Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
Australian Journal of Botany Australian Journal of Botany Society
Southern hemisphere botanical ecosystems
Shopping Cart: ( empty )
You are here: Home > Journals > BT > BT10051
RESEARCH ARTICLE
Contents Vol 58(5)

Ageing mallee eucalypt vegetation after fire: insights for successional trajectories in semi-arid mallee ecosystems

Michael F. Clarke A D , Sarah C. Avitabile A , Lauren Brown A , Kate E. Callister A , Angie Haslem A B , Greg J. Holland B , Luke T. Kelly B , Sally A. Kenny C , Dale G. Nimmo B , Lisa M. Spence-Bailey A , Rick S. Taylor A , Simon J. Watson B and Andrew F. Bennett B
+ Author Affiliations
- Author Affiliations

A Department of Zoology, La Trobe University, Bundoora, Vic. 3086, Australia.

B School of Life and Environmental Sciences, Deakin University, Burwood, Vic. 3125, Australia.

C Department of Botany, La Trobe University, Bundoora, Vic. 3086, Australia.

D Corresponding author. Email: m.clarke@latrobe.edu.au

Australian Journal of Botany 58(5) 363-372 https://doi.org/10.1071/BT10051
Submitted: 19 February 2010  Accepted: 14 May 2010   Published: 21 July 2010

Abstract

A critical requirement in the ecological management of fire is knowledge of the age-class distribution of the vegetation. Such knowledge is important because it underpins the distribution of ecological features important to plants and animals including retreat sites, food sources and foraging microhabitats. However, in many regions, knowledge of the age-class distribution of vegetation is severely constrained by the limited data available on fire history. Much fire-history mapping is restricted to post-1972 fires, following satellite imagery becoming widely available. To investigate fire history in the semi-arid Murray Mallee region in southern Australia, we developed regression models for six species of mallee eucalypt (Eucalyptus oleosa F.Muell. ex. Miq. subsp. oleosa, E. leptophylla F.Muell. ex. Miq., E. dumosa J. Oxley, E. costata subsp. murrayana L. A. S. Johnson & K. D. Hill, E. gracilis F.Muell. and E. socialis F.Muell. ex. Miq.) to quantify the relationship between mean stem diameter and stem age (indicated by fire-year) at sites of known time since fire. We then used these models to predict mean stem age, and thus infer fire-year, for sites where the time since fire was not known. Validation of the models with independent data revealed a highly significant correlation between the actual and predicted time since fire (r = 0.71, P < 0.001, n = 88), confirming the utility of this method for ageing stands of mallee eucalypt vegetation. Validation data suggest the models provide a conservative estimate of the age of a site (i.e. they may under-estimate the minimum age of sites >35 years since fire). Nevertheless, this approach enables examination of post-fire chronosequences in semi-arid mallee ecosystems to be extended from 35 years post-fire to over 100 years. The predicted ages identified for mallee stands imply a need for redefining what is meant by ‘old-growth’ mallee, and challenges current perceptions of an over-abundance of ‘long-unburnt’ mallee vegetation. Given the strong influence of fire on semi-arid mallee vegetation, this approach offers the potential for a better understanding of long-term successional dynamics and the status of biota in an ecosystem that encompasses more than 250 000 km2 of southern Australia.


Acknowledgements

We gratefully acknowledge funding and support for this project from Parks Victoria, Department of Sustainability and Environment (Vic.), Mallee Catchment Management Authority, NSW National Parks and Wildlife Service, Department of Environment and Climate Change (NSW), Lower Murray–Darling Catchment Management Authority, Department for Environment and Heritage (SA), Land and Water Australia, Natural Heritage Trust, Birds Australia (Gluepot Reserve), Australian Wildlife Conservancy (Scotia Sanctuary) and the Murray Mallee Partnership. We are grateful to the University of Ballorat and to the Doyle and Barnes families for granting access to Nanya, Petro and Lethero Stations, respectively. Thanks go to Lauren Fraser for assistance with references and many volunteers who assisted with vegetation surveys and to Martin Westbrooke and Simon Cook who directed us to many of the validation sites. We are also very grateful for the constructive suggestions of two anonymous referees.


References


Barker S (1988) Population structure of snow gum (Eucalyptus pauciflora Sieb. ex Spreng.) subalpine woodland in Kosciusko National Park. Australian Journal of Botany 36, 483–501.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Benshemesh J (1989) Management of malleefowl with regard to fire. In ‘The mallee lands: a conservation perspective’. (Eds JC Noble, PJ Joss, GK Jones) pp. 206–211. (CSIRO: Adelaide)

Bolker BM (2008) ‘Ecological models and data in R.’ (Princeton University Press: Princeton, NJ)

Bond WJ, Woodward FI, Midgley GF (2005) The global distribution of ecosystems in a world without fire. New Phytologist 165, 525–538.
| Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Bos DG, Carthew SM (2003) The influence of behaviour and season on habitat selection by a small mammal. Ecography 26, 810–820.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Bowman D, Balch JK, Artaxo P, Bond WJ, Carlson JM, Cochrane MA, D’Antonio CM, DeFries RS, Doyle JC, Harrison SP, Johnston FH, Keeley JE, Krawchuk MA, Kull CA, Marston JB, Moritz MA, Prentice IC, Roos CI, Scott AC, Swetnam TW, van der Werf GR, Pyne SJ (2009) Fire in the earth system. Science 324, 481–484.
| Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Bradstock RA (1989) Dynamics of a perennial understorey. In ‘Mediterranean landscapes in Australia, mallee ecosystems and their management’. (Eds JC Noble, RA Bradstock) pp. 141–154. (CSIRO: Australia)

Bradstock RA , Cohn JS (2002) Fire regimes and biodiversity in semi-arid mallee ecosystems. In ‘Flammable Australia: the fire regimes and biodiversity of a continent’. (Eds RA Bradstock, J Williams, A Gill). (Cambridge University Press: Cambridge, UK)

Bradstock RA, Bedward M, Gill AM, Cohn JS (2005) Which mosaic? A landscape ecological approach for evaluating interactions between fire regimes, habitat and animals. Wildlife Research 32, 409–423.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Brockett BH, Biggs HC, van Wilgen BW (2001) A patch mosaic burning system for conservation areas in southern African savannas. International Journal of Wildland Fire 10, 169–183.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Brown S, Clarke M, Clarke R (2009) Fire is a key element in the landscape-scale habitat requirements and global population status of a threatened bird: the mallee emu-wren (Stipiturus mallee). Biological Conservation 142, 432–445.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Burrows ND (2008) Linking fire ecology and fire management in south-west Australian forest landscapes. Forest Ecology and Management 255, 2394–2406.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Cheal PD , Day JC , Meredith CW (1979) ‘Fire in the national parks of north-west Victoria.’ (National Parks Service: Melbourne)

Clarke MF (2008) Catering for the needs of fauna in fire management: science or just wishful thinking? Wildlife Research 35, 385–394.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Clarke RH (2005) ‘Ecological requirements of birds specialising in mallee habitats: modelling the habitat suitability for threatened mallee birds.’ (La Trobe University: Melbourne)

Clarke RH, Boulton RL, Clarke MF (2005) Estimating population size of the black-eared miner, with an assessment of landscape-scale habitat requirements. Pacific Conservation Biology 11, 174–188. open url image1

Driscoll DA, Henderson MK (2008) How many common reptile species are fire specialists? A replicated natural experiment highlights the predictive weakness of a fire succession model. Biological Conservation 141, 460–471.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Emison WB , Bren WM (1989) Common birds of the mallee, northwestern Victoria. In ‘Mediterranean landscapes in Australia: mallee ecosystems and their management’. (Eds JC Noble, RA Bradstock) pp. 221–242. (CSIRO: Melbourne)

Fire Ecology Working Group (2002) ‘Analysis of disturbance by fire on public land in Victoria.’ (Department of Natural Resources and Environment: Melbourne)

Fox BJ, Taylor E, Thompson PT (2003) Experimental manipulation of habitat structure: a retrogression of the small mammal succession. Journal of Animal Ecology 72, 927–940.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Friend GR (1993) Impact of fire on small vertebrates in mallee woodlands and healthlands of temperate Australia. Biological Conservation 65, 99–114.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Gill AM (1994) How fires affect biodiversity. In ‘Biodiversity and fire: the effects and effectiveness of fire management’, 8–9 October 1994, Melbourne.

Holland PG (1969) Weight dynamics of Eucalyptus in the mallee vegetation of southeast Australia. Ecology 50, 212.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Keeley JE (1995) Seed-germination patterns in fire-prone mediterranean-climate regions. In ‘Ecology and biogeography of mediterranean ecosystems in Chile, California, and Australia’. (Eds MTK Arroyo, PH Zedler, MD Fox) pp. 239–273. (Springer-Verlag: New York)

Land Conservation Council (1987) Report on the mallee area review. Land Conservation Council, Melbourne.

Letnic M, Dickman CR, Tischler MK, Tamayo B, Beh CL (2004) The responses of small mammals and lizards to post-fire succession and rainfall in arid Australia. Journal of Arid Environments 59, 85–114.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Lindenmayer DB, MacGregor C, Welsh A, Donnelly C, Crane M, Michael D, Montague-Drake R, Cunningham RB, Brown D, Fortescue M, Dexter N, Hudson M, Gill AM (2008) Contrasting mammal responses to vegetation type and fire. Wildlife Research 35, 395–408.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Lunt ID (2002) Grazed, burnt and, cleared: how ecologists have studied century-scale vegetation changes in Australia. Australian Journal of Botany 50, 391–407.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Mackowski CM (1984) The ontogeny of hollows in blackbutt (Eucalyptus pilularis) and its relevance to the management of forests for possums, gliders and timber. In ‘Possums and gliders’. (Eds AP Smith, ID Hume) pp. 553–567. (Surrey Beatty: Sydney)

National Land and Water Resources Audit (2001) ‘Australian native vegetation assessment.’ (Commonwealth of Australia: Canberra)

Noble JC, Vines RG (1993) Fire studies in mallee (Eucalyptus spp.) communities of western New South Wales: grass fuel dynamics and associated weather patterns. The Rangeland Journal 15, 270–297.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Noble JC, Smith AW, Leslie HW (1980) Fire in the mallee shrublands of western New South Wales. The Rangeland Journal 2, 104–114.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Ogden J (1978) On the dendrochronological potential of Australian trees. Austral Ecology 3, 339–356.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Parkes DM , Cheal DC (1990) Perceptions of mallee vegetation. In ‘The mallee lands: a conservation perspective’. (Eds JC Noble, PJ Joss, GK Jones) pp. 3–7. (CSIRO Publishing: Melbourne)

Parr CL, Andersen AN (2006) Patch mosaic burning for biodiversity conservation: a critique of the pyrodiversity paradigm. Conservation Biology 20, 1610–1619.
| Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Pausas JG, Bradstock RA (2007) Fire persistence traits of plants along a productivity and disturbance gradient in mediterranean shrublands of south-east Australia. Global Ecology and Biogeography 16, 330–340.
| Crossref | GoogleScholarGoogle Scholar | open url image1

R Development Core Team (2009) ‘R: a language and environment for statistical computing.’ (R Foundation for Statistical Computing: Vienna)

Rumpff L, Cutler SC, Thomas I, Morgan JW (2009) An assessment of the relationship between tree-ring counts and basal girth of high-altitude populations of Eucalyptus pauciflora (Myrtaceae). Australian Journal of Botany 57, 583–591.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Sparrow A (1989) Mallee vegetation in South Australia. In ‘Mediterranean landscapes in Australia: mallee ecosystems and their management’. (Eds JC Noble, RA Bradstock) pp. 109–124. (CSIRO Publishing: Melbourne)

Sparrow A (1990) Floristic patterns in South Australian mallee vegetation and some implications for conservation. In ‘The mallee lands: a conservation perspective’. (Eds JC Noble, JP Joss, GK Jones) pp. 12–15. (CSIRO Publishing: Melbourne)

Torre I, Diaz M (2004) Small mammal abundance in Mediterranean post-fire habitats: a role for predators? Acta Oecologica 25, 137–142.
| Crossref | GoogleScholarGoogle Scholar | open url image1










Appendix 1.  Coefficient estimates and standard errors (s.e.) for models of the change in mean stem diameter (cm) per site in relation to time since fire for six species of mallee eucalypts in the Murray Mallee region
Models are based on data from sites of known time since fire ranging from 0 to 94 years. Alternative models are presented for which time (years) is modelled in linear form and square-root transformed (sqr). D2 = the percentage of deviance explained by the model
Click to zoom



Appendix 2.  Coefficient estimates and standard errors (s.e.) for models of the change in mean stem diameter (cm) per site in relation to time since fire for mallee eucalypts in the Murray Mallee region
Models are based on data recorded from all mallee eucalypts at a site, regardless of species. Models are presented for datasets based on sites of <35 years since fire and 0–94 years since fire, respectively. In each case, alternative models are presented for which time (years) is modelled in linear form and square-root transformed (sqr). D2 values represent the percentage of deviance explained by the overall model
Click to zoom



Appendix 3.  Relationship between the predictions of two methods of generating time-since-fire predictions by using (1) the average across species of the best linear or square-root species-specific models from the combined dataset of 0–94 years (x-axis) and (2) the average across-species time-since-fire predictions from the linear species-specific models built only on 0–35-year data (y-axis) (Pearson’s correlation (r) = 0.94, P < 0.001). The solid line depicts where a 1 : 1 correspondence between predicted ages of sites determined by each model would fall.
FA3