Rainfall:
For 2030, the projected changes for annual rainfall range from 62 to 191mm, highest along the south
coast and in the northern darling ranges. The projected percentage reduction in rainfall ranges from
13% in the south-west to 19% in the north-eastern edge of the SWCC region. The area of potential
highest impact is in the north, with the south-west somewhat less affected. Apart from much higher
levels of stress, the difference in 2090 is a strong trend to more severe impacts in the west. (This is
not apparent with the scales used, but exists in the data).
Growing Season:
Projected changes in growing season rainfall for 2030 are similar in distribution to 2090, but much
less pronounced. Growing season (May-October) rainfall reductions vary from 55 to 180mm, verses
81-380mm in 2090.
Temperature Stress:
The pattern of temperature stress is similar in 2030 to 2090 but much less severe, again greatest in
the north-east of the region and grading southwest. But increases of between 0.9 and 1.1 degrees
(max summer temp) for 2030 are far less than projected increases of 3.5 to 4.4 degrees in 2090.
Perhaps more significantly, average annual temperatures are projected to increase by only 0.9 to
1.35 degrees in 2030 but by up to 4.3 degrees in 2090.
Indicative Climate stress:
This combination indicator in 2030 looks slightly different to 2090: peaking in the north and east of
the region, with lower values along and to the east of the Leeuwin ridge. The values for the indicator
are lower: a mean of 1.7 verses 5.5 means a much lower climate stress.
This result for non-growing season stress in 2030 are similar. The implications of these projections
are that climate change will be relatively less pronounced in 2030.
9. Biosequestration
Taken from Simon Neville, Ecotones. May 2014. Spatially representing South West Catchments
Council priorities for biosequestration plantations and high biodiversity planting under climate
change.
Full report available: http://www.swnrmstrategy.org.au/climate-change-in-the-region/sequesteringcarbon/
This document provides the information required to meet the requirements of the Australian
Government to update Regional Strategies to:

Identify where tree plantings could fit into the landscape without causing adverse impacts.

Provide clarity to Carbon Farming Initiative (CFI) proponents when considering whether their
carbon emission abatement projects adhere to Regional NRM plans and do not have
unintended impacts by taking into consideration priority agricultural land, hydrology and
biodiversity.
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The process for obtaining this information was to form a Technical Working Group and undertake a
facilitated process using a decision support tool (MCAS-S).
The project delivered four major components:

Component 1 - What landscapes need to be protected from carbon plantings?

Component 2 - Where would SWCC encourage low biodiversity carbon plantings (e.g.
monocultures, tree-crops)?

Component 3 - High value biodiversity or conservation areas (intrinsic/internal values)

Component 4 - Where in the landscape do we want carbon plantings to enhance habitat
corridors and protect high biodiversity areas?
A number of useful layers were developed in consultation with the Technical Working Group that
were then used in the components above. These can be seen in the model diagrams for each of the
components below. To understand how each of the input layers were derived, please see the full
report.
9.1
Component 1 - Landscapes that need to be protected from carbon
plantings
The output layer 'Landscapes that need to be protected from carbon plantings' is a composite layer
producing 3 classes; No Protection, Mid-Priority Protection and Full Protection.
The composite function is generated from the sum of:
3 x '*High Quality Agricultural Land'
1 x 'Growing Season Percentage Change'
1 x 'Protection Zones for PDWSA'
0.1 x 'Remnant Vegetation'
The result is classed into three zones on an equal areas basis.
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Blue - areas without protection,
Green - areas with Low Priority protection, and
Red - areas with high priority (Full) protection.
Figure 3: Component 1: MCAS-S Output
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9.2
Component 2 – Locations for Low-Biodiversity Plantings
Layer 'Areas to encourage low-biodiversity carbon Plantings' is a composite layer producing 3 classes.
The composite function is generated from the sum of:
3 x '*Low Value Agricultural Land'
1 x '*Potential Salinity Areas'
1 x 'cleared_2014'
1 x 'WRRC Catchments for Salinity and Biodiversity'
The result is classed according to an equal-area classification:
1 - up to 1.895257 – No Low-Biodiversity Plantings
2 - up to 2.3966 – Low Priority Low-Biodiversity Plantings
3 - above 2.3966 – High Priority Low-Biodiversity Plantings
These three classes become the direction from this Component. The final Component model is shown
below, where:
Blue - areas without protection,
Green - areas with Low Priority protection, and
Red - areas with high priority (Full) protection.
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Figure 4: Component 2 Output – Locations for Low-Biodiversity Plantings
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9.3
Component 3 –Areas with High Biodiversity or Conservation Value
The final layer ‘Areas of High Biodiversity/Conservation Value' is a composite layer producing 5 classes
The composite function is generated from the sum of:
6 x '* High Value Biodiversity Areas'
2 x '* Potential Climate Refugia'
1 x '* Proximity to Threatened Species'
The result is classed according to this table:
1 - up to 1.5
2 - up to 2
3 - up to 4.2
4 - up to 6.176396
5 - above 6.176396.
Knowledge gap
Threatened fauna was not incorporated into the model
due to the bias and unreliability of the data. Only
threatened and Priority1 rare flora was used on advice
from Kim Williams. NCCARF Terrestrial refugia layer
was used to capture fauna values.
This component was light on for biodiversity input and
could possibly be consulted on further and improved.
Although not used in the final bio-sequestration
combined output, this layer has been used extensively
in other analysis and should be revisited and
potentially updated with the AdaptNRM layers and
consideration given to the other biodiversity layers
included and not I included in the analysis such as
threatened fauna.
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Figure 5: Component 3 Output –Areas with High Biodiversity or Conservation Value
This output was further classified to identify a total of 15% of remaining vegetation as “High Value”,
shown in red in the following figure.
Highest Value conservation areas – red
Other remnant vegetation – blue.
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Figure 6: Areas defined as High Conservation Value (red) using the 15% threshold.
9.4
Component 4 – Locations for carbon plantings to enhance habitat
corridors and protect high biodiversity areas
The component contains five major sub-components shown in the MCAS_S diagram below:





Proximity to High Biodiversity/conservation values (Component 3)
Proximity to known biodiversity assets
Rivers and buffers zones
Proximity to Priority Linkages, and
Potential for infill.
All of these sub-components are locational – indicating identified assets that are considered important
to plant near. As in the case of components 1 & 2, it removes remnant vegetation from consideration.
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Figure 7: Component 4 - MCAS-S Diagram
Layer 'Areas where we want Biodiversity Plantings (All Criteria Multiply)' is a composite layer
producing 3 classes – No, Low and High-Priority High-Biodiversity Plantings.
The composite function is generated from the product of:
1 x '* Rivers & Buffer Zones'
2 x '*Areas Close to Component 3 Biodiversity/Conservation Areas Final'
1 x '*Potential for Infill'
3 x '*Proximity to known Biodiversity Assets'
2 x '*Proximity to Priority Linkages'
1 x 'cleared_2014'
The result is classed according to this table:
1 - up to 0.02005758– No High-Biodiversity Plantings, (blue)
2 - up to 0.04011515 - Low Priority High-Biodiversity Plantings (green)
3 - above 0.04011515 - High Priority High-Biodiversity Plantings (red)
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Figure 8: MCAS-S Final Output – Component 4
9.5
Combining the components for Decision Support
In order to provide clear direction, we have combined the results for the three components (1, 2 & 4)
in a single map using ArcGIS by making a grid of each component output, and multiplying the grids
together to create a final grid with every different combination of component outputs indicated by a
unique cell value.
Producing this map requires the adoption of a hierarchy of outcomes to select a preferred outcome
from multiple options for each cell. For example, if a cell was indicated as being Low Priority for HighBiodiversity Planting, and High Priority for Low-Biodiversity planting and Low Priority for Protection,
which usage should be preferred? The hierarchy provides the answer.
The hierarchy of outcomes is based on discussion in the working group about the issues generally
surrounding plantations and carbon plantations in particular. It is shown in the figure below.
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Full Protection
High Priority High-Biodiversity Planting
High Priority Low-Biodiversity Planting
Low Priority Protection
Low Priority High-Biodiversity Planting
Low Priority Low-Biodiversity Planting
No Protection or No Planting
Figure 9: Outcome Hierarchy
The mapping of the highest ranking outcome provides the best options for each cell as shown in the
following map. This represents the final recommendations arising out of the entire process.
Cross-Regional Decision Matrix
Under development
Using CMIP3 Datasets in Component 1
Using CMIP3 climate model data in component 1
currently; a brief look at the implications of using
CMIP5 best case or worst case models (in place of the
CMIP3 Growing season rainfall % change) shows
changes in the protection priority given to specific
areas (of note - possible changes to the protection
priority of areas on the Darling Scarp foothills –
changing from planting to no planting).
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Website content:
These four layers are already
loaded into a mapping browser on
the website under the
sequestering carbon page
http://www.swnrmstrategy.org.au
/climate-change-in-theregion/sequestering-carbon/
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