The Effects of Prey, Habitat Heterogeneity and Fire on the Spatial

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Austral Ecology (2014) 39, 181–189

The effects of prey, habitat heterogeneity and ﬁre on the spatial ecology of peninsular Diamond Pythons (Morelia spilota spilota: Pythonidae)

DAMIAN R. MICHAEL,* ROSS B. CUNNINGHAM, CHRISTOPHER MACGREGOR, DARREN BROWN AND DAVID B. LINDENMAYER Fenner School of Environment and Society, The Australian National University, Canberra, ACT 0200, Australia (Email: [email protected])

Abstract Understanding an organism’s home range is an important component of effective wildlife management. However, home ranges can vary spatially and temporally within and between populations. Landscape ecology theory can provide a framework for understanding spatio-temporal variability in animal traits. We used radio- telemetry in a population of diamond python Morelia spilota spilota Lacépède (Pythonidae) from a biologically rich and structurally heterogeneous reserve in eastern Australia to explore the relationship between home range size, optimal foraging theory and vegetation mosaic theory.Twelve adult snakes were tracked between September 2004 and February 2008. Male home ranges were significantly larger (P < 0.05) and more variable (41 Ϯ 30 ha) than female home ranges (23 Ϯ 5 ha), and males moved further between observations (123 m c.f. 65 m). Core activity centres varied significantly among habitat (P < 0.05) with larger home ranges observed in heathland, a vegetation community which supported comparatively low mammal diversity. No other variables examined including number of fixes, body length, prey abundance, vegetation heterogeneity or fire history explained home range variability. In this system, relatively high mammalian prey diversity and rapid post-fire vegetation succession may limit prey availability and fire effects as being significant determinants of home range variability in M. spilota.

Key words: home range, optimal foraging theory, prey availability, pyro-diversity, vegetation heterogeneity.

INTRODUCTION reptiles have the ability to reduce metabolic costs when there is a shortage of food, and incredibly high densi- Effective wildlife management is underpinned by ties of some species such as the red-sided garter snake knowledge of species resource requirements, including Thamnophis sirtalis (Gregory & Stewart 1975) may be an understanding of the factors that influence move- accounted for by this reptilian trait. ment patterns and space utilization (Caughley & Many early studies of snakes reported strong differ- Sinclair 1994). Developments in radio-telemetry over ences in home range size between sexes (Shine 1987; the past three decades have enabled researchers to Macartney et al. 1988; Slip & Shine 1988c; Weatherhead study space use in a wide range of organisms (White & Hoysak 1989), non-significant differences in home & Garrott 1990). Understanding differential spatial range size between sexes (e.g. Natrix natrix Madsen 1984) responses in vertebrates can result from examin- and contrasting home range size sex differences between ing density-dependent predator-prey relationships different populations (e.g. Morelia spilota imbricata (Tilman & Kareiva 1997). Many studies on large Pearson et al. 2005). These conflicting accounts obscure mammals have found inverse relationships with home general spatial patterns from being identified based solely range size and prey density. For example, home ranges on gender (Macartney et al. 1988). Clearly, there are of the Eurasian lynx Lynx lynx increased in response to other factors that influence space utilization in snakes, low densities of roe deer Capreolus capreolus (Herfindal including migratory behaviour (Gregory & Stewart 1975; et al. 2005). Litvaitis et al. (1986) found home ranges Larsen 1987; Neumann & Mebert 2011), agonistic inter- of the bobcat Felis rufus increased in response to actions (Whitaker & Shine 2003), landscape hetero- declining numbers of the snowshoe hare Lepus geneity (Hoss et al. 2010; Kapfer et al. 2010), and prey americanus. These patterns are often attributed to the distribution and abundance (Schwaner 1991; Madsen & high metabolic rate and energy expenditure costs Shine 1996; Whitaker & Shine 2003; Heard et al. 2004). that are characteristic of large carnivorous mammals Prey diversity can fluctuate over various spatial and (Carbone et al. 2011). In contrast, unlike mammals, temporal scales. For example, the relationship between fluctuating small mammal populations and climatic *Corresponding author. conditions is well documented (Dickman et al. 1999; Accepted for publication April 2013. Letnic & Dickman 2006; Greenville et al. 2012).

Resources and conditions that fluctuate unpredictably context of landscape ecology theories, as well as com- may cause individuals to utilize more space depending paring sex effects with other studies. on seasonal conditions (Brown & Shine 2002; Roe 1. Do home ranges differ between males and et al. 2004; Schofield et al. 2010). Whitaker and Shine females? We predicted that male home ranges will (2003) found home ranges in male eastern brown be larger than females because reproductive males snakes Pseudonaja textilis increased when populations tend to monopolize areas with access to many of the house mouse Mus musculus declined with females (Slip & Shine 1988c). drought conditions. Resource productivity also can be 2. Is there a relationship between prey abundance marginal near the edge of a species geographical range and home range size (sensu optimal foraging resulting in large home ranges (Arvisais et al. 2002; theory)? Degregorio et al. 2011). Optimal foraging theory 3. Is there a relationship between habitat attributes (sensu MacArthur & Pianka 1966) predicts that space (e.g. vegetation association and vegetation hetero- use will be related to the distribution and abundance geneity) and home range size (sensu vegetation of resources over large spatial-scales. Because animal mosaic theory)? movements often come at a cost of increased predation 4. Is there a relationship between fire attributes and risk and energy expenditure, one hypothesis is that home range size (sensu pyro-diversity theory)? animals will occupy the smallest home range that A central prediction of this study was that pythons which includes adequate critical resources, such as prey and occupy home ranges in burnt, highly heterogeneous veg- shelter sites, thereby minimizing movement associ- etation communities or in areas with high prey diversity ated costs (Hoss et al. 2010). Consequently, if these will have smaller home ranges than pythons which occupy resources are more accessible or abundant in particu- home ranges in unburnt, homogeneous vegetation com- lar environments then home range size may be directly munities or in areas with low prey diversity. related to prey abundance (Hoss et al. 2010). Variability in the abundance of prey for snakes such as terrestrial mammals can be a function of land use METHODS history such as fire regimes (Andersen et al. 2005), as well as intrinsic landscape features which are known to Study animal influence vegetation patterns such as soil and moisture gradients (Feldhamer 2010). These concepts give rise The diamond python Morelia spilota spilota is a colour morph to vegetation mosaic theory (sensu Wiens 1995) and of the widely distributed Australian carpet python Morelia pyro-diversity theory (sensu Martin & Sapsis 1992), spilota complex (Taylor 2005) and can attain a length of which predict that high variability in patterns of veg- 3.5 m (Wilson & Swan 2010). The species is semi-arboreal etation or fire can promote high levels of biotic diver- and can withstand long periods of reduced metabolic activity sity, which may in turn influence predator – prey space during the winter months (Slip & Shine 1988a). Morelia use dynamics. The relative effects of these ecological spilota is a non-venomous, ambush predator preying on a theories are often difficult to unravel as the effects of wide range of small mammals and lizards as a juvenile and fire on vegetation (and associated fauna) in heteroge- transitioning to prey such as medium-sized mammals and neous landscapes can produce complex and confound- nestling birds as an adult (Slip & Shine 1988b). The species is generally solitary but individuals aggregate during the ing interactions (Lindenmayer et al. 2008a; Williams breeding season and in some areas, spend the winter in et al. 2012). hibernacula such as deep rock crevices (Slip & Shine 1988a). The python Morelia spilota is an ideal species in Females lay a single clutch of up to 54 eggs in a nest of leaf which to study spatial ecology for several reasons. litter beneath dense vegetation, in tree cavities or hollow logs (i) Home ranges have previously been reported in (Slip & Shine 1988c). Incubation lasts for 60–80 days and M. spilota (e.g. Slip & Shine 1988a; Shine & Fitzgerald hatching occurs between late February and March. Along the 1996; Pearson et al. 2005; Corey & Doody 2010), east coast of Australia, M. spilota can attain high densities in enabling direct comparison with other studies. (ii) suitable habitat (Slip & Shine 1988a; Shine & Fitzgerald Home ranges are variable both within and between 1996; Fearn et al. 2001) despite evidence of a broader in- populations (Pearson et al. 2005) providing a founda- land decline (Shine 1994; Heard et al. 2004; Michael & Lindenmayer 2008; Corey & Doody 2010; Michael 2011). tion for testing the validity of ecological theory in explaining home range size variability. (iii) Morelia spilota attain large body sizes (3.5 m in total length) Study area enabling the use of long-life radio-transmitters. To explore factors that might influence home range This study was conducted in Booderee National Park (BNP) size we radio-tracked M. spilota in a biologically rich (35°09′14″S, 150°42′41″4) on the south-east coast of Aus- and structurally heterogeneous reserve on the east tralia (Fig. 1).The park covers an area of 5437 ha within the coast of Australia. We posed four questions with the Jervis Bay Territory and is co-managed by the Wreck Bay aim of examining home range size variability in the Aboriginal Community and Parks Australia. The area has doi:10.1111/aec.12056 © 2013 The Authors Austral Ecology © 2013 Ecological Society of Australia SPATIAL ECOLOGY IN MORELIA SPILOTA 183

probing (Laszlo 1975) and fitted with a temperature- sensitive A1-2T radio-transmitter (43 ¥ 15 mm, 20.5 g with a battery life of 30 months; Holohil Systems Ltd, Ontario, Canada). Transmitters did not exceed 3% of a snake’s mass. Animals were anesthetized via a mobile gas unit using 5% isofluorane administered with medical grade oxygen at five breaths per minute. During surgery, snakes were maintained on 2% isofluorane at two breaths per minute and were revived using oxygen at one breath every 2 min.Transmitters were implanted within the coelomic cavity following the procedures described in Webb and Shine (1997). All snakes were subcutaneously injected with a passive integrated trans- ponder approximately 30 cm anterior of the vent. Following surgery, all snakes were held in captivity, housed separately in glass tanks (150 cm ¥ 80 cm ¥ 70 cm) and provided with water ad libitum in a room that was maintained at a constant Fig. 1. Location of Booderee National Park in Jervis Bay temperature of 26°C. After a minimum of three days in Territory, south-eastern Australia. recovery snakes were released at their point of capture. a temperate maritime climate with an average annual rain- Radio-telemetry fall of 1150 mm spread evenly over the year (Bureau of Meteorology 2012). The average minimum and maximum We commenced radio-tracking within three weeks after temperature ranges from 18–24°C in February and 9.5°C- the release date and located snakes once every 2–3 weeks 16°C in July (Bureau of Meteorology 2012). The geology of between October 2004 and February 2008. We located BNP is dominated by Permian (approx. 260 million year old) animals using a standard radio receiver and hand-held sandstone sequences that form part of the southern bound- three-element folding Yagi antenna and recorded Universal ary of the Sydney Basin (Cho 1995). Transverse Mercator (UTM) coordinates using a GPS unit In 1977, a prescribed fire regime was established in BNP to (Garmin, Etrex). maintain vegetation heterogeneity (Mills 1995). Since Euro- pean settlement, fire severity has changed dramatically with major wildfires burning 80% and 65% of the park in 1972 and Home range analysis 2003 respectively (Lindenmayer et al. 2008a). Historically, parts of BNP were grazed by livestock, logged and converted to pine Pinus spp. plantation or developed to accommodate a Overall home range small village, camp grounds and parking areas. Despite past and present land use, BNP supports large areas of highly We defined home range as the area used by an individual to significant coastal vegetation (Mills 1995). BNP also supports conduct activities such as locating prey, searching for mates rich biological diversity including over 625 native plant and seeking shelter over a defined time period (White & species (Taws 1998), 30 mammal species (Braithwaite et al. Garrott 1990).Toestimate overall home range, we included all 1995; Lindenmayer et al. 2008a), 34 species of herpetofauna snakes (n = 12) with >25 observations over the study period (Lindenmayer et al. 2008b; Penman & Brassil 2010) and over (mean = 45 Ϯ 15 fixes, range = 25–73 fixes) (Powell 2000). 200 bird species (Lindenmayer et al. 2009). Furthermore, We computed parametric (100% minimum convex polygon, BNP is characterized by extraordinary patchiness and hetero- MCP) and non-parametric home ranges (95% and 50% fixed geneity in vegetation types (Baker et al. 2002), ranging from kernel density estimates, KDE) using Ranger VI software dry heathland to warm temperate rainforest (Taws 1998). (Anatrack Ltd). For KDE estimates, we applied a fixed band These vegetation types vary markedly in floristic diversity and width and determined the smoothing parameter using least structural complexity (Mills 1995) making BNP an ideal place squares cross validation (Seaman et al. 1999). The KDE to study spatial ecology. estimate requires 30–50 observations per animal to produce robust estimates (Seaman et al. 1999). However, observations collected over long temporal scales can overcome the limita- Capture of study animals and implantation of tions of low sample size (Swihart & Slade 1985). radio-transmitters

We captured 12 pythons between September 2004 and Annual home range 2005 by searching rocky outcrops, hollow logs, tree cavities and vegetation. Several animals crossing roads or removed To estimate annual home ranges we used snakes with > 10 from camping ground were collected incidentally. Snakes observations per year (04/05: n = 8 snakes; 05/06: n = 10 were measured from snout to vent (x male = 160.45 cm, snakes; 06/07 n = 2 snakes) giving a total of 20 annual home x female = 170.11 cm) and weighed (x male = 1630 g, range estimates. Annual home ranges were deﬁned as the x female = 2298 g) in the laboratory prior to transmitter activity period between emergence from hibernacula in implantation (Appendix S1). Snakes were sexed by cloacal spring (e.g. tree cavity, hollow log, rock crevice or dense

vegetation) and winter retreat (i.e. the warm period spanning within the home range (MCP and 50% KDE) of all snakes approximately eight months over two consecutive years). using GIS software. The vegetation community with the largest proportional area within the home range was termed the primary habitat and this variable was used in analysis.We Prey abundance (mammal surveys) calculated vegetation heterogeneity by summing all vegetation types within the overall home range and core activity We recorded mammalian prey in BNP based on trapping centre of all snakes to produce an index of habitat complexity surveys of 109 sites (Fig. 2) in February and April 2004, ranging from 1–4. November 2004, January and February 2005, November 2005, January and February 2006. Survey protocols involved checking six pitfall traps, ten Elliott traps and six cage traps along a 100 m transect for three consecutive days. Pitfall traps consisted of 20 litre buckets buried level with the ground, Fire spaced 20 m apart and connected by black plastic drift fences between 0–20 m, 40–60 m and 80–100 m. Pitfall traps and To explore the relationship between fire and home range cages were checked once each day between sunrise and 09.00 size, we plotted overall home ranges and core activity hours. Elliott traps and cage traps in which an animal had been centres of all snakes and overlaid a GIS spatial layer to show captured were wiped clean, re-baited and re-positioned where mammal trapping sites that were burnt in 2003 (Fig. 2). We the initial capture had taken place. We marked the ears of then categorized home ranges as burnt or unburnt depend- captured animal with a semi-permanent white pen to identify ing on whether they included burnt or unburnt trapping recaptures (see Lindenmayer et al. 2008a for additional detail sites, or selected the nearest trapping site. We visually on trapping methodology). Mean terrestrial mammal abun- assessed fire severity at each trapping site and assigned a = = dance was calculated by summing the number of individual score ranging from 0 to 5; where 0 no fire, 1 understo- = = animals of each species captured during each survey divided rey burnt, 2 midstorey burnt but not killed, 3 midstorey = by the number of surveys and transects in each vegetation burnt and killed, and 4 overstorey burnt and killed. We community. Arboreal marsupials were recorded annually categorized home ranges according to the corresponding between 2004 and 2007 during spotlight surveys along the fire severity score of the inclusive or nearest trapping site. same 100 m transect for a total of 20 min between 20.30 and Where two or more inclusive trapping sites with different 23.30 hours. Mean arboreal marsupial abundance was calcu- fire severity scores occurred within a home range, the most lated in the same way as terrestrial mammals. representative score for that vegetation type in the sur- rounding landscape was used. One caveat in using this technique is that fire severity is confounded with vegetation Habitat type (see Lindenmayer et al. 2008a,b). To examine temporal effects of fire on home range size, we classified home ranges We classified habitat based on vegetation associations. We according to four time-since-fire categorizes (0 = unburnt, calculated the relative area of six vegetation communities 1, 2, 3 years after fire).

Fig. 2. Location of mammal trapping sites (dots) and the spatial relationship with home ranges (100% MCP) of six male and six female Morelia spilota in Booderee National Park (red dots indicate trapping sites that were burnt in December 2003). doi:10.1111/aec.12056 © 2013 The Authors Austral Ecology © 2013 Ecological Society of Australia SPATIAL ECOLOGY IN MORELIA SPILOTA 185

Statistical analysis ranges (male MCP = 41.3 Ϯ 29.7 ha, female MCP = 23.3 Ϯ 4.97 ha). Overall, male home ranges varied from To evaluate factors influencing home range size, we used 18 to 97 ha and female home ranges varied from 15 to generalized linear models (GenStat V15) in an a priori model 29 ha. Male core activity centres also were significantly set.We used MCP and 50% KDE as our response variables in larger (P = 0.037) and more variable than females (male separate analyses.We included a range of different explanatory 50% KDE = 8.84 Ϯ 3.61 ha, female 50% KDE = 1.9 Ϯ variables in our models including sex, SVL, number of fixes, 0.78 ha). MCP, 95% and 50% KDE estimates did not mean prey abundance, primary vegetation association, vegetation heterogeneity index, fire history, fire severity and time differ significantly between years for either sex (female since fire.These explanatory variables are fixed effects.Animal t-test = 0.48, d.f. = 9, P = 0.6; male t-test = 1.27, d.f. = 7, identification was incorporated as a random effect to account P = 0.2). On average, males moved further between for intra-animal dependence between years. We used anova observations than females (123.13 Ϯ 52.7 m c.f. 65.8 Ϯ (spss v17) to examine differences in both terrestrial mammal 32.4 m). Two snakes were gravid and incubated eggs and arboreal marsupial mean abundance among six vegeta- during the study. MCP home ranges for these females tion communities (rainforest, forest, woodland, shrubland, during their reproductive year were larger than other years heathland and sedgeland).We found no significant association (snake #6: 04/05 MCP = 13.57 ha, n = 27 fixes; 05/06 with home range size and SVL or number of fixes so these MCP = 6.8 ha, n = 26) (snake #11 MCP: 04/05 = variables are not discussed further. 4.87 ha, n = 34; 05/06 MCP = 2.52 ha, n = 9; 06/07 MCP = 15.19 ha, n = 5) and coincided with large post- RESULTS parturition movements.

Correlates of home range size estimates Prey abundance We found MCP and 95% KDE overall home range anova estimates to be positively correlated (r2 = 0.89, P < revealed a signiﬁcant difference in the mean 0.001, Fig. 3a). Both estimates produced similar abundance of total mammal species among vegeta- = = results for all snakes combined over the study tion communities (F5,11 12.46, P 0.007), but not = = period (MCP x =±32.. 28 22 36 ha, 95% KDE between years (F1,6 1.28, P 0.3). Overall, the mean x =±31.. 95 24 68 ha) and between years (04/05 MCP abundance of terrestrial mammals and arboreal mar- x =±11.. 76 5 75 ha, 95% KDE x =±14..ha 12 6 65 , supials was lowest in heathland ( x terrestrial mammal = 05/06 MCP x =±17..ha 64 17 23 , 95% KDE abundance 5.03 individuals/site; x arboreal marsu- = x =±26..ha 82 24 27 ). After log transformation we pial abundance 0.12 individuals/site) and highest in = found weak correlation between the two methods rainforest (x terrestrial mammal abundance 11.27 = (r2 = 0.24, Fig. 3b). Thus, we used MCP to describe individuals/site; x arboreal marsupial abundance overall home range and 50% KDE to describe core 1.24 individuals/site). activity centres. Three species differed signiﬁcantly in abundance among vegetation communities; brown antechinus

Antechinus stuartii (F5,11 = 8.48, P = 0.01), swamp rat

Effect of sex Ratus lutreolus (F5,11 = 5.87, P = 0.03) and common

brushtail possum Trichosurus vulpecula (F5,11 = 5.95, We found overall male home ranges were signiﬁcantly P = 0.03). Overall, A. stuartii (x abundance = 3.54 larger (P = 0.031) and more variable than female home individuals/site) and T. vulpecula x abundance = 0.56

Fig. 3. Correlation between 100% minimum convex polygon (MCP) and 95% kernel density estimate (KDE) for: (a) overall home range and (b) annual home range.

© 2013 The Authors doi:10.1111/aec.12056 Austral Ecology © 2013 Ecological Society of Australia 186 D. R. MICHAEL ET AL. individuals/site) were most abundant in forest and rain- Fire forest respectively, and R. lutreolus was most abundant in heathland (x abundance = 0.41 individuals/site). We found no significant association between home Trichosurus vulpecula was the only species to fluctuate range estimates and the 2003 wildfire (burnt versus significantly in abundance between years (F1,11 = 6.16, unburnt) (MCP: P = 0.9; 50% KDE: P = 0.7). Nor P = 0.05), where it was observed twice as frequently did we find any significant association with home in forest and almost three times more frequently in range estimates and fire severity (MCP: P = 0.09; 50% rainforest during the 2005/2006 survey. Despite signifi- KDE: P = 0.5) or time since fire (MCP: P = 0.9; 50% cant differences in the relative abundance of mammals KDE: P = 0.6). among vegetation types, we found no statistically significant association between snake home range and DISCUSSION terrestrial mammal abundance (MCP: P = 0.7; 50% KDE: P = 0.87) or arboreal marsupial abundance (MCP: P = 0.55; 50% KDE: P = 0.15). Effect of sex

Previous studies on M. spilota have found gender dif- Habitat ferences in home range size (Slip & Shine 1988a) as well as considerable variation in home range estimates Snakes were located in all six broad vegetation commu- among geographically isolated populations (Pearson nities; rainforest, forest, woodland, shrubland, heath- et al. 2005). In BNP, we found male overall home land and sedgeland. However, because of the patchy ranges to be twice as large, and more variable, than nature and small area of rainforest and sedgeland in female home ranges (41.32 Ϯ 29.67 ha c.f. 23.26 Ϯ BNP, these two vegetation communities did not consti- 4.97 ha). This result is congruent with the work of tute a primary vegetation association for any individual. other researchers. For example, male M. spilota from Therefore, only four vegetation communities were coastal sandstone escarpments north of Sydney, NSW, included in the analysis. We found no significant rela- used more space than females (52 Ϯ 35.4 ha c.f. tionship between MCP and primary vegetation asso- 27.84 Ϯ 29.14 ha), with one male occupying an area ciation (P = 0.7). However, we found the size of core up to 124 ha (Slip & Shine 1988a). Home ranges of activity centres differed significantly between vegeta- M. spilota from inland NSW were comparatively small tion types (P = 0.019). In heathland, core activity (mean 4.6 Ϯ 6.7 ha), although males occupied up centres were significantly larger than in other vegetation to an order of magnitude more space than females type and almost twice as large as in shrubland (Fig. 4). (Corey & Doody 2010). In contrast, home ranges in We found no significant association between home M. spilota from coastal northern NSW did not differ range estimates and vegetation heterogeneity (MCP: significantly between sexes (Shine & Fitzgerald 1996). P = 0.5; 50% KDE: P = 0.7). Appendix S2 shows the Similarly, in Western Australia, male M. spilota on the spatial relationship between annual core activity centres mainland occupied more space than females and con- and vegetation community for all snakes. versely, less space than females on an off-shore island (Pearson et al. 2005). One hypothesis is that home range size variation between genders is based on density-dependent mate- searching behaviour (Pearson et al. 2005), whereby males occupy more space in environments where female numbers are low. In our study, due to the low sample size, we were unable to estimate male and female population densities for each broad vegetation community. However, two males (#14 and #17) in forest with large home ranges occupied areas where no females were caught or observed during the study (Appendix S2). In contrast, a male (#12) with one of the smallest home ranges occupied an area which strongly overlapped the core activity centre of several females (Appendix S2).

Prey abundance Fig. 4. Variation in the mean size (ha) of Morelia spilota core activity centres (50% KDE) among four broad vegetation communities in Booderee National Park. KDE, kernel Ambush predators spend long periods of time motion- density estimate. less in areas with high prey density (Slip & Shine doi:10.1111/aec.12056 © 2013 The Authors Austral Ecology © 2013 Ecological Society of Australia SPATIAL ECOLOGY IN MORELIA SPILOTA 187

1988b; Madsen & Shine 1996; Brito 2003). Morelia found vegetation type to be an important factor in spilota is an ambush predator and feeds on a wide explaining home range size. Snakes in heathland had range of mammals including rats Rattus sp., bandi- significantly larger core activity centres than snakes in coots Perameles sp., ringtailed possum Pseudocheirus forest, woodland or shrubland (Fig. 4). One reason to peregrinus, the introduced European rabbit Oryctolar- explain these differences is the lack of suitable shelter gus cunninculus and birds (Slip & Shine 1988b; Shine sites (e.g. large logs and trees with hollows) in heathland & Fitzgerald 1996; Heard et al. 2004). We used data which may cause pythons to use more space than in from our long-term mammal monitoring program vegetation types which support hollow logs or hollow- (Lindenmayer et al. 2008a) to extrapolate relative bearing trees. However, snakes located in heathland abundance of terrestrial mammals and arboreal mar- were often found sheltering beneath dense vegetation supials across vegetation types. We did not include (e.g. Lambertia formosa), coiled in low shrubs, or long-term bird data (Lindenmayer et al. 2009) as birds sequestered in cavities below the ground (D. Michael, comprise a small proportion of the diet of M. spilota unpubl. data, 2007).This suggests M. spilota is flexible (Slip & Shine 1988b). in its use of shelter sites in different vegetation types. Although we found significant differences in mammal abundance among vegetation types, we found no significant relationships between home range esti- Fire mates and prey abundance. This result is surprising considering snakes in heathland had large core activity Based on pyro-diversity theory (sensu Martin & Sapsis centres (Fig. 4) and this vegetation community also 1992) and vegetation mosaic theory (sensu Wiens 1995), supported low mammal diversity – a relationship that we hypothesized that fire would alter vegetation cover would be consistent with optimal foraging theory. It is which, in turn, would affect prey distribution and abun- possible that the scale of resolution used to map and dance (Pearson et al. 2005). This process, termed post- delineate broad vegetation types in BNP was too coarse fire (secondary) succession, has been documented for to detect small-scale changes in vegetation communi- mammals in other flammable Australian ecosystems ties. Similarly, at the vegetation sub-formation level, the (Williams et al. 2012). However, we found fire history mapping resolution may have been too fine to relate (burnt versus unburnt), fire severity and time-since-fire to our mammal trapping data. One possibility is that were not significant factors in explaining home range size. within a given vegetation type, irrespective of the rela- It is possible the effects of the 2003 wildfire were medi- tive differences in prey abundance between vegetation ated by rapid post-fire vegetation recovery and high levels types, M. spilota will occupy relatively prey-rich areas of burn patchiness which left mosaics of unburnt habitat within their overall home range. Examination of the refuges across the park. Furthermore, we found that wild- spatial arrangement of activity centres over time may fire had very limited short-term negative effects on terres- support optimal foraging theory, as most individuals trial mammal distribution and abundance. For example, a occupied partially overlapping or completely discrete previous study found prey such as the long-nosed bandi- areas from previous years (Appendix S2).This pattern coot P. nasuta increased following the fire (Lindenmayer implies that pythons may have the spatio-temporal et al. 2008a). It is likely that when we began tracking cognitive abilities necessary to remember predation pythons nine months after the wildfire, any immediate success at a particular site and respond accordingly effects of the fire were no longer evident. by moving from a low productivity area to a high Fire in naturally heterogeneous landscapes may not productivity area within their home range. directly influence space use in wide ranging predators for the reason mentioned above. However, fire frequency, fire severity and the seasonal timing of fires Habitat may have a long-term influence on habitat use and reproductive success of pythons. For example, during Several studies have found habitat quality is an impor- this study two snakes incubated eggs between January tant component of home range size variability in snakes. and March (snake #6 nested in burnt forest whereas For example, the home range of bullsnakes Pituophis snake #11 nested in unburnt woodland). Both incu- catenifer sayi in North America increased as a function bation sites consisted of a mound of leaf litter located of the amount of unsuitable habitat (Kapfer et al. beneath dense vegetation. Incubating females and 2010), whereas the eastern indigo snake Drymarchon their clutch would be vulnerable to fire from early couperi used a smaller area in fragmented habitat summer through to autumn. Similarly, snakes which compared to snakes in natural areas (Breininger et al. occur in areas devoid of suitable refuges (e.g. subter- 2011). Similarly, Hoss et al. (2010) found the eastern ranean holes, deep rock crevices, hollow logs or tree diamond-backed rattlesnake Crotalus adamanteus in cavities) may be affected by frequent high severity North America occupied a smaller area in landscapes fires. It is not known what avoidance strategies, if any, with more heterogeneous vegetation types. We also pythons have to escape fire.

CONCLUSION Bureau of Meteorology (2012) [Cited March 2012.] Available from URL: http://www.bom.gov.au. Our findings suggest home range size variability in Carbone C., Pettorelli N. & Stephens P. A. (2011) The bigger they come, the harder they fall: body size and prey abun- M. spilota is influenced by gender and habitat. Because dance influence predator-prey ratios. Biol. Lett. 7, 312–15. we did not find any statistically significant relationship Caughley G. & Sinclair A. R. E. (1994) Wildlife Ecology and with mammalian prey abundance, vegetation heteroge- Management. Blackwell Scientific, Oxford. neity or any of the fire variables we measured, optimal Cho G. (1995) The Jervis Bay environment. In: Jervis Bay. A foraging theory, vegetation mosaic theory and pyro- Place of Cultural, Scientific and Educational Value. Kowari 5 diversity theory did not help explain home range size (eds G. Cho, A. Georges, R. Stoutjesdijk & R. Longmore) variability in this system. Relatively high prey diversity pp. 3–8. Australian Nature Conservation Agency, Canberra. Corey B. & Doody J. (2010) Anthropogenic influences on the and rapid post-fire vegetation succession may mitigate spatial ecology of a semi-arid python. J. Zool. 281, 293–302. prey availability (optimal foraging theory) and fire DeGregorio B. A., Manning J.V., Bieser N. D. & Kingsbury B. A. effects (pyro-diversity theory) as being useful concepts (2011) The spatial ecology of the eastern massasauga in explaining home range variability in M. spilota. (Sistrurus c. catenatus) in Northern Michigan. Herpetologica 61, 71–9. Dickman C. R., Mahon P. S., Masters P. & Gibson D. F. (1999) ACKNOWLEDGEMENTS Long-term dynamics of rodent populations in arid Aus- tralia: the influence of rainfall. Wildl. Res. 26, 389–403. This study was funded by the Australian Research Fearn S., Robinson B., Sambono J. & Shine R. (2001) Pythons Council, the Department of Sustainability, Environ- in the pergola: the ecology of ‘nuisance’ carpet pythons ment, Water, Population and Communities, the (Morelia spilota) from suburban habitat in south-eastern Department of Defence and the Earthwatch Institute Queensland. Wildl. Res. 28, 573–9. and was supported by the Wreck Bay Aboriginal Feldhamer G. A. (2010) Vegetative and edaphic factors affecting abundance and distribution of small mammals in southeast Community. Nick Dexter, Matt Hudson and Tony Oregon. West. N. Am. Nat. 39, 207–18. Carter assisted with project logistics. Simon McDon- Greenville A. C., Wardle G. M. & Dickman C. R. (2012) ald (Spatial Analysis Unit, Charles Sturt University) Extreme climatic events drive mammal irruptions: regres- produced Figures 1, 3 and S2. Volunteers from the sion analysis of 100-year trends in desert rainfall and Earthwatch Institute assisted with mammal surveys. temperature. Ecol. Evol. 2012, 2645–58. 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