This is the pre-peer-reviewed version of the following article: Changes in plant species and functional
composition with time since fire in two mediterranean climate plant communities, Carl R. Gosper, Colin J.
Yates, Suzanne M. Prober. Journal of Vegetation Science, vol. 23, issue 6, Copyright © 2012, International
Association for Vegetation Science. Wiley-Blackwell. http://dx.doi.org/10.1111/j.1654-1103.2012.01434.x
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Changes in plant species and functional composition with time since
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fire in two Mediterranean-climate plant communities
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Carl R. Gosper, Colin J. Yates & Suzanne M. Prober
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Gosper, C.R. (corresponding author, [email protected]): Science Division, Department of
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Environment and Conservation, Locked Bag 104, Bentley Delivery Centre, Western Australia 6983,
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Australia; CSIRO Ecosystem Sciences, Private Bag 5, Wembley Western Australia 6913, Australia
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Yates, C.J. ([email protected]): Science Division, Department of Environment and
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Conservation, Locked Bag 104, Bentley Delivery Centre, Western Australia 6983, Australia
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Prober, S.M. ([email protected]): CSIRO Ecosystem Sciences, Private Bag 5, Wembley
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Western Australia 6913, Australia
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Keywords
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Fire-return interval; Plant functional type; Mallee; Obligate seeder; Seed bank; Senescence; Serotinous;
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South-western Australia; Sprouter
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Nomenclature
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Western Australian Herbarium (1998-2011)
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Abbreviations: PFT = plant functional type
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Running head: Plant functional type changes with time since fire
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Abstract
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Question: Do floristic composition and Plant Functional Type (PFT) richness and
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dominance change with time since fire, in the directions predicted through
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consideration of their fire response traits?
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Location: Two vegetation communities in the highly fragmented south-western
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Australian wheatbelt: mallee, dominated by sprouters, and mallee-heath, dominated
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by non-sprouters.
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Methods: Species richness and cover were sampled in replicated plots across a time
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since fire gradient ranging from 2 to > 55 yrs post-fire, using a space-for-time
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approach. Species were allocated to PFTs according to their capacity to sprout, the
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location and persistence of the seed bank, competitive stratum and longevity.
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Ordination and ANOVA were used to test for differences in floristic and PFT
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composition between young (< 10 yrs post-fire), mature (19-35 yrs) and old (> 40 yrs)
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vegetation in each community.
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Results: PFT and floristic analyses were similar, showing substantial changes in the
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composition of mallee-heath vegetation with time since fire, but not in mallee. The
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direction of change in PFT composition in mallee-heath was consistent with
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predictions, with increasing cover of non-sprouting serotinous PFTs, an intermediate
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peak in cover of PFTs with persistent soil-stored seed banks, and decreasing cover of
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post-fire ephemerals and non-sprouting non-serotinous dwarf shrubs, herbs and
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graminoids with increasing time since fire. Success in predicting changes in PFT
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dominance in mallee was lower.
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Conclusions: The similarity of floristic and PFT analyses suggest that these
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approaches are interchangeable for characterizing vegetation change with increasing
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time since fire. PFTs were more effective for predicting fire response trajectories in
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the vegetation community dominated by non-sprouters (mallee-heath) than the
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community dominated by sprouters (mallee). The PFTs that declined most in richness
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and cover with increasing time since fire were those with persistent soil-stored seed
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banks in the community dominated by non-sprouters. While knowledge of seed bank
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longevity is poor overall, in some representatives of these PFTs the decline in the
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incidence of fire in remnants represents a significant threat.
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Introduction
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Plant functional types (PFTs) are groupings of plant taxa that share particular
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functional traits. Whilst the traits used in such classifications necessarily vary
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depending on the purpose of the study and the mechanisms through which responses
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occur (Noble & Gitay 1996), the PFT approach has been widely used in predicting
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plant community changes in response to a variety of environmental perturbations
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(Noble & Slatyer 1980; McIntyre et al. 1995; Keith et al. 2007). Fire is one such
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perturbation, shaping vegetation patterns and plant community composition in
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seasonally dry landscapes worldwide (Bond & van Wilgen 1996; Bond et al. 2005;
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Verdú & Pausas 2007).
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Fires consume biomass and promote plants with functional traits that enable
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survival, recruitment and/or reproduction during and shortly after fire. The
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communities which then assemble are influenced by a variety of factors, such as the
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time since the last fire, the characteristics of the fire, the pool and traits of the species
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that can reach the site, post fire conditions and species interactions (Noble & Slatyer
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1980; Bond & van Wilgen 1996). Understanding the effects of components of a fire
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regime, such as time since fire, is important for fire management for biodiversity
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conservation. The critical functional traits likely to determine the response of species
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to time since fire are the methods of population persistence through fire (sprouting,
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seed banks, and dispersal from elsewhere), competition during the inter-fire period,
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and the timing of life-history stages, such as reproductive maturity and senescence
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(Keith et al. 2007).
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Changes in plant community composition with time since fire are also addressed
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through models of ecological succession or assembly (Clements 1916; Capitanio &
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Carcaillet 2008). The ‘initial floristic composition’ model of succession (Egler 1954)
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proposes that all (or at least the majority of) plant species present during the
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succession re-establish shortly after fire, that re-establishment is relatively rapid, and
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that changes over time reflect differential growth rates and survivorship (Collins et al.
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1995; Capitanio & Carcaillet 2008). Changes in diversity indices have been in
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concordance with the initial floristic composition model of succession in a number of
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fire-prone communities (Russell & Parsons 1978; Grace & Keeley 2006; Gosper et al.
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in press), although classical relay floristic succession (Clements 1916) may also apply
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in some cases over longer time scales (e.g. Jackson 1968; Maher et al. 2010).
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By combining predictions arising from an understanding of PFTs and vegetation
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assembly models, changes in plant communities with time since fire can be predicted.
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Given expected re-establishment of most species shortly after fire under the initial
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floristics model (Gosper et al. in press), predictions include the following PFT
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responses after fire (relative to PFTs equivalent in fire response traits other than the
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trait under consideration):
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1.
Non-sprouting PFTs will increase in cover, but not in richness,
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with greater time since fire. Sprouting PFTs are likely to change little in
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cover or richness beyond the immediate post-fire period, as sprouts
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typically recover biomass more rapidly after fire than germinates (Keith &
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Bradstock 1994; Pausas 1999; Keith et al. 2007).
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2.
PFTs with soil-stored seed might peak in cover at an
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intermediate time since fire, and decrease in richness with increasing time
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since fire, as soil-stored seed banks can persist long after adult plant death
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(Weston 1985) meaning that greater adult longevity is less crucial for long-
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term population persistence. PFTs with canopy-stored seed (serotinous)
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might change little in richness but have increasing cover with time since
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fire. This is predicted as greater longevity would be important to maximise
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seed bank size at the time of fire in environments where inter-fire
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recruitment and maturation is typically low, post-fire conditions are
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conducive to seed survival and recruitment, and seeds stored on dead plants
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or shed after inter-fire plant dead are typically lost (Lamont et al. 1991;
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Lamont et al. 2007).
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3.
Post-fire ephemerals, due to their limited longevity and fire-
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stimulated germination, are likely to decline rapidly in richness and cover
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with time since fire (Bond & van Wilgen 1996).
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4.
Due to competitive interactions in the inter-fire period, cover
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and richness of PFTs in lower vegetative strata may decline with time since
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fire, while there would likely be little change in richness and an increase in
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cover in upper strata PFTs (Keith & Bradstock 1994; Keith et al. 2007).
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While a variety of studies have tested predictions of fire response using the
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functional trait approach in sites of known histories of disturbance (Keith &
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Bradstock 1994; Pausas et al. 2004), few analyses have extended these to multiple
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communities with different PFT compositions but subject to the same range of
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disturbances. Further, few studies have compared analyses of functional vs. species
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composition with respect to their value for informing fire management for
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biodiversity conservation.
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To better establish PFTs as a tool for informing vegetation management, we
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investigated whether plant species and PFT composition and richness change with
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time since fire in the direction predicted by their fire response traits. Explicit
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predictions of fire response, derived by combining relevant predictions above, are
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given in Table 1 for component PFTs of these communities. We used a space for time
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approach to compare the effectiveness of predictions in two contrasting vegetation
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types, mallee and mallee-heath, in the globally significant biodiversity hotspot of
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south-western Australia. Mallee and mallee-heath are prominent and diverse
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vegetation types in this Mediterranean-climate region, that occur in a mosaic across
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the topographically subdued, fire-prone landscapes (Beard 1990).
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Recent research has suggested that mallee and mallee-heath respond differently in
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diversity indices, structure and vigour to time since fire (Parsons & Gosper 2011;
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Gosper et al. in press), possibly due to their differing functional composition. Thus we
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also predicted that changes in species and functional composition would be more
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pronounced in mallee-heath than in mallee, due to dominance by fire-sensitive
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serotinous non-sprouters and fire-resilient serotinous sprouters respectively (Capitanio
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& Carcaillet 2008; Gosper et al. 2010; Parsons & Gosper 2011). Finally, we tested
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whether a PFT approach sufficiently captures time-since-fire responses in our study
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communities, or whether floristic compositional data provides additional insights
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relevant to management.
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Methods
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The study was conducted in the south-eastern wheatbelt in Western Australia. All
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Nature Reserves and parcels of unallocated crown land were considered for sampling
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in the 50 x 70 km area bounded by Newdegate (33˚04’S, 119˚04’E), Lake King,
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Cocanarup and Pingrup. The region has a dry Mediterranean climate, with average
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annual rainfall in Lake Grace (the nearest long-term weather station) of 354 mm,
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mainly falling in winter. Mean monthly daily temperature maxima range from 15.4 to
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31.4°C, and mean monthly minima from 5.6 to 15.1°C (Bureau of Meteorology 2008).
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The region supports a mosaic of mallee, mallee-heath and woodland, with vegetation
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type determined by climate and especially edaphic factors (Beard 1990), and
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influenced by historic disturbance patterns.
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The mallee-heath community is characterized by a diverse shrub layer dominated
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by serotinous obligate seeders (often Proteaceae), with scattered emergent mallees,
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most frequently Tallerack (Eucalyptus pleurocarpa) (Gosper et al. 2010). The mature
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mallee community is characterized by a close-spaced canopy of mallees (most
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frequently E. scyphocalyx, E. phaenophylla and E. flocktoniae), over a sparse layer of
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mostly sprouting shrubs (especially Melaleuca spp.) and sedges (Parsons & Gosper
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2011). Mallees are long-lived Eucalyptus spp. characterised by numerous aerial
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stems, a narrow canopy zone, and a large lignotuber from which plants resprout after
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disturbances (Noble 2001).
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Experimental design
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Five replicates (except where indicated) were located in each of nine mallee-heath and
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eight mallee vegetation age treatments: 2 yrs since the last fire (four samples, mallee-
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heath only), 3-4 yrs, 6 yrs (six samples in mallee-heath), 18 – 20 yrs, 25 yrs, 30 yrs,
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35 yrs, 45 yrs and ‘long unburnt’ (eight samples in mallee-heath). Long unburnt
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should be interpreted as the site having not experienced fire since at least 1956, which
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we have allocated an age of 55 yrs post-fire for analyses (although actual age is likely
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to be substantially greater in many cases; see Gosper et al. in press for further details).
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Information on other aspects of fire regime other than age (such as intensity, previous
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fire intervals) was not available.
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Our ‘space-for-time’ approach assumed that floristic composition at each of the
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different sites is comparable (or at least that differences between them are randomly
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distributed across fire ages; Hurlbert 1994; Oksanen 2001) and that fire event effects
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(Bond & van Wilgen 1996) do not confound time since fire effects. We took a number
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of steps to minimise uncertainty in attributing differences to time since fire. In
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particular, replicates were spread across the available range of individual fire events
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and across the study area where possible, and where multiple samples were placed
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within an individual fire scar, samples were spaced at least 150 m apart (described
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further in Gosper et al. in press).
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Sampling
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Plots of 10 x 10 m were placed at a random point 20-150 m into the vegetation from
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an access track. In spring 2007, we recorded all vascular plant species present and
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determined abundance using a line intercept technique by systematically placing a
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12.5 mm diameter pole vertically at 50 points spread across the plot in a grid.
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Abundance for any species was the proportion of points at which any of its leaves,
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stems or inflorescences intercepted the pole. This technique provided an objective
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measure of abundance reflecting but not equivalent to projective cover, and is
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hereafter referred to as ‘cover’. Species that were present but not recorded at point
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intercepts were allocated a nominal proportional abundance of 1%.
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Plant functional types
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We classified species on the basis of traits for which information was readily
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observable or available, as follows: (i) the capacity to sprout from fire-resistant organs
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(e.g. lignotubers, rhizomes etc); (ii) the location and persistence of the seed bank (i.e.
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persistent canopy, persistent soil, transient soil); (iii) competitive stratum (upper, mid
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and low), largely reflecting growth form; and (iv) longevity (i.e. species divided into
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those species that grow, reproduce and senesce primarily in the immediate post-fire
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period (≤ 6 yrs post-fire) and those that do not) (Table 1).
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Not all of the resultant 36 possible PFT combinations were represented in the
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sampled flora (Table 1). Further, following Keith et al. (2007), we combine some
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allied PFTs to increase sample sizes and thus the capacity to detect changes, leaving
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11 PFTs used in analyses. For sprouters, we combined species with transient and
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persistent soil seed banks into one PFT per competitive stratum. Due to trade-offs
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with the capacity for persistence, recruitment in this PFT is often low (Bond &
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Midgley 2001), rendering the significance of the seed bank peripheral in many cases.
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Both sprouting and non-sprouting representatives of short-lived species were
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combined into a single PFT (fire ephemeral herbs), occurring across the lower two
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competitive strata, as these species are largely functionally equivalent in avoiding
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competition with other PFTs through rapid growth and reproduction post-fire, then
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retreating below-ground (in seeds or dormant tubers or rhizomes) through the bulk of
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the inter-fire period (see Keith et al. 2007).
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For all species recorded in plots, we used published sources (primarily Flora of
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Australia series; Western Australian Herbarium 1998–2011; Hassell 2000; Barrett et
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al. 2009; DEC 2010, but other studies to fill gaps) and field observations to allocate
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them to PFTs. The variability that exists within species for some of the traits under
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consideration (Vivian et al. 2010) made allocation to a PFT difficult in some cases.
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Where there was inconsistency between literature and field observations, field
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observations were used.
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Of the 305 taxa recorded in mallee-heath, 16.4% could not be allocated to a PFT.
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In mallee, 22.2% of the 243 recorded taxa could not be allocated to a PFT. These
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were mostly taxa with low abundance, as taxa of an unknown PFT contributed only
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5.8% of all cover across mallee-heath sites and 11.4% for mallee sites. For each plot
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richness and total cumulative cover of each PFT were calculated.
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Statistical analyses
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PRIMER analysis software (Version 6.1.11, PRIMER-E, Plymouth, UK) was used for
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ordination analysis of floristic and PFT composition. To reduce the effects of regional
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differences in the flora associated with high rates of species turnover and endemism in
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south-western Australia (Cowling et al. 1994), plant species recorded from only a
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single part of the study area were omitted from species-level analyses (not PFT-level
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analyses). The study region was broadly divided in two, approximately north-south by
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Lake Magenta and associated salt lakes. Only species that occurred on both sides of
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this band of unsuitable habitat were included in analyses. This reduced total taxa per
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habitat from 305 to 168 in mallee-heath, and 243 to 116 in mallee.
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We completed separate analyses in both habitats using presence/absence data
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(species only) and square-root transformed cover data (species and PFTs).
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Presence/absence data emphasises changes in species composition (giving greater
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weight to uncommon taxa), whilst cover data gives greater weight to larger and/or
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more abundant species or PFTs. We used non-metric multi-dimensional scaling, with
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the Bray-Curtis dissimilarity metric, and PERMANOVA and PERMDISP to test for
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differences in location and dispersion respectively among vegetation ages. The
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SIMPER algorithm was used to determine which species contributed most to
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similarity within and dissimilarity between fire-ages. For simplicity in presentation
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and reflecting gaps in the span of vegetation ages sampled, we aggregated ages into
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‘young’ (< 10 yrs post-fire), ‘mature’ (19-35 yrs) and ‘old’ (> 40 yrs).
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Analysis of variance (ANOVA), using Statistica (Version 7.1, Statsoft, Tulsa, OK,
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US), was used to test for differences in richness and cover of PFTs and total
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vegetation cover due to vegetation age (young, mature and old) in each vegetation
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community. To homogenise variances, square-root (x + 1) transformation was applied
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to mallee total cover, richness of NNtree (see Table 1 for PFT codes) in mallee-heath
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and cover of SNherb in mallee; and natural log (x +1) transformation to richness of
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NA, SNherb and Ephem in mallee-heath, and cover of NStree, NNtree and SNshrub
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in mallee and NStree, SNtree, NNherb and Ephem in mallee-heath. Due to the
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absence of SNtree from mallee, and Ephem from the old age class in mallee, ANOVA
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was not used in these cases.
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Results
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Species composition
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Time since the last fire exerted a detectable effect on species cover in both habitats. In
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mallee-heath, sites less than 10 yrs post-fire were orientated in one direction on the
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ordination, mature (19-35 yrs) in another, with old (> 40 yrs) somewhat intermediate
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(Figure 1a). There were differences in composition but not dispersion (Table 2)
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between time since fire groups, with pair-wise comparisons indicating that all mallee-
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heath age groups were distinct. Mean between vegetation age group dissimilarity was
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greatest between young and mature, but old was on average more similar to mature
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than to young (Table 3). Total cover in mallee-heath was least in young vegetation,
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but reached a plateau across both mature and old vegetation (Table 4).
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For analyses of mallee-heath cover, non-sprouting serotinous shrubs were the
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greatest contributors to similarity within vegetation age groups and to dissimilarity
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between vegetation age groups (Table 3). As predicted, representatives of this PFT
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had much lower cover in young vegetation, higher cover in old and mature vegetation,
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but variable patterns of increase or decrease between mature and old probably
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depending on individual species’ longevity. Among the species contributing highly to
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similarity/dissimilarity within/between vegetation age groups, vectors of some were
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orientated in ordination along the division between vegetation ages, whilst others
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were also associated with particular locations across the study area. Of those
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orientated with the division between vegetation age groups, the direction of vectors
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matched PFT predictions, with sprouters (Melaleuca villosisepala) associated with
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young vegetation and non-sprouting serotinous trees (Hakea pandanicarpa) and
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shrubs (Banksia erythrocephala, H. cygna) with mature vegetation. Sprouters,
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including trees, serotinous shrubs and non-serotinous graminoids, contributed the
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highest within-group similarity in young vegetation cover (Table 3). The strongest
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contributors to similarity in mature and old vegetation were all non-sprouting
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serotinous trees or shrubs. Between-group dissimilarity reflected this change from
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sprouter to non-sprouter dominance with increasing time since fire.
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Presence/absence data, while giving similar ordination and PERMANOVA results
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to cover (Table 2), highlighted different indicators of changes with time since fire. As
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predicted, sprouters and long-lived non-sprouters (i.e. serotinous trees and shrubs)
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usually had little variation in occurrence between vegetation ages in mallee-heath
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(Table 3) and hence contributed highly to similarity within ages but little to
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dissimilarity between ages. The highest contributors to between group dissimilarity
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included two species of PFTs with predicted declines in richness with time (non-
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sprouting non-serotinous trees and shrubs) and a change in occurrence of a non-
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spouting serotinous tree which was not predicted.
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For mallee vegetation, species cover differed with time since fire, but dispersion
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did not (Table 2). Pair-wise comparisons indicated that all mallee age groups were
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distinct (Table 2), but this was not clearly apparent on the ordination (Fig. 1a).
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Further, there was much lower similarity within ages overall than in mallee-heath
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(Table 3). Between vegetation age group dissimilarity was greatest between young
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and both older groups. In mallee, total cover remained similar across all vegetation
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age categories (Table 4). The strongest contributors to within/between vegetation age
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group similarity/dissimilarity were all sprouters and among the species with greatest
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covers overall (Table 3). Cover of these sprouters was high at all times since fire,
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although contrary to predictions, there was no evidence for differences in response to
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time since fire between vegetation ages in sprouters occurring in different vegetation
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strata.
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Presence/absence ordinations and PERMANOVA results in mallee were similar to
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those using cover data (Table 2). However, responses of individual species did not
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always match PFT predictions. Mallee eucalypts, for example, being sprouting
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serotinous trees, were predicted to be highly resistant to time since fire and thus
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change little in occurrence between vegetation ages. That two did probably indicates
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some effects of non-fire age factors (e.g. landform, soils, detectability) on occurrence.
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PFT composition
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Time since fire exerted a significant influence on the PFT composition of both
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vegetation communities, in similar ways to analyses based on the composition of
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plant species. In mallee-heath, young sites had greater variability in PFT composition
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than the other vegetation ages (Table 2). Young sites also clearly differed in position
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in ordination space, as did old and mature vegetation but to a lesser extent (Table 2;
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Figure 1b). All time since fire groups differed in PFT composition in pair-wise
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comparisons (Table 2).
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Vectors showing the orientation of PFTs largely supported predictions (Table 1).
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Post-fire ephemerals, and non-sprouting and sprouting non-serotinous dwarf shrubs,
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herbs and graminoids were associated with sites < 10 yrs post-fire (Figure 1b). Non-
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sprouting serotinous trees and shrubs had greater cover in old and mature vegetation.
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Sprouting serotinous shrubs and non-sprouting non-serotinous trees appeared less
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responsive to time since fire, with the orientation of these vectors largely
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perpendicular with the main division between young and not young vegetation in
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ordination. Mean similarity within vegetation ages peaked in mature vegetation (mean
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SIMPER similarity; young = 79.6, mature = 84.6 and old = 82.8), with the greatest
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contribution to within vegetation age similarity contributed by sprouting non-
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serotinous dwarf shrubs, herbs and graminoids for all vegetation ages, sprouting
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serotinous shrubs in young vegetation, and non-sprouting serotinous shrubs in mature
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and old vegetation. Dissimilarity between vegetation ages was greater between young
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and mature and young and old (both mean SIMPER dissimilarities = 23.5), than
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between old and mature (dissimilarity = 17.2).
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Mallee PFT composition also differed with time since fire. Times since fire
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differed in dispersion, although pair-wise comparisons were inconsistent (Table 2).
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Given these differences in dispersion, there is uncertainty as to whether the significant
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PERMANOVA result indicates differences in PFT composition between time since
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fire groups (Table 2). The pair-wise comparisons indicate that differences in PFT
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composition do exist, as differences in pair-wise comparisons largely contradict those
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in dispersion, with young vegetation being different from old and mature, but old and
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mature vegetation being similar (Table 2).
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As there was poor distinction of vegetation age groups in ordination (Figure 1b),
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interpretation of PFT vector orientation is of little value. Within vegetation age group
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similarity peaked in mature (SIMPER similarity = 79.0) over young (74.4) and old
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353
(73.2) vegetation. Dissimilarity in PFT composition of vegetation groups largely
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increased with the age difference between them (mean SIMPER dissimilarity young
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vs. old = 28.3; young vs. mature = 24.9 and mature vs. old = 23.9).
Richness and cover of many of PFTs varied according to vegetation age. In most
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cases, these differences were in the direction predicted through consideration of their
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response to fire (Table 4). Of the 11 PFTs in mallee-heath, ten responded as predicted
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to time since fire for richness and ten in cover. One exception was richness in non-
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sprouting serotinous shrubs, which was not stable. The other was cover in sprouting
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non-serotinous dwarf shrubs, herbs and graminoids, which had a non-significant
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decline in cover with age when a decline was predicted.
In mallee, PFT response to time since fire matched predictions less well, with
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seven of the ten PFTs represented responding as predicted in richness but only four of
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ten for cover. The only PFT other than post-fire ephemerals showing a response in
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richness or cover to time since fire in mallee was non-sprouting serotinous trees,
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which unexpectedly were most rich in mature vegetation (although pair-wise
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comparisons were inconsistent; Table 4) and as predicted, increased in cover from
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young to mature and old. Other PFTs in which a change in richness was predicted, but
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did not eventuate in mallee, were in non-sprouting non-serotinous shrubs and non-
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sprouting non-serotinous dwarf shrubs, herbs and graminoids. Cover failed to show
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the expected increase with age in non-sprouting serotinous trees and shrubs, decrease
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with age in sprouting and non-sprouting non-serotinous dwarf shrubs, herbs and
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graminoids or intermediate peak in non-sprouting non-serotinous trees and shrubs.
Of those species with an unknown response to fire, no differences with time since
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fire were recorded in mallee, but more species occurred in young than in mature or
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old mallee-heath, but without time since fire differences in their overall cover (Table
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4).
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Discussion
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Time since fire changes in species and PFT composition
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Changes in cover and richness of plant function types with time since the last fire
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were broadly predicted. This supports the utility of PFTs as a framework for
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predicting and interpreting vegetation change (e.g. McIntyre et al. 1995; Keith et al.
13
385
2007). However, more of the predictions were upheld in mallee-heath than mallee,
386
indicating that careful consideration should be given to the ecological processes
387
underlying vegetation dynamics when applying PFTs to predict community responses
388
to fire, and other disturbances.
389
There are several possible explanations for why mallee-heath showed much greater
390
effects of time since fire than mallee. First, mallee-heath might support an abundant
391
and geographically widespread post-fire ephemeral assemblage, possibly driving the
392
uniqueness of young vegetation. Certainly some post-fire ephemerals were
393
widespread in mallee-heath (e.g. Goodenia incana), but many others were not (e.g.
394
Gyrostemon prostratus). Mallee similarly supported widespread and localised post-
395
fire ephemerals, showed similar changes in post-fire ephemeral cover over time and
396
had only marginally less richness and cover of this PFT overall, suggesting that it was
397
not changes in this PFT that drove overall differences in fire response between the
398
communities.
399
A second, and more plausible explanation, relates to the relative dominance (at
400
least in cover) of the communities by different PFTs at different times since fire, with
401
mallee-heath exhibiting greater change in species and PFT composition than mallee.
402
This illustrates the capacity of the dominant long-lived sprouters in mallee to resist
403
changes with time since fire, and suggests that communities dominated by sprouters
404
can be inherently robust to large variation in times since fire (Keeley 1986). In
405
contrast, the substantial changes in species composition indicate that time since fire
406
has a significant effect on the above-ground vegetation in mallee-heath. This
407
community, dominated by non-sprouting serotinous PFTs when mature (Gosper et al
408
2010; Table 4), may thus be more susceptible to wide variation in times since fire
409
(Keeley 1986; Gosper et al. in press). These PFTs contributed proportionally much
410
less to cover in the years immediately after fire, as these species need to recruit from
411
seed and as such often lag in growth behind post-fire ephemerals and sprouters (Keith
412
et al. 2007), which were largely absent and relatively less dominant in mature
413
vegetation respectively. Mallee, in contrast, being largely dominated in cover by
414
sprouters (particularly serotinous trees and shrubs, non-serotinous shrubs and non-
415
serotinous dwarf shrubs, herbs and graminoids), could be expected to have these
416
species also being dominant immediately post-fire as well as in mature vegetation,
14
417
allowing non-fire factors (such as minor variation in soils, drainage etc) to have a
418
greater bearing on post-fire vegetation composition.
419
Old vegetation was more distinct from mature vegetation in mallee-heath than in
420
mallee. There was a decline in cover and/or richness of non-sprouting non-serotinous
421
trees and shrubs, and sprouting non-serotinous shrubs, between mature and old
422
vegetation mallee-heath, but not in mallee. As most representatives in these PFTs
423
have persistent soil-stored seed banks, these changes reflect a transition from above-
424
ground plants to existing in the soil seed bank. Although seed banks are likely to be
425
very long-lived in many cases (Weston 1985), this could suggest a further
426
vulnerability in mallee-heath to long intervals between fires. Additionally, the
427
richness of post-fire ephemerals (non-significant) and sprouting non-serotinous dwarf
428
shrubs, herbs and graminoids in old mallee-heath increased, relative to mature
429
vegetation, which was unpredicted. This suggests that these PFTs have some capacity
430
for expansion in the absence of a fire-cued establishment event to capitalise on newly
431
available resources following the senescence (Bond 1980; Gosper et al. in press) of
432
some components of the vegetation. The most plausible mechanisms for this are
433
through gradual loss of seed dormancy (Orscheg & Enright 2011) and recruitment in
434
gaps for post-fire ephemerals, and vegetative growth and lateral spread to avoid
435
competition among sprouting non-serotinous dwarf shrubs, herbs and graminoids
436
(Keith et al. 2007). The capacity for inter-fire recruitment is often overlooked in
437
studies aimed at establishing appropriate fire return intervals for vegetation
438
communities; however it can be significant in some circumstances (Ooi et al. 2006).
439
Contrary to predictions, there were no declines in richness and/or cover in mallee
440
of non-sprouting non-serotinous shrubs, non-sprouting non-serotinous dwarf shrubs,
441
herbs and graminoids and sprouting non-serotinous dwarf shrubs, herbs and
442
graminoids. The reasons for this are unclear, but as competition with dominant
443
vegetation layers has been cited as a possible mechanism (Keith et al. 2007), it may
444
indicate less intense competition for resources (light, moisture) in lower vegetation
445
layers in mallee. Some support for this possibility is provided by the lower overall
446
cover of vegetation in mallee (Table 4), especially in lower strata in mature and old
447
vegetation (Parsons & Gosper 2011). An additional possibility is that hydraulic
448
redistribution of groundwater by the dominant mallees (Brooksbank et al. 2011) may
449
facilitate, rather than reduce, understory diversity by providing additional soil
15
450
moisture during dry periods. There are no plausible ecological explanations for the
451
unexpectedly lower richness of sprouting serotinous trees (all mallee Eucalyptus) in
452
young mallee. However, richness may have been underestimated in young mallee due
453
to the difficulty in identifying mallee Eucalyptus in the absence of reproductive
454
material.
455
Other statistical and technical problems may have contributed to unexpected
456
responses, and if these could be overcome, may enhance the utility of the PFT
457
approach. Some PFTs (e.g. sprouting non-serotinous trees) had few representatives
458
and contributed little cover; hence there was limited statistical power to detect
459
changes between times since fire. More information on the response to fire of species
460
unable to be classified into a PFT may have improved this situation. Grouping of
461
aligned PFTs, while increasing sample sizes and thus potential statistical power, may
462
have had the contrary effect if trait differences contributed to divergent responses.
463
Variability in functional responses to fire (Vivian et al. 2010) and misclassifications
464
of species based upon this could also have contributed to unexpected responses.
465
Finally, the age of ‘old’ vegetation was greater than 40 yrs (although some sites may
466
have been substantially older than this; Gosper et al. in press). As some mallee
467
Eucalyptus are known to live for centuries (Wellington & Noble 1985), it is possible
468
that predicted changes in species and PFT composition may only become apparent
469
over longer time scales than those sampled. Improved estimation of the age of long-
470
unburnt vegetation (e.g. Clarke et al. 2010) may improve predictive ability.
471
472
Species vs. Plant Functional Type approaches
473
The floristic composition and PFT approaches produced very similar results and
474
implications for management. While having the outcomes replicated at different
475
levels of aggregation adds to the robustness of the conclusions, it also suggests that
476
using a single approach would be more efficient and not substantially less
477
informative. Where explicit time since fire analyses are not feasible, predictions based
478
on PFT composition of the vegetation can be expected to reflect patterns in species
479
composition. In particular, floristic composition is expected to be more sensitive to
480
fire interval in communities dominated by non-sprouters.
16
481
Differences between communities in PFT composition also reflect the influence of
482
factors other than fire. In the communities studied here, both are likely to have similar
483
flammability and, as they occur in a mosaic, are likely to have evolved under similar
484
selective pressure from fire. Major differences in the substrate on which they occur
485
(Beard 1990), however, may have influenced the relative dominance of PFTs. This
486
may introduce complexity and contribute to unpredictability when using PFTs to
487
predict vegetation dynamics with time since fire.
488
489
Management implications
490
Understanding changes in species and PFT composition of vegetation with the
491
passage of time since fire can contribute to improved ecological fire management.
492
Supporting an increasing body of evidence derived from similar Mediterranean-
493
climate shrublands in south-west Western Australia (Maher et al. 2010; Yates & Ladd
494
2010; Gosper et al. in press), our findings indicate substantial changes in composition
495
with increasing time since fire in mallee-heath. However, where significant declines
496
in richness or cover of PFTs occurred, these changes were predictable based on their
497
response to fire, and these PFTs typically had persistent soil-stored seed banks (but
498
this was not the case for all individual species). While knowledge on the longevity of
499
persistent soil-stored seed banks is poor, seed banks of some species can persist for
500
centuries (Weston 1985) and lack of fire does therefore not necessarily reflect a long-
501
term conservation concern even in fragmented landscapes where fire return intervals
502
are much greater than those experienced historically (O’Donnell et al. 2011; Parsons
503
& Gosper 2011). For other species, seed bank longevity is much shorter, and a lack of
504
fire does represent a significant threatening process (Yates & Ladd 2005, 2010).
505
Mallee communities appear more resistant to change due to variation in time since
506
fire, so would appear at a lower priority for fire management interventions based on
507
time since fire (Parsons & Gosper 2011; Gosper et al. in press).
508
509
Acknowledgements
510
This study was jointly funded by the Department of Environment and Conservation’s
511
(DEC) Saving Our Species Initiative and CSIRO Ecosystem Sciences (CES). The
512
spatial distribution of sampling was based in part on remote sensing data derived from
17
513
the research of Dr Li Shu, in digital image processing and remote sensing at Fire
514
Management Services, Regional Services Division, DEC. We thank Anne Rick for
515
assistance with floristic surveys, and Georg Wiehl (CES), Blair Parsons (CES), Tanya
516
Llorens (DEC) and Hafeel Kalideen (DEC) for field and technical assistance.
517
518
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Table 1. Plant functional types (PFT) and their predicted response to increasing periods since fire. %, percentage of all taxa per habitat allocated
629
to each PFT.
Plant functional type
PFT code
Seed bank
Stratum
Longevity
Long
Mallee
Mallee-heath
Predicted response
Example
%
Example
%
Richness
Cover
Eucalyptus
scyphocalyx
7.0
Eucalyptus
pleurocarpa
2.3
Stable
Stable or
increase
2.5
Callitris roei
3.9
Stable
Increase
0
Persoonia
quinquenervis
1.3
Stable
Stable or
increase
Sprouting serotinous trees
SStree
Canopy
Upper
Non-sprouting serotinous trees
NStree
Canopy
Upper
Long
Hakea laurina
Sprouting non-serotinous trees
SNtree
Persistent
soil
Upper
Long
None
Non-sprouting non-serotinous trees
& climbers
NNtree
Persistent
soil
Upper
Long
Exocarpos
sparteus
2.1
Grevillea
cagiana
3.6
Stable or
decrease
Intermediate
peak
Sprouting serotinous shrubs
SSshrub
Canopy
Mid
Long
Melaleuca
lateriflora
3.3
Allocasuarina
humilis
6.9
Stable
Stable
Non-sprouting serotinous shrubs
NSshrub
Canopy
Mid
Long
Melaleuca
rigidifolia
10.7
Banksia pallida
10.2
Stable
Increase
Sprouting non-serotinous shrubs
SNshrub
Persistent
& transient
soil
Mid
Long
Boronia
crenulata
9.1
Bossiaea
spinosa
8.9
Stable or
decrease
Stable or
decrease
Non-sprouting non-serotinous shrubs
NNshrub
Persistent
soil
Mid
Long
Grevillea
oligantha
21.0
Gompholobium
knightianum
17.4
Decrease
Intermediate
peak
Sprouting non-serotinous dwarf
shrubs, herbs & graminoids
SNherb
Persistent
& transient
soil
Low
Long
Lepidosperma
brunonianum
11.5
Amphipogon
turbinatus
15.7
Stable or
decrease
Decrease
Non-sprouting non-serotinous dwarf
shrubs, herbs & graminoids
NNherb
Persistent
soil
Low
Long
Desmocladus
parthenicus
5.3
Stylidium
piliferum
6.9
Decrease
Decrease
Post-fire ephemeral herbs,
graminoids & shrubs
Ephem
Persistent
& transient
soil
Lowmid
Short
Goodenia
concinna
5.3
Gyrostemon
prostratus
6.6
Post-fire
only
Decrease
Unknown
NA
16.4
-
-
(> 6 yrs)
(≤ 6 yrs)
22.2
21
Total taxa (n)
630
243
305
22
631
Table 2. PERMANOVA results for the effect of time since fire on the species and Plant Functional Type (PFT) composition of mallee-heath and
632
mallee vegetation, and PERMDISP results for differences in dispersion. All mallee heath df 2,45; all mallee df 2,37. Cover = square root
633
transformed cover data; P/A = presence/absence data; Young (Y) = < 10 yrs; Mature (M) = 19-35 yrs; Old (O) = > 40 yrs post-fire. Pair-wise
634
comparisons show t value. ***P ≤ 0.001; ** P ≤ 0.01; * P < 0.05.
Pair-wise comparisons
PERMANOVA
Pseudo-F
Y vs. M
Y vs. O
M vs. O
Dispersion (mean±SE)
Y
Pair-wise comparisons
PERMDISP
M
O
F
Y vs. M
Y vs. O
M vs. O
Species-level
Mallee-heath cover
4.30***
2.45***
1.96***
1.60**
35.8±0.8
33.7±0.9
32.8±0.9
2.59
-
-
-
Mallee cover
1.92***
1.48**
1.29*
1.35*
46.7±2.0
42.9±0.8
43.8±1.6
2.01
-
-
-
Mallee-heath P/A
3.85***
2.41***
1.78**
1.50**
30.4±0.8
27.5±1.1
26.9±1.1
3.10
-
-
-
Mallee P/A
2.48***
1.67**
1.49*
1.53**
41.6±2.0
39.1±1.1
39.0±1.2
0.95
-
-
-
Mallee-heath cover
8.34***
3.59***
2.83***
1.64**
14.3±0.5
11.7±0.7
10.6±0.6
8.94**
4.10*
2.98*
1.08
Mallee cover
2.21**
1.60*
1.71**
1.10
17.3±1.2
14.6±0.7
18.2±1.3
4.23*
2.11
0.51
2.76**
PFT-level
23
635
Table 3. Species contributing most to similarities within and differences between times since fire classes in mallee-heath and mallee, ordered by
636
plant functional type (PFT) (see Table 1). Young (Y) = < 10 yrs; Mature (M) = 19-35 yrs; Old (O) = > 40 yrs. SIMPER scores for the three
637
(cover analyses) or two (presence/absence analyses) species contributing most for each comparison are highlighted. See Table 1 for PFT codes.
Figure 1 code
Species
Mallee-heath cover
Eucalyptus pleurocarpa
Hakea pandanicarpa subsp. crassifolia
Banksia rufa subsp. chelomacarpa
Melaleuca villosisepala
Banksia erythrocephala var. erythrocephala
Beaufortia schaueri
Hakea cygna subsp. cygna
Beaufortia micrantha var. micrantha
Cryptandra leucopogon
Neurachne alopecuroidea
EUCPLE
HAKPANCRA
BANRUFCHE
MELVIL
BANERYERY
BEASCH
HAKCYGCYG
BEAMICMIC
CRYLEU
NEUALO
Mean % within age class similarity/between class dissimilarity
Mallee cover
EUCFLOFLO
Eucalyptus flocktoniae subsp. flocktoniae
EUCPHAPHA
Eucalyptus phaenophylla subsp. phaenophylla
EUCSCY
Eucalyptus scyphocalyx
MELHAM
Melaleuca hamata
GAHANC
Gahnia ancistrophylla
LEPBRU
Lepidosperma brunonianum
LEPPUB
Lepidosperma pubisquameum
SPYCOR
Spyridium cordatum
Mean % within age class similarity/between class dissimilarity
Mallee-heath presence/absence
Allocasuarina pinaster
Hakea pandanicarpa subsp. crassifolia
Grevillea cagiana
Leptospermum spinescens
PFT
SStree
NStree
SSshrub
SSshrub
NSshrub
NSshrub
NSshrub
NSshrub
SNherb
SNherb
SStree
SStree
SStree
SSshrub
SNherb
SNherb
SNherb
NNherb
NStree
NStree
NNtree
SSshrub
Mean cover ± SE (%)
Within age
similarity
Between age
dissimilarity
Y
M
O
Y
M
O
5.5±1.6
1.5±0.3
5.8±1.8
7.5±2.5
1.3±0.3
2.5±1.5
1.3±0.4
14±6.0
1.0±0.4
4.1±1.0
6.9±1.4
9.7±2.0
6.6±1.2
3.9±0.7
8.5±1.6
12±3.8
8.8±1.3
9.5±2.7
12±2.4
2.8±0.5
4.6±1.5
5.3±0.8
5.7±1.2
6.4±1.8
6.7±1.2
10±4.4
14±1.7
25±7.2
0.9±0.1
1.9±0.4
3.2
1.8
3.4
3.3
1.8
0.9
1.0
2.4
0.5
3.2
3.4
4.3
3.6
2.7
3.7
2.1
4.5
2.0
3.4
2.1
2.7
3.9
3.2
3.0
4.1
2.4
6.6
4.8
1.5
2.0
48.2
51.4
4.3
4.0
4.9
12.8
4.2
5.4
5.9
2.4
5.8±3.9
7.1±3.0
5.7±2.1
12±4.3
5.2±2.6
0.9±0.1
4.9±2.9
3.5±1.7
40
87
60
100
6.7±1.8
12±2.9
9.2±2.4
11±1.8
7.3±1.4
1.1±0.5
3.6±1.1
6.9±2.9
4.8±2.0
13±3.8
18±4.3
14±3.7
3.7±1.3
1.3±0.8
6.4±2.4
4.8±2.4
% sites occupied
75
23
100
100
85
31
65
92
Y-M
Y-O
M-O
1.3
1.7
1.2
1.3
1.7
2.2
1.9
2.6
2.4
0.9
1.2
1.2
1.4
1.6
1.5
2.1
2.9
3.6
0.7
0.9
1.4
1.3
1.3
1.3
1.4
2.8
1.4
3.5
2.5
0.8
52.2
57.8
55.0
50.9
4.9
6.7
6.2
12.2
8.2
0.7
4.9
2.4
2.6
7.6
15.2
12.9
3.1
1.1
7.5
2.1
2.8
3.5
2.9
2.2
2.5
1.1
1.8
2.6
2.6
3.4
3.7
2.5
2.2
1.0
1.9
2.3
2.8
3.5
3.5
2.1
2.5
1.2
1.8
2.8
30.6
38.1
34.8
68.5
69.5
65.2
0.4
2.0
0.9
2.7
1.5
2.8
2.0
1.1
0.1
2.9
0.2
2.3
0.9
0.2
0.7
0.6
0.8
0.3
1.0
0.1
1.3
0
1.3
0.8
24
Banksia rufa subsp. chelomacarpa
Banksia erythrocephala var. erythrocephala
Banksia violacea
Hakea cygna subsp. cygna
Baeckea preissiana
Olax benthamiana
Hibbertia gracilis
Lepidosperma brunonianum
Lomandra mucronata
Neurachne alopecuroidea
Stackhousia scoparia
SSshrub
NSshrub
NSshrub
NSshrub
SNshrub
NNshrub
SNherb
SNherb
SNherb
SNherb
NA
Mean % within age class similarity/between class dissimilarity
Mallee presence/absence
Eucalyptus phenax subsp. phenax
SStree
Eucalyptus scyphocalyx
SStree
Melaleuca hamata
SSshrub
Dodonaea viscosa subsp. spatulata
Leucopogon cuneifolius
Rinzia communis
Gahnia ancistrophylla
Lepidosperma brunonianum
Lepidosperma pubisquameum
Westringia rigida
Mean % within age class similarity/between class dissimilarity
638
639
SNshrub
NNshrub
SNherb
SNherb
SNherb
SNherb
NA
100
87
73
67
80
73
100
100
73
100
80
10
60
100
30
0
70
70
90
90
10
100
95
95
100
90
5
95
85
75
90
10
65
75
10
0
20
5
70
95
40
90
65
92
100
100
100
100
0
100
100
100
92
15
2.7
2.0
1.4
1.1
1.7
1.4
2.7
2.7
1.4
2.7
1.7
2.8
2.5
2.5
2.8
2.2
0
2.5
2.0
1.5
2.2
0.0
2.4
2.9
2.9
2.9
2.9
0
2.9
2.9
2.9
2.4
0.0
0
0.3
0.5
0.6
0.4
1.2
0.1
0.3
0.6
0.2
1.2
0.1
0.2
0.5
0.6
0.4
1.3
0
0
0.5
0.1
1.3
0.2
0.1
0.1
0
0.2
0.1
0.1
0.3
0.5
0.3
0.5
56.0
60.4
60.8
47.8
45.0
41.3
20
100
100
0
2.6
8.3
3.1
4.0
7.2
0.2
8.6
8.6
1.6
1.2
0
0.7
1.1
0
1.7
0.7
0
70
60
100
60
50
100
20
0.5
0
3.7
3.7
7.0
6.5
0
0.2
0
3.3
6.5
1.0
5.7
3.0
4.5
2.7
8.6
2.4
1.6
8.6
0.2
0.9
0.1
1.1
0.9
1.5
0.5
1.6
1.6
1.6
0.8
1.3
1.4
0.3
0.7
1.9
1.6
0.9
1.3
1.4
0.3
1.7
38.3
43.6
42.2
62.9
63.2
59.7
25
640
Table 4. Richness and cover of each plant functional type (PFT) between vegetation age classes in mallee and mallee-heath. See Table 1 for PFT
641
codes. Mean ± standard error for each age class per habitat shown, with F-values and significance levels (**** P < 0.0001; ** P < 0.01; * P <
642
0.05) from ANOVA. Different superscripts indicate significant differences in age class according to post-hoc Newman-Keuls tests. Young = <
643
10 yrs post-fire, mature = 18-35 yrs post-fire, old = > 40 yrs. Grey shading indicates differences (or lack thereof) inconsistent with predictions.
PFT
Mallee-heath PFT richness
Young
Mature
Mallee PFT richness
Old
F2,45
Young
Mature
b
4.65±0.3
Old
a
SStree
1.67±0.2
1.25±0.2
1.69±0.2
1.62
3.40±0.3
NStree
2.40±0.3
2.85±0.2
2.85±0.3
0.84
0.50±0.3
0.45±0.2
SNtree
0.47±0.2
0.65±0.2
0.38±0.1
0.80
0
NNtree
2.47±0.5
2.80±0.3
1.69±0.2
2.41
SSshrub
8.67±0.6
7.80±0.5
8.92±0.5
NSshrub
b
a
10.8±0.6
a
12.3±0.3
ab
11.6±0.4
Prediction
3.80±0.4
F2,37
ab
4.51*
Stable
0.90±0.4
0.87
Stable
0
0
-
Stable
0.60±0.2
0.85±0.2
0.40±0.2
1.36
Stable or decrease
1.21
1.70±0.2
1.70±0.2
2.10±0.4
0.88
Stable
ab
3.46*
3.10±0.6
3.15±0.6
2.90±0.9
0.03
Stable
b
3.70*
4.50±0.3
4.45±0.4
4.40±0.3
0.01
Stable or decrease
SNshrub
7.27±0.7
NNshrub
9.53±0.6a
9.85±0.3a
6.92±0.6b
10.4***
8.50±1.2
6.70±0.5
6.50±0.9
1.70
Decrease
18.7±1.2
a
a
a
3.23*
6.90±0.7
7.20±0.7
6.20±0.7
0.43
Stable or decrease
4.47±0.5
a
2.92±0.6
b
6.13**
2.20±0.6
1.95±0.3
1.20±0.3
1.62
Decrease
3.07±0.7
a
0.62±0.2
b
16.7***
2.60±0.7
0.05±0.1
0
-
Post-fire only
9.87±0.9
a
5.54±0.6
b
11.1***
7.90±1.0
6.90±0.5
5.30±1.0
2.56
-
SNherb
NNherb
Ephem
NA
5.90±0.4
15.4±0.5
2.60±0.3
b
0.35±0.1
b
6.45±0.3
b
5.31±0.4
17.0±0.9
Mallee-heath PFT % cover
Mallee PFT % cover
SStree
8.80±1.9
9.45±2.0
7.65±1.8
0.22
30.8±3.7a
42.5±2.7b
48.4±3.1b
6.12**
Stable or increase
NStree
3.33±0.7a
20.2±2.9b
15.1±3.9b
24.5***
0.80±0.6
0.90±0.4
5.40±3.4
2.44
Increase
SNtree
0.47±0.2
2.15±0.8
0.54±0.2
2.24
0
0
0
-
Stable or increase
NNtree
4.07±1.1
a
10.2±1.6
b
4.77±1.2
a
7.07**
1.80±1.2
1.55±0.4
2.30±1.5
0.10
Intermediate peak
SSshrub
27.4±3.5
22.2±2.1
32.4±4.3
2.67
13.0±4.3
12.0±2.1
16.9±5.0
0.55
Stable
26
644
NSshrub
33.9±6.6c
79.3±4.8b
100.2±9.8a
22.6***
7.40±1.7
6.75±1.6
7.20±2.8
0.03
Increase
SNshrub
14.4±2.0
11.1±1.3
9.77±1.7
1.95
12.5±2.4
9.75±1.0
17.5±4.2
2.55
Stable or decrease
NNshrub
16.7±1.8
b
25.5±1.9
a
18.4±2.9
b
5.13**
23.5±6.6
21.9±2.9
25.6±5.2
0.18
Intermediate peak
SNherb
41.6±5.2
35.9±2.9
31.1±3.7
1.61
22.7±7.3
20.1±2.3
20.0±4.4
0.01
Decrease
NNherb
6.40±1.0
a
2.90±0.3
b
3.00±0.5
b
8.40***
6.50±2.2
9.45±2.8
5.60±2.3
0.57
Decrease
Ephem
6.73±2.1
a
0.35±0.1
b
0.62±0.2
b
16.9***
3.90±1.4
0.05±0.1
0
-
Decrease
NA
15.3±2.1
10.5±1.2
12.8±2.4
1.92
19.0±2.5
15.1±2.0
18.1±4.8
0.56
-
Total
cover
179±7.6b
230±5.7a
236±9.4a
17.3***
142±10.8
140±5.9
167±16.5
1.80
27
645
Fig. 1. Non-metric multi-dimensional scaling ordination of sites in each habitat by (a) floristic cover and (b) cover of plant functional types (PFT), with
646
age class indicated by numbers. MDS on square-root transformed data, 100 runs, random start configurations and three dimensional final solutions,
647
with bubble size showing the 3rd dimension. Vectors are (a) those for the top three species contributing to similarity within and dissimilarity between
648
times since fire (Table 2; also has species names) and (b) PFTs (see Table 1) with a Pearson correlation coefficient > 0.5.
649
Mallee-heath
650
(a) Floristic cover
Mallee
3D Stress: 0.18
3D Stress: 0.16
1
1
1
1
1
BEAMICMIC
3 1
1
3 1
MELVIL
33 1
3
2 22
BANRUFCHE EUCPLE
2
HAKPANCRA
2
HAKCYGCYG
BANERYERY
2
652
1
EUCSCY
1
3
3
2
EUCFLOFLO
32
BEASCH
22 3
2
2
2
2
Age post-fire
1 = < 10 yrs
2 = 19-35 yrs
3 = > 40 yrs
2 2
2
2
2
1
3
3
2
3
2
GAHANC
1
1
2
3EUCPHAPHA2
22
2
1
3
MELHAM
LEPBRU
3
3
CRYLEU
2 2
2
651
1
2
2
3
2 LEPPUB
1
1
1 1
3
2
1
1 2
SPYCOR
1
3
3NEUALO
3
22
1
3
2
2
2
2
3
1
28
653
654
(b) Cover of PFTs
3D Stress: 0.15
3D Stress: 0.14
1
1
2
1
3
3
1
SSshrub
3
1
1
NSshrub
NNherb
1
1
1
1
2
3 3
Ephem
2
2
2
2
1
1
SNherb
1
1
1
2
NStree
3
2
2
2
3
2
656
3
2
2 2
1
1
2
1
22
SStree
2
2
2
2 2
2
NStree
2
NNshrub
2
SNherb
1 SSshrub
22
Age post-fire
1 = < 10 yrs
2 = 19-35 yrs
3 = > 40 yrs
3
3
2
3
3
2
SNshrub
2
2
3
NNtree
655
1
NSshrub
22
2
2
3
1
2
1
3
3
2
3 2
2
2
3
3
3
1
2
1
3
1
3