
class 010: Northern Tableland Wet Sclerophyll Forests
class 011: Southern Tableland Wet Sclerophyll Forests
class 015: Sydney Coastal Dry Sclerophyll Forests
class 016: Sydney Hinterland Dry Sclerophyll Forests
class 017: Sydney Montane Dry Sclerophyll Forests
class 019: Coastal Dune Dry Sclerophyll Forests
class 020: North Coast Dry Sclerophyll Forests
class 021: Northern Hinterland Wet Sclerophyll Forests
class 022: South Coast Sands Dry Sclerophyll Forests
class 024: Southern Lowland Wet Sclerophyll Forests
class 025: Northern Escarpment Dry Sclerophyll Forests
class 026: South East Dry Sclerophyll Forests
class 027: Northern Tableland Dry Sclerophyll Forests
class 028: Southern Tableland Dry Sclerophyll Forests
class 029: Western Slopes Dry Sclerophyll Forests
class 030: Pilliga Outwash Dry Sclerophyll Forests
class 031: Wallum Sand Heaths
class 032: Sydney Coastal Heaths
class 033: Northern Montane Heaths
class 034: Sydney Montane Heaths
class 035: Southern Montane Heaths
class 036: Alpine Heaths
class 040: Tableland Clay Grassy Woodlands
class 041: New England Grassy Woodlands
class 042: Western Slopes Grassy Woodlands
class 044: Western Peneplain Woodlands
class 045: Subalpine Woodlands
class 046: Temperate Montane Grasslands
class 047: Semi-arid Floodplain Grasslands
class 048: Coastal Swamp Forests
class 050: Coastal Floodplain Forests
class 051: Eastern Riverine Forests
class 052: Inland Riverine Forests
class 053: Inland Floodplain Woodlands
class 054: Coastal Heath Swamps
class 055: Montane Bogs and Fens
class 056: Coastal Freshwater Lagoons and Floodplain Meadows
class 057: Inland Saline Lakes
class 058: Mangrove Swamps
class 059: Riverine Chenopod Shrublands
class 060: Aeolian Chenopod Shrublands
class 061: Dune Mallee Woodlands
class 062: Sand Plain Mallee Woodlands
class 063: Semi-arid Sand Plain Woodlands
class 064: Sydney Sand Flats Dry Sclerophyll Forests
class 065: South Coast Heaths
class 066: Northern Gorge Dry Sclerophyll Forests
class 067: Clarence Dry Sclerophyll Forests
class 068: New England Dry Sclerophyll Forests
class 069: Hunter-Macleay Dry Sclerophyll Forests
class 070: Coastal Headland and Foredune Scrubs
class 071: Saltmarshes
class 072: Coastal Valley Grassy Woodlands
class 074: Montane Lakes
class 075: Southern Warm Temperate Rainforests
class 078: Montane Wet Sclerophyll Forests
class 079: Central Gorge Dry Sclerophyll Forests
class 080: Cumberland Dry Sclerophyll Forests
class 081: Southern Hinterland Dry Sclerophyll Forests
class 082: Southern Wattle Dry Sclerophyll Forests
class 084: Upper Riverina Dry Sclerophyll Forests
class 086: Southern Tableland Grassy Woodlands
class 088: Riverine Sandhill Woodlands
class 089: Inland Rocky Hill Woodlands
class 090: Riverine Plain Woodlands
class 091: Riverine Plain Grasslands
class 092: Inland Floodplain Shrublands
class 094: Subtropical Semi-arid Woodlands
class 095: Desert Woodlands
class 097: North-west Floodplain Woodlands
class 098: Gibber Chenopod Shrublands
class 099: Stony Desert Mulga Shrublands
class 100: Sand Plain Mulga Shrublands
class 101: Brigalow Clay Plain Woodlands
class 102: North-west Plain Shrublands
class 103: Gibber Transition Shrublands
class 104: Alpine Fjaeldmarks
class 106: Yetman Dry Sclerophyll Forests
class 107: North-west Alluvial Sand Woodlands
class 108: Inland Floodplain Swamps
class 109: Floodplain Transition Woodlands
class 110: Western Slopes Grasslands
class 112: Seagrass Meadows
class 113: North-west Slopes Dry Sclerophyll Woodlands
class 114: Alpine Herbfields
class 115: Alpine Bogs and Fens
class 116: Maritime Grasslands
class 117: Oceanic Rainforests
class 118: Oceanic Cloud Forests
class 119: Western Vine Thickets
class 120: Temperate Swamp Forests
class 124: Southern Riverina Grasslands
class 125: Wadi Woodlands
class 126: Floodplain-Estuarine Transition Forests

Listing sub-form dependencies¶

In [13]:

for name, num in zip(form_names, form_nums):
    subforms = list(meta['ClassName'][meta['Formatio_1'] == num].unique())
    subforms.sort()
    print(f"-- Form: {name} | Contains {len(subforms)} sub-forms --")
    [print(subform) for subform in subforms]
    print('')

for name, num in zip(form_names, form_nums): subforms = list(meta['ClassName'][meta['Formatio_1'] == num].unique()) subforms.sort() print(f"-- Form: {name} | Contains {len(subforms)} sub-forms --") [print(subform) for subform in subforms] print('')

-- Form: Cleared | Contains 1 sub-forms --
Cleared

-- Form: Rainforests | Contains 9 sub-forms --
Cool Temperate Rainforests
Dry Rainforests
Littoral Rainforests
Northern Warm Temperate Rainforests
Oceanic Cloud Forests
Oceanic Rainforests
Southern Warm Temperate Rainforests
Subtropical Rainforests
Western Vine Thickets

-- Form: Wet sclerophyll forests (Shrubby subformation) | Contains 4 sub-forms --
North Coast Wet Sclerophyll Forests
Northern Escarpment Wet Sclerophyll Forests
South Coast Wet Sclerophyll Forests
Southern Escarpment Wet Sclerophyll Forests

-- Form: Wet sclerophyll forests (Grassy subformation) | Contains 5 sub-forms --
Montane Wet Sclerophyll Forests
Northern Hinterland Wet Sclerophyll Forests
Northern Tableland Wet Sclerophyll Forests
Southern Lowland Wet Sclerophyll Forests
Southern Tableland Wet Sclerophyll Forests

-- Form: Grassy woodlands | Contains 7 sub-forms --
Coastal Valley Grassy Woodlands
Floodplain Transition Woodlands
New England Grassy Woodlands
Southern Tableland Grassy Woodlands
Subalpine Woodlands
Tableland Clay Grassy Woodlands
Western Slopes Grassy Woodlands

-- Form: Grasslands | Contains 6 sub-forms --
Maritime Grasslands
Riverine Plain Grasslands
Semi-arid Floodplain Grasslands
Southern Riverina Grasslands
Temperate Montane Grasslands
Western Slopes Grasslands

-- Form: Dry sclerophyll forests (Shrub/grass subformation) | Contains 10 sub-forms --
Central Gorge Dry Sclerophyll Forests
Clarence Dry Sclerophyll Forests
Cumberland Dry Sclerophyll Forests
Hunter-Macleay Dry Sclerophyll Forests
New England Dry Sclerophyll Forests
North-west Slopes Dry Sclerophyll Woodlands
Northern Gorge Dry Sclerophyll Forests
Pilliga Outwash Dry Sclerophyll Forests
Southern Hinterland Dry Sclerophyll Forests
Upper Riverina Dry Sclerophyll Forests

-- Form: Dry sclerophyll forests (Shrubby subformation) | Contains 14 sub-forms --
Coastal Dune Dry Sclerophyll Forests
North Coast Dry Sclerophyll Forests
Northern Escarpment Dry Sclerophyll Forests
Northern Tableland Dry Sclerophyll Forests
South Coast Sands Dry Sclerophyll Forests
South East Dry Sclerophyll Forests
Southern Tableland Dry Sclerophyll Forests
Southern Wattle Dry Sclerophyll Forests
Sydney Coastal Dry Sclerophyll Forests
Sydney Hinterland Dry Sclerophyll Forests
Sydney Montane Dry Sclerophyll Forests
Sydney Sand Flats Dry Sclerophyll Forests
Western Slopes Dry Sclerophyll Forests
Yetman Dry Sclerophyll Forests

-- Form: Heathlands | Contains 7 sub-forms --
Coastal Headland and Foredune Scrubs
Northern Montane Heaths
South Coast Heaths
Southern Montane Heaths
Sydney Coastal Heaths
Sydney Montane Heaths
Wallum Sand Heaths

-- Form: Alpine complex | Contains 4 sub-forms --
Alpine Bogs and Fens
Alpine Fjaeldmarks
Alpine Heaths
Alpine Herbfields

-- Form: Freshwater wetlands | Contains 6 sub-forms --
Coastal Freshwater Lagoons and Floodplain Meadows
Coastal Heath Swamps
Inland Floodplain Shrublands
Inland Floodplain Swamps
Montane Bogs and Fens
Montane Lakes

-- Form: Forested wetlands | Contains 6 sub-forms --
Coastal Floodplain Forests
Coastal Swamp Forests
Eastern Riverine Forests
Floodplain-Estuarine Transition Forests
Inland Riverine Forests
Temperate Swamp Forests

-- Form: Saline  wetlands | Contains 4 sub-forms --
Inland Saline Lakes
Mangrove Swamps
Saltmarshes
Seagrass Meadows

-- Form: Semi-arid woodlands (Grassy subformation) | Contains 5 sub-forms --
Brigalow Clay Plain Woodlands
Inland Floodplain Woodlands
North-west Floodplain Woodlands
Riverine Plain Woodlands
Wadi Woodlands

-- Form: Semi-arid woodlands (Shrubby subformation) | Contains 9 sub-forms --
Desert Woodlands
Dune Mallee Woodlands
Inland Rocky Hill Woodlands
North-west Alluvial Sand Woodlands
Riverine Sandhill Woodlands
Sand Plain Mallee Woodlands
Semi-arid Sand Plain Woodlands
Subtropical Semi-arid Woodlands
Western Peneplain Woodlands

-- Form: Arid shrublands (Chenopod subformation) | Contains 3 sub-forms --
Aeolian Chenopod Shrublands
Gibber Chenopod Shrublands
Riverine Chenopod Shrublands

-- Form: Arid shrublands (Acacia subformation) | Contains 4 sub-forms --
Gibber Transition Shrublands
North-west Plain Shrublands
Sand Plain Mulga Shrublands
Stony Desert Mulga Shrublands

Create a table of all form/subform names/classes¶

In [7]:

for name, num in zip(form_names, form_nums):
    subforms = list(meta['ClassName'][meta['Formatio_1'] == num].unique())
    subforms.sort()
    for subform in subforms:
        subform_num = list(meta['ClassNumbe'][meta['ClassName'] == subform].unique())[0]
        print(f"{name}, {subform}, {int(num)}, {subform_num}")

for name, num in zip(form_names, form_nums): subforms = list(meta['ClassName'][meta['Formatio_1'] == num].unique()) subforms.sort() for subform in subforms: subform_num = list(meta['ClassNumbe'][meta['ClassName'] == subform].unique())[0] print(f"{name}, {subform}, {int(num)}, {subform_num}")

Cleared, Cleared, 0, 0
Rainforests, Cool Temperate Rainforests, 1, 3
Rainforests, Dry Rainforests, 1, 4
Rainforests, Littoral Rainforests, 1, 5
Rainforests, Northern Warm Temperate Rainforests, 1, 2
Rainforests, Oceanic Cloud Forests, 1, 118
Rainforests, Oceanic Rainforests, 1, 117
Rainforests, Southern Warm Temperate Rainforests, 1, 75
Rainforests, Subtropical Rainforests, 1, 1
Rainforests, Western Vine Thickets, 1, 119
Wet sclerophyll forests (Shrubby subformation), North Coast Wet Sclerophyll Forests, 2, 6
Wet sclerophyll forests (Shrubby subformation), Northern Escarpment Wet Sclerophyll Forests, 2, 8
Wet sclerophyll forests (Shrubby subformation), South Coast Wet Sclerophyll Forests, 2, 7
Wet sclerophyll forests (Shrubby subformation), Southern Escarpment Wet Sclerophyll Forests, 2, 9
Wet sclerophyll forests (Grassy subformation), Montane Wet Sclerophyll Forests, 3, 78
Wet sclerophyll forests (Grassy subformation), Northern Hinterland Wet Sclerophyll Forests, 3, 21
Wet sclerophyll forests (Grassy subformation), Northern Tableland Wet Sclerophyll Forests, 3, 10
Wet sclerophyll forests (Grassy subformation), Southern Lowland Wet Sclerophyll Forests, 3, 24
Wet sclerophyll forests (Grassy subformation), Southern Tableland Wet Sclerophyll Forests, 3, 11
Grassy woodlands, Coastal Valley Grassy Woodlands, 4, 72
Grassy woodlands, Floodplain Transition Woodlands, 4, 109
Grassy woodlands, New England Grassy Woodlands, 4, 41
Grassy woodlands, Southern Tableland Grassy Woodlands, 4, 86
Grassy woodlands, Subalpine Woodlands, 4, 45
Grassy woodlands, Tableland Clay Grassy Woodlands, 4, 40
Grassy woodlands, Western Slopes Grassy Woodlands, 4, 42
Grasslands, Maritime Grasslands, 5, 116
Grasslands, Riverine Plain Grasslands, 5, 91
Grasslands, Semi-arid Floodplain Grasslands, 5, 47
Grasslands, Southern Riverina Grasslands, 5, 124
Grasslands, Temperate Montane Grasslands, 5, 46
Grasslands, Western Slopes Grasslands, 5, 110
Dry sclerophyll forests (Shrub/grass subformation), Central Gorge Dry Sclerophyll Forests, 6, 79
Dry sclerophyll forests (Shrub/grass subformation), Clarence Dry Sclerophyll Forests, 6, 67
Dry sclerophyll forests (Shrub/grass subformation), Cumberland Dry Sclerophyll Forests, 6, 80
Dry sclerophyll forests (Shrub/grass subformation), Hunter-Macleay Dry Sclerophyll Forests, 6, 69
Dry sclerophyll forests (Shrub/grass subformation), New England Dry Sclerophyll Forests, 6, 68
Dry sclerophyll forests (Shrub/grass subformation), North-west Slopes Dry Sclerophyll Woodlands, 6, 113
Dry sclerophyll forests (Shrub/grass subformation), Northern Gorge Dry Sclerophyll Forests, 6, 66
Dry sclerophyll forests (Shrub/grass subformation), Pilliga Outwash Dry Sclerophyll Forests, 6, 30
Dry sclerophyll forests (Shrub/grass subformation), Southern Hinterland Dry Sclerophyll Forests, 6, 81
Dry sclerophyll forests (Shrub/grass subformation), Upper Riverina Dry Sclerophyll Forests, 6, 84
Dry sclerophyll forests (Shrubby subformation), Coastal Dune Dry Sclerophyll Forests, 7, 19
Dry sclerophyll forests (Shrubby subformation), North Coast Dry Sclerophyll Forests, 7, 20
Dry sclerophyll forests (Shrubby subformation), Northern Escarpment Dry Sclerophyll Forests, 7, 25
Dry sclerophyll forests (Shrubby subformation), Northern Tableland Dry Sclerophyll Forests, 7, 27
Dry sclerophyll forests (Shrubby subformation), South Coast Sands Dry Sclerophyll Forests, 7, 22
Dry sclerophyll forests (Shrubby subformation), South East Dry Sclerophyll Forests, 7, 26
Dry sclerophyll forests (Shrubby subformation), Southern Tableland Dry Sclerophyll Forests, 7, 28
Dry sclerophyll forests (Shrubby subformation), Southern Wattle Dry Sclerophyll Forests, 7, 82
Dry sclerophyll forests (Shrubby subformation), Sydney Coastal Dry Sclerophyll Forests, 7, 15
Dry sclerophyll forests (Shrubby subformation), Sydney Hinterland Dry Sclerophyll Forests, 7, 16
Dry sclerophyll forests (Shrubby subformation), Sydney Montane Dry Sclerophyll Forests, 7, 17
Dry sclerophyll forests (Shrubby subformation), Sydney Sand Flats Dry Sclerophyll Forests, 7, 64
Dry sclerophyll forests (Shrubby subformation), Western Slopes Dry Sclerophyll Forests, 7, 29
Dry sclerophyll forests (Shrubby subformation), Yetman Dry Sclerophyll Forests, 7, 106
Heathlands, Coastal Headland and Foredune Scrubs, 8, 70
Heathlands, Northern Montane Heaths, 8, 33
Heathlands, South Coast Heaths, 8, 65
Heathlands, Southern Montane Heaths, 8, 35
Heathlands, Sydney Coastal Heaths, 8, 32
Heathlands, Sydney Montane Heaths, 8, 34
Heathlands, Wallum Sand Heaths, 8, 31
Alpine complex, Alpine Bogs and Fens, 9, 115
Alpine complex, Alpine Fjaeldmarks, 9, 104
Alpine complex, Alpine Heaths, 9, 36
Alpine complex, Alpine Herbfields, 9, 114
Freshwater wetlands, Coastal Freshwater Lagoons and Floodplain Meadows, 10, 56
Freshwater wetlands, Coastal Heath Swamps, 10, 54
Freshwater wetlands, Inland Floodplain Shrublands, 10, 92
Freshwater wetlands, Inland Floodplain Swamps, 10, 108
Freshwater wetlands, Montane Bogs and Fens, 10, 55
Freshwater wetlands, Montane Lakes, 10, 74
Forested wetlands, Coastal Floodplain Forests, 11, 50
Forested wetlands, Coastal Swamp Forests, 11, 48
Forested wetlands, Eastern Riverine Forests, 11, 51
Forested wetlands, Floodplain-Estuarine Transition Forests, 11, 126
Forested wetlands, Inland Riverine Forests, 11, 52
Forested wetlands, Temperate Swamp Forests, 11, 120
Saline  wetlands, Inland Saline Lakes, 12, 57
Saline  wetlands, Mangrove Swamps, 12, 58
Saline  wetlands, Saltmarshes, 12, 71
Saline  wetlands, Seagrass Meadows, 12, 112
Semi-arid woodlands (Grassy subformation), Brigalow Clay Plain Woodlands, 13, 101
Semi-arid woodlands (Grassy subformation), Inland Floodplain Woodlands, 13, 53
Semi-arid woodlands (Grassy subformation), North-west Floodplain Woodlands, 13, 97
Semi-arid woodlands (Grassy subformation), Riverine Plain Woodlands, 13, 90
Semi-arid woodlands (Grassy subformation), Wadi Woodlands, 13, 125
Semi-arid woodlands (Shrubby subformation), Desert Woodlands, 14, 95
Semi-arid woodlands (Shrubby subformation), Dune Mallee Woodlands, 14, 61
Semi-arid woodlands (Shrubby subformation), Inland Rocky Hill Woodlands, 14, 89
Semi-arid woodlands (Shrubby subformation), North-west Alluvial Sand Woodlands, 14, 107
Semi-arid woodlands (Shrubby subformation), Riverine Sandhill Woodlands, 14, 88
Semi-arid woodlands (Shrubby subformation), Sand Plain Mallee Woodlands, 14, 62
Semi-arid woodlands (Shrubby subformation), Semi-arid Sand Plain Woodlands, 14, 63
Semi-arid woodlands (Shrubby subformation), Subtropical Semi-arid Woodlands, 14, 94
Semi-arid woodlands (Shrubby subformation), Western Peneplain Woodlands, 14, 44
Arid shrublands (Chenopod subformation), Aeolian Chenopod Shrublands, 15, 60
Arid shrublands (Chenopod subformation), Gibber Chenopod Shrublands, 15, 98
Arid shrublands (Chenopod subformation), Riverine Chenopod Shrublands, 15, 59
Arid shrublands (Acacia subformation), Gibber Transition Shrublands, 16, 103
Arid shrublands (Acacia subformation), North-west Plain Shrublands, 16, 102
Arid shrublands (Acacia subformation), Sand Plain Mulga Shrublands, 16, 100
Arid shrublands (Acacia subformation), Stony Desert Mulga Shrublands, 16, 99