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J Appl Ecol. 2023;60:146–157.wileyonlinelibrary.com/journal/jpe
Received: 10 March 2021
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Accepted: 4 September 202 2
DOI : 10.1111/136 5-2664.14315
RESEARCH ARTICLE
A field test of mechanisms underpinning animal diversity in
recently burned landscapes
Katharine L. Senior1,2 | Katherine M. Giljohann1,3 | Michael A. McCarthy2 |
Luke T. Kelly2
This is an op en access arti cle under the ter ms of the Creative Commons Attribution-NonCommercial License , which permits use, dis tribu tion and reprod uction
in any medium, provided the original work is properl y cited an d is not use d for comm ercial purposes.
© 2022 The Author s. Journal of Applied Ecology published by John Wiley & Sons Ltd on behalf of British Ecological So ciety.
1School of BioScie nces, Faculty of S cience ,
The Universit y of Melbo urne, P arkv ille,
Victoria, Australia
2School of Ecosystem and Forest Sciences,
Faculty of Science, The Uni versit y of
Melbou rne, Parkville, Victoria, Australia
3CSIRO L and and Water, Commonwealth
Scientific and I ndust rial Res earch
Organisation, Clayton, Victoria , Australia
Correspondence
Kathar ine L. S enior
Email: kate.l.senior@gmail.com
Funding information
Australian Ac ademy of Science; Austra lian
Government, Department of Education;
Australian Res earch Council , Grant /Award
Number : LP150100765; Ecological Societ y
of Austr alia; Uni versit y of Melb ourne;
Australian Government Research Training
Program; Margaret Middleton Fund;
Holsworth Wildlife Re search Endowme nt;
Albert Shimmins Fund
Handling Editor: Miriam Muñoz- Rojas
Abstract
1. Planned burning generates different types of pyrodiversity, however, experi-
mental tests of how alternative spatial patterns of burning influence animal
communities remain rare. Field tests are needed to understand the mechanisms
through which spatial variation in planned fire affects fauna, and how fire can be
applied to benefit biodiversity.
2. We tested five hypotheses of how fire- driven variation in habitat composi-
tion and configuration affects fauna at fine scales. Small mammal, reptile and
invasive predator activity was monitored at 12 burnt and eight unburnt sites
through the year following a large, planned burn in semi- arid ‘mallee’ woodlands
of southern Australia. We explored measures of burnt or unburnt habitat (‘habi-
tat status’); amount of unburnt vegetation (‘habitat amount’); interspersion of
burnt and unburnt patches (‘habitat complementation’); distance to external or
internal unburnt vegetation (‘habitat connectivity’); and unburnt patch size and
local vegetation cover (‘habitat refuge’). Generalized linear models were used to
test the influence of each variable on capture rates of three small mammal and
11 reptile species; activity of the introduced red fox (Vulpes vulpes); and species
richness of native animals.
3. We found strong support for the habitat status hypothesis and moderate sup-
port for four hypotheses relating to spatial patterns of fire. Reptile assemblages
varied between burnt and unburnt sites, and relationships were identified be-
tween abundance of one or more reptile species and each measure of spatial
variation. Reptile species richness was higher at unburnt sites and at sites with
more unburnt vegetation in the surrounding area. Sites that were less connected
to unburnt vegetation had fewer reptile species. Mammals did not have clear
relationships with fine- scale fire patterns.
4. Synthesis and applications. Application of planned fire to promote biodiversity is
globally important. We show that retaining unburnt areas and well- connected
habit at refuges is import ant for reptile diversity. We also found that several spe-
cies of small mammals and reptiles appear resilient to the fine- scale patterns of
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1 | INTRODUC TION
A central theme in fire ecolog y is that variation in the frequency,
intensity, patchiness and timing of fire promotes animal diversity.
However, the underlying mechanisms that shape animal responses
to pyrodiversity (i.e. spatial and temporal variation in fires; Martin
& Sapsis, 19 91) are rarely disentangled using manipulative ex-
periments (Jones & Tingley, 2021). Planned burning is widely ap-
plied to achieve multiple goals in fire- prone landscapes (Moreira
et al., 2020) and this deliberate use of fire provides an excellent
opportunity to explore mechanisms through which fire shapes bio-
diversity (Andersen, 2020; Letnic, 2003; Pastro et al., 2011; Shaw
et al., 2021). Moreover, reducing uncert ainty about how species re-
spond to planned burning will boost the effectiveness of conser va-
tion management (Nicol et al., 2019).
Several alternative mechanisms have been proposed to explain
how variation in the composition (amount, diversity and type) and
configuration (spatial arrangement) of fire- created habitats shapes
animal diversity (Jones & Tingley, 2021; Kelly et al., 2017 ). The
‘habitat amount hypothesis’ proposes that population size and spe-
cies richness increases in landscapes with more suitable habitat
(Fahrig, 2013). Therefore, sites with larger amounts of preferred
fire- driven habitat (e.g. post- fire age classes or severity types) should
have larger populations of individual species and higher numbers
of species. There is support for the habitat amount hypothesis at
broad scales (>1000 ha landscapes), with increased extent of long-
unburnt vegetation correlated with populations of small mammals
and reptiles in eucalypt- dominated vegetation in Australia (Kelly
et al., 2012; Lawes et al., 2015; Lindenmayer et al., 2013; Senior
et al., 2021). Large amounts of recently burnt vegetation can also be
important habitat, including for native rodents in heathland vegeta-
tion (Pereoglou et al., 2016). While many studies have explored how
the discrete measure of burn status (burnt vs. unburnt; hereafter
‘ha bi ta t status hypot hesi s’ ) sh ap es sma ll mam ma l an d re pt il e po pu la-
tions (Flanagan- Moodie et al., 2018; Leahy et al., 2015; Letnic, 2003;
Pastro et al., 2011), few experimental studies have examined how
the amount of burnt and unburnt vegetation influence animals at the
fine scales (1– 50 ha treatments) typically associated with planned
burning (Berry et al., 2015; Shaw et al., 2021).
The configuration of habitat is another important component
shaped by planned burning yet rarely tested with field experi-
ments. For example, interspersed burnt and unburnt patches within
an animal's home range provide some vertebrate species with
different food and shelter resources that support larger populations
(Pereoglou et al., 2016; Stillman et al., 2019). This observation un-
derpins the ‘habitat complementation hypothesis’, which proposes
that landscapes with a mix of contrasting fire histories, juxtaposed
at fine scales, complement the needs of more species and individuals
(Brotons et al., 2005).
Habitat connectivity is an aspect of configuration that can be
measured by the distance to unburnt patches or other preferred
habitat s (Simms et al., 2019). Although individual animals often sur-
vive a fire event in situ, animals dispersing from adjacent unburnt
areas provide an important recolonisation source (Banks et al., 2017;
Puig- Gironès et al., 2018). Where burnt areas are a barrier to an-
imal movement, unburnt patches may provide stepping- stones for
recolonisation (Nimmo et al., 2019). Fir e ca n al so imp ro ve connect iv-
ity – for example, planned fire aids eastern collared lizard dispersal
by opening up woodland vegetation (Templeton et al., 2 011). In the
present study, we refer to the expectation that larger populations
and higher species richness are inversely related to the distance be-
tween unburnt patches as the ‘habitat connectivity hypothesis’.
Planned burning also shapes availability of local habitat ref-
uges or microhabitats used by animals including vegetation cover,
logs or tree hollows (Robinson et al., 2013; Smith et al., 2013). The
prediction that increased availability of habitat refuges decreases
predation risk in recently burnt environments underpins the ‘habitat
refuge hypothesis’ (Kelly et al., 2 017). Increased predation pressure
on native animals by invasive predators such as Vulpes vulpes (red
fox) and Felis catus (feral cat) can affect animal recovery from fire in
Australian ecosystems (Hradsky, 2020; Leahy et al., 2015). However,
the impact of predation, and importance of different types of ref-
uges, is still unknown for many fire- prone areas (Hradsk y, 2020).
In this study, we conducted a field test to investigate five alter-
native hypotheses that could explain how fine- scale spatial variation
in fire shapes the relative abundance and species richness of small
mammals and reptiles. We sampled biodiversity within and outside
of a large, planned burn (1400 ha) in semi- arid ‘mallee’ woodlands
of south- eastern Australia. Following the fire, biodiversity was sur-
veyed five times over 12 months. Mallee woodlands are home to
small mammals and reptiles with distributions known to be shaped
by coarse patterns of fire (Nimmo et al., 2013; Senior et al., 2021).
The relative abundance of many ver tebrate species' peaks in mid-
to late- successional vegetation, with a small number of species pre-
ferring early successional vegetation (Clarke et al., 2021). Planned
burns are used in mallee vegetation to create low- fuel barriers that
planned fire experienced in this study, despite activity of introduced predators.
The diversity of animals can remain relatively high in areas subject to planned
fire, provided that internal and external habitat refuges are retained.
KEY WORDS
biodiversity, fire management, fire mosaic, mammals, planned fire, prescribed fire,
pyrodiversity, reptiles
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SENIOR et al.
reduce the risk of large wildfires, and to meet the needs of biota that
benefit from fire. However, the influence of fine- scale variation in
fire on mallee fauna is largely unknown. Hypotheses we developed
and tested were:
1. Species richness will be higher at unburnt sites compared to
burnt sites. While the relative abundance of individual species
will vary by habitat status, we expect the relative abundance
of most species to be positively associated with unburnt sites
(‘habitat status hypothesis’).
2. Species richness, and the relative abundance of individual species,
will be higher at sites with larger amount s of unburnt vegetation
(‘habitat amount hypothesis’).
3. Species richness, and the relative abundance of individual
species, will be higher at sites where unburnt and burnt patches
are interspersed than at sites where a single patch type is more
aggregated (‘habitat complementation hypothesis’).
4. Sites further from unburnt vegetation will have lower species
richness and species abundances compared to sites closer to
unburnt vegetation (‘habitat connectivity hypothesis’).
5. Sites with larger unburnt patches and greater cover of unburnt
vegetation will have higher species richness and relative
abundances of small mammals and reptiles (‘habitat refuge
hypothesis’).
2 | MATERIALS AND METHODS
2.1 | Study area and design
This study was conducted in Murray Sunset National Park (hereaf-
ter, the Park), a large nature reser ve that encompasses 6330 km2 of
north- west Victoria. The vegetation is characterized by woodland
stands of ‘tree mallee’, Eucalyptus species with a multi- stemmed
growth form, and an understorey of Triodia scariosa (hummock grass).
The climate is semi- arid, with high inter- annual rainfall variability and
mean annual rainfall of 320 mm. Dunes and swales provide moderate
topographic variation.
Mallee vegetation is fire- prone, with large wildfires >10,000 ha
occurring in the broader Murray Mallee bioregion every 10– 20 years
and smaller wildfires occurring more frequently (Clarke et al., 2021).
Nevertheless, some mallee vegetation in the region has experienced
intervals of >100 years between fires (Clarke et al., 2021). The Park
experiences active fire management, with planned burning under-
taken in spring and autumn, of ten in linear strips ~1 km wide. While
wildfires in mallee vegetation consume most above- ground vege-
tation, planned burns are usually less severe and unburnt plants or
patches are common. Adult mallee eucalypts typically sur vive fire
and resprout from a basal lignotuber.
The study was designed to take advantage of a large (1 km by
14 km extent) planned burn in the Park (Figure 1), implemented in
May 2018 via aerial ignition and which burned most of the treat-
ment area at a low severity. This burn was selected for study through
collaboration with land managers, who tailored their application of
fire to generate spatial variation in mallee vegetation with a T. sca ri -
osa understorey. This vegetation type is important for several small
mammal (Kelly et al., 2011) and reptile species (Nimmo et al., 2013) as
T. scari os a hummocks provide food and shelter resources. The area
burnt by planned fire, and surrounding vegetation, was last burnt by
wildfire in 1977 (time since fire in May 2018 = 41 years). Prior to the
planned burn, we established 12 ‘impact sites’ within the proposed
burn perimeter, stratified at distances of 100 m (n = 4), 300 m (n = 4)
and 500 m (n = 4) from the expected edge of the burn to measure
the effect of external connectivity (Figure 1). We also established 8
‘control’ sites outside of the expected burn area but within the same
vegeta tio n typ e and fire his tor y (Figure 1). Scheduling of the planned
FIGURE 1 Map of Murray Sunset
National Park, Victoria, Australia, showing
the location of 12 impact (burnt) sites
within the planned burn perimeter
(hashed areas) and 8 control (unburnt)
sites.
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burn meant that pre- burn biodiversity data was collected in cool
temperatures and did not yield large samples of mammals and rep-
tiles. Therefore, we did not undertake a before- af ter- control- impact
(BACI) stat istical analys is; instea d, we model led the high- quality bio-
diversit y data collected at treatment and control sites during five
post- fire surveys (detailed below). All sites were located on sandy
flats or dune slopes and had similar habitat structure prior to the
planned burn (Figure S1.1, Supporting Information). Sites were lo-
cated ≥200 m apart and treated as spatially independent, based on
previous research that did not identify movement of individual ani-
mals between pitfall trapping sites at this distance (Kelly et al., 2011).
2.2 | Field surveys
Five post- fire surveys were completed to measure changes in animal
populations at each site. Surveys were conducted in May– June 2018
(immediately after the planned fire), October 2018, December 2018,
March 2019 and May 2019. Three of the surveys were clustered
in warmer months (October– March) to boost reptile captures. All
fieldwork was undertaken with ethic s approval from the University
of Melbourne Animal Ethics Committee (project #1814465) and
research permits and approval from the Victorian Government
Department of Environment, Land, Water and Planning and Parks
Victoria (permit #10008462).
We employed three methods of sur veying biodiversity: pitfall
traps, Elliott aluminium box traps and remote cameras. At each site
(n = 20), we established a 50 m pitfall trap line, consisting of ten 20 L
buckets spaced five metres apart and connected by a 30 cm high
flywire drift- fence (Kelly et al., 2011; Nimmo et al., 2013). Pitfall
traps were open for five consecutive night s during each survey pe-
riod (with minor exceptions during extreme weather). Each trap con-
tained a PVC pipe and cloth for shelter and a polystyrene float in
case of rainfall. We sprayed around each bucket with insecticide to
deter inver tebrates that might harm captured animals.
A line of Elliott traps (9 cm × 10 cm × 33 cm) was placed 10 m
from the pitfall line, consisting of five traps placed 10 m apar t (Kelly
et al., 20 11). Elliott traps were baited with a mix of oats, peanut but-
ter, vanilla extract, golden syrup and linseed oil. Bait s were replaced
after captures and half way through each survey period to keep the
scent fresh. Each Elliott trap contained leaf litter for shelter, was in-
sulated by a plastic bag and, where possible, was placed in a shel-
tered position under or next to vegetation.
Elliott and pitfall traps were checked each morning and cap-
tured animals were identified to species- level. Reptiles were marked
ventrally with a nontoxic permanent marker to identify recaptures
within the same trapping session. Small mammals were individually
marked by clipping small ear notches.
We installed a remote- sensing camera at each site to target the
invasive predators F. catus and V. vulpes. Cameras were mounted
50 cm high on a star picket and angled 45° towards a lure on the
ground 1 m away from the base of the picket. Lures were made from
super- absorbent cladding soaked in peanut butter, tuna and linseed
oil, encased in a 10 cm long PVC pipe, capped at one end and pegged
to the ground with the exposed end upright. Fresh lures were placed
at each camera after each trapping survey and left in place for at
least 14 nights (Payne et al., 2014).
2.3 | Data analysis
Live captures of small mammals and reptiles were pooled across the
five post- fire survey periods for statistical analyses. Power analysis
using the SIMR package (Green & MacLeod, 2016) indicated that
pooling the data provided >80% power to detect a large effect
size (i.e. changes in relative abundance or species richness of >33%
associated with variation in fire pat terns). Capture rate of native
mammals and reptiles was expressed per site as total captures of a
species/total pitfall trap nights. The introduced Mus musculus (house
mouse) was the only species captured in Elliot t traps, so capture
rate of that species included the combined sur vey effort from pitfall
and Elliott traps. Reptile and native mammal species richness was
calculated as the total number of species in each group per site. All
reptiles were native.
Camera traps recorded V. vulpes at all sites pos t- f ir e, so re po rting
rate was used as an index of fox activity. Records of V. vulpes were
not temporally independent (i.e. cameras could record the same indi-
vidual multiple times each night) so we only included the first record
of a fox at a site within a 24 h period from 10 am. The number of 24 h
periods in which foxes were recorded for each site was divided by
camera trap effort, which varied from 78 to 84 days, to calculate fox
activity for each site.
Vegetation sur veys were completed at each site before and after
the fire to measure the fine- scale influence of fire on habitat refuge
availability. We measured the number of times near surface vegeta-
tion cover (including T. scar iosa, shrubs, tree trunks and resprouting
eucalypts <0.5 m tall) and canopy cover (trees >2 m) were present
(defined as ≥1 ‘touch’ on or above a structure pole) each metre along
a 50 m transect.
After the fire, we used a drone to capture images that enabled
classification of burnt and unburnt vegetation (Appendix S2).
Classified images were then used to calculate four variables in
Fragstats v4 (McGarigal et al., 2012) that represented spatial vari-
ation of burnt and unburnt vegetation in a one- hec tare area sur-
rounding each site at a very fine scale (0.02 × 0.02 m). These were:
the amount of unburnt vegetation, interspersion of burnt and un-
burnt vegetation, percent age of the one- hec tare area comprised
of the largest patch of unburnt vegetation (largest unburnt refuge),
and distance from the middle of each site to the nearest unburnt
patch >25 m2 in size (i nte rn al conn ec tivity; Table S3.1). Interspersion
was calculated using a contagion index varying from 0% to 100% (Li
& Reynolds, 1993 ). Values closer to zero indicate that patch types
are highly juxtaposed, whereas values closer to 100 indicate that
a single patch type is dominant. Therefore, a negative relationship
between animal occurrence and interspersion would support the
‘habitat complementation hypothesis’.
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Several fire variables were correlated (Pearson correlation co-
efficient >0.80; Figure S3.1) so we did not include them in the same
model. We therefore built univariate Generalized Linear Models
(GLMs) in R v3.8.3 (R Core Team, 2020) for species richness and
the relative abundance of each species, against eight predictor vari-
ables calculated to test the five different hypotheses (Table S3.1).
Continuous predictor variables were standardized by subtracting
the mean from each predictor and dividing by two standard devi-
ations (Gelman & Hill, 2007). Binomial GLMs were used for the in-
dividual species models, and Poisson GLMs for models of species
richness. Tests of model residuals for issues, such as overdispersion,
were performed using the DHARMa package (Hartig, 2017) and
showed that model residuals did not deviate from what would be
expected under the distributions used. We explored the relation-
ship between predictor and response variables, and compared al-
ternative hypotheses, by considering the size and uncertainty (95%
confidence intervals) of model coefficients. Models where the 95%
CI aroun d a model est imate did not overla p zer o were consider ed in-
dicative of a clear relationship between variables, with positive val-
ues indicating a positive relationship between variables and negative
values the opposite.
3 | RESULTS
We recorded 239 unique captures of reptiles of 19 species over
2760 pitfall trap nights, including dragons (four species), geckos
(three species), legless lizards (three species), skinks (five species)
and snakes (four species; Table S4.1). We also recorded 57 captures
of small mammals from four species (a dasyurid, burramyid, native
rodent and introduced rodent) from 1406 Elliott and 4625 pitfall
trap nights. Two species of introduced predators were recorded
using remote cameras: F. catus and V. vulpes (Table S4.1). Felis catus
was present at <50% of sites, with low reporting rates (0%– 1.2%)
and was not included in st atistical analysis. Across all sites, mean
reptile species richness was 6.85 species (range 3– 15) and mean
native mammal species richness was 0.6 (range 0– 2). We built
statistical models for: species with >5 total captures, including three
small mammal and 11 reptile species; for V. vulpes reporting rate;
native small mammal species richness; and reptile species richness
(Table S4.2).
3.1 | Habitat status hypothesis
Three reptile species were associated with unburnt sites, one
species was associated with burnt sites and seven showed no clear
relationship with burn status (Figure 3). Brachyurophis australis (coral
snake) and Strophurus intermedius (southern spiny- tailed gecko) were
more abundant in unburnt sites compared to burnt sites (model
coefficients = 0.70 ± 0.33 SE and 1.54 ± 0.51 SE, respectively).
Complete separation of the predictor variables (i.e. a species was
only present in one treatment type, for example unburnt sites)
occurred in the models for Liopholis inornata (desert skink) and
Menetia greyii (common dwarf skink) so model coeff ici ent s could not
be estimated and are not shown in Figure 2. Liopholis inornata was
only found in unburnt sites (4 of 8 unburnt sites; Figure S6.8) and
M. greyii only found in burnt sites (8 of 12 burnt sites; Figure S6.10).
Reptile species richness was higher in unburnt sites than burnt sites
(model coefficient = 0.51 ± 0.17 SE; Figure 3). Small mammals and
V. vulpes did not have clear relationships with burn status (Figure 4).
For example, Cercartetus lepidus (little pygmy- possum) was found at
an equal number of burnt and unburnt sites.
3.2 | Habitat amount hypothesis
Three reptile species had a positive relationship with the amount
of unburnt vegetation and eight showed no clear relationship
(Figure 2). Capture rates of Diporiphora nobbi (nobbi dragon), L.
inornata and S. intermedius increased with more unburnt vegetation
at a site (model coefficients = 1.37 ± 0.57 SE, 2.13 ± 0.91 SE and
1.01 ± 0.45 SE, respectively). Reptile species richness also showed a
positive relationship with the amount of unburnt vegetation at a site
(model coefficient = 0. 47 ± 0.17 SE; Figure 3). Amount of unburnt
vegetation did not have a clear relationship with capture rates of
small mammals, native mammal species richness or reporting rate of
V. vulpes (Figure 4).
3.3 | Habitat complementation hypothesis
One reptile species had a positive relationship with the interspersion
of burnt and unburnt patches, one species had a negative relationship,
and nine species had no clear relationship (Figure 2). Capture rates
of M. greyii increased at sites where burnt and unburnt patches
were more interspersed (model coefficient = −1. 62 ± 0.78 SE). In
contrast, captures rates of D. nobbi increased at sites dominated
by a single, aggregated patch type (model coefficient = 1. 41 ± 0.66
SE). Interspersion of burnt and unburnt patches did not have a clear
relationship with any of the mammal species modelled, and native
mammal or reptile species richness (Figure 4).
3.4 | Habitat connectivity hypothesis
Two reptile species had a negative relationship with external con-
nectivity, two reptile species had a negative relationship with in-
ternal connectivit y and eight species had no clear relationship with
either variable (Figure 2). Lucasium damaeum (beaded gecko) abun-
dance decreased towards the inte rior of burned areas (model coef fi-
cient = −0.99 ± 0.36 SE). S. intermedius abundance increased at sites
located closer to unburnt patches (model coefficient = −1. 47 ± 0.73).
Complete separation of the predictor variable occurred again in both
connectivity models for L. inornata. Reptile species richness showed
a negative relationship with ex ternal and internal connectivity
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(model coefficients = −0.56 ± 0.20 SE and − 0.53 ± 0.20 respec-
tively). External or internal connectivity did not have clear relation-
ships with any of the mammal species modelled or native mammal
species richness.
3.5 | Habitat refuge hypothesis
Three reptile species had a positive relationship with size of
the largest unburnt refuge and eight species did not have a clear
relationship (Figure 2). Capture rates of three reptile species,
Ctenophorus fordi (mallee dragon), D. nobbi and L. inornata increased
with larger unburnt refuges (model coefficients = 1.06 ± 0.47 SE,
1.29 ± 0.49 SE and 1.93 ± 0.73 SE, respectively). Reptile species
richness also increased with larger unburnt refuges (model
coefficient = 0.45 ± 0.16 SE; Figure 3). Unburnt refuge size did not
have a clear relationship with any of the mammal species modelled,
or with native mammal species richness (Figure 4).
Near- surface or canopy refuge availability did not have a clear
relationship with nine reptile and two small mammal species, with
native reptile or mammal species richness or with reporting rate of
V. vulpes. At this microhabitat scale, one reptile and one mammal
species were negatively correlated with near- surface refuge avail-
ability: capture rates of Sminthopsis murina (common dunnart) and
D. nobbi decreased with higher cover of near- surface plants (model
coefficients = −1 .77 ± 0.72 and − 2.18 ± 0.76, respec tively). Near sur-
face refuge composition (mean = 15.7%, range = 4– 28%) varied be-
tween burnt and unburnt sites, with cover at burnt sites dominated
by resprouting eucalypt shrubs (mean eucalypt shrub cover at burnt
sites = 10.5% vs. at unburnt sites = 0.22%). Capture rates of C. fordi
increased with greater canopy cover whilst capture rates of M. greyii
decreased (model coefficient = 1.0 0 ± 0.49 and − 3.80 ± 1.7).
4 | DISCUSSION
We found strong support for the habitat status hypothesis— whether
a site was burnt or not influenced the relative abundance of individual
reptile species and the number of reptile species— and moderate
support for four hypotheses about how the spatial variation of
fire- affected habitats shape reptile assemblages. Thus, our field
experiment indicates that several mechanisms underpin biodiversity
responses to spatial variation in fire, even after accounting for burnt
and unburnt habitat. However, capture rates of small mammals, and
reporting rate of the introduced predator V. vulpes, were largely
unchanged by fine- scale spatial variation created by planned fire.
This indicates that some fauna were resilient to the fine- scale
patterns of fire applied in this study.
4.1 | Occurrence of planned fire
On average, an additional four reptile species were present at
unburnt sites compared with burnt sites. Some species were closely
linked to habitat status: L. inornata, a skink that shelters in hummock
grass in mallee environments, was only found in unburnt sites.
By contrast, the more generalist burrowing skinks M. greyii and L.
bougainvillii were common at burnt sites. (Santos & Poquet, 2010;
Smith et al., 2013). Nevertheless, most reptiles and small mammal
species occurred at both burnt and unburnt sites and appeared
resilient to the low severity planned fire experienced in this study.
Interestingly, M. greyii was only captured at burnt sites post- fire.
It is possible that this species is more detectable in open environ-
ments immediately after fire. However, this species was present in
both control and impact sites prior to the planned burn, and we re-
corded evidence of breeding in burnt areas after the planned fire (i.e.
presence of juveniles), so we reason that capture rates of M. greyii
reflect changes in relative abundance. Reptile responses to fire often
reflect their shelter requirements (Santos & Poquet, 2010; Smith
et al., 2013).
4.2 | Amount of unburnt vegetation
Some species showed different responses to fire patterns when the
area surrounding a site was considered (unburnt areas in the 1 ha
‘buffer’ ranged from 303– 1834 m2). For example, the dragon D. nobbi
showed a strong preference for larger amounts of unburnt vegetation
surrounding a site, and this relationship held even at unburnt sites. In
addition, reptile species richness was higher at burnt sites with larger
amounts of unburnt vegetation, compared with sites burnt more
uniformly. We interpret this as moderate evidence that the amount
of preferred fire- driven habitat, even at relatively fine- scales, is an
important influence on reptiles in fire- prone environments.
Interestingly, native small mammals did not have a clear rela-
tionship with the amount of unburnt vegetation at the relatively
fine scale of this study. This is likely because the low severity of the
planned fire meant that critical resources for mammals were retained
in the landscape. The dunnarts and pygmy- possums we obser ved
use a range of shelter and food resources (Bennett et al., 2006),
which aids sur vival in a variety of habitats. In the present study, we
did not capture the more fire- sensitive mallee ningaui (Ningaui yvon-
neae), a small marsupial that occurs in other areas of the Park and is
associated with the amount of mid- and late- successional vegetation
at larger scales (Kelly et al., 2012; Senior et al., 2021). Other studies
in the Aus tralian ari d- zone als o sh ow that co nt empor ar y popu la tions
of small mammals are resilient to patchy planned fire in arid hum-
mock grasslands (Letnic, 2003; Pastro et al., 2 011).
FIGURE 2 Results from univariate GLMs testing the influence of fire variables on the capture rate and species richness of reptiles
(see Table S4.1 for full species names). Dots represent the coefficient estimate for a predictor variable and lines 95% confidence intervals
around that estimate. For two species on panel a (L. inornata and M. greyii), one species on panel d (L. inornata) and one species on panel e (L.
inornata) complete separation of the predictor variable occurred, and model coefficients could not be estimated.
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FIGURE 3 Modelled response of reptile species richness to each fire variable. Solid lines show the predicted response from each model
and dotted lines represent 95% confidence intervals. Grey dots are the obser ved data of the number of reptile species against each fire
variable from 20 sur vey sites.
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FIGURE 4 Results from univariate GLMs testing the influence of spatial characteristics of fire on small mammal capture rates and species
richness or V. vulpes reporting rate (see Table S2.1 for full species names). Dots represent the coefficient estimate for a predictor variable
and lines 95% confidence intervals around that estimate.
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4.3 | The configuration of planned fire
This study tested two hypotheses for how the post- fire configuration
of habit at might affect animals: the ‘habitat complementation’
and ‘habitat connectivity’ hypotheses. We found limited evidence
that fine- scale juxtaposition of dif ferent patch types provided
complementary food and shelter resources that would support
a higher abundance of animals or increased diversity. Reptiles
responded more strongly to the amount of unburnt habitat compared
to availability of complement ary patches. A possible explanation for
this is that the area burnt by planned fire provided few resources
for animals, in part because the fire was followed by a particularly
dry year. Rainfall in the 12- months after fire was low, and post- fire
ephemeral plant species that often appear under average and above-
average rainfall conditions were largely absent from the treated
area. Resource availability in mallee vegetation changes over time
(Clarke et al., 2021; Haslem et al., 2011) and it is also possible that
other mixes of age- classes provide complementary resources for
fauna. For example, the high cover of T. s ca riosa 15– 40 years post-
fire (Haslem et al., 2011) may complement long- unburnt vegetation
with large, hollow stems (40– 80 years post- fire).
The ‘habitat connectivity hypothesis’ proposes that dispersal is a
key constraint to re- colonization of burnt areas, with differences in
relative abundance or species richness based on distance to unburnt
vegetation (i.e. source populations). We found that reptile species
richness at the most remote sites (in terms of both internal and ex-
ternal connectivity) was approximately half that at well- connected
sites (e.g. 10:5 reptile species). Within the burnt area, sites 300–
500 m from the external perimeter had lower mean reptile species
richness than sites only 100 m away. Previous research on several
species of diurnal reptiles in mallee vegetation found they were
more sensitive to local patch conditions than external connectivity
(Simms et al., 2019).
Animal community composition pre- fire— including in areas later
burnt or unburnt— also affect s patterns of recolonization in post- fire
environments (Simms et al., 20 19). It is plausible that some early-
successional species were already absent, or at low abundance, in
the area subject to planned fire. In that case, lower species richness
of reptiles in burnt vegetation might be explained by constraint s on
recolonization by early- successional species. However, we reason
that movement constraints are unlikely to explain the association of
rept il es wi th unbu rnt ve get at ion in th e pre se nt st ud y bec aus e co ndi-
tions before the fire provided a mix of resources— such as hummock
grass, mallee eucalypts and open spaces— utilized by many species
(Nimmo et al., 2013; Senior et al., 2021).
4.4 | The role of fire refuges
Activity of the invasive predator V. vulpes was high at all sites post-
fire. However, V. vulpes activity varied temporally, with low activity
prior to the planned burn and activity increasing sharply afterwards
(Figure S7.1). Introduced predators often increase activity in recently
burnt landscapes as these open environments assist hunting (Leahy
et al., 2015). We recorded high fox activity in recently burnt areas
and un bur nt areas (Figure S7.1). While this pattern suggests that fire
might have increased activity of this highly mobile species across the
whole landscape, we interpret this result cautiously as it should be
tested in multiple landscapes.
Under the ‘habit at refuge hypothesis’, prey species such as
reptiles and small mammals would be more abundant in sites
with high ground cover that provides shelter from their predators
(Hra ds k y, 2020; Kelly et al., 2017). Size of the largest unburnt ref-
uge was important for reptile species richness, with larger patches
(>50 m2) providing impor tant microhabitat for reptiles and allowing
species such as C. fordi to persist within the burnt area. However, it
is difficult to disentangle the role of unburnt vegetation in providing
refuge from predation per se compared to other benefit s it provides
such as a suitable microclimate. That is, while we identified a signal
for the role of habitat refuges, future research could help to estab-
lish the role of habitat refuges by manipulating the amount and size
of unburnt patches in the presence and absence of intro duced pre d-
ators. Most species did not have clear relationships with the canopy
or near- surface microhabitat availability. Surprisingly, the insectivo-
rous marsupial S. murina was negatively ass oc ia te d wi th near sur face
ground cover, likely because cover in burnt areas was dominated by
resprouting eucalypts that do not provide the preferred resources of
many ground- dwelling animals.
4.5 | Conservation and management implications
Planned burning occurs in many Australian ecosystems and there
are calls to increase the application of fire following unprecedented
burnt area by wildfires in 2019/20. This study shows that planned
burning that retains unburnt vegetation within the burn perimeter
provides better short- term outcomes for reptile diversity than
more uniformly burnt areas. Maintaining connectivity between
these unburnt patches— and to external unburnt areas— will boost
populations of reptiles in post- fire landscapes.
But maintaining animal habitat through time is challenging. In
fire- prone ecosystems, this involves balancing the need to main-
ta in habita t at a gi ve n tim e with th e n ee d to re du ce th e risk of ver y
large fires that can harm biodiversit y. It also means balancing the
needs of biodiversity with other social and environmental values
(Moreira et al., 2020). In the mallee, it is plausible that retaining
large and co nnected unb urnt patches within pla nned burn s pe rim-
eters could reduce the effectiveness of planned fire in reducing
the risk of very large, uniform wildfires. This important trade- off
re qu ire s furt h er ex plo rat ion . T he pr ese nt st udy info rms th is tr ade -
of f by of fer ing insi g hts int o what la n d mana ger s can achi eve if th ey
pursue a planned burning strateg y that retains unburnt patches at
fine scales. In some locations, such as in small nature reserve s and
near built assets, this type of low severity planned fire is likely
to be the only type of planned burning that is possible. Thus, we
expect the results of the present study to be applicable to many
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locations in semi- arid Australia, and it adds to literature showing
that planned fire that considers landscape context, connectivity
and retention of unburnt vegetation is important for maintain-
ing diverse populations of native species (Andersen, 2020; Berry
et al., 2015; Shaw et al., 2021).
In conclusion, small mammals, reptiles and invasive predators
showed a wide range of responses to planned fire. The patterns we
observed did not fit one single hypothesis for how pyrodiversity af-
fects animal persistence and recovery af ter fire but indicated that a
variety of fire- driven mechanisms are important. Ultimately, incor-
porating different kinds of spatial patterns in fire planning— including
the composition and configuration of habitat elements at different
scales— will enhance biodiversity conser vation.
AUTHOR CONTRIBUTIONS
All author s conceived the ide as and designed the study; Katharine
Senior collected the data and performed the GIS work and data
analysis. Katharine Senior interpreted the results with assistance
from Katherine Giljohann, Michael McCarthy and Luke Kelly.
Katharine Senior led the writing of the manuscript. All authors
contributed critically to writing and gave final approval for
publication.
ACKNOWLEDGEMENTS
This research was funded through the Australian Research Council
Linkage Project (LP150100765) ‘Spatially explicit solutions for
managing fire and biodiversity’, Australian Government Research
Training Program, Margaret Middleton Fund, Holsworth Wildlife
Research Endowment and Albert Shimmins Fund. All fieldwork
was conducted under AEC project #1814465 at The University of
Melbourne and research permit #10008462 from the Department of
Environment, Land, Water and Planning (DELWP) and Parks Victoria.
We thank the many volunteers who helped with fieldwork. Several
land managers from DELWP advised the project, and planned and
implemented the planned burn, including Nathan Christian, Marcus
Boulton, Natasha Schedvin and Victor Hurley. Alan Andersen and
two anonymous reviewers made valuable comments that improved
the manuscript. Open access publishing facilitated by The University
of Melbourne, as par t of the Wiley - The University of Melbourne
agreement via the Council of Australian University Librarians.
CONFLICT OF INTEREST
The authors declare no competing interests.
DATA AVA ILAB ILITY STATE MEN T
Data available via the Dryad Digital Repository ht t p s : //d o i.
org/10.5061/dryad.x69p8 czn2 (Senior et al., 2022).
ORCID
Katharine L. Senior https://orcid.org/0000-0003-1123-1472
Katherine M. Giljohann https://orcid.org/0000-0003-1622-5821
Michael A. McCarthy https://orcid.org/0000-0003-1039-7980
Luke T. Kelly https://orcid.org/0000-0002-3127-3111
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SUPPORTING INFORMATION
Additional supporting information can be found online in the
Suppor ting Information section at the end of this article.
How to cite this article: Senior, K. L., Giljohann, K. M.,
McCar thy, M. A., & Kelly, L. T. (2023). A field test of
mechanisms underpinning animal diversity in recently burned
landscapes. Journal of Applied Ecology, 60, 146–157. h t tp s : //
doi .org /10.1111/1365-26 64.14315