Next Article in Journal
Soil Microbial and Organic Carbon Legacies of Pre-Existing Plants Drive Pioneer Tree Growth during Subalpine Forest Succession
Next Article in Special Issue
Biomass Production and Quality of Twelve Fast-Growing Tree Taxa in Short Rotation under Mediterranean Climate
Previous Article in Journal
Individual Tree Basal Area Increment Models for Brazilian Pine (Araucaria angustifolia) Using Artificial Neural Networks
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Testing New Provenances of Eucalyptus polybractea: A Eucalypt Oil Mallee Adapted to Semi-Arid Environments

1
CSIRO Australian Tree Seed Centre, GPO Box 1700, Canberra, ACT 2601, Australia
2
3 Canning St, Ainslie, Canberra, ACT 2602, Australia
3
G.R. Davis Pty Ltd., Queanbeyan, NSW 2620, Australia
*
Author to whom correspondence should be addressed.
Forests 2022, 13(7), 1109; https://doi.org/10.3390/f13071109
Submission received: 1 June 2022 / Revised: 11 July 2022 / Accepted: 12 July 2022 / Published: 15 July 2022

Abstract

:
Novel genetic accessions of Eucalyptus polybractea from a previously untested, hotter and drier part of the species’ natural range were tested in a common garden trial at a semi-arid site in NSW, Australia. Eucalyptus polybractea is a mallee eucalypt cultivated for essential oils (1,8-cineole), bioenergy and carbon sequestration on dryland sites in southern Australia (sites receiving about 450 mm mean annual rainfall, MAR). A trial of six previously untested provenances from the relatively hot, dry part of the species’ natural range in South Australia (SA) (250–450 mm MAR) was established alongside seven provenances from New South Wales (NSW) and Victoria within a commercial plantation in NSW. The trial was assessed at age 3.7 years for growth and oil characteristics. While survival was excellent, most of the SA sources were slower growing and of sub-standard oil concentration and quality relative to those from Victoria and NSW. However, a single SA provenance, with the highest oil concentration and 1,8-cineole percentage of all provenances tested, may have potential as a source of selected germplasm. Infusion of SA material into the breeding populations of E. polybractea, which are currently based on NSW and Victorian selections only, may provide more resilience in the face of hotter and drier temperatures expected under projected climate change scenarios, and/or allow the introduction of the species to hotter and drier climates in Australia or other parts of the world with semi-arid climates. However, high-intensity selection of infusions will be required to maintain the growth and oil characteristics in the existing breeding population.

1. Introduction

Eucalyptus polybractea R.T. Baker (blue-leaved or blue mallee) is a short (5–10 m), multi-stemmed mallee eucalypt. Mallee eucalypts are typically adapted to harsh, drought- and fire-prone environments and are able to regrow their aboveground shoots repeatedly following their loss to fires, animal browsing or harvesting. Two disjunct regions of provenance (ROP), West Wyalong, New South Wales (NSW) and Bendigo, Victoria (Vic), have been harvested as a source of 1,8-cineole-rich Eucalyptus oil since the early 1900s (Shiel, 1985). However, it has more recently been confirmed that a third ROP exists in South Australia (SA) [1,2]. The SA ROP comprises discrete upland provenances from the Flinders Ranges to the Gammon Ranges (Figure 1). SA provenances of E. polybractea have not been harvested commercially for their foliar oils, nor, to our knowledge, have they previously been cultivated for any purpose.
Eucalyptus polybractea is commercially significant as the major domestic source of Eucalyptus oil in Australia. It is increasingly sourced from plantations rather than harvested from natural woodlands. It produces exceptionally high-quality, medicinal-grade oil used in health care products, disinfectants and solvents [3,4]. It is this grade of oil that commands the greatest share of the current international market. Eucalyptus oils are classified and priced according to the percentage of 1,8-cineole (typically ranging from 70%, to near-pure) and must legally satisfy the requirements of various pharmacopoeial monographs [5,6]. E. polybractea oil is among the few that meet all international and national standards direct from the still. The 1,8-cineole levels (%cineole) in this species generally range between 75% and 90% of total oil while oil concentration in fresh foliage from coppiced trees is typically between 4% and 6 % (w/w% dry weight) with a range of 2% to 10% [7].
In the 1970s, two of Australia’s largest E. polybractea oil-producing companies, GR Davis Pty Ltd. at West Wyalong, NSW, and Felton, Grimwade and Bosisto’s Pty Ltd., 40 km west of Bendigo, Vic, commenced transition from harvesting wild stands to plantations. Early plantations were established from wild-collected seed with only rudimentary levels of selection for oil yield and %cineole. By the 1990s, this had changed [8], with the realisation that the drivers of oil quality and yield per hectare, namely %cineole, concentration of oils in the leaves, and leaf biomass, were independent traits of low (growth traits) to high (oil traits) heritability and all amenable to concurrent improvement by selection and breeding [9,10]. The companies in NSW and Vic commenced tree improvement based on seed and clones from stands near their centres of operation in the 1990s: though formal provenance and family testing was not carried out, the local region of provenance is thought to perform best at both locations. The Government of Western Australia also commenced planting and domestication of E. polybractea in the 1990s, motivated by the need for economic incentives to encourage revegetation for dryland salinity control. Returns from integrated production of biomass bioenergy, activated charcoal and Eucalyptus oil provide an impetus for planting on privately owned farmland [10,11,12]. An additional use for E. polybractea in southern Australia is carbon sequestration, where it is planted and retained in perpetuity [13].
Adjusting the breeding programs of key crops to provide adaptation to future climate-change-impacted environments is now a global priority [14,15]. Testing of crop wild relatives from warmer and drier places is seen as an informative strategy, applicable to analogous climates that are likely to become hotter and drier due to climate change, as these populations will already have been under natural selection and be well adapted [16]. Deploying provenances of long-lived forest trees from hotter and drier climates to those that are currently more mesic, but likely to undergo significant climate change within the next generation and beyond, has also been suggested [17]. The importance of common-garden testing of a wider range of forest tree species in this context has also been argued for [18].
Climate change is projected to lead to a hotter and drier climate in southern Australia [19] where E. polybractea is grown, presenting challenges to plantation establishment and productivity [20]. The historical and present climates (Australian Bureau of Meteorology (BoM) climate records. Available online: http://www.bom.gov.au/climate/ accessed 17 June 2022) of the NSW and Victorian ROPs are similar—Mean Annual Rainfall (MAR) is around 475 mm while Mean Maximum Temperature (MTmax) is 21.2 and 24.1 °C at Bendigo and West Wyalong, respectively (see Figure 1 for MAR and Table 1 for additional detail). The climate in the South Australian ROP is significantly drier (310–395 mm MAR) and exposed to hotter maximum temperatures (25.3 to 26.5 °C MTmax), though due to their higher elevation, Mean Annual Temperature experienced by these provenances is similar or slightly lower than those of the NSW ROP. The SA provenances may therefore be better adapted to future climates in the present industrial plantation regions and could potentially be used to expand the plantation range to hotter and drier environments.
The objective of this study was to test the SA provenances relative to those of NSW, in a common-garden trial situated within a commercial plantation on a semi-arid site at West Wyalong in southern Australia. Traits assessed included survival, growth performance, oil yield and oil quality. The implications of the results are discussed in the context of germplasm exploration and genetic selection for semiarid environments and environments that are likely to become hotter and drier in the face of climate change.

2. Materials and Methods

2.1. Selection of Seedlots for Trial

Eucalyptus polybractea herbarium records for SA were downloaded from the Atlas of Living Australia (Available online: http://www.ala.org.au accessed on 17 May 2014) and used to target sampling areas. Seed and leaf samples were collected by the CSIRO Australian Tree Seed Centre (ATSC) from 54 trees representing six provenances, which were further grouped into three ROPs, namely New South Wales, Victoria and South Australia (Table 1, Figure 1). Shoot samples (leaves, fruit, flower capsules) from each mother tree were examined and verified as E. polybractea by staff at the Australian National Herbarium (CANB). Leaf tissue and extracted DNA samples from these trees were also retained for future reference. Seed of families of Vic and NSW origin were chosen from those available at ATSC. The 48 families from West Wyalong were assigned to six putative provenances, each a remnant of a much wider occurrence before clearing for agriculture started more than 100 years ago. A single provenance from Wedderburn, Vic, was also included as a performance checklot.

2.2. Trial Establishment and Design

Seedlings for the trial were sown in August 2016 at Narromine Transplants Pty Ltd., Narromine, NSW, Australia, in 90 cm3 Hyco® tray cells using the open-pollinated seedlots specified in Table 1. The trial was planted in January 2017 amongst GR Davis Pty Ltd. commercial oil plantations of E. polybractea west of West Wyalong, NSW (Figure 1) when the plants were around 30 cm tall. The planting site had a slight southerly aspect. Soils are classified as sandy clay loam. The MAR for the region is about 470 mm, uniformly distributed. MTmax is 24.1 °C.
An Alpha trial design was utilised with families randomly allocated to five-tree row plots with six replicates of 109 treatments. Spacing was 1 m within rows and 3 m between rows. A single-row surround of E. polybractea was planted to minimise edge effects. The trees were watered-in at time of planting, a routine establishment practice in summer.

2.3. Growth Traits

At age 3.7 years after planting and 1.6 years after the first coppice harvest, all trees in replicates one to five were measured for height (HT), width of crown (CW) across the row and crown leaf density (scale: 1 sparse to 6 very dense) (CD). To estimate green, aboveground biomass (BM) 50 (23 NSW, 3 Vic and 24 SA), trees covering the range of height growth in the trial, with sample sizes proportional to their representation in the trial (see Table 1), were harvested and weighed in the field. A crown volume index (CVI) was calculated as CVI = HT × CW2.

2.4. Foliar Oil Characteristics

Large provenance bulk samples were constructed by stripping 20 g of leaf from the mid-crown of all individual trees from four replicates, with replicates kept separate. Two 100 g samples for distillation and a 10 g sample for moisture determination were subsampled from the large, thoroughly mixed bulks, in the field. These samples were placed in paper bags and allowed to air-dry.
Oil extraction was undertaken by hydrodistillation in the laboratory of GR Davis Pty Ltd., NSW, using Clevenger-type stills. A two-hour distillation time for each sample was employed following optimisation trials to determine time to complete extraction. Oil concentrations (w/w% fresh weight) were derived from the known weight (100 g) of fresh leaves, the volume of oil extracted from that known weight of leaves multiplied by a specific gravity of 0.92 [21]. Moisture content of the 10 g samples of leaves was determined after oven drying (70 °C, 12 h), allowing calculation of oil concentration on a dry weight basis (w/w% dry weight).
Gas chromatography of distilled oils was carried out on a GCMS-QP2010SE (Shimadzu, Japan) with a DB-35 GC column. Compounds were identified by matching their GLC retention time to that of known compounds. The oils of E. polybractea are known to contain at least 55 terpenoid compounds [22]. This study assessed 16 priority compounds that determine commercial oil potential under the BP [5] standard and that are known to influence physical properties and fragrance.

2.5. Data Analysis

Determination of the best proxy estimator for BM was carried out by exploratory linear (FIT directive) and non-linear model fitting (FITCURVE directive) using regression and linear fitting functionality in Genstat 19 (VSN International, Hemel Hempstead, UK). The relationships between BM and both untransformed and log-transformed explanatory variates (HT, CD, CW, CVI) were considered. Preliminary analysis showed that the best fits were achieved by linear regression and exponential curve fits with ROP fitted as an explanatory factor. Relationships among traits were visualised using the R software [23] library GGPLOT2 [24].
Linear Mixed Models of individual tree data for each trait were analysed as follows:
y = Xb + Zu + e
where y is the vector of observations on the trait; b and u are vectors of fixed- and random-effect estimates, respectively; X and Z are incidence matrices for fixed and random model terms, respectively, and e is a vector of random residual effects. For the growth traits, vector b contained sub-vector estimates for fixed effects of replicate and subpopulation (provenance) effects, and u contained sub-vectors for the random effects of incomplete blocks (field rows and columns) and plots. Survival was analysed using a Generalised Linear Mixed Model as described in Equation (1), but assuming a binomial data distribution and a logit link function. Oil trait data (provenance bulks from four replicates) were analysed using a simplified form of Equation (1) incorporating fixed effects only, with vector b containing replicate and genetic effects. Significance of fixed effects was gauged using Wald F tests and approximate significance of differences between pairs of provenances gauged by comparing predicted means and their average standard errors of difference, with means more than twice the SED apart considered to be significantly different. All analyses were implemented in Genstat.

3. Results

3.1. Survival and Growth

Survival was high for all provenances and averaged 94% overall with no significant difference among provenances (p = 0.28). Linear regression between BM and each of HT, CW and CVI traits (untransformed data) resulted in significant relationships (p < 0.001) with 66.7%, 77.4% and 91.4% of variance accounted for, respectively. Inclusion of the region of provenance (ROP) factor was significant for CVI and CW (p < 0.001 and p = 0.03, respectively) although dropping these terms only reduced explained variance by around 2% in both cases. Analysis of log-transformed data gave slightly better relationships between BM and both HT (86% variance explained) and CW (78.7% variance explained). Similarly, an exponential curve fit involving the CW and BM data was superior to the straight-linear fit (85.5% versus 77.4% variance explained, respectively) between these variates. Fits for the best linear and curvilinear models for each trait are shown in Figure 2.
The relationship between BM and the subjectively scored CD trait was also significant (p < 0.001), explaining 52.3% of the variance.
Significant differences (p < 0.001) were found among ROP and provenances in all growth and oil quality variates. Provenances from NSW and Vic were generally not significantly different from each other but accumulated more biomass (estimated by CVI) than those from SA (Table 1). Buddigower and Blinman provenances performed particularly poorly (although the latter was only represented by seed sampled from two mother trees), while Wedderburn performed best.

3.2. Oil Characteristics

Significant differences (p < 0.001) were found among provenances for both oil yield and %cineole. Generally, there was little within-provenance variation of oil yield and %cineole (distributions are shown in Figure 3; %CVp in Table 2) and oil yield was consistent among the NSW provenances (around 5%–6% w/w dry weight). The Victorian checklot (Wedderburn) was also within this range. Oil yields were generally much lower for the SA provenances (around 3%–4%), with the major exception of The Oaks. The latter provenance had an oil concentration 31% higher than the eastern provenances and 50% higher than other SA provenances. The Oaks also had the highest %cineole of any oil, while SA provenances Blinman, Mt Hack and Wilpena contained less than 70% cineole (below the threshold for medicinal oil). Significant differences among ROP and provenances were also detected for some minor oil constituents (see Supplementary Material Table S1 for a full table of oil analysis results).

4. Discussion

Previously untested provenances of E. polybractea from relatively dry provenances in SA demonstrated mixed potential in an industrial plantation trial at West Wyalong, NSW. While the survival of SA material was excellent, matching that of NSW and Vic provenances, the growth performance was generally inferior to those locally native to West Wyalong and to the Wedderburn, Victoria provenance. Oil yield of SA provenances was generally low, around 3%, but one, The Oaks, had the highest yield (7.5%) on a dry leaf-weight basis of any provenance. Moreover, this provenance had the highest %cineole composition. The average oil concentration of the eastern state provenances was 5.7%, which is consistent with published averages for the species [7]. The %cineole composition of some SA provenances was slightly below the threshold for medicinal-grade oils, but still well above many other eucalypt species. The implication is that selection for oil traits from SA material should be targeted to the better provenances, though high-intensity selection for vigour would also be required. Testing of more families from The Oaks provenance and further exploration of still-untested provenances in South Australia is certainly warranted.
The relationship between green, aboveground biomass (BM) and measured growth traits (HT, CW) was strong, particularly when the measured traits were combined into a CVI in the first coppice rotation of this trial. This finding echoes those of other studies of mallee eucalypts that have made use of CVI, e.g., [25,26]. A difference between this study and others is that our CVI involved only a single measure of width, rather than two orthogonal crown measures: the decision to take only one measure was partly driven by the practical difficulty of identifying crown width in adjacent trees once crown closure has occurred. Taking a single measure is quicker, allowing the assessment of more trees per unit time, and it is notable that the single width (CW) measure explained 86% of the green biomass variance. The crown density score (CD), which was assessed qualitatively, was also a reasonably effective estimator of BM (54% variance explained), though markedly inferior to CVI (91%). Rapid biomass assessment techniques are potentially useful for mass screening of trees, allowing for higher selection intensity, leading to increased genetic gain. To this end, aerial assessment of crown width using unmanned aerial vehicle (UAV) technology, e.g., [27,28] might significantly increase the efficiency of screening of trials such as this, especially as the CW parameter, which can readily be obtained from an aerial view, is an effective estimator of biomass.
Climate change is expected to impact southern Australia including the current and target E. polybractea plantation zones in NSW, Victoria and Western Australia. There is very high confidence in continued, substantial increases in projected temperatures, and high confidence that cool season (winter and spring) rainfall will decrease, driven by further increases in greenhouse gas concentrations [19]. Testing and selection of E. polybractea from more xeric environments is therefore a good strategy to provide resilience to hotter and drier climates in the current planting zones. Another potential application for the SA provenances of E. polybractea is planting in drier sections of the Western Australia wheatbelt or further west in NSW. Eucalyptus polybractea, based mainly on NSW selections, is currently planted in the relatively high rainfall part of the WA wheatbelt with E. lissophloia being used on drier sites [26]. Testing the SA material on these sites would not only provide an indication of adaptation there, but also serve as an analogue of the climate futures that the plantations might experience in the current plantation zones in both Western Australia and the eastern States. The species would likely be suitable to other parts of the world with Mediterranean or dry temperate climates, although it has not been widely tested outside of Australia.
Although a considerable number of Australia’s > 600 Eucalyptus species have been widely tested in Australia and overseas, much of the testing has been focused on fast-growing species and provenances endemic to, and suitable for planting in, high rainfall environments. Plantation forestry is likely to experience a shift towards more climatically and edaphically challenging sites [20], and be called upon for goods such as biomass energy [29], biofuels [30], chemical constituents and carbon sequestration, in addition to traditional timber and fibre products. Testing of previously unexplored genetic material including novel species from more xeric environments, and as demonstrated here, novel provenances of species that are already under domestication, will be an important element of industrial forest crop development.

5. Conclusions

This paper presents a first-time comparison of the growth and foliar oils of SA provenances of E. polybractea with seedlots from the main centres of production of the 1,8-cineole oil type near West Wyalong, NSW and Wedderburn, Vic in a trial at West Wyalong. The main finding was that although survival was generally excellent, most of the SA sources were slow growing, had low foliar oil concentrations and some yielded oils below the standard for 1,8-cineole composition. The exception was The Oaks, SA provenance, that, although slower growing than most eastern provenances, had a high oil concentration containing a high proportion of 1,8-cineole. Further testing of families of this provenance and other currently untested provenances from South Australia is now warranted. The inclusion of selections from the hotter, drier part of the E. polybractea natural range is a recommended strategy for increasing the resilience of the breed. This may provide insurance against projected climate change and also allow the introduction of the species into hotter and drier climates for uses including Eucalyptus oil production, biomass cropping and carbon sequestration.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f13071109/s1, Table S1: Eucalyptus polybractea oil composition (expressed as % of total oil) in the E. polybractea trial established at West Wyalong, New South Wales (NSW) in 2016.

Author Contributions

All authors contributed to the study conception and design. Data Collection and preliminary processing was carried out by D.S. and J.D. Oil distillations were carried out by D.S. and J.D. Statistical analysis was performed by D.B. The first draft of the manuscript was written by D.B. and J.D. and all authors commented on this and subsequent versions of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

The research was co-funded by CSIRO and G.R. Davis Pty Ltd.

Acknowledgments

We wish to thank David Kleinig and the late Andrew Slee for assistance in tracking the history of the naming of E. polybractea in South Australia. The late Ian Brooker (eucalypt botanist, CANB) provided advice about the locations of some of the material sampled in South Australia and verified that the correct species had been collected from pressed and dried samples of each tree. We also thank staff of the CSIRO Australian Tree Seed Centre including former staff member, Paul Macdonell, who participated in the South Australian seed collection, Sarah Whitfeld who extracted the seed from store for dispatch to Narromine Transplants and Nigel England for assistance in designing and planting this trial. Simon Southerton assisted with field measurements and Scott Bool of GR Davis undertook the GC/MS chemical analyses. Fabiano Ximenes, NSW Department of Primary Industries, provided valuable suggestions on a draft of the MS.

Conflicts of Interest

The authors do not have competing interest to disclose.

References

  1. Nicolle, D. Native Eucalypts of South Australia; Dean Nicolle: Adelaide, Australia, 2013; p. 237. [Google Scholar]
  2. Slee, A.V.; Brooker, M.I.H.; Duffy, S.M.; West, J.G. EUCLID Eucalypts of Australia, 4th ed.; Identic Pty Ltd.: Brisbane, Australia, 2020. [Google Scholar]
  3. Beerling, J.; Meakins, S.; Small, L. Eucalyptus oil products: Formulations and legislation. In Eucalyptus: The Genus Eucalyptus. Medicinal and Aromatic Plants—Industrial Profiles; Coppen, J.J.W., Ed.; Taylor and Francis: London, UK; New York, NY, USA, 2002; pp. 345–364. [Google Scholar]
  4. Abbott, P.; Abbott, T. Eucalyptus Oil: Australia’s Natural Wonder; Felton, Grimwade and Bosisto’s Pty Ltd.: Melbourne, Australia, 2013; p. 134. [Google Scholar]
  5. BP. British Pharmacopoeia. Ph. Eur. 10.0 Update; The Stationery Office: London, UK, 2020.
  6. Coppen, J.J.W. Eucalyptus: The Genus Eucalyptus; Taylor and Francis: London, UK; New York, NY, USA, 2002. [Google Scholar]
  7. Doran, J.C. Genetic improvement of eucalypts: With special reference to oil-bearing species. In Eucalyptus: The Genus Eucalyptus. Medicinal and Aromatic Plants—Industrial Profiles; Coppen, J.J.W., Ed.; Taylor and Francis: London, UK; New York, NY, USA, 2002; pp. 75–101. [Google Scholar]
  8. Barton, A.F.M.; Cotterill, P.P.; Brooker, M.I.H. Short note-heritability of cineole yield in Eucalyptus kochii. Silvae Genet. 1991, 40, 37–38. [Google Scholar]
  9. Spencer, B.; Mazanec, R.; Gibberd, M.; Zerihun, A. Sapling and coppice biomass heritabilities and potential gains from Eucalyptus polybractea progeny trials. Tree Genet. Genomes 2021, 17, 15. [Google Scholar] [CrossRef]
  10. Mazanec, R.A.; Grayling, P.M.; Doran, J.; Spencer, B.; Turnbull, P. Genetic parameters and potential gains from breeding for biomass and cineole production in three-year-old Eucalyptus polybractea progeny trials. Aust. For. 2021, 84, 13–24. [Google Scholar] [CrossRef]
  11. Doran, J.; Bush, D.; Davis, R. Breeding to improve foliar oil yields in Eucalyptus polybractea. In Proceedings of the Forest Genetics for Productivity, Rotorua, New Zealand, 14–28 March 2016; p. 41. [Google Scholar]
  12. Goodger, J.Q.D.; Connelly, C.A.; Woodrow, I.E. Examination of the consistency of plant traits driving oil yield and quality in short-rotation coppice cultivation of Eucalyptus polybractea. For. Ecol. Manag. 2007, 250, 196–205. [Google Scholar] [CrossRef]
  13. Paul, K.I.; Roxburgh, S.H.; de Ligt, R.; Ritson, P.; Brooksbank, K.; Peck, A.; Wildy, D.T.; Mendham, D.; Bennett, R.; Bartle, J.; et al. Estimating temporal changes in carbon sequestration in plantings of mallee eucalypts: Modelling improvements. For. Ecol. Manag. 2015, 335, 166–175. [Google Scholar] [CrossRef]
  14. Satori, D.; Tovar, C.; Faruk, A.; Hammond Hunt, E.; Muller, G.; Cockel, C.; Kühn, N.; Leitch, I.; Lulekal, E.; Pereira, L.; et al. Prioritising crop wild relatives to enhance agricultural resilience in sub-Saharan Africa under climate change. Plants People Planet 2021, 4, 269–282. [Google Scholar] [CrossRef]
  15. Ortiz, R.; Sayre, K.D.; Govaerts, B.; Gupta, R.; Subbarao, G.V.; Ban, T.; Hodson, D.; Dixon, J.M.; Iván Ortiz-Monasterio, J.; Reynolds, M. Climate change: Can wheat beat the heat? Agric. Ecosyst. Environ. 2008, 126, 46–58. [Google Scholar] [CrossRef]
  16. Cortés, A.J.; López-Hernández, F. Harnessing Crop Wild Diversity for Climate Change Adaptation. Genes 2021, 12, 783. [Google Scholar] [CrossRef] [PubMed]
  17. Prober, S.; Byrne, M.; McLean, E.; Steane, D.; Potts, B.; Vaillancourt, R.; Stock, W. Climate-adjusted provenancing: A strategy for climate-resilient ecological restoration. Front. Ecol. Evol. 2015, 3, 65. [Google Scholar] [CrossRef] [Green Version]
  18. Fady, B.; Rihm, G. Arboretums, common gardens and forest tree resilience. New For. 2022, 53, 603–606. [Google Scholar] [CrossRef]
  19. CSIRO and Bureau of Meteorology. Climate Change in Australia Information for Australia’s Natural Resource Management Regions: Technical Report; CSIRO and Bureaa of Meteorology: Melbourne, Australia, 2015; p. 216.
  20. Bush, D.; Harwood, C.; Pinkard, E. Species for changing climates–Australian dryland forestry opportunities. Aust. For. 2018, 81, 102–115. [Google Scholar] [CrossRef]
  21. Weiss, E.A. Essential Oil Crops; CAB International: New York, NY, USA, 1997; 600p. [Google Scholar]
  22. Kainer, D.; Bush, D.; Foley, W.J.; Külheim, C. Assessment of a non-destructive method to predict oil yield in Eucalyptus polybractea (blue mallee). Ind. Crops Prod. 2017, 102, 32–44. [Google Scholar] [CrossRef]
  23. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2015. [Google Scholar]
  24. Wickham, H. ggplot2: Elegant Graphics for Data Analysis; Springer: New York, NY, USA, 2016. [Google Scholar]
  25. Mazanec, R.A.; Grayling, P.M.; Doran, J.; Spencer, B.; Neumann, C. Provenance variation, genetic parameters and potential gains from selection for biomass and cineole production in three-year-old Eucalyptus loxophleba subsp. gratiae progeny trials. Aust. For. 2020, 83, 75–90. [Google Scholar] [CrossRef]
  26. Mazanec, R.A.; Grayling, P.M.; Spencer, B.; Doran, J.; Neumann, C. Provenance variation, genetic parameters and potential gains from breeding for biomass and cineole production in three-year-old Eucalyptus loxophleba subsp. lissophloia progeny trials. Aust. For. 2017, 80, 34–42. [Google Scholar] [CrossRef]
  27. Pont, D.; Dungey, H.S.; Suontama, M.; Stovold, G.T. Spatial Models With Inter-Tree Competition From Airborne Laser Scanning Improve Estimates of Genetic Variance. Front. Plant Sci. 2021, 11, 596315. [Google Scholar] [CrossRef] [PubMed]
  28. Kotivuori, E.; Kukkonen, M.; Mehtätalo, L.; Maltamo, M.; Korhonen, L.; Packalen, P. Forest inventories for small areas using drone imagery without in-situ field measurements. Remote Sens. Environ. 2020, 237, 111404. [Google Scholar] [CrossRef]
  29. Ximenes, F. Forestry, bioenergy and climate—A way forward in Australia. Aust. For. 2021, 84, 1–3. [Google Scholar] [CrossRef]
  30. Shepherd, M.; Bartle, J.; Lee, D.J.; Brawner, J.; Bush, D.; Turnbull, P.; Macdonell, P.; Brown, T.R.; Simmons, B.; Henry, R. Eucalypts as a biofuel feedstock. Biofuels 2011, 2, 639–657. [Google Scholar] [CrossRef] [Green Version]
Figure 1. Locations of the trial near West Wyalong, NSW; provenances included in the trial from NSW, Vic and SA, and mean annual rainfall (MAR) distribution.
Figure 1. Locations of the trial near West Wyalong, NSW; provenances included in the trial from NSW, Vic and SA, and mean annual rainfall (MAR) distribution.
Forests 13 01109 g001
Figure 2. Fitted relationships between green biomass (BM) and explanatory variables including crown volume index (CVI), height (HT), crown width (CW) and crown density score (CW). Regions of provenance are represented by red circles (SA); asterisks (NSW) and blue diamonds (Victoria). The 95% confidence intervals for the fitted blue lines are indicated by the surrounding grey regions.
Figure 2. Fitted relationships between green biomass (BM) and explanatory variables including crown volume index (CVI), height (HT), crown width (CW) and crown density score (CW). Regions of provenance are represented by red circles (SA); asterisks (NSW) and blue diamonds (Victoria). The 95% confidence intervals for the fitted blue lines are indicated by the surrounding grey regions.
Forests 13 01109 g002
Figure 3. Box plots showing: boxes the mean andinterquartile range; whiskers the extent of the 0th and 100th percentiles, and; dots outlying values for oil yield and %cineole traits by provenance and ROP.
Figure 3. Box plots showing: boxes the mean andinterquartile range; whiskers the extent of the 0th and 100th percentiles, and; dots outlying values for oil yield and %cineole traits by provenance and ROP.
Forests 13 01109 g003
Table 1. Geographic, climatic and CSIRO Australian Tree Seed Centre (ATSC) family composition data for provenances included in the E. polybractea trial at West Wyalong established in 2016. Climate data were accessed from the Bureau of Meteorology (BoM) (Australia) http://www.bom.gov.au/climate/. accessed on 17 June 2022.
Table 1. Geographic, climatic and CSIRO Australian Tree Seed Centre (ATSC) family composition data for provenances included in the E. polybractea trial at West Wyalong established in 2016. Climate data were accessed from the Bureau of Meteorology (BoM) (Australia) http://www.bom.gov.au/climate/. accessed on 17 June 2022.
Region-Of-Provenance and ProvenanceATSC Seedlot NumberNo. of Families in ProvenanceLatitude (Decimal Degrees)Longitude (Decimal Degrees)Altitude (m above Sea Level)MAR (mm/ Year)MAT (°C)
South Australia-Modified BoM Koeppen climate is Grassland, warm (persistently dry)
W of Blinman, Flinders Ranges21,3362−31.1033138.667463033016
ENE Mt Rowe, Vulkathuna-Gammon Ranges21,33713−30.5200138.982875035015
Mt Hack, Warraweena Station21,33815−30.7917138.794770032015
Illuka Hill, Flinders Ranges21,3405−31.6006138.631761036014
The Oaks, SW of Hawker21,3429−31.9464138.323150031016
Wilpena Pound, Flinders Ranges21,34310−31.5431138.566758639516
Victoria-Modified BoM Koeppen climate is Temperate, no dry season (hot summer)
Wedderburn19,3617−36.3333143.600018051014
New South Wales-Modified BoM Koeppen climate is Temperate, no dry season (hot summer)
Mid-Western Hwy19,920, 21,0606−33.8928147.072231047016
West Wyalong township19,649, 21,059, 21,0608−33.9237147.204726046016
Tallimba Rd19,649, 19,920, 21,059, 21,060, 21,3659−33.9589147.045329047016
Neds Track19,920, 20,680, 21,06010−34.0011147.159428046016
Winters Lane19,649, 21,060, 21,3657−34.0244147.150826546016
Buddigower NP19,649, 21,0608−34.0061147.082227045016
TOTAL 109
Table 2. Provenance means (best linear unbiased estimates), average standard errors of difference (SED) and coefficients of phenotypic variation (%CVp) for CVI, oil yield and %cineole.
Table 2. Provenance means (best linear unbiased estimates), average standard errors of difference (SED) and coefficients of phenotypic variation (%CVp) for CVI, oil yield and %cineole.
ProvenanceCVI (m3)Oil Yield w/w (g/100 g Dry Leaf)%Cineole
Mean%CVpMean%CVpMean%CVp
South Australia
Illuka Hill4.871.83.011.572.20.9
Mt Hack4.586.62.921.466.38.8
Mt Rowe4.4101.12.97.971.75.9
The Oaks4.773.37.57.387.31.4
W Blinman3.4105.13.623.061.93.8
Wilpena Pound5.180.92.623.166.26.4
Victoria
Wedderburn6.772.35.414.883.12.5
New South Wales
Buddigower NP3.888.65.313.677.11.4
Mid-Western Highway5.964.75.86.982.23.5
Neds Lane5.264.36.08.881.22.5
Winters Lane6.071.06.112.676.25.0
Talimba Rd5.367.95.710.479.02.5
West Wyalong Town5.661.65.55.578.43.0
Average SED *0.47 0.42 1.9
* Where trait means differ by more than 2 × average SED, they can be considered significantly different.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Bush, D.; Spencer, D.; Doran, J.; Davis, R. Testing New Provenances of Eucalyptus polybractea: A Eucalypt Oil Mallee Adapted to Semi-Arid Environments. Forests 2022, 13, 1109. https://doi.org/10.3390/f13071109

AMA Style

Bush D, Spencer D, Doran J, Davis R. Testing New Provenances of Eucalyptus polybractea: A Eucalypt Oil Mallee Adapted to Semi-Arid Environments. Forests. 2022; 13(7):1109. https://doi.org/10.3390/f13071109

Chicago/Turabian Style

Bush, David, David Spencer, John Doran, and Richard Davis. 2022. "Testing New Provenances of Eucalyptus polybractea: A Eucalypt Oil Mallee Adapted to Semi-Arid Environments" Forests 13, no. 7: 1109. https://doi.org/10.3390/f13071109

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop