Appendix 16: Terrestrial Biodiversity Forecasting Tool methodology
The Biodiversity Forecasting Tool generated priorities by estimating the relative differences in the persistence of biodiversity across the Region as a consequence of changing landuse or management at different locations. For this Plan, information on the pre-1750 and current extent, condition and configuration (connectivity, size and shape) of vegetation was coupled with information on threats and ecological processes (Turbill & Steed 2006). The Biodiversity Forecasting Tool provides maps of priority values indicating the potential contribution of each location to the overall priorities for the Region that would arise from a predefined conservation action. A brief description of the process and the derivation of datasets used by the Tool are provided below. (For more detailed information, refer to DEC 2006). The application of the Tool involved three main interacting components:
1.	Predicting the condition of future vegetation as a function of current vegetation condition, spatial distribution and magnitude of threats, and existing or proposed landuse and management (Drielsma & Ferrier 2006).
2.	Predicting the likelihood of persistence for each vegetation community as a function of its spatial distribution (Drielsma et al. 2007) and the configuration of future vegetation condition for that community.
3.	Aggregating the predicted persistence levels of each vegetation community into an overall estimate of persistence for biodiversity across the Region.
1.1	Data inputs
The Biodiversity Forecasting Tool uses the pre-1750 and current extent, condition and configuration of vegetation communities, together with threat consequence and probability estimates to predict the future condition for each one hectare grid cell of vegetation in the Region. The main data inputs used by the Tool are a map of existing vegetation communities, an estimate of the pre-1750 areal extent of these communities, a map of current vegetation condition, and a map of threats across the Region. These are briefly described here.
A spatial layer of vegetation communities and an estimate of the pre-1750 extent of each community. This spatial layer and estimate information was based on forest ecosystem mapping, modelling and estimations conducted for the Comprehensive Regional Assessment (NPWS 1999a). Subsequent to the Assessment process, the forest ecosystem layer was integrated with aerial photograph coverage to produce a new vegetation map for the Region. This represented a substantial improvement over the original forest ecosystem layer as it standardised nomenclature, incorporated new mapping, and improved the spatial rigour of forest ecosystem distribution (ELA 2005). This vegetation layer was further refined to include the most recent information on the location of timber plantations. Broad vegetation formations are shown in Figure 10 of the main report. 
The current vegetation condition map was derived using the following:
•	For the majority of sclerophyll forests, growth stage mapping conducted during the Comprehensive Regional Assessment (NPWS 1999b) was used as a surrogate for vegetation condition. This was updated with information on the location of recent timber harvesting operations (where available) and plantation establishment. While there is likely to have been changes to the growth stage condition of some areas due to regrowth, logging, burning, clearing and other landuse changes, it is the best available regional assessment of forest condition. 
•	For non-sclerophyllous rainforest communities, a combination of logging and fire history, tenure, slope and soil fertility were used to estimate current condition. 
•	For all other areas, a combination of tenure, slope and soil fertility were used to infer condition. 
•	For all areas, where spatial data were available, the map was revised to reflect vegetation condition due to impacts by Bell Miner associated dieback, grazing and weeds.
For each class of vegetation condition, a relative score was assigned based on the above factors with variations within condition classes occurring due to differences in the degree of disturbance. The maximum and minimum relative condition scores and areal extent for each condition class are provided in Table 1. The broad current vegetation condition classes of the Region are shown in Figure 1 below.
Table 1	Current condition class scores and areal extent
Vegetation condition class	Broad condition class	Min	Max	Area (Ha)	
Candidate old growth	Old growth forest	78	95	983 619	
Disturbed old growth	Old growth forest	68	85	526 945	
Mature forest	Mature forest	58	75	150 674	
Disturbed mature forest	Mature forest	47	65	377 585	
Young forest	Young forest	37	55	262 572	
Recently disturbed	Young forest	28	45	186 500	
Rainforest - national park (NP)	National park	73	90	67 626	
Rainforest - NP & historic fire	National park	70	89	1 413	
Rainforest - NP & old fire	National park	63	84	6 598	
Rainforest - NP & recent fire	National park	58	75	16 174	
Rainforest - historic logging	Private land vegetated	68	90	67 880	
Rainforest - historic logging & fire	Private land vegetated	65	87	2 835	
Rainforest - historic logging & old fire	Private land vegetated	58	84	5 610	
Rainforest - historic logging & recent fire	Private land vegetated	50	75	13 645	
Rainforest - old logging	Private land vegetated	58	80	62 640	
Rainforest - old logging & historic fire	Private land vegetated	60	79	3 548	
Rainforest - old logging & fire	Private land vegetated	50	74	6 854	
Rainforest - old logging & recent fire	Private land vegetated	43	65	10 676	
Rainforest - recent logging & historic fire	Private land vegetated	67	69	29	
Rainforest - recent logging	Private land vegetated	58	69	4 747	
Rainforest - recent logging & old fire	Private land vegetated	45	64	718	
Rainforest - recent logging & fire	Private land vegetated	45	55	787	
Rainforest - low fertility public	Public land vegetated	48	90	7 434	
Rainforest - low fertility private	Private land vegetated	30	90	34 030	
Rainforest - mod fertility public	Public land vegetated	38	80	5 203	
Rainforest - mod fertility private	Private land vegetated	20	85	40 923	
Rainforest - high fertility public	Public land vegetated	30	65	610	
Rainforest - high fertility private	Private land vegetated	10	65	5 767	
Rainforest - high fertility private & old fire	Private land vegetated	20	35	68	
Low fertility private	Private land vegetated	50	90	22 561	
Low fertility other public	Public land vegetated	58	90	3 057	
Mod fertility private	Private land vegetated	35	85	142 347	
Mod fertility other public	Public land vegetated	45	80	10 715	
High fertility private	Public land vegetated	25	65	133 662	
High fertility other public	Public land vegetated	35	65	14 592	
Old logging	Private land vegetated	60	80	4 198	
Recent logging	Private land vegetated	59	70	1 707	
National parks	National park	75	90	66 671	
Hardwood plantations	Plantation	15	30	58 697	
Softwood plantations	Plantation	17	20	22 399	
Major exotics	Introduced exotics	16	40	13 416	
Camphor laurel	Introduced exotics	28	30	2 367	
Cleared	Cleared	5	5	1 638 310	

Figure 1	Broad vegetation condition classes

The Tool requires that threats to biodiversity be represented spatially across the Region. However, the complexity of some threats, such as inappropriate fire frequencies and weeds, meant that not all were able to be mapped. The threats that were able to be mapped for this Region were clearing, grazing, infrastructure and logging. For each of these broad threats, a number of classes were mapped to provide finer detail or definition of each threat type. The datasets used to derive these layers are listed in Table 2. 
Table 2	Datasets used to derive threat layers
Threat layer	No. of classes (examples)	Datasets used in derivation	
Clearing	12 
(e.g. urban, rural residential, rural)	Tenure
Local environment plan zones
Agricultural land capability	
Grazing	9 
(e.g. very high, medium, very low threat)	Tenure
Slope and fertility (e.g. flatter more fertile areas more likely to be grazed)	
Infrastructure	26 
(e.g. powerlines, highway)	Tenure
Wilderness – declared or identified
Proximity to urban areas, roads, railways, powerlines, recreation and community facilities	
Logging	20 
(e.g. private/public forest, native forest, timber plantation)	Exclusion zones in Forests NSW’s Integrated Forestry Operations Approval
Exclusion zones in the Private Native Forestry Code of Practice
Slope
Commercial forest types
Plantations 	
For each threat class, the relative impact on biodiversity and the length of time before that impact would be fully realised were estimated. This provided an estimate of the consequence of the threat and the probability of its occurrence on an annual basis. These inputs provided the necessary requirements for modelling changes in vegetation condition based on the interactions between regeneration and mapped threats (Drielsma & Ferrier 2006). The consequence and probability rankings for the classes in each of the four threat layers are provided in Tables 3 to 6.  The broad threat classes for the threat layers used in the Biodiversity Forecasting Tool threats are shown in Figures 2 to 5.
Table 3	Broad threat classes for clearing threat
Threat class	Broad threat class	Consequence	Probability	Area (ha)	
Urban/development	Urban development	Severe	Very High	11 304	
Urban investigation	Urban development	Severe	High	1 770	
Rural residential	Urban development	Severe	High	12 203	
Rural high productivity	Rural high productivity	Severe	High	70 303	
Rural mod productivity	Rural mod productivity	Severe	Very Low	861 738	
Rural low productivity	Rural low productivity	Severe	Moderate	396 789	
Open space	Open space	Severe	Moderate	1 955	
Environment protection	Environment protection	Severe	Very Low	84 560	
Crown lands	Crown lands	Severe	Minimal	191 658	
State forests	State forests	Severe	Minimal	614 282	
Proposed national parks	National parks	Severe	Very Low	1 395	
National parks	National parks	Severe	Minimal	1 102 142	
Cleared	Cleared	Severe	Very High	1 638 310	

Table 4	Broad threat classes for grazing threat
Threat class	Broad threat class	Consequence	Probability	Area (ha)	
Very high grazing threat	Very high grazing threat	Moderate	High	91 935	
High grazing threat	High grazing threat	Moderate	High	313 945	
Mod-high grazing threat	Mod-high grazing threat	Moderate	Mod - high	293 371	
Moderate grazing threat	Moderate grazing threat	Moderate	Moderate	326 733	
Mod-low grazing threat	Mod-low grazing threat	Moderate	Very Low	346 872	
Low grazing threat	Low grazing threat	Moderate	Very Low	366 207	
Very low grazing threat	Very low grazing threat	Moderate	Minimal	180 534	
State forests no grazing	State forests no grazing	Moderate	Minimal	336 787	
National parks	National parks	Moderate	Minimal	1 093 715	
Cleared	Cleared	Severe	Very High	1 638 310	
Table 5	Broad threat classes for infrastructure threat
Threat class	Broad threat class	Consequence	Probability	Area (Ha)	
Urban	Urban	Moderate	High	25 208	
Urban	Urban	Moderate	High	2 995	
Urban	Urban	Moderate	High	19 860	
Powerline	Powerline	Low	High	93 683	
Railway	Railway	Low	High	2 592	
Highway	Highway	Low	High	30 247	
Road	Road	Low	High	114 876	
Vehicle track	Road	Very Low	High	259 766	
Building	Facility	Low	High	1 450	
Camping area	Facility	Low	High	2 095	
Day use area	Facility	Low	High	294	
Helibase	Facility	Low	High	944	
Lookout	Facility	Low	High	143	
Tower	Facility	Low	High	1 937	
Camping area informal	Facility	Very Low	High	6	
Hang glider launch	Facility	Very Low	High	31	
Walking track	Facility	Very Low	High	1 384	
Private property	Private property	Minimal	Moderate	1 115 588	
Private conservation	Private property	Minimal	Minimal	17 553	
Commonwealth lands	Crown lands	Minimal	Moderate	1 556	
Crown lands	Crown lands	Minimal	Moderate	107 337	
State forests	State forests	Minimal	Minimal	412 833	
National parks	National parks	Minimal	Minimal	304 425	
Declared wilderness	Wilderness	Minimal	Minimal	478 968	
Identified wilderness	Wilderness	Minimal	Minimal	247 470	
Nominated wilderness	Wilderness	Minimal	Minimal	106 858	
Cleared	Cleared	Severe	Very High	1 638 310	

Table 6	
Broad threat classes for logging threat
Threat class	Broad threat class	Consequence	Probability	Area (Ha)	
Private softwood plantation	Softwood plantation	Very high	Mod - high	7 723	
Public softwood plantation	Softwood plantation	Very high	Mod - high	15 766	
Private hardwood plantation	Hardwood plantation	Very high	Mod - high	15 164	
Public hardwood plantation	Hardwood plantation	Very high	Mod - high	32 530	
Private commercial forest	Private commercial forest	Moderate	Moderate	831 551	
Private commercial forest - mod steep	Private commercial forest	Moderate	Moderate	89 823	
Private commercial forest - steep	Private commercial forest	Moderate	Low	49 007	
Public commercial forest	Public commercial forest	Moderate	Moderate	259 334	
Public commercial forest - mod steep	Public commercial forest	Moderate	Moderate	31 570	
Public commercial forest  - steep	Public commercial forest	Moderate	Low	6 885	
Private non-commercial forest	Private non-commercial	Moderate	Moderate	125 604	
Private non-commercial forest - mod steep	Private non-commercial	Moderate	Low	16 704	
Private non-commercial forest - steep	Private non-commercial	Moderate	Low	3 368	
Public non-commercial forest	Public non-commercial	Moderate	Moderate	3 424	
Public non-commercial forest - mod steep	Public non-commercial	Moderate	Low	125	
Public non-commercial forest - steep	Public non-commercial	Moderate	Low	268	
Public exclusion zone	Public exclusion zone	Moderate	Minimal	254 265	
Private exclusion zone	Private exclusion zone	Moderate	Very Low	513 280	
National parks	National parks	Moderate	Minimal	1 093 715	
Cleared	Cleared	Severe	Very High	1 638 310	

Figure 2	Broad clearing threat classes

Figure 3	Broad grazing threat classes

Figure 4	Broad infrastructure classes

Figure 5	Broad logging threat classes

1.2	
Data outputs
The primary outputs of the Tool are spatial layers which were used to map ‘Conserve’ and ‘Repair’ areas. Figure 6 provides a diagrammatic explanation of the ‘Conserve’ and ‘Repair’ outputs for one demonstration grid cell under a specific example scenario. It is not the actual function that applies to each grid cell.

Future condition with threats
With threats

Current Condition
condition

Time (years)

Present

15 years

Pristine condition

Cleared

Future condition without threats

 CONSERVE

REPAIR

Figure 6	Diagrammatic representation of BFT ‘Conserve’ and ‘Repair’ outputs
Note the shape of the line shown in Figure 6 varies for every grid cell, depending upon the current condition and the expected threats. The aggregation of these Conserve and Repair measures across the Region form the basis (once the consequences to spatial configuration and representation of vegetation communities is calculated) for estimating the priorities for conserving and repairing vegetation. Figure 6 demonstrates how the Tool calculates the future condition for each grid cell of vegetation over a 15-year time frame for two management strategies:
1.	Conservation: where no threats operate at that grid cell (the blue line).
2.	Regeneration: where the predicted threats are operating at the expected probability and consequence (orange line).
The ‘Conserve’ value is the difference between a grid cell’s predicted future condition if threats are not controlled, and future condition of that grid cell if it was cleared (i.e. at the minimum condition). So grid cells with a higher Conserve value are those where you would lose more biodiversity if that area was cleared, even after all threats had been operating in that area for 15 years. Even after threats had been operating, the condition of that grid cell is relatively higher than others—thus it is more important to biodiversity. That is because in these areas, the predicted future condition of these areas is greater than the predicted future condition in other, lower value Conserve areas. 
Those grid cells with higher ‘Conserve’ values are those that, if they were cleared, would have the greatest adverse impact on the Region’s biodiversity. They generally represent areas of high conservation value vegetation in relatively good condition. The conservation of biodiversity in these areas is important for the overall biodiversity of the Region. In particular, future threats which may not have been predicted (or included) in the Biodiversity Forecasting Tool should be circumvented through incentives and investment to ensure their long-term value to biodiversity persistence in the Region.
The Repair value is the difference between a grid cell’s predicted future condition where the threats have operated, and the grid cell’s future condition where these threats have not operated. Those grid cells with higher ‘Repair’ values are those with greater predicted threats. They generally represent poorly conserved or over-cleared vegetation communities in lower condition. If the threats predicted to occur in the higher value ‘Repair’ cells were circumvented, this would prevent the greatest loss of biodiversity in the Region. Preventing the future degradation of these areas from predicted threats and restoring or improving their condition will make a significant contribution to the overall biodiversity of the Region.

References
DEC – see Department of Environment and Conservation. 
Department of Environment and Conservation 2006, Decision Support Tools for Biodiversity Conservation: Biodiversity Forecasting Toolkit, report prepared for the Department of Planning, DEC, Armidale. Available at: http://home.iprimus.com.au/tombry/BiodiversityForecasting/11BiodiversityFT.pdf
Drielsma, M, & Ferrier, S 2006, ‘Landscape Scenario Modelling of Vegetation Condition’, Ecological Management and Restoration, vol. 7, pp. S45-S52. 
Drielsma, M, Ferrier, S & Manion, G 2007, ‘A Raster-based Technique for Analysing Habitat Configuration: The Cost-benefit Approach’, Ecological Modelling, vol. 202, pp. 324-332. 
Eco Logical Australia 2005, ‘A Vegetation Map for the Northern Rivers Catchment Management Authority to Support the Application of the BFT’, Project No. 99-01, report prepared for the Northern Rivers Catchment Management Authority, Eco Logical Australia, Sutherland, NSW.
ELA – see Eco Logical Australia.
National Parks and Wildlife Service 1999a, Forest Ecosystem Classification and Mapping for the Upper and Lower North East CRA Regions, Project Undertaken for the Joint Commonwealth NSW Regional Forest Agreement Steering Committee, Project No. NA35/EH, Northern Zone NPWS, Hurstville, NSW. Available at: http://www.daffa.gov.au/__data/assets/word_doc/0020/50717/nsw_ne_na35eh.doc
National Parks and Wildlife Service 1999b, Old-Growth Forest Related Projects - UNE / LNE CRA Regions, Project Undertaken as Part of the NSW Comprehensive Regional Assessments, Project No. NA 28/EH, National Parks and Wildlife Service, Hurstville, NSW. Available at: http://www.daffa.gov.au/rfa/regions/nsw-northeast/environment-reports/old-growth
Turbill, J & Steed A 2006, ‘Landscape Prioritisation: Maximising Biodiversity Outcomes Through Targeted Investment’, Proceedings of Vegetation Futures, Greening Australia, Albury. Available at: http://ga.yourasp.com.au/vegfutures/pages/images/Workshop%201_Turbill.pdf