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The Forest Productivity Optimisation System – A decision support

1. Fig 22 Pre dawn water potential over the duration of the experiment Error bars show 1 SEM 0 T 0 5 O D 1 c U pu 9 15 9 2 3 c z EW E globulus o i E E smithii amp 3 5 CH e e ei N N N N e en e e e e e e e e e O c a 5 o 3 c o B lt i O 5 Ea i O B Ea Date 20 Fig 23 Minimum daily water potential measured over the duration of the experiment Error bars show 1 SEM F globulus ef E smithii Minimum daily water potential MPa O O a N N N N co m A a ei ei a ei E c a E O c A E c 5 O E CS O E O E E Date FPOS interface development The FPOS interface was successfully developed and released The user manual see Appendix 2 describes the system its assumptions and flow of logic so this is not repeated here 21 Discussion CABALA model development and species parameterisation Species specific parameter sets for the CABALA model have been developed from the daily weather conditions prevailing during the growth of plantations This has some implications for how well CABALA will predict growth using long term average climatic data Overall with P radiata and E globulus there is no consistent bias in the predictions when using monthly data however predictions are not as accurate This may become prove to be a more serious issue for the E smithii parameter set where
2. 41 75 41 6 41 7 41 4 41 5 41 4 41 35 41 1 40 95 41 05 41 1 42 4 42 5 41 85 41 55 41 4 41 3 41 2 41 35 41 15 41 05 42 45 42 1 41 9 41 5 41 4 NRM Region South West South Coast South West South West South Coast South West South West South Coast South West South West South West South West South North North North North West North West North West North West North North North North North North West North North North North North North West North West North West North West North West North West South South North North North North North West North West North West North West South North South North North 31 Worst Scenario miroc3_hires miroc3 medres miroc3 hires miroc3 hires miroc3 medres miroc3 hires miroc3 hires miroc3 medres miroc3 hires miroc3 hires miroc3 hires miroc3 hires CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 Most Likely Scenario miroc3 medres CSIRO3 5 miroc3 medres miroc3 medres CSIRO3 5 miroc3 medres miroc3 medres CSIRO3 5 miroc3 medres miroc3 medres miroc3 medres m
3. Carpenters Site Summary Site Details Observed productivity EH Add edit economic scenarios Example site New site 016 Test sawlog radiate Test sawlog regim Update button rameter editor Create new scenario Delete button io by selecting it Ea the Came Delete Create new Cancel _ Cancel Select Example scenario Scenario name Example scenario Establishment costs Seedlings seedling 0 25 Planting seedling 0 072 Starter fertilizer 0096 seedling Soil preparation a ha 0 04 Soil preparation b ha 42 Establishment bos Soil preparation cost Vs Stocking 90 co EIC Soil prep cost ha aNBESBEc Sf INE 400 600 600 1000 1200 Stocking stemsiha Soil preparation cost in relation to stocking rate Parameter a is the slope of the relationship and parameter b is the intercept iQ Management costs Management cost Harvest and Transportation costs Establishment costs ha Plantation roading green 4 Ongoing annual costs 300 tonne ha Transport green tonne 0 09 Additional Annual costs ha ms Year 0 Year 0 Year 0 a Lan Gelee 5 1 2 3 3 Harvesting cost a 16 Harvest and A 0 0 Wetz 0 tonne ha transportation MERI RES E Harvesting cost b 2400 costs mit cu UL tonne ha Year 0 Year 0 Year 0 z
4. Date 13 At a finer timescale the dendrometers showed the pattern of diameter growth was highly responsive to rainfall Fig 12 Both species grew strongly from April through to December January and tended to plateau or even show a decrease in stem diameter over the summer months typically when rainfall was below 20 mm month There was no apparent difference between the species in short term diameter response to rainfall although the E smithii trees had a higher increment than the E globulus trees that we measured This difference in relative ranking was not reflected in the overall stand level diameter increment Fig 11b which was similar for both species 29 9 mm and 30 6 mm for E globulus and E smithii respectively for the period July 2010 June 2012 Tree growth fine time scale Fig 12 Monthly tree diameter and rainfall derived from SILO Note that rainfall bars represent the rainfall in the month prior to each of the diameter points Error bars represent 1 standard error of the mean AS 160 rainfall E 40 z E globulus diameter 140 35 ll E Smithii diameter CT 120 E 9 30 S D 100 25 i so E ta e 20 60 s 15 c O 2 40 bp 10 g E 5 20 a O 0 0 Aug Oct Dec Feb Apr Jun Aug Oct Dec Feb Apr Jun Aug Oct Dec 10 10 10 11 11 11 11 11 11 12 12 12 12 12 12 Date The stems of both species exhibited significant diurnal shrinkage Fig 13 which was least during winter typica
5. la Forest amp Wood mu a ew Products Austral Knowledge for a sustainable Australia 7 LLI O D O 7 LLI 14 D z O O D C Z a O D Wel D O 2 co Si O lt F gt O L LL O o lt ceo O gt O O O 2 CO CO CN co N O O pes O CO LL O O N Co N O O co mm O N CO e The Forest Productivity Optimisation System A decision support tool for enhancing the management of planted forests in southern Australia under changing climate Prepared for Forest amp Wood Products Australia by Daniel Mendham Jody Bruce Kimberley Opie Gary Ogden NO p B d roducts Australia Knowledge for a sustainable Australia Publication The Forest Productivity Optimisation System A decision support tool for enhancing the management of planted forests in southern Australia under changing climate Project No PNC168 0910 This work is supported by funding provided to FWPA by the Department of Agriculture Fisheries and Forestry DAFF 2013 Forest amp Wood Products Australia Limited All rights reserved Whilst all care has been taken to ensure the accuracy of the information contained in this publication Forest and Wood Products Australia Limited and all persons associated with them FWPA as well as any other contributors make no representations
6. 2 and Eastern Victoria Fig 3 are based on historical rainfall and evaporation with each zone representing a 100 mm rainfall band and a 200 mm evaporation band while the zones in Tasmania Fig 4 are based on variation in historical rainfall and altitude 33 Fig 1 FPOS Climatic zones in south western Australia Legend Major towns 550 mm rainfall 1500 mm evaporation IE 550 mm rainfall 1300 mm evaporation KX 650 mm rainfall 1500 mm evaporation VZ 650 mm rainfall 1300 mm evaporation 650 mm rainfall 1100 mm evaporation KX 750 mm rainfall 1500 mm evaporation V 7 750 mm rainfall 1300 mm evaporation 750 mm rainfall 1100 mm evaporation BA 850 mm rainfall 1500 mm evaporation TO 850 mm rainfall 1300 mm evaporation m 850 mm rainfall 1100 mm evaporation KX 950 mm rainfall 1500 mm evaporation 71 950 mm rainfall 1300 mm evaporation 950 mm rainfall 1100 mm evaporation BEN 1050 mm rainfall 1500 mm evaporation UJ 1050 mm rainfall 1300 mm evaporation EN 1050 mm rainfall 1100 mm evaporation P 1150 mm rainfall 1500 mm evaporation EZA 1150 mm rainfall 1300 mm evaporation I 1150 mm rainfall 1100 mm evaporation IE 1250 mm rainfall 1100 mm evaporation el LES F Legend Ballarat Major towns 550 mm rainfall 1300 mm evaporation ZA 550 mm rainfall 1100 mm evaporation KX 650 mm rainfall 1300 mm evaporation 771 650 mm rainfall 1100 mm evaporation 650 mm rainfall 900 mm evaporation E 750
7. SCS Ta LATA e EE 44 TEE 46 D BILES a mmmmmm mmvmrmm mmmmmmmmmmrmrmmmmmmmmmmmrmmmmmmmmmmmmHHHHmrHHrrrmmicmrme 47 EH 48 SR erent atte weet A A atten vate eet neues 49 Ebbe 50 SDOCIe S COMPARSO cit e Ee Ee E 52 CINTO THO EE 52 Muste OU EE 53 ed 53 EELER 54 SeBsTtrVTEy A HAN SSL penas ta ea P ee tete Dent en Et AURIA 55 iere 56 FPOS EE eebe 57 IRCTCICNCOS ege 58 Introduction Plantation managers need to make management decisions based on information from a range of sources New information arising from research can sometimes be difficult to assimilate into an overall understanding of its importance to productivity and profitability especially in conditions of uncertainty surrounding new management and new soil types or changing climate and water availability This project developed the Forest Productivity Optimisation System tool to help managers integrate current knowledge with outcomes of new research The FPOS tool also allows managers to explore the potential for changing species to adapt to more marginal areas of the estate and or under changing climate As well as the 3 core species used in most of the estate of southern Australia E nitens E globulus and P radiata E smithii and P pinaster are now included in the system as the two species that show the most promise for adaptation to drier and hotter conditions to demonstrate their potential at different site types or under changing climate The FPOS DS
8. The combination of all possible alternative scenarios 49 Fig 15 Water use efficiency tab highlighting 1 the current and comparison scenarios 2 the button to run CABALA for missing data 3 and 4 the water use efficiency output graphs gt Site Outputs gt Water Use Welcome daniel 32 FPos Nutrients Economics Water Use Current sites Nitrogen Species Climate Model Carpenters a New site 016 radiata GT Test sawlog radiate Test sawlog regime Current and Comparison scenarios i Run CABALA for missing data Stand level water use efficiency Tree level water use efficiency m wood ML water GPP ML transpired Example site Rainfall 1100 1200mm Evaporation 1000 1200mm Above average rainfall deep sand 4 m depth E globulus 900 stems ha Age 10 years Predicted final volume 292 m2 ha Predicted final LAI chu ied Predicted WUE GPP ML transpired NPV 3860 22 Predicted WUE m3 ML sp IRR NA 300 250 amp 200 150 o gt 100 Nitrogen The nitrogen tab is intended to help users make decisions about nitrogen fertilizer management This module is relatively weak and not intended to replace more complex tools such as NPOpt for P radiata in the Green Triangle rather it is intended to give users a feel for the economics of N fertilizer addition The first step is to characterise the shape of the response curve Item 3 Fig 16 For E globulus this may be achieved by adjust
9. globulus cesses 4 EEX DENCH Lal TEE 5 IC AS TV s nde NUS uenis mios un LE Ant he S 6 EPOS Interface dev oi a FL immemmmmmmmmmrmmmmmmmmmmrmmmmmmmmmmmmmmrmmmmmmmmmrmkvmmmmmmmmmrmmmiH 6 Heer 7 CABALA model development and parameterisation for different species 7 Climate model selection and application tout Us Oige idea TA S 10 Detailed comparative studies into E smithii and E globulus in response to environment EEE EEE 12 PPOS 1nterrace de ve EE dE ennemie meme 21 Ree EE 22 CABALA model development and species parameterisation ccccccceceeeesseeeeeceeeeeeeees 22 Climate model selection and application UV 22 Comparative physiology of E smithii and E globulus s seeeeesseeeeeeeee 23 Conchi TON rare ne EE nie ne On on ieee 24 IRC OORT nda ons EE 25 EE eegene 26 PECK MO WAC CCM CIES en nine mine ade Acada 26 Researcher S Dise KIO EE 28 Appendix 1 FPOS Climatic Zones and future climate scenarios The latitude and longitude is the location of a representative SILO cell within the climate zones identified 30 Appendix 2 TF POS users T anudlc EE 33 ele ei O WEE 33 EE 33 CHa ZONES ee RE nel der ar hc SES aoe cfe E eui 33 WHEE POS MST EE EE Ee 36 LOS E 36 THOM CP TT 37 D LATE Src shes esc grafts a aan ce whe eval da cia ae waa ge adi caine ata 38 el Rn EE 38 Site DE EE 39 Observed PrOdUcttydl td EE 42 Add edit economic scenarios aD EE 42 TEE 44
10. 1 8 1 18 9 52 7 17 3 November 22 4 10 0 22 0 37 9 11 9 December 25 6 11 8 25 0 18 7 7 8 The study period started in 2010 when the 2 rotation plantation was 3 years old Fig 3 shows the study period in relation to the annual rainfall and establishment of the first and second rotation plantations at the Shuttleworth site Fig 3 Annual rainfall for the 30 years from 1983 2012 at the Shuttleworth site with the study period highlighted in green The planting dates of the first and second rotations are highlighted with arrows Rainfall mm y LP O O 400 Ms Study period 300 Annual rainfall 200 1R establishment 100 2R establishment 0 o NN D do A D Sy ES Gi ue PF LP Y ke Experimental plots The Shuttleworth site had been planted with 2 wide belts about 60 m wide and 700 m long of E smithii amongst a large E globulus 2 rotation plantation Fig 4 The belts had been planted as part of an operational trial into the potential deployment of E smithii on drought prone sites The lower southern most belt was not used because it was close to the valley floor and may have been affected by salinity or presence of a hard pan Measurement plots 20 x 20 m were established in pairs 20 m from the edge of the E smithii E globulus interface Fig 4 Oblique image of the Shuttleworth plantation showing locations of the E smithii belts and the experimental plots Surrounding plantation is E gl
11. 42 2 42 25 42 1 42 1 41 45 42 15 NRM Region North South North North North North North West South South North South South South South North South 32 Worst Scenario CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 CSIRO3 5 Most Likely Scenario miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires Best Scenario bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 Appendix 2 FPOS users manual Introduction The FPOS system is designed to deliver research outputs in a user friendly format that is accessible to managers and growers of plantations in southern Australia It allows the user to easily perform what if scenarios around management site or climate climate change FPOS Structure FPOS is a web based system that consists of the following elements 1 A live version of tree size distribution CABALA configured to run with a large but limited number of combinations of inputs See Table 1 2 A database of pre run CABALA outputs Initially this database is small but will grow as users request different co
12. CABALA is embedded into the system and is run on request of the user The interface integrates all of the outputs from the other sections of this project including the climate futures CABALA development and parameterisation and comparative physiology of E globulus and E smithii into a format that can be easily accessed by plantation managers and growers The decision to embed a live version of CABALA was taken about mid way through the project when it became apparent that the number of possible combinations of input variables desired by the steering committee members was far more than was possible to run prior to release This change means that there is a delay in running scenarios that have not been previously run with each scenario usually taking around minute This is done on the server so the run time is also dependent on the current server workload Results CABALA model development and parameterisation for different species For all plots used in developing the parameterisation sets for CABALA detailed growth silvicultural and soils data were collected For each species they covered the range of fertility rainfall and temperature ranges within the estates as far as was feasible The growth and silvicultural data were provided by industry partners and included planting dates and stems per ha at planting detailed thinning information sph and volumes removed fertiliser events and any other potential impacts on growth such as nutrient de
13. E g 60 150 Ki y 0 38x 45 1 d y 0 58x 27 3 R2 0 77 e AO R 0 74 100 20 0 50 100 150 0 200 400 600 Observed Volume m ha Eucalyptus smithii Parameterisation of E smithii is still ongoing There are some limitations with the calibration dataset all sites are young 3 5 years old and all are relatively fertile So we are uncertain as to how the model will perform on older stands and lower fertility sites The model 1s generally over predicting Fig 9 the one site that 1s under predicted is the oldest site At present there is little differentiation between the productivity of the shallow and deep sites in observed volume and CABALA is only just starting to predict water stress as the soil profiles dry out Additional data as the stands more fully occupy the site will help improve the parameter set So care must be taken when using the model for predictions above age 5 Fig 9 CABALA validation using data from 12 E smithii plots from Western Australia Stands are at time of measurement were between 3 and 5 years of age and are all on reasonably fertile sites 160 140 GA O N O O l Predicted Volume m ha O0 60 ee 3 y 0 58x 27 3 40 R 0 74 20 4 O zi 0 50 100 150 Observed Volume m ha Preliminary parameter sets are also available within FPOS for P pinaster and these will be refined into the future Climate model selection and application At present the Clima
14. all the validation plots were planted at about the same time so the sites have had the same period of historical weather For P radiata E globulus and E nitens the plots span a much larger weather span so there is less of a bias A second parameter will need to be built for E Smithii using long term average monthly data There are also some unknowns predicting growth into future climates under elevated CO We presume that for the medium term at least to 2030 the range of conditions of temperature and rainfall are likely to be encompassed within the historical data record If plantation performance can be reliably simulated for historical situations across the environmental domain in which the species are planted we can be more confident of future predictions The inclusion of the Farquhar model of photosynthesis appears to have improved CABALA s performance under elevated CO with nutrient and water limited sites showing a much smaller response than non limited sites as shown by Norby et al 2010 Climate model selection and application There is much uncertainty around future climate projections While there 1s agreement that greenhouse gases in the atmosphere will increase we do not know how quickly or to what level emissions will increase and the extent to which global temperatures will respond to elevated greenhouse gases There is also uncertainty about how GCM results will reflect regional or local climate As the models become m
15. and it allows the user to explore different rainfall variation that may occur within a climate prediction and is based on running 10 year averages for the 30 year period of the climate model either 1975 2005 for the existing model or 2015 2045 for the future scenarios The average monthly climate is used for each climatic zone and only rainfall is varied as follows e Well below average is the mean monthly rainfall less 2 standard deviations e Below average is the mean monthly rainfall less standard deviation e Average is the mean monthly rainfall e Above average is the mean monthly rainfall plus 1 standard deviation e Well above average is the mean monthly rainfall plus 2 standard deviations Climate model This menu has 4 options no change based on historical data from 1975 2005 best case scenario based on the climate model with the highest rainfall prediction for the future worst case scenario based on the climate model with the lowest rainfall prediction for the future and the most likely scenario which is based on the model that predicts the median rainfall among the group of climate models used in the study These models are different for each region see section on climate models above This input is required by CABALA to produce any output for a scenario Species This menu allows the user to choose from the 5 species available in FPOS E globulus E nitens E smithii P pinaster P radiata This input 1s required
16. and shows a graph of the predicted macronutrient export Item 3 Fig 12 in kg ha and the predicted micronutrient export Item 46 4 Fig 12 in g ha The export data for Eucalyptus species are based on our own studies with E globulus in Western Australia whilst the export data for Pinus species are based on the study of Hopman and Elms 2009 Economics The economics tab allows the user to look in detail at the itemised costs and returns of the chosen scenario This tab allows the user to compare the effect of different economic models and or different rotation lengths through 2 pull down menus Item 1 Fig 13 There is also a link to edit the economic model if the users want to The graphs on this tab Item 2 Fig 13 show the potential net present values and internal rates of return that the model predicts for the full range of potential harvest ages This allows the user to explore the optimum rotation length The table below the graphs Item 3 Fig 13 has a detailed listing of the costs and returns associated with the harvest age that is chosen in the pull down menu in Item 1 Fig 13 47 Fig 13 The Economics tab highlighting the 1 Alternative economic scenario options 2 estimated NPV and IRR and 3 a detailed break down of costs and returns gt Site Outputs gt Economics Welcome daniel y AE on lt gt EZ 5 ty vi g M jt A n a w i ee 7 e 0 42 EN Aas FPOS Home Site Inputs Site Outputs Mul
17. are consistently over predicted The reasons for unexpected tree mortality are often not evident in the available data and consequently difficult to represent in model inputs Fig 6 CABALA validation using data from 40 P radiata plots from Tasmania Victoria and South Australia Stands are at time of measurement were between 12 and 40 years of age and cover a range of silvicultural treatments including thinning and fertilisation 800 700 P On O O 0 P e B 7 UT O O I O O 2 Predicted Volume m3 ha e K y 0 84x 93 1 R2 0 78 N O O 100 0 200 400 600 800 Observed Volume m ha For P radiata there are still some issues of over estimation of productivity in sites where temperatures are high and evaporation greatly exceeds precipitation Work is being done to improve the predictions under these conditions For the Tasmanian sites there are also some under predictions where terrain is complicated and the SILO weather is too coarse to capture site specific conditions Eucalyptus nitens Parameterisation of E nitens is still ongoing There is a clear bias in the current parameter set with low productivity sites being over predicted and high productivity sites generally under predicted Fig 7 Fig 8 We are still working to understand why the observed growth is so low on some sites sites are weed free A number of these plots were 4 5 years old at measurement and fu
18. more about the potential for E smithii as an alternative to E globulus in hotter and drier conditions we established an experiment in an existing 2 rotation plantation in the Shuttleworth plantation managed by WA Plantation Resources which had E smithii and E globulus growing adjacent to each other We measured the growth and physiological responses of the 2 species to differing environmental stimuli over a period of nearly 3 years The location of the Shuttleworth plantation is shown in Fig 2 and it has an average annual rainfall of 659 mm and evaporation of 1108 mm 30 year average to 2012 derived from the SILO data drill service Jeffrey et al 2001 Average monthly climatic data for the Shuttleworth site is shown in Table 1 Fig 2 map showing the location of the Shuttleworth plantation Bunbury Manjimup Shuttleworth Legend Major towns O Experimental site Rainfall isohyets Table 1 Selected average monthly climate data at the Shuttleworth site 30 years to 2012 derived from the SILO data drill service Jeffrey et al 2001 Month Average daily temp C Radiation Rainfall Rain days Maximum Minimum MJ m mm January 27 6 13 2 25 1 16 8 6 3 February 27 5 13 7 22 2 18 8 6 0 March 25 4 12 7 17 8 20 6 8 4 April 22 1 10 9 13 0 37 4 11 7 May 18 4 8 9 9 4 85 3 17 9 June 15 8 7 3 8 1 93 2 20 7 July 14 9 6 5 8 7 109 5 22 5 August 15 3 6 5 11 5 95 0 22 0 September 17 0 7 2 14 9 75 2 19 7 October 19
19. scenario If the maximum fertility is chosen then there will be no predicted productivity loss due to lower fertility e The development of height diameter and volume are also shown in graphical form Item 3 Fig 14 and in tabular form Item 4 Fig 14 48 Fig 14 Productivity tab with 1 CAI MAI curves highlighted 2 predicted losses due to lower fertility 3 height diameter and volume curves and 4 tabulated outputs highlighted Site Outputs Productivity Welcome daniel 32 FPos Current sites trients Below you may observe the nutrient and biomass removed from your site based on site Infomation is derived from CABALA outputs Test sawlog radiate Test sawlog regime Predicted loss due to lower productivity L_MAICA graphs Carpenters Rainfall 1100 1200mm Evaporation 1200 1400mm Average rainfall deep clay loam 8 m depth E globulus 1500 stems ha Age 18 years Predicted final volume 521 2 m ha Predicted final LAI 1 7 m2 m NPV 7041 74 IRR 5 7 Unable to display graph Water Use The water use tab is to allow the user to understand the water use efficiency of a given scenario and to compare this with an alternative scenario Alternative scenarios can include different soil depths soil fertility stocking rate rainfall and or harvest age The alternative scenario can be selected by choosing different options in the comparison scenario pull down menus Item 1 Fig 15
20. the DSS and 4 develop the FPOS system to integrate existing and new knowledge and present it in a form that was readily accessible by industry partners Methodology This project was conducted through 4 main activities as follows e CABALA model development and parameterisation for different species e Climate model selection and application e Detailed comparative studies into E smithii and E globulus in response to environment e FPOS interface development The methodology for each of these is detailed below CABALA model development and parameterisation CABALA Battaglia et al 2004 links the carbon nitrogen and water balances in forests to predict productivity and water use It is specifically targeted to silvicultural decision support and is underpinned by a large body of data describing the physiological responses of trees to both environmental and management factors CABALA operates on a daily time step simultaneously predicting fluxes of carbon water and nitrogen within a forest stand Mass of foliage branch stem bark coarse and fine roots are predicted Carbon and nitrogen pools in the soil and litter layers are updated daily and vary according the balance between additions from residues and atmospheric deposition in the case of nitrogen and losses from decomposition A more detailed description of CABALA is available in Battaglia et al 2004 There are limitations in using CABALA to predict potential growth rates CABAL
21. the expansion period Fig 15 shows the overall relationship whilst Fig 16 shows the lower end of the data which has the more than of the data points 15 days continuous expansion There is no obvious difference between the species in this attribute 15 Fig 15 Relationship between the number of days of continuous stem expansion and the rainfall during that time 60 O c 50 gt y 0 20x 0 400 c R 2 0 92 x 40 OU E 2 30 E lt y 0 17x 0 75 a R 0 84 o 20 2 o oO E globulus 10 e WE or WE 374 1 O E smithii CH M e o BET 0 50 100 150 200 250 Rainfall during expansion period mm Fig 16 Relationship between the number of days of continuous stem expansion and the rainfall during that time limited to periods with 15 or less days of continuous stem expansion this is the bottom end of the data in Fig 15 16 0 13x 1 45 14 P c R 0 70 A O o 12 i o o 10 O O E 949 AC 8 e e e 4 y 0 12x 1 79 D gt eu 99 R 0 70 O 6 WW Wal WW IW g IW Be 9 90 E 4 00 Je 9 E globulus z ego 0e 5 We 2 WEGE Dis 90900 990 O E smithii oO Lie 0 0 10 20 30 40 50 60 70 80 90 100 Rainfall during expansion period mm Soil moisture The soil moisture measurements Fig 17 suggested that both species drew heavily on the soil water available down to 2 25 metres Interestingly the winter of 2011 showed different rechar
22. the use of the FPOS system and use of the system implies acceptance of this disclaimer DISCLAIMER The general information and tools available at this website are for use in assisting tree plantation growers in making decisions about managing their plantations Neither the information nor the tools should be used for any other purpose without prior written consent of CSIRO and FWPA Use of the website is not intended as a basis for users business decisions The information and tools are used entirely at the user s own risk and should not be relied upon without seeking professional advice for specific situations Whilst every care has been taken in compiling the information and developing the tools no assurances or representations are given or made that they are complete accurate reliable free from error or omission or suitable for a user s individual circumstances or purpose CSIRO FWPA the Forestry CRC and the authors make no express or implied warranty or representation of merchantable quality or fitness for purpose of the information and tools and hereby disclaim all liability for the consequences of anything done or omitted to be done by any person in reliance upon the information or tools CSIRO FWPA and the Forestry CRC will not be liable for any loss damage costs or injury including consequential incidental or financial loss arising out of use of this website Every effort 1s made to keep this website running smoothly however no re
23. the user to add upload edit or delete the current site Some of the inputs for each site are essential shown with asterisks for the model to run adequately while others are required for other parts of the system and or for information only The key inputs are as follows Site name is used to identify the site Latitude and Longitude These are optional inputs but if you enter values the system will attempt to identify the appropriate Region and Climatic zone Note that you can override the systems choice if you feel that it has not characterised your region climatic zone appropriately This is probably more important for the regions where climatic zone is based on altitude Tasmania as the altitude grid 1s reasonably coarse Exposed site This check box allows the user to choose whether the site 1s exposed The effects of exposure have not been fully quantified so the system currently deals with exposed sites in Tasmania by changing the climatic zone to increase the altitude by 1 level eg an exposed site at 200 300 m altitude will instead draw its results from a 300 400 m altitude site with the same rainfall In Eastern Victoria the exposed site effect is created by drawing the results from a lower evaporation zone which 1s also linked to altitude The exposed site option is not applicable in WA or the GT This input is optional with non exposed being the default option Rainfall variation This is a required input for CABALA
24. 0 stems ha Age 18 years Predicted final volume 521 2 m ha Predicted final LAI 1 7 m m NPV 7041 74 IRR 5 7 Climate model The climate model tab allows the user to explore the impact of different projected climate models on the predicted productivity and economics 52 Fig 18 Climate model comparison tab with the 1 evaluation parameter selection 2 Run CABALA button and 3 model output highlighted gt Site Outputs gt Climate Model Welcome daniel Site information Nutrients Economics Productivity Water Use Current sites Nitrogen Species Climate Model Carpenters fani Ul i Change evaluation parameter ee mm Fab EN Run CABALA for missing scenarios radiata GT Predicted output Rainfall 600 700mm T Evaporation 1000 1200mm Average rainfall deep clay loam 4 m depth P radiata 1300 stems ha Age 36 years Predicted final volume 355 m ha Predicted final LAI 3 2 m m NPV 2851 31 IRR 6 396 Sas Worst case scenario 4 Unable to display Most likely scenario Multi site Outputs Multi site outputs allow the user to explore the model efficiency and predicted wood flow across their range of sites Model efficiency The model efficiency tab shows a graph of observed vs predicted productivity height and or diameter This is an opportunity for the user to compare how well the system is predicting productivity across their sites that are entere
25. 1 Note that a typical CABALA run takes around minute so if there are 60 missing scenarios it may take around 1 hour to complete depending on server load Once the 55 scenarios are completed and in the output database then they are available for the next time the same query is run or if a different query is run that uses some or all of those outputs Fig 21 Sensitivity analysis tab highlighting 1 and 2 Inputs for comparison sites 1 and 2 3 and 4 button to run CABALA for scenarios that are not yet in the database 5 the evaluation parameter and 6 and 7 the output tables Sensitivity analysis Welcome daniel Curentsies Fun CABAMLA se Factor 1 e Site 2 inputs Carpenters Columns K New site 016 Factor 2 Rows radiata GT Test sawlog regime 4 ae sin OJ Run CABALA Site 2 Results may be incomplete if not all factors sare ds Example site Rainfall 1100 1200mm 6 Evaporation 1000 1200mm Above average rainfall Outputs Site 1 deep sand 4 m depth E globulus 900 stems ha Age 10 years Predicted final volume 292 m2 ha Predicted final LAI 3 2 m m Mapping tool The mapping tool allows users to view the location of their sites and view summaries of the outputs for each site The FPOS climatic zones are also shown so that the most appropriate climatic zone can be chosen The maps are derived from Google Maps so the user can zo
26. 10 11 12 Harvesting cost Vs Productivity 7000 Year Year Year 13 E 14 15 T 6000 Year 0 Year 0 Year a 5000 16 17 18 E 4000 Year Year Year 19 0 20 21 0 E 3000 Year 0 Year 0 Year 0 E 2000 22 23 24 1000 Year 0 Year 0 Year 0 25 26 27 50 100 150 200 250 Year 0 Year 0 Year 0 e Productivity mima 28 29 30 Harvesting cost relationship to productivity Parameter a is the slope omg keng 0 a 0 and parameter b is the intercept of the relationship Year Year Year 0 0 0 34 35 36 Year 0 Year 0 Year 0 ed 37 38 39 Year 0 40 Fertilizer plus application costs Nitrogen tonne 200 elemental N Phosphorus tonne 500 elemental P Weight conversion green 1 tonnes m3 Basic density bone dry 550 kg green tonne Minimum log diameter cm 10 Log value lt 15 cm m3 40 2 Log value 15 20 cm m3 50 Returns Log value 20 25 cm m3 60 Log value 25 30 cm m3 70 Log value 30 35 cm m3 80 _ Log value 35 40 cm m3 90 Log value 40 45 cm m3 100 Log value 45 50 cm m3 110 Log value 50 55 cm m3 120 Log value gt 55 cm m3 130 Sawlog info Inflation rates Inflation rate for costs 5 Cost of thin to waste 5 y operations stem Change in price for 5 Cost of commercial thinning 110 products y operations of clearfall Discount rate for NPV 10 LAW Sawlog regime Pruning 1 Time age in 2 costs years Pruning 1 Cost stem 2
27. A does not account for nutrient limitations other than nitrogen For a site where phosphorus or other nutrients are limiting CABALA will generally overestimate rates of growth There have been recent updates to the model which are listed below more detail can be found in Battaglia 2012 l The Farquhar model of photosynthesis is now incorporated into CABALA and improves the temperature interactions with elevated CO 2 Effects of elevated CO on water use efficiency are now better predicted with the incorporation of the Farquhar photosynthesis model combined with the Ball Berry model already built into CABALA 3 Incorporation of high temperature effects on leaf membranes and photosynthesis While high temperature effects were already integrated into CABALA this did not allow for evaporative cooling which is an important response protecting leaves from death under high temperature conditions This has now been rectified 4 Inclusion of the SPA framework for predicting hydraulic gradients in trees provides the basis for predicting the diurnal course of tree water stress see White et al 2011 for summary information Combined these changes are anticipated to improve model predictions of the effects of elevated CO and climate change more generally on plantation productivity Climate model selection and application Appropriate sampling of uncertainty is a fundamental part of assessing the impacts of future climates on the gro
28. PV 3860 22 IRR NA 51 Species Comparison The species comparison tab allows the user to compare the model outputs for some or all of the 5 species that are currently in the system The evaluation parameter Item 1 Fig 17 allows the user to explore the predicted volume height diameter leaf area index water use efficiency IRR or NPV All 5 of the species can be compared or a subset of the most relevant species can be compared by checking unchecking the individual species Item 2 Fig 17 If the relevant CABALA runs do not exist in the database the user can choose to run CABALA for the missing scenarios by clicking Run CABALA Item 3 Fig 17 Fig 17 Species comparison tab with the 1 evaluation parameter 2 species selection 3 run CABALA button and 4 output graph highlighted gt Site Outputs gt Species Comparison Welcome daniel he gt amp 4 es L L e MP ore St to gt b o gt eer y PERS Ee X DIL ud JJ FPos Site information Nutrients Economics Productivity Water Use Current sites Nitrogen Species ate Model O i Evaluation parameter Example site New site 016 Setect species to plot radiata GT Species to plot Test sawlog radiate 2 Test sawlog regime ER Run CABALA for missing data Carpenters Rainfall 1100 1200mm Evaporation 1200 1400mm Average rainfall deep clay loam 8 m depth E globulus 150
29. Pruning 2 Time age in 3 Inflation and discount rates years Pruning 2 Cost stem 3 Pruning 3 Time age in 4 years Pruning 3 Cost stem 2 Management costs Item 7 Fig 10 which include other area based establishment costs not already accounted for and ongoing annual costs which may include land 43 lease costs management fees etc The fixed annual costs can be entered at the top and any annual costs that vary during the rotation can be entered separately for each year Enter the costs in todays dollar values The user can also enter fertilizer costs here 3 Harvest and transportation costs Item 8 Fig 10 include costs that are based on tonnes of timber harvested roading transportation and loading costs and harvesting cost is on an area basis Harvesting cost can vary with the productivity by adjusting the harvesting cost a slope and b intercept parameters This operates the same way as the establishment costs in that a constant harvesting cost can be set if desired by setting the a parameter to zero 4 Returns Item 9 Fig 10 include the value for different size logs in 5 cm increments from 15 cm to 55 cm the minimum log diameter and the weight conversion and basic density 5 Inflation rates Item 10 Fig 10 can be set individually for costs and prices and the discount rate as used in NPV calculations can be set here too 6 Sawlog information Item 11 Fig 10 allows the user to
30. S has built on the Blue Gum Productivity Optimisation System BPOS version 2 which was developed by the CRC Forestry BPOS v2 0 was designed to assist E globulus growers with making management decisions and through this project we have expanded its capabilities so that FPOS has application to both softwood and hardwood growers It allows managers to explore different product options across the range of site types within the current estate and alternative species The process based model CABALA is the engine that drives FPOS but the DSS framework helps to 1 simplify the user s interaction with CABALA and 2 allows for incorporation of information that cannot be currently or realistically captured in process level models It also helps people to migrate to CABALA for answers to more specific questions that they have for any given site climate or management option The aims of this project were to 1 understand the physiological differences between E globulus and E smithii that may make E smithii better adapted to the hotter and drier conditions that are predicted to occur in many of the plantation growing regions 2 explore the range of down scaled global circulation model predictions to understand the best worst and most likely outcomes for future climate in each of the climatic regions that we focussed on 3 calibrate and or validate the CABALA model for the existing and new species across the range of sites that were used in
31. aporation To 1450 mm rainfall 1100 mm evaporation I 1450 mm rainfall 900 mm evaporation Legend Do Major towns NEE 50m 550 mm NEE 50 m 650 mm IN 50 m 750 mm I so m 850 mm IN 50 m 950 mm I 50 m 1050 mm NN 50 m 1150 mm DS 250 m 950 mm I 250 m 1050 mm X 250 m 1150 mm IX 250 m 1250 mm IE 250 m 1350 mm I 250 m 1450 mm E 250 m 1550 mm IN 350 m 550 mm EN 50m 1200 mm DR 350 m 650 mm EN 150 m 550 mm IN 150 m 650 mm 150 m 750 mm Fo 150 m 850 mm E 150 m 950 mm D 350 m 750 mm _ 350 m 850 mm 350 m 950 mm X 350 m 1050 mm 350 m 1150 mm IE 50 m 1000 mm DM 350 m 1250 mm IE 250 m 550 mm IE 250 m 650 mm 250 m 750 mm 250 m 850 mm EE 350 m 1350 mm RT 450 m 750 mm _ 450 m 850 mm _ 450 m 950 mm _ 450 m 1000 mm 550 m 550 mm _ 550 m 650 mm _ 550 m 750 mm _ 550 m 850 mm _ 550 m 950 mm _ 550 m 1000 mm _ 650 m 750 mm 650m 850 mm 650m 900 mm 750 m 550 mm 750m 650 mm 750 m 750 mm E 350 m 1400 mm 750 m 850 mm E 450 m 550 mm 450 m 650 mm 750m 950 mm _ 750 m 1000 mm The FPOS interface The individual components of the interface are detailed below Login Page The web address to access the system is https www crcforestrytools com au fpos login aspx The login page Fig 5 is the first page the user will have access to The rest of the system i
32. apping tool to K view your site locations and ee details spatially 37 Site Inputs The Site Input page consists of 4 tabs Item 2 Fig 7 the Site Summary Site Details Observed productivity and Add Edit economic scenario The site based pages also have a listing of the sites that have currently been entered through the existing login on the left hand site Item 1 Fig 7 Site summary The Site Summary page Fig 7 shows a listing of the sites that have currently been entered via the existing login with the region climatic zone species area rotation thinning regime and climate model for each scenario in the listing Note that this list will only contain the example site initially note that the example site is viewable by all logins but cannot be edited To add a new site manually click Add new site manually Item 5 Fig 7 or upload an excel file with your sites click on this button Item 6 Fig 7 When you add a new site manually a new blank site named New Site XXX where XXX is the next number in the sequence starting with 001 and incrementing appears in the list which can be edited directly To edit or delete an individual site you can enter the site details tab see Item 2 Fig 7 or click on the edit or delete buttons for each site Item 6 Fig 7 Also highlighted on this screen shot is the print screen icon Item 6 Fig 3 which extracts the page in PDF format for printing o
33. by CABALA to produce any output PlanTable area and Planting date are both optional inputs and are only required if you are interested in estimating potential wood flow across your estate under different rainfall or climate model Note that planting date 1s only used for calculating wood flow not for calculating yield at any given site and it doesn t account for the effects of planting at different times of the year 39 Fig 8 The site details page showing 1 add new site button 2 Upload site file button 3 Edit site details button 4 Delete site button and 5 The details pane highlighted gt Site Inputs gt Site details Welcome daniel FPOS Home Site Inputs Site Outputs Multi site outputs Sensitivity analysis Mapping Tool Change Password Log Out a F 4 Current sites Carpenters a Example site Add new site Upload excel file 1 New site 016 Edit site details Test sawlog radiate St e details of your site selected in the left hand list ave a are the fields Test sawlog regime requ togun the CABALA model d information can be Ge a pm this site without CABALA model results Add new site manually Upload site file Edit site details Delete site Mo Delete site Example site Site Summary Site Details Observed productivity Add edit economic scenarios Site name Example site Latitude degrees GDA1994 34 43 Longitude degrees GDA94 116 79 Reg
34. by that colum Table to enter data Add edit economic scenarios tab This tab allows the user to create and or modify their economic scenarios The example scenario IS provided as a starting point but will need to be modified appropriately A scenario can be selected from the pull down menu Item 5 Fig 10 A new scenario can be created by clicking on the new scenario button Item 3 Fig 10 which copies the values from the scenario that is currently selected into a new scenario The inputs are grouped into 6 different costs and returns categories as follows 1 Establishment costs Item 6 Fig 10 which include per seedling based prices seedling price planting price and starter fertilizer and area based costs for soil preparation Note that soil preparation cost is based on a linear relationship between stocking and cost where the a parameter is the slope of the relationship and the b parameter is the intercept If the land preparation cost does not vary with stocking you can set the a value to zero The graph shows the relationship between stocking and soil preparation cost as defined by the function 42 Fig 10 Add edit economic scenarios tab Highlighted items are described in the text gt Site Inputs gt Add edit economic scenarios Welcome daniel FPOS Home Site Inputs Site Outputs Multi site outputs Sensitivity analysis Mapping Tool Change Password Log Out 2 Current sites
35. cm3 CZ040 117 45 34 45 South Coast miroc3_medres CSIRO3 5 inmcm3 CZ041 116 5 32 2 Avon CSIRO3 5 miroc3 medres inmcm3 CZ042 116 9 34 4 South Coast miroc3 medres CSIRO3 5 inmcm3 CZ043 117 7 34 7 South Coast miroc3_medres CSIRO3 5 inmcm3 CZ044 116 4 32 5 South West miroc3_hires miroc3 medres inmcm3 CZ045 116 5 34 4 South West miroc3 hires miroc3 medres inmcm3 CZ046 117 65 34 85 South Coast miroc3 medres CSIRO3 5 inmcm3 CZ047 116 3 33 South West miroc3 hires miroc3 medres inmcm3 30 FPOS Climate Zone CZ048 CZ049 CZ050 CZ051 CZ052 CZ053 CZ054 CZ055 CZ056 CZ057 CZ058 CZ059 CZ060 CZ061 CZ062 CZ063 CZ064 CZ065 CZ066 CZ067 CZ068 CZ069 CZ070 CZ071 CZ072 CZ073 CZ074 CZ075 CZ076 CZ077 CZ078 CZ079 CZ080 CZ081 CZ082 CZ083 CZ084 CZ085 CZ086 CZ087 CZ088 CZ089 CZ090 CZ091 CZ092 CZ093 CZ094 CZ095 CZ096 CZ097 CZ098 CZ099 Latitud e 116 1 117 45 116 2 115 5 117 15 116 05 115 95 116 95 116 115 95 116 35 116 65 147 95 147 65 148 147 3 146 4 144 8 144 9 144 85 147 25 147 05 147 65 147 1 146 85 145 1 147 35 147 4 146 95 146 9 146 65 146 35 146 2 145 75 145 4 145 35 145 4 147 6 147 6 148 146 7 146 65 146 75 146 05 146 1 145 75 145 45 147 3 147 8 147 95 147 35 148 Longitude 34 05 34 9 33 05 34 34 85 33 1 34 2 34 9 32 85 34 55 34 85 35 42 4 40 9 40 9 41 1 41 3 40 8 40 85 40 95 41 6 41 55 41 05 41 2 41 3 41 05
36. d into the system The user can choose which sites to present in the output by selecting from the list Item 1 Fig 19 Note that the system can only show sites where observed data has been entered by the user see Fig 9 above and where CABALA has been run The system will not allow you to select sites where either of these criteria have not been met It gives a warning about the number of sites that don t have data Item 5 Fig 19 and the number of sites that don t have CABALA runs available Item 6 Fig 19 The user can choose to run the missing sites by clicking on the run CABALA button Item 6 Fig 19 The outputs of the observed vs predicted productivity are shown in graphical Item 2 Fig 19 and tabular Item 4 Fig 19 form and regressions are fitted to the data Item 3 Fig 19 to describe the goodness of fit between observed and predicted values 53 Fig 19 Model efficiency tab showing 1 the site selection panel 2 the observed and predicted outputs in graphical form 3 regression outputs 4 the tabulated output of observed vs predicted output 5 the number of sites without observed data and 6 the number of sites without CABALA outputs gt Multi site outputs Welcome daniel e Sen TUUS ee di 32 FPos Current sites Boyup Brooktest Model efficiency Wood flow predictions The Model Efficiency section of this site allows users to compare their entered observations with
37. d to be better adapted to the likely increases in temperature and decreases in rainfall The engine behind FPOS is a live version of CABALA connected to a database of outputs so that CABALA does not need to be re run twice for the same scenario This report 1 describes the detailed physiological Studies into E smithii that we conducted to be able to include it in the DSS the climatic modelling and model choice and the CABALA parameterisation and 2 includes the user manual for FPOS describing each part of the system and the assumptions and underlying models that are used to produce the relevant output The FPOS system should be regarded as a synthesis of the best currently available knowledge but there is still significant scope for further improvement of both the interface and underlying models The benefits of the FPOS system would be maximised by investing time in the training of industry staff in its use CRC Forestry members and FWPA levy payers have free access to the system and should enquire with the developers about arranging for a username and password The system login page is at https www crcforestrytools com au fpos login aspx Table of Contents EHNEN eebe ee ee ee het 1 DAMME SCI ra ae ee tn 1 NY id ee de EE EE 2 CABALA model development and parameterisation cccccccccssseeeseeeeeeeceeaeeeseseceeeeeeaaas 2 Climate model selection and application ss ns nn nid 3 Comparative physiology of E smithii and E
38. de and longitude of the mouse poin Carpenters New site 001 radiata GT Test sawlog regime ma IE the map window The user may remove the visibility of layers over the Bee een th Selected climatic zone en clicking on the upper left side of the map window Selecting a visible climatic zone will provide the 1 the name of that zone above the map window Selected climate zone E Layer selection New site 016 gigi ic is Rcs i Pinaster WA test Le EVO POLO Fe e I 115 t LR Site information E 4 Perth 120 LJ Pan Zoom 2 M OS controls amp _ Rockingham oyup Brook test Site details Falcon Example site Rainfall 1100 1200mm Evaporation 1000 1200mm Above average rainfall deep sand 4 m depth E globulus 900 stems ha Age 10 years Predicted final volume 267 4 m ha Predicted final LAI 0 5 m m NPV 1982 19 IRR NA96 300 250 200 3150 FPOS Report a map error Google ere data Is avalta Current mouse position fto pan Hold down the shift key and drag to zoom to a particular region limitations FPOS is not a perfect tool and will not always give the right result Key limitations include the following One of the key strengths of FPOS is also one of its weaknesses which is that it relies upon CABALA as the underlying engine to predict productivity CABALA is useful for conducting what if type analyses but can also provid
39. dres CZ016 148 5 37 East Gippsland inmcm3 CSIRO3 5 miroc3 medres CZ017 147 4 37 85 East Gippsland inmcm3 CSIRO3 5 miroc3 medres CZ018 147 2 35 8 Murray CSIRO3 5 inmcm3 miroc3 medres CZ019 147 75 37 6 East Gippsland inmcm3 CSIRO3 5 miroc3 medres CZ020 143 15 38 2 Corangamite CSIRO3 5 inmcm3 miroc3 medres CZ021 147 8 35 6 Murrumbidgee inmcm3 bccr bcm2 miroca medres CZ022 148 2 37 25 East Gippsland inmcm3 CSIRO3 5 miroc3 medres CZ023 146 8 36 3 North East CSIRO3 5 inmcm3 miroc3 medres CZ024 148 55 37 35 East Gippsland inmcm3 CSIRO3 5 miroc3 medres CZ025 147 85 35 8 Murray CSIRO3 5 inmcm3 miroc3 medres CZ026 148 7 35 75 Southern Rivers miroc3 hires miroc3 medres inmcm3 CZ027 146 85 36 6 North East CSIRO3 5 inmcm3 miroc3 medres CZ028 148 3 35 85 Murrumbidgee inmcm3 bccr bcm2 miroca medres CZ029 146 95 36 4 North East CSIRO3 5 inmcm3 miroc3 medres CZ030 147 55 36 3 North East CSIRO3 5 inmcm3 miroc3_medres CZ031 146 45 37 6 West Gippsland CSIRO3 5 inmcm3 miroc3 medres CZ032 146 85 36 75 North East CSIRO3 5 inmcm3 miroc3_medres CZ033 146 9 37 North East CSIROS3 5 inmcm3 miroc3 medres CZ034 146 3 37 55 Goulburn Broken CSIRO3 5 inmcm3 miroc3 medres CZ035 146 95 36 65 North East CSIRO3 5 inmcm3 miroc3_medres CZ036 147 05 37 15 North East CSIROS3 5 inmcm3 miroc3 medres CZ037 147 05 36 65 North East CSIRO3 5 inmcm3 miroc3 medres CZ038 146 75 37 25 West Gippsland CSIRO3 5 inmcm3 miroc3 medres CZ039 116 7 32 45 Avon CSIROS3 5 miroc3_medres inm
40. e Is a required input for the interface The available options are dependent on the species chosen with different thinning regimes available for softwood and hardwood species approximately 15 for each Note that each regime has a unique number so you can easily find your preferred regime from the list once you have found some regimes in the list that you want to work with Distance to port mill Is a required input for the economics module Note that the system will attempt to calculate a distance to the nearest port if the user enters latitude longitude coordinates This is a simple algorithm that calculates a direct as the crow flies distance and adds a 20 tortuosity factor Economic scenario is a required input for the economics module The user can enter as many economic scenarios as they wish An example scenario is included for demonstration purposes but it should not be relied upon for your specific circumstances Comments provides the user with an option to enter any comments or remarks about the particular scenario Include in CSIRO CRC model improvements This option is to allow your data to feed back into future model improvements Note that we will not release individual site information or be looking at any of the economic information This is about trying to understand where the model is working well and where it could use future improvement The inputs regarding confidence in soil chemistry and soil depth information are used
41. e counter intuitive or perverse results under some scenarios or combinations of inputs Thus the output must always be considered in this context CABALA is under continual improvement and identification of sites and situations where CABALA doesn t appear to work well are welcome for further investigation The climate models embedded into the system are necessarily a simplification of the actual model output with the primary limitation being that FPOS uses average monthly data so it cannot replicate the extreme events For example it does not model drought climatic sequences per se only reduced rainfall by user choice or changes in frost frequency FPOS does not attempt to deal with some factors that can have a significant impact on plantation productivity these include pests disease weeds micronutrients and most macronutrients other than through the generic fertility ranking Other tools are 57 more suitable to assess these effects and or more research is required to allow them to be embedded into FPOS e Coppice productivity may be over predicted due to a lack of knowledge about coppice physiology post reduction Currently CABALA assumes that the coppice trees have the same shape and response to environment as seedling trees after they are reduced to 1 or 2 stems Note that FPOS models coppice reduction down to stem per stool at age 2 e The calculation of log sizes from the predicted tree size distribution relies on a c
42. eir plantations Neither the information L Remember me next time nor the tools should be used for any other purpose without prior written consent of CSIRO and FWPA Use of the website is not r Forest Wood CRC Products Australia E Forestry Knowledge for a sustainable Australia results graphically Copyright CSIRO 2012 Disclaimer 36 Home Page The home page Fig 6 has a brief description of each of the components of the system and hyperlinks to the rest of the system The different sections of the system can also be accessed on any page via the menu bar highlighted as item 2 in Fig 6 at the top of the screen and the current place within the system can be viewed by looking at the navigation breadcrumbs at the top of the screen highlighted as item 1 in Fig 6 The user can change their password to access the system through the change password menu item Fig 6 The FPOS home screen The navigation breadcrumbs 1 and menu bar 2 are highlighted Navigation breadcrumbs GC Ms Menu bar 2 i jm i 3 y Ld y La Nu Vet PU ES FPOS attempts to synthesize and Site Outputs m communicate complex growth and The stand information section of tt nutrition models for a variety of tree A allows the user to explore predicte crops in southern Australia The user can ES information about their stand including select output from a set of predefined AXES parameters and is provided with
43. enter information about the cost of thin to waste operations on a stem basis the cost of commercial thinning operations as a percentage of clearfall costs as defined in the Harvest and Transportation costs and the cost of pruning Note that pruning does not affect growth or estimates of sawlog recovery but is only used in the economic calculations Site Outputs The Site Outputs page has 8 tabs including Site Information Nutrients Economics Productivity Water Use Nitrogen Species and Climate Model This is where the majority of the model output can be retrieved for individual sites Site Information Each page within the Site Outputs menu shows a summary of the scenario outputs on the left hand side Item 1 Fig 11 including the selected climatic zone rainfall variation soil type and depth stocking rate and harvest age along with the predicted final volume final LAI as well as the NPV and IRR A thumbnail graph of the predicted volume growth is shown as well with observed data as points and model predicted productivity as a line on the graph Note that the IRR is calculated using a solving function which is not able to find a solution if the IRR is too low If this is the case the IRR is shown as NA The predicted outputs are also shown in larger format at the bottom of the Site Information tab Item 3 Fig 11 along with the scenario details Item 2 Fig 11 44 Fig 11 Site Information tab high
44. ficiencies and insect attack Soil physical and nutrient data was either provided by the industry partner or drilling was undertaken as part of the project Daily rainfall and air temperature data for all plots were from the Bureau of Meteorology s Data Drill http www longpaddock qld gov au silo The data in the Data Drill is synthetic consisting of interpolated grids splined using data from meteorological station records but has the benefit of being available for all locations in Australia on a scale of 0 05 degree Fig 5 CABALA validation using data from 58 E globulus plots from Tasmania Victoria South Australia and Western Australia Stands are at time of measurement were between 6 and 14 years of age and cover a range of silvicultural treatments including thinning and fertilisation 500 450 400 350 300 i e 250 e i Bet We y 1 18x 15 8 200 R2 0 75 Predicted Volume m ha 200 300 400 500 Although some plots are poorly predicted there is no bias against the measures of fertility rainfall or temperature indicating that predicative capacity is reasonable Consistently poor predictions under estimates are made on inland Victorian sites where frost limitations are over predicted Work being undertaken in a separate FWPA project is attempting to resolve the issue of fine downscaling to capture the effects of frosty and cold locations Sites where mortality has been high
45. ge patterns between the species with the middle layers 1 4 25m recharging under E smithii and the lower layers 4 25 7 75 m recharging more under E globulus E smithii tended to maintain a larger soil water deficit in the lower layers 16 Fig 17 Measured soil water deficit under E globulus a and E smithii b over the duration of the experiment Na Qe 0 100 E 200 bel H P 300 run E O 1 m 9 400 S H1 2 25m F me m2 25 4 25m 600 m4 25 6 25m 700 a E globulus m6 25 7 75m 0 100 E E 200 bel S 300 D im 9 400 O 3 500 un 600 b E smithii 00 Gas exchange The diurnal gas exchange rates were measured at 5 times during the experiment under different seasonal conditions Only 2 of these occasions had suitable weather to permit a full diurnal daylight period measurement with rainfall interfering with the other measures such that gas exchange could only be assessed 2 3 times during the day The highest photosynthetic rates were typically observed in the early or mid morning Fig 18 and when these mid morning rates were plotted over time Fig 19 it is evident that the peak photosynthetic times were in spring Several of the measures had low or negative photosynthetic rates November 2010 and April 2011 and these low photosynthetic rates were associated with high temperatures gt 35 C and high vapour pressure deficits 24 KPa The envelope of the relationship betwee
46. ide enough information to managers to allow for the risk of worst case scenarios or potential opportunities with the best case Selecting a small number of models should be based on criteria that limit bias and are as objective as possible Clarke 201 1 The Climate Futures Framework Clarke 2001 overcomes these limitations by classifying the projected changes from the full suite of climate models into classes defined by two climate variables usually annual mean temperature and rainfall Relative likelihoods are assigned to each class or climate future based on the number of climate models that fall within that category For example if 12 of 24 models fall into the Warmer Drier climate future it is given a relative likelihood of 50 Clarke 2011 A subset of models can be selected to represent the range in climate futures In this instance we have selected a best 1e highest rainfall least temperature rise worst 1e the lowest rainfall and highest temperature rise and most likely future climate 1e the temperature and rainfall change that is predicted by the majority of the models This allows the user to focus on the output from the most likely model where the future climate predictions converge while the best and worst case can provide bounds around the uncertainty of those predictions The model choices for each climatic zone are detailed in Appendix 1 Comparative physiology of E smithii and E globulus To understand
47. in this regard as we will not be able to use data for future model improvements unless the sites have been well characterised 41 Observed Productivity tab The Observed Productivity tab allows the user to enter their own site information This data is shown on the model output graphs so that the user can see how closely the model is representing their observed productivity The data can also be used to compare model performance across several sites under the Multi site output menu option Data can be entered manually through the interface or it can be uploaded via an Excel spreadsheet file To enter data manually type values into the empty boxes in the data entry table Item 3 Fig 9 and save the edits Item 1 Fig 9 Upon saving a new blank row will appear to allow the user to enter another measurement if it is available Fig 9 Observed productivity tab showing 1 the Save edits button 2 the Load from File button and 3 the data entry table gt Site Inputs gt Observed productivity Welcome daniel Site Summary Site Details Observed productivity Add edit economic scenarios Current sites Carpenters Example site New site 016 i site produc e site selected from the list of sites on the left Note that Testsawlog regime e is not edrean ese values to assess erg ABALA model outputs i me in meters Diameter is in centimeters LAI m2 m2 H select a column heading to sort
48. ing the approximate C N ratio of the top 10 cm of soil Item 1 Fig 16 For other species this is not likely to be very accurate so the user needs to enter their own intercept and curvature R factor into the input boxes Item 2 Fig 16 The output Item 4 Fig 16 calculates the optimal rate of N fertilizer to maximise NPV for the fertilizer application The calculations assume that fertilizer is applied in only one of the application years and estimates the additional volume that may be achieved by application in that year 50 Fig 16 Nitrogen fertilizer tab highlighting 1 the C N ratio input box 2 the fertilizer response curve coefficients 3 the response curve shown graphically and 4 the output from the module gt Site Outputs gt Nitrogen Welcome daniel Current sites Carpenters New site 016 radiata GT Test sawlog radiate Test sawlog regime Response curve graph Response curve coefficients Reset Fertilizer response curve coefficients Example site Rainfall 1100 1200mm Evaporation 1000 1200mm Predicted responses and economics Above average of N fertilizer addition rainfall deep sand 4 m depth E globulus 900 stems ha Age 10 years Predicted final volume 292 m ha Tote The nutrition module is the least reliable part of FPOS due to paucity of input Predicted final LAI information Use it with caution until we can improve the underlying response surfaces 3 2 m2 m N
49. iology of E smithii and E globulus The studies into the comparative physiology of E smithii and E globulus did not draw out any large differences in the capacity of E smithii to respond to the drier or hotter conditions that are likely to prevail in some areas of the plantation estate under likely future climate change This does not mean that E smithii does not convey a benefit for these conditions just that we were not able to specifically identify what the cause of that benefit may be However it is worth noting that E smithii appears to be more of a steady performer than E globulus showing the following attributes e A substantially lower initial standing volume in our experiment Fig 8 and lower height growth response between the October 2011 and January 2013 measures This latter growth period was not associated with significantly different depletion of the soil water stores under E globulus compared to E smithii Fig 14 e esser diurnal shrinkage at most of the measurement times but especially in the dry summer periods It is also apparent that initial survival rates of E smithii have been lower than for E globulus in many of the plantations that we initially surveyed although not at Shuttleworth where this experiment was conducted with the lower stocking rate possibly conveying a natural advantage to E smithii plantations in drought conditions White et al 2011 also used the Shuttleworth site to compare drought sensit
50. ion Western Australia Climatic zone Rainfall 1100 1200mm Evaporation 1000 1200mm Exposed site False Rainfall variation Above average Climate model no change Species E globulus Plantable area ha 120 Planting date 1 07 2000 Genetic material Planting stock free text trees Soil type deep sand Soil depth m 4m Site details Confidence in soil depth Low only a guess Soil Organic C 0 10 cm 10 Total soil N 0 10 cm 0 5 Confidence in soil chemistry Low only a guess Soil Fertility medium fertility Stocking rate stems ha 900 Rotation 1R Planned harvest age 10 Product Pulpwood Thinning Regime 1 Pulpwood coppice Distance to port mill km 50 Economic scenario Example scenario View Edit economics Include in CSIRO CRC model improvements True Comments test Genetic material planting stock This information is not used by the system but is there to allow the user to make notes for their own use about any particular scenario Soil type This 1s a required input for CABALA The soil types a user can select is dependent on the climatic zone and there are typically 2 3 soils available within any given climatic zone The main attribute of soil type that is used by the system is the water holding capacity of the soil as soil fertility 1s a separate input Soil depth This is a required input for CABALA and the options change depending on the climatic zone that is chosen The available soi
51. iroc3 medres miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires miroc3 hires Best Scenario inmcm3 inmcm3 inmcm3 inmcm3 inmcm3 inmcm3 inmcm3 inmcm3 inmcm3 inmcm3 inmcm3 inmcm3 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 bccr bcm2 FPOS Climate Zone CZ100 CZ101 CZ102 CZ103 CZ104 CZ105 CZ106 CZ107 CZ108 CZ109 CZ110 CZ111 CZ112 CZ113 CZ114 CZ115 Latitud e 146 25 147 4 147 65 147 45 147 4 147 6 145 9 147 25 146 85 147 75 146 7 146 45 146 95 146 7 147 4 146 3 Longitude 41 5 42 4 41 95 41 55 41 5 41 65 41 35 42 2 42 15 42 05
52. ivisions Marine Atmospheric Research Climate Change Technical Report 2007 aspx Jeffrey S J Carter J O Moodie K M and Beswick A R 2001 Using spatial interpolation to construct a comprehensive archive of Australian climate data Environmental Modelling and Software Vol 16 4 pp 309 330 Mitchell P J O Grady A P Tissue D T White D A Ottenschlaeger M L Pinkard E A 2012 Drought response strategies define the relative contributions of hydraulic dysfunction and carbohydrate depletion during tree mortality Norby R J J M Warren C M Iverson B E Medlyn and R E McMurtie 2010 CO enhancement of forest productivity constrained by limited nitrogen availability Proceedings of the National Academy of Sciences 107 19368 19373 White D A et al 2011 Climate driven mortality in forest plantations prediction and effective adaptation Report to the Department of Agriculture Fisheries and Forestry CSIRO CanberraUSGCRP 2009 Global Climate Change Impacts in the United States Thomas R Karl Jerry M Melillo and Thomas C Peterson eds United States Global Change Research Program Cambridge University Press New York NY USA White D A O Grady A P Pinkard E A Green M J Carter J L Battaglia M Bruce J L Hunt M A Bristow M Stone C Dzidic P Penman T Ogden G N Short T M Opie K Crobmie D S Kovacs M Grant D 2011 Climate driven mortality in f
53. ivity between E globulus and E smithii and they found that there were few differences between the 2 species in their hydraulic characteristics that relate to drought sensitivity Mitchell et al 2012 however did show that pot grown E smithii had a shghtly longer survival than E globulus 92 days vs 69 days under drought conditions but the differences between these 2 species were small compared to Pinus species which exhibited a much greater tolerance to drought conditions Thus planting of E smithii may convey some survival advantage under extreme drought conditions but this 1s likely to have a cost of lower biomass production It is likely that a similar level of drought tolerance could be attained in these plantations through management of stocking rates of E globulus instead of changing species 23 Conclusions This project has developed a forestry plantation decision support system to allow users to explore the impacts of various management climate and species choices on predicted productivity and profitability The tool that has been produced is not designed to answer all questions or to be the definitive reference for all situations but rather its intended use 1s to support managers in their decision making processes about understanding the relative impacts of site selection management regime and future climate on the predicted productivity and profitability 24 Recommendations The FPOS tool allows managers and growers to
54. lighting 1 the Summary output panel 2 the Site information and 3 the predicted outputs gt Site Outputs Welcome daniel A D ww E 7 FPOS Home Site Inputs Site Outputs Multi site outputs Sensitivity analysis Mapping Tool Change Password Log Out Nm 3 e Site information Nutrients Economics Productivity Water Use ae SEE Nitrogen Species Climate Model Carpenters Example site Below is a summary of the site selected from the list on the left CABALA outputs may be viewed below if New site 016 they are available To enter more details for your site visit Site Details Test sawlog radiate Test sawlog regime Example site Site name Example site Latitude degrees GDA1994 34 43 Longitude degrees GDA94 116 79 Climatic zone Rainfall 1100 1200mm Evaporation 1000 1200mm Summary panel Rainfall variation Above average 1 Plantable area ha 120 A Planting date 1 07 2000 Genetic material Planting stock free text trees Example site Rainfall SAOR en Site information Evaporation Soil type deep sand 1000 1200mm Above average Soil depth m 4m rainfall Confidence in soil depth Low only a guess deep sand 4 m depth Soil Organic C 9 o 0 10 cm 10 E globulus Done na Total soil N 0 10 cm 0 5 Age 10 years Confidence in soil chemistry Low only a guess Predicted final ae ms A 5 volume 292 m2 ha Soil Fertility medium fertilit
55. lly 0 05 mm and greatest during summer typically 0 1 0 15 mm E globulus tended to exhibit a greater shrinkage than E smithii especially during the extended dry summer of 2011 12 14 Fig 13 Monthly diurnal shrinkage and coincident rainfall Error bars show 1 SEM 0 2 160 rainfall 0 18 E globulus 140 0 16 E smithii E 120 0 14 T ap 100 E 0 12 E z 0 1 h X 80 g 3 0 08 i I b 7 H AAC N Let W 0 06 4 T 2 LA 40 0 04 0 02 i 0 0 Aug Oct Dec Feb Apr Jun Aug Oct Dec Feb Apr Jun Aug Oct Dec 10 10 10 11 11 11 11 11 11 12 12 12 12 12 12 Date Net stem diameter growth after rainfall was generally restricted to only a few days after a rainfall event for both species averaging from 2 days for the smallest size E globulus to around 5 days for the largest size class trees Fig 14 However the trees also exhibited the capacity for continuous stem growth for up to 140 days for one of the E smithii trees and up to 96 days for one of the E globulus trees Fig 14 Average number of days of net stem expansion by size class 1 lowest quartile 4 highest quartile of stem diameter Note that there is large variation around these data points so the error bars are not shown ME globulus E E smithii Average number of days of expansion LA Tree size class The number of days of continuous stem expansion was directly related to the rainfall occurring during
56. ls in WA and the Green Triangle tend to be deeper than those that are available in Tasmania and Victoria Soil organic C and total N 0 10 cm are optional inputs but are intended to help the user to classify their soil fertility If the user has a good feel for their soil fertility they can skip 40 directly to that input and not worry about selecting a C or N value Alternatively if they choose C and N values and are not happy with the fertility rating that the system chooses they are welcome to override the system choice Soil Fertility is a required input for CABALA from high fertility which is intended to represent an ex pasture site with a good fertilizer history through to low fertility which is intended to represent an ex bush site with no fertilizer history Stocking rate is a required input for CABALA with the user able to select a value from 600 stems ha to 2000 stems ha in 100 stems ha increments Rotation 1s a required input for the interface with users able to choose from first rotation or 2 rotation or later seedling all species or coppice E globulus and E smithii Planned harvest age 1s a required input for the interface with users able to choose any age up to 20 for a pulpwood regime or any age up to 40 for a sawlog regime Product 1s a required input for the interface with users able to choose from sawlogs or pulpwood Note that the product choice influences the potential rotation length Thinning regim
57. lume xamiple site prediction Rainfall 1100 1200mm Evaporation 1000 1200mm Above average rainfall deep sand 4 m depth E globulus 900 stems ha Age 10 years Predicted final volume 267 4 m ha Predicted final LAI NPV 1982 19 IRR NA 300 250 Note If site in not selectable inadequate details are defined for the site to calculate volume or CABALA has not been run for this scenario Run CABALA for data ABALA results 4 sites missing parameters g 200 5 2006 56 65 Sensitivity Analysis The sensitivity analysis tool allows the user to explore model predictions in a matrix style output for the factor levels that are available in the system For example a combination of soil type and soil depth for a given site presents all of the CABALA predictions for each combination of soil type and soil depth in this example a total of 15 scenarios The page gives the user the option to compare 2 output matrices tables alongside each other A site needs to be selected as the base scenario for each table and then the row and column factors to explore need to be selected Items and 2 Fig 21 As this analysis draws output from many individual CABALA runs it is likely that there may not be all of the runs in the database at least initially so the interface will tell the user how many CABALA scenarios need to be run and the user can start these by clicking Run CABALA Items 3 and 4 Fig 2
58. mbinations of scenarios CABALA is run as new scenarios ie that aren t already in the database are requested by the user Once these have been run once they do not need to be run again unless the model is updated The model is run on the server and usually takes around 1 minute depending on the server load 3 Empirical processing modules to add value to CABALA outputs including calculation of economic outputs calculations of nutrient export rates under different harvesting regimes and calculations of water use efficiency 4 An interface to allow the user to easily extract information from the database and overlay model output with empirically processed information The user can also print and or save output from the interface for reporting Table 1 Potential combinations of inputs to run CABALA Input Number of Notes combinations Climatic zone 115 Species 5 Not all species will grow in all climatic zones Stocking rates 15 Soil fertility ratings 5 Soil depths 5 Depths vary with region Thinning regimes 30 Dependent on product type and species Climate model 4 Rainfall variation 5 Total combinations 129 375 000 Note that this is the maximum number of possible combinations but some combinations cannot be selected in the interface because they are not sensible Climatic zones The FPOS system is based around climatic zones There are a total of 115 climatic zones The zones in Western Australia Fig 1 the Green Triangle Fig
59. mm rainfall 1100 mm evaporation ES 750 mm rainfall 900 mm evaporation ZA 850 mm rainfall 1100 mm evaporation m 850 mm rainfall 900 mm evaporation 7A 950 mm rainfall 1100 mm evaporation 950 mm rainfall 900 mm evaporation N 4 H o Mount Gambier e A q eh RL Warrnambool ts z SS CT NN E LS Tl N N 34 Fig 3 FPOS climatic zones in Victoria other than Green Triangle Legend O Major towns 550 mm rainfall 1300 mm evaporation ZO 550 mm rainfall 1100 mm evaporation b2 650 mm rainfall 1300 mm evaporation V 650 mm rainfall 1100 mm evaporation 650 mm rainfall 900 mm evaporation KX 750 mm rainfall 1300 mm evaporation a 750 mm rainfall 1100 mm evaporation El 750 mm rainfall 900 mm evaporation PX 850 mm rainfall 1300 mm evaporation oa 850 mm rainfall 1100 mm evaporation 850 mm rainfall 900 mm evaporation BY 950 mm rainfall 1300 mm evaporation ZA 950 mm rainfall 1100 mm evaporation ES 950 mm rainfall 900 mm evaporation a e ES 1050 mm rainfall 1300 mm evaporation IE lr ZA 1050 mm rainfall 1100 mm evaporation H t LGL mas P Melb THE PAY 1150 mm rainfall 1300 mm evaporation i Er Li A 1150 mm rainfall 1100 mm evaporation DOA 1250 mm rainfall 1300 mm evaporation 7 7 1250 mm rainfall 1100 mm evaporation ee 1250 mm rainfall 900 mm evaporation KAY 1350 mm rainfall 1300 mm evaporation Cz 1350 mm rainfall 1100 mm evaporation E 1350 mm rainfall 900 mm ev
60. n VPD and conductance Fig 20 is important to describe a species response to environmental conditions within CABALA and it suggested that the E globulus trees had slightly more stomatal control at VPDs between about 2 and 4 KPa 17 Fig 18 Diurnal photosynthesis from 4 of 5 measurement occasions Note that inclement weather prevented full acquisition of the latter 2 diurnal curves 16 1 a September 2010 16 4 b November 2010 14 14 E globulus 12 12 f E smithii 10 10 2 2 O O O O O O O O O O O O o e S SS a oo o N sf co e e e e CH e a ed e e 16 1 c April 2011 16 7 d Feburary 2012 CO fixation umoles m2 s 08 00 10 00 12 00 14 00 16 00 18 00 08 00 10 00 12 00 14 00 16 00 18 00 Measure time WST 18 Fig 19 Measured photosynthetic rate at around 10 am at each of the measurement times Error bars show 1 SEM Note that only E smithii was assessed in November 2011 18 16 14 12 10 E globulus fi E smithii N A o 0 O nl 3 Oct10 Jan 11 Apr 11 Jul 11 Oct 11 Jan 12 Apr 12 Jul 12 Oct 12 Jan 13 Apr 13 Fig 20 Relationship between measured leaf conductance and leaf vapour pressure deficit The envelope of this relationship defines the phenomenological model used in CABALA to describe maximum possible conductance 0 7 0 6 0 5 0 4 E globulus BE smithii 0 3 0 2 Conductance mmole
61. ng cost Annual Costs Annual Costs Annual Costs Annual Costs Annual Costs Annual Costs Annual Costs Annual Costs Annual Costs Year 1 Year 2 Cost of pruning 1 Year 3 Cost of pruning 2 Year 4 Cost of pruning 3 Year 5 Value of logs 20 25 cm at thinning 1 Value of logs 15 20 cm at thinning 1 Value of logs 10 15 cm at thinning 1 Cost of thinning 1 Year 6 Year 7 Year 8 Year 9 Year 10 Year 11 Year 12 Year 13 Year 14 AO o o H DN H uw b oe uU RN NM Do 315 00 330 75 3307 50 347 29 5209 31 364 65 7293 04 382 88 50 25 1900 09 1474 39 4465 50 402 03 422 13 443 24 465 40 488 67 513 10 538 76 565 69 593 98 286 36 273 35 2733 47 260 92 3913 83 249 06 4981 24 237 74 31 20 1179 81 915 48 2772 72 226 94 216 62 206 77 197 38 188 40 179 84 171 67 163 86 156 41 G detailed break down of costs and returns Productivity The productivity tab allows the user to explore the predicted productivity including e MAT and CAI curves Item 1 Fig 14 The example in Fig 14 exhibits a negative CAI and reduced MAI in year 6 associated with a thinning event followed by a rapid increase in CAI e The predicted loss in productivity due to lower than optimum fertility Item 2 Fig 14 is calculated as the difference between the model output for maximum soil fertility and the model output for the chosen soil fertility
62. ng for other purposes which is strictly reserved only for the owner or licensee of copyright under the Copyright Act is prohibited without the prior written consent of FWPA ISBN 978 1 921763 78 6 Researcher s Daniel Mendham Jody Bruce Kimberley Opie Gary Ogden CSIRO Sustainable Agriculture Flagship College Road Sandy Bay Tas 7005 Bayview Avenue Clayton Vic 6138 Brockway Road Floreat WA 6014 Final report received by FWPA in April 2013 Forest amp Wood Products Australia Limited Level 4 10 16 Queen St Melbourne Victoria 3000 T 61 3 9927 3200 F 61 3 9927 3288 E info fwpa com au W www fwpa com au Executive Summary This project developed the Forest Productivity Optimisation System a web based decision support system to help plantation managers understand the impacts on plantation productivity and profitability of changing climate and different management sites and species choices FPOS is based on the Blue gum Productivity Optimisation System which was a product of the Forestry CRC FPOS is a major enhancement to BPOS extending it in several key ways including 1 allowing the user to explore many more climatic zones 2 modelling up to 5 species instead of 1 3 accounting for solid wood as well as pulpwood products The 3 commonly used species in southern Australia were included in FPOS E nitens E globulus and P radiata as well as P pinaster and E smithii that are considere
63. obulus Image copyright Google Earth Note the location of the plots and E smithii belts is approximate as the plot corners were measured with a standard GPS with an accuracy of around 20 m f 2013 Whereis Sensis Pty Ltd 7 E 2013 Cnes Spot Image I AA LITO Google earth C Measurements To track the tree growth and water stress at the Shuttleworth site we made the following measurements over 2 5 years 2010 2013 e Tree growth was measured on every tree in each plot annually e Dendrometers were installed to measure diameter on 4 trees per plot representing 4 evenly distributed size classes at 30 minute intervals e Soil characterisation and NMM tube installation was completed using deep drilling at the start of the experiment 1 hole tube per plot e Diurnal leaf gas exchange was measured four times per year in seasonally wet and dry conditions 5 trees per plot however not all plots were measured at each time due to time constraints e LAI was measured twice per year during summer and winter e Pre dawn leaf water potential was measured approximately 4 times per year e Soil moisture was measured with a neutron moisture meter approximately 4 times per year after the NMM tube installation in early 2011 FPOS Interface development The FPOS web interface was based on the original code for the BPOS interface It 1s developed in Microsoft NET 2 0 and interfaces with 2 Microsoft SQL Server databases A live version of
64. om in to treefarm or sub treefarm level in most cases Zooming and panning can be done directly with the mouse and scroll wheel or with the map controls Item 2 Fig 22 The climatic zones and or sites can be shown on or removed from the map by selecting the appropriate layers from the layer selection menu Item 3 Fig 22 The site locations are indicated with green diamonds Item 4 Fig 22 which if clicked on will result in a pop up site information box Item 5 Fig 22 which includes some of the inputs and some of the outputs for the selected site A climatic zone can be highlighted by clicking on it and the name will appear at the top of the map Item 1 Fig 22 The coordinates of the point under the mouse cursor can be viewed at the bottom of the screen Item 6 Fig 22 which can be used as a guide for entering into the site information section Fig 8 Note that this is not yet automatic but we may be able to include this feature in the future 56 Fig 22 The mapping tool page highlighting 1 the currently selected climatic zone 2 the pan zoom controls 3 the layer selection 4 an example site marker 5 the site information popup box and 6 the current mouse position gt Mapping Tool Welcome 32 FPos Current sites daniel The Mapping Tool section allows the user to observe where plots occur in an interactive map Selec ing will display the detail of the site in that locaiton Location in latitu
65. on in absolute rainfall across a single cell in the GCM grids The average monthly climates were then calculated for each climatic zone over the entire 30 year sequence 11 Detailed comparative studies into E smithii and E globulus in response to environment Tree growth overall The standing volume in the E globulus plots started higher than that of the E smithii plots 46 m ha versus 30 m ha and the productivity differential between the species widened especially in the ae year of measurement Fig 11 mainly due to an increased height increment in 2012 1 21 min E globulus compared to 0 6 m in E smithii 12 Fig 11 Measured standing volume a diameter b and height c of each species over the 2 5 year life of the experiment Error bars show 1 SEM O O e a Standing volume O On E smithii E globulus O O O O O O O O PT O N st M A ey gW euinjoA Suipuejs 10 ET dy T uer TO CL IAL cT dy cT uef TTPO TT IAL TT dy TT Uef 01190 OT IAL Date 180 b Average diameter 160 O O O O O O N O O O a el ei ww JaJawWeIp aSelany eT idy ET uer TO CT Inf cT 4dy cT uef L T3190 II Inf TT 4dy TT Uef 01190 OT IAL Date N ci c Average height GO LO St w 43194 aSelany ET dy eT uef CTHVO CL IAL cT dy cT uer TTVO TT IAL TT dy TT Uef OTWO OT IAL
66. onical approximation to calculate the lengths of logs in each of the log size categories pro rated back to the calculated volume but trees grown for sawlogs typically have less of a taper in the clear section of the bole so the conical function will probably tend to underestimate the quantities of larger logs and over estimate the quantities of smaller logs e Nutrient export calculations are based on allometrics for biomass of different tree components and standard tissue concentrations for nutrients The best characterised species are E globulus and P radiata so the outputs for these species are likely to be reasonable but the other species are not as well characterised so may not be as accurate in their predictions References Hopmans and Elms 2009 Changes in total carbon and nutrients in soil profiles and accumulation in biomass after a 30 year rotation of Pinus radiata on podsolised sands 58
67. or give any warranty regarding the use suitability validity accuracy completeness currency or reliability of the information including any opinion or advice contained in this publication To the maximum extent permitted by law FWPA disclaims all warranties of any kind whether express or implied including but not limited to any warranty that the information is up to date complete true legally compliant accurate non misleading or suitable To the maximum extent permitted by law FWPA excludes all liability in contract tort including negligence or otherwise for any injury loss or damage whatsoever whether direct indirect special or consequential arising out of or in connection with use or reliance on this publication and any information opinions or advice therein and whether caused by any errors defects omissions or misrepresentations in this publication Individual requirements may vary from those discussed in this publication and you are advised to check with State authorities to ensure building compliance as well as make your own professional assessment of the relevant applicable laws and Standards The work is copyright and protected under the terms of the Copyright Act 1968 Cwth All material may be reproduced in whole or in part provided that it is not sold or used for commercial benefit and its source Forest amp Wood Products Australia Limited is acknowledged and the above disclaimer is included Reproduction or copyi
68. ore sophisticated these uncertainties will be minimised but never eliminated So when trying to assess the impact of future climates on forest growth it is important to understand there will be range in potential futures rather than a single future There are some limitations in using the Climate Futures Framework The NRM boundaries do not always follow climatic gradients and as a result there will be occasions where the worst and most likely future climates are reversed Often the most likely is actually very close to the worst outcome and the results will be very similar To allow a uniform approach across the NRM regions we have assumed the changes in average temperature and annual rainfall accurately define the best worst and most likely outcome This may not always be the case We chose a relatively simple stationary approach to the statistical downscaling of the future climates This method is appropriate for use with average monthly climate but there are some limitations Most importantly there is the assumption there is no change in the number of rain days in future scenarios compared to historical climate Where there is an overall drying trend this can result in an increased number of days with very small rainfall events It 1s more likely rainfall will be concentrated into fewer rain days with more intense precipitation events Nor does it capture the predicted increase in extreme weather events such as droughts 22 Comparative phys
69. orest plantations prediction and effective adaptation Report produced by the CSIRO Climate Adapation Flagship and the Australian Government Department of Agriculture Fisheries and Forestry Acknowledgements We wish to thank the industry steering committee members for their helpful guidance and ongoing suggestions for improvement of the system This committee was chaired by Martin Stone Forestry Tasmania and comprised Andrew Moore Green Triangle Forest Products 26 Ben Bradshaw Australian Bluegum Plantations Don McGuire Forestry SA Geoff Rolland Albany Plantation Forests Limited Andrew Lyon Forest Products Commission WA Sara Mathieson WA Plantation Resources Steven Elms Hancock Victoria Plantations We also express our gratitude to thank Georg Wiehl Tammi Short Craig Baillie Ian Dumbrell and Stuart Crombie for their contributions to the field work and data synthesis We also thank Justine Edwards for her tireless efforts helping us with promoting adoption of the system The project was financially supported by CSIRO Sustainable Agriculture Flagship Forest and Wood Products Australia the CRC for Forestry and the partner companies Green Triangle Forest Products WA Plantation Resources Hancock Victoria Plantations Australian Blue gum Plantations Forestry Tasmania Albany Plantation Forests Limited and the Forest Products Commission 27 Researcher s Disclaimer The following disclaimer applies to
70. ose whether the residues are burnt or not burnt as burning will result in loss of much of the volatile nutrients Fig 12 Nutrient export tab highlighting 1 harvesting options 2 predicted biomass removed and retained 3 the predicted macronutrient export and 4 the predicted micronutrient export TI kees Az a NE D Welcome daniel ry gt ge WC Lu F EI AS 2 EL JJ FPOS Current sites Carpenters Site information Nutrients Economics Productivity Water Use Nitrogen Species Climate Model Below you may observe the nutrient and biomass removed from your site based on site treatments New site 016 Infomation is derived from CABALA outputs Testsawlog radiate Predicted nutrient export at harvest Test sawlog regime 2R ka Example site Rainfall Evaporation d 1000 1200mm Above average rainfall deep sand 4 m depth E globulus 900 stems ha Age 10 years Predicted final volume 292 m2 ha Ts Pradicted final LAT Notes on thse predictions Nutrient estimates are based on measures of trees under E xport ount for luxury consumption 2 These relationships are 3 2 m m Predicted macronutrient e oxiately 300 m2 ha Beyond this they are extrapolated NPV 3860 22 and should be used with caution IRR NA 300 250 200 3 150 The system estimates the biomass removed in stem wood and non stem wood components and also the amount retained on site Item 2 Fig 12
71. output are selected individually through the check boxes Item 2 Fig 20 54 Fig 20 Wood flow predictions tab highlighting 1 the pull down comparison options 2 site selection 3 graphical output of standing volume prediction 4 graphical output of harvest volumes and 5 tabular output of standing volume and harvested volumes Multi site outputs Wood flow predictions Welcome daniel 4 M e gt EN S S A Lx Le eh Do RU a ICA Ve NO Ics cian ee BE JA U je 13e Si met FPOS Home Site Inputs Site Outputs gt Multi site outputs gt Sensitivity analysis Mapping Tool Change Password Log O e JJ FPOS E Current sites Boyup Brook test Carpenters a Model efficiency Wood flow predictions w The Wood Flow Predictions section allows users to select sites where preducted volumes and woodflows are available The data is presented so that the user may assess the complete life cycle of all selected sites over time The user may also observe the difference in applying different rainfall and climate models to all of the selected sites Only sites where a CABALA output exists are available for selection The user may process more CABALA outputs for sites that contain all manditory parameters by selecting the Run CABALA button below 1 Comparison options New site 001 New site 016 Pinaster WA test radiata GT Test sawlog regime Climate model Standing Site selection vo
72. predicted af e Site details and predicted outputs growth and nutrient outputs for that e Nutrient exports specific scenario These outputs can be compared with real world data for comparison As there is a spatial e Economic analyses component to the scenarios the inclusion of spatial tool enables communication of e Productivity Curves results graphically e Water Use efficiency e Species analysis Site inputs e Climate model analysis e Nitrogen nutrition analysis e Product output analysis 24 The site editor allows you view add delete and edit i Multi site outputs your site characterisation 2 7 75S View results across your portfolio of sites details and economic eee including observed vs predicted productivity scenarios Site information and predicted woodflow under different may also be uploaded from a ees scenarios xls file An example of the e CABALA model prediction efficiency file format is available here e Explore wood flow predictions over i time across your portfolio of sites e Summary of all sites e Understand parts of your portfolio of e View add edit individual sites that are likely to be more site details responsive to nutrients e Summary of all productivity observations e View add edit economic scenarios Sensitivity analysis Perform a matrix analysis using one or many of your sites to find out the predicted sensitivity of productivity to site climate and Mapping management factors Use the FPOS M
73. r saving Fig 7 Site Inputs Site Summary page Highlighted areas are 1 Site listing panel 2 Site input page tabs and 3 Print screen icon 4 Add new site button 5 Upload site file button 6 Site edit and delete buttons gt Site Inputs gt Site summary Welcome daniel d H Print screen Below is a eege of the sites ate have created Limited details appear in this table for detailed tails and select the site of interest from the list on the left pl d 2 Plantable G C Thinning Climate Species Rotation harvest 3 area ha ed regime model i p i on Carpenters Western Rainfall 3 300 best i O Edit delete buttons Australia 1100 1200mm globulus sph 4y case i Evaporation scenario 1200 1400mm Example Western Rainfall E 1 no Edit Delete site Australia 1100 1200mm globulus Pulpwood change Evaporation coppice 1000 1200mm List of sites New site Western Rainfall E 2 best Edit Delete 016 Australia 1100 1200mm globulus Pulpwood case Evaporation seedling scenario 1000 1200mm Test Green Edit Delete sawlog Triangle radiata Test Green Rainfall P 3 300 no Edit Delete sawlog Triangle 500 600mm radiata sph 4y change regime Evaporation 1000 1200mm select a column heading to sort by that column 38 Site Details The site details page Fig 8 allows the user to view and or edit the details of each of their sites scenarios The buttons at the top highlighted 1 4 Fig 8 allow
74. rther inventory may be useful as the stands more fully occupy the sites Some of these sites have been planted on gravels and sand dunes and the hydraulic and nitrogen mineralisation models in CABALA are unlikely to capture the processes accurately Some of the sites are in areas of high terrain variability and predictions may be improved with fine downscaling of climate Conversely the sites in Victoria are generally under predicted and further work is required to understand why the reported growth rates are much higher Fig 7 CABALA validation using data from 32 E nitens plots from Tasmania and Victoria Stands are at time of measurement were between 3 and 12 years of age and are predominately un thinned stands 350 300 N LI 200 ra LI O lt 0 56x 69 7 CLD O R 0 59 100 e Predicted Volume m ha so 1 0 200 400 600 800 Observed Volume m ha This parameter set needs to be used with caution until the underlying issues can be resolved as absolute measures of production may not be accurately predicted A more suitable use may be to look at relative changes in production as a result of varying silviculture Fig 8 CABALA validation for E nitens split between Tasmania a and Victoria b Stand volume is generally over predicted on Tasmanian sites and under predicted on Victorian sites 160 a Tasmanian sites 400 b Victorian sites 140 350 A 120 300 Em E 100 250 a 5 S 80 200
75. s not available until the user logs in Typically logins are available at an organisational level and any information that users enter into the system site information growth data economic model is only available to that login The system is available to 1 members of the Forestry CRC and 2 FWPA levy payers If you fit into one of these categories and don t already have organisational access please contact Daniel Mendham csiro au for login details Note that you need to accept the disclaimer in order to log into the system Fig 5 FPOS login page F gt O S FOREST PRODUCTIVITY OPTIMISATION SYSTEM Welcome to the Forest Productivity Optimisation System Author Daniel Mendham Web Development Kimberley Opie User Name Welcome to the Forest Productivity Optimisation System FPOS daniel website hani Password FPOS attempts to synthesize and communicate complex growth and nutrition models for a number of tree species and products in southern Australia The user can select output from a set of predefined parameters and is provided with predicted growth and nutrient outputs for that specific scenario These outputs can be compared with DISCLAIMER The general information and tools available at this real world data for comparison As there is a spatial component to the website are for use in assisting tree plantation growers in making scenarios the inclsion of spatial tool enables communication of decisions about managing th
76. s m s 0 1 VPD KPa LAI The leaf area index LAI showed similar trends between the 2 species Fig 21 with the exception that E smithii LAI was tending to increase over the first year of measurement while the E globulus LAI had already peaked and showed a decline until the spring of 2012 when both species had marginal increases in LAI E smithii maintained a higher LAI than E globulus around 0 3 units from October 2011 until the end of the experiment 19 Fig 21 Leaf area index over the duration of the experiment Error bars show 1 standard error of the mean 1 8 1 6 1 4 12 LA E os 3 0 6 em em 04 E globulus 02 E E smithii 0 e e e e CN N N N e en e ve e e e ei e e e e 3 6 E s 3 SS 3 6 Ss 8 Date Leaf water potential Both species showed very similar patterns of pre dawn water potential over the experimental period Fig 22 but E smithii tended to have a lower pre dawn water potential at almost all of the measurement times suggesting that it was slightly more water stressed than E globulus at any given time It is worth while noting that the biggest difference in pre dawn water potential in February 2012 was also associated with the biggest difference in 10am photosynthetic rate cf Fig 19 The midday water potential also showed a similar trend in both species over time Fig 23 with E smithii tending to have a similar or lower water potential to E globulus
77. sponsibility or liability is accepted in the event that the website is temporarily unavailable due to technical or other reasons Use of this website assumes agreement to these conditions of use COPYRIGHT 2013 28 29 Appendix 1 FPOS Climatic Zones and future climate scenarios The latitude and longitude is the location of a representative SILO cell within the climate zones identified FPOS Latitud Worst Most Likel Best eamate e PER CARA Megion Scenario a Scenario Zone CZ001 143 1 36 8 North Central CSIRO3 5 inmcm3 miroc3 medres CZ002 141 4 37 Wimmera CSIRO3 5 bccr bcm2 miroc3 medres CZ003 144 95 37 05 Goulburn Broken CSIRO3 5 inmcm3 miroc3_medres CZ004 142 15 37 7 Glenelg Hopkins CSIRO3 5 miroc3 hires miroc3 medres CZ005 143 5 38 3 Corangamite CSIRO3 5 inmcm3 miroc3 medres CZ006 141 05 37 9 Glenelg Hopkins CSIRO3 5 miroc3 hires miroc3 medres CZ007 142 55 38 3 Glenelg Hopkins CSIRO3 5 miroc3 hires miroc3 medres CZ008 141 35 38 05 Glenelg Hopkins CSIRO3 5 miroc3 hires miroc3 medres CZ009 142 95 38 35 Glenelg Hopkins CSIRO3 5 miroc3 hires miroc3 medres CZ010 142 3 37 25 Glenelg Hopkins CSIRO3 5 miroc3_hires miroc3 medres CZ01 1 143 3 38 5 Corangamite CSIRO3 5 inmcm3 miroc3 medres CZ012 143 6 38 45 Corangamite CSIRO3 5 inmcm3 miroc3 medres CZ013 145 95 36 25 Goulburn Broken CSIROS3 5 inmcm3 miroc3 medres CZ014 149 36 55 Southern Rivers miroc3 hires miroc3_medres inmcm3 CZ015 147 15 35 65 Murray CSIRO3 5 inmcm3 miroc3 me
78. ssed in South Australia as the representative points for the climatic zones in the Green Triangle which did extend into SA see Fig 2 in Appendix 2 were coincidentally located on the Victorian side of the border All Plots NRM Regions BEI csiro3 5 becr_bem2 inmcm3 miroc3 hires gs miroc3 medres Downscaling future climates Historical climate data for each climatic zone refer to FPOS manual for more detail on climatic zones was obtained from the Bureau of Meteorology s Data Drill http www longpaddock qld gov au silo The data in the Data Drill is synthetic consisting of interpolated grids splined using data from meteorological station records but has the benefit of being available for all locations in Australia with a resolution of 0 05 degrees Blocks of 30 years of historical data were used for the base data 1975 2005 as defined by the IPCC as the base historical climate A relatively simple stationary approach was used to modify the historical weather The temperature and rainfall was modified using monthly averages from the potential future climates Radiation was not adjusted as it 1s expected there will be only small changes of between 1 to 2 CSIRO 2007 The monthly changes in temperature for the 2030 time period were added to the historical data Rainfall was modified using proportional change a simple additive approach is not appropriate given the variati
79. te Futures Framework can only be used for regional assessments based on NRM boundaries Each NRM region containing an FPOS climatic zone was run and the best worst and most likely future climate was selected Only a limited number of the 24 Global Circulation Models had maximum and minimum temperature change values available resulting in a pool of only 5 models to select from Fig 10 The 5 models are shown in Table 2 Table 2 Summary of global circulation models GCM s used in the FPOS system Model Publisher Publication date CSIRO 3 5 CSIRO 2006 bccr_bcm2 Bjerknes Centre for Climate Research University of 2005 Bergen inmcm3 Institute of Numerical Mathematics 2004 Russian Academy of Science Russia miroc3 hires Japanese Centre for Climate System Research 2004 miroc3 medres Japanese Centre for Climate System Research 2004 10 Fig 10 The global circulation models selected in each NRM region The colours represent the model selected for that region Future climate predictions vary substantially across regions and what may be the most likely or best future climate in one region may be the worst in another Note that best is the model that predicts the highest rainfall and lowest temperature increase worst is the model that predicts the lowest rainfall and highest temperature increase while most likely is the temperature and rainfall changes that most of the models predict Note that no NRM regions were asse
80. those e predicted in CABALA Sites without observations will not be selectable If CABALA outputs are not available for the selected site then NA will appear in the table below and they will not be included in the relationship assessment Predicted values of 0 indicate that CABALA did not process the value correctly and they will not t be included in the relationship assessment radiata GT Test sawlog regime Selected sites Observed vs predicted outputs Example site Rainfall Note If site in not 1100 1200mm selectable inadequate details Evaporation E the site to calculate volume or CABALA 1000 1200 has not been run for this Above average re volume 267 4 m ha Predicted final LAI 0 5 m2 m NPV 1982 19 IRR NA Note that the appearance of NA in predicted values means CABALA has not been run for this scenario Values of 0 indicate that CABLA failed to run These observations are not included in the analysis Wood flow predictions The wood flow predictions allow the user to explore the potential impact of rainfall variation and or alternative climate model on the predictions of long term standing volume and harvested wood volumes The user can vary comparison options independently for rainfall variation and for climate model Item 1 Fig 20 with the predicted output shown graphically for standing volume Item 3 Fig 20 and harvest volumes Item 4 Fig 20 The sites that are included in the
81. ti site outputs Sensitivity analysis Mapping Tool Change Password Log Out 2 Current sites en NE Productivity Climate Model Site information Nutrients Economics Water Use Nitrogen Scenario economic analysis K JOME H3 Example site New site 016 radiata GT Test sawlog radiate Testsawlog regime Current economic scenario Example scenario i Alternative economic options Choose alternative economic scenario Daniel20130227 3 Current rotation length y 18 Choose alternative rotation length y 15 Detailed economic outputs in present values for a rotation of 15 years 2000 4000 6000 8000 Carpenters 10000 Rainfall 42000 1100 1200mm Evaporation HE 1200 1400mm 16000 Average rainfall deep clay loam 8 m depth E globulus 1500 stems ha Age 18 years Predicted final P Estimated NPV and IRR IRR H amp RU O 0 10 20 30 10 20 30 Harvest Ag Harvest Age Year green tonne Amount in future ha Present Value ha Establishment Costs Planting Cost 627 00 o 627 00 Establishment Costs Soil Preparation Cost 102 00 102 00 Establishment Costs Establishment Cost 1500 00 1500 00 volume 521 2 m ha Predicted final LAI 1 7 m2 m NPV 7041 74 IRR 5 7 Unable to display graph Annual Costs Annual Costs Pruning cost Annual Costs Pruning cost Annual Costs Pruning cost Annual Costs Return Return Return Thinni
82. understand the predicted impacts of climate change rainfall variability management including stocking rate and thinning regime and site climate soil type soil depth soil fertility on plantation productivity and profitability Adoption of the system to aid managers in site selection and site management including over multiple rotations could easily improve productivity and or reduce risk by at least 10 at many sites The system provides a wealth of information currently and is also a potential platform for delivery of new research output as it is generated The CRC Forestry FWPA and developers are keen to assist with deployment and welcome feedback or suggestions for improvement 25 References Battaglia M 2012 Milestone Report to FWPA New knowledge on responses to drought heat waves and CO2 incorporated into models Project number PNC 228 1011 Battaglia M Sands PJ White D Mummery D 2004 CABALA a linked carbon water and nitrogen model of forest growth for silvicultural decision support Forest Ecology and Mangement 193 251 282 Clark J M Whetton P H Hennessy K J 2011 Providing application specific climate projections datsets CSIRO s Climate Futures Framework 19 International Congress on Modelling and Simulation Perth Australia 12 16 December 2011 http mssanz org au modsim201 1 CSIRO 2007 Climate Change in Australia Technical Report 2007 http www csiro au Organisation Structure D
83. wth of production forests Currently there are 24 global circulation models 23 from the Coupled Model Intercomparison Project CMIP3 plus the CSIRO MK3 5 model that are well tested for Australia and readily available We also used the A2 emission scenario see Fig 1 which assumes continued rapid economic growth and increasing population with minimal global migration to a low CO emissions economy Note that current global emissions are above this scenario Fig 1 Fig 1 Summary of emissions scenarios we have used the A2 scenario in this project Source USGCRP 2009 Carbon from Fossil Fuel CO Emissions Atmospheric CO Concentrations 1000 gt 900 p E Q amp 800 0 D o D 700 9 c c 600 2 c S so ile oe sd a 300 2000 2020 2040 2060 2080 2100 2000 2020 2040 2060 2080 2100 Year Year Carbon from Fossil Fuel CO Emissions Even higher emissions scenario A1FI Higher emissions scenario A2 Lower emissions scenario B1 Stabilization 450 ppm e e Observations Carbon Gigatons yr 1990 1995 2000 2005 2010 Year There can be substantial differences between the future climates predicted by the models and it often unviable for end users with limited resources to run all 24 models to cover the range in potential futures While it may be tempting to use a single mid range model this overlooks other out lying and potentially important future climates Clarke 2011 and does not prov
84. y Predicted final LAI Stocking rate stems ha 900 3 2 m m ne NPV 3860 22 Rotation iR gr NA Planned harvest age 10 250 Distance to port km 50 o E amm Economic scenario Example scenario o Include in CSIRO CRC model improvements True Comments test Predicted outputs Predicted final volume 292 m3 ha Predicted final LAI 3 2 m2 m2 Predicted NPV 3860 22 Predicted IRR NA 300 250 200 Predicted Outputs Volume nn o 100 D 0 4 10 Age Solid dots that appear on the graph above represent observed volume 45 Nutrients The Nutrients tab allows the user to explore the impacts of different harvesting options on export of biomass and nutrients from the site This information is based on the quantity of nutrients in each of the biomass fractions so 1s subject to some error where there has been significant luxury uptake of nutrients or the biomass split between components is different at a given site to the values used in the FPOS system The options for levels of residues removed are e Whole tree extraction meaning that the trees are cut at the base and removed from the site without debarking or debranching e Residues retained on site If residues are retained on site the user needs to select whether the bark is removed on site or off site If the bark is removed at a landing it should be considered to be off site unless it is redistributed back across the site The user also needs to cho

The Forest Productivity Optimisation System – A decision support

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The Forest Productivity Optimisation System &ndash; A decision support

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The Forest Productivity Optimisation System – A decision support