Recolonisation of powerline corridor vegetation by small mammals: Timing and the influence of vegetation management

Landscape and Urban Planning 87 (2008) 108–116

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Recolonisation of powerline corridor vegetation by small mammals: Timing and the influence of vegetation management Donna J. Clarke 1 , John G. White ∗ School of Life and Environmental Sciences, 221 Burwood Highway, Burwood, Deakin University, Melbourne, 3125, Australia

a r t i c l e

i n f o

Article history: Received 4 July 2007 Received in revised form 2 January 2008 Accepted 16 April 2008 Available online 11 June 2008 Keywords: Mammal succession Vegetation succession Rights-of-way

a b s t r a c t Powerline corridors through forested ecosystems have been criticised due their potential to fragment the landscape and facilitate the intrusion of undesirable species into natural areas. This study investigates the effects of vegetation management (slashing), on: (1) timing of small mammal recolonisation; (2) vegetation characteristics that drive small mammal responses; and (3) the point where corridor resources are sufficient to provide functional habitat for native species. Small mammal trapping was undertaken within Bunyip State Park, Australia, across three sites, once a month from January 2001 to May 2002 and every 2 months thereafter until January 2004. Changes in vegetation around each trap station were assessed annually in the forest and bi-annually in the corridor. Principal components analysis on the vegetation structural complexity values produced factors for use in species abundance models. Native small mammal species recolonised the corridor 1.5–3.5 years after management and the corridor supported a breeding population of small mammals around 2.5 years post-management. Males however, generally recolonised the corridor first, resulting in a sex-biased population in these areas. Species corridor habitat models for five native and one introduced species suggested cover and shelter were more important in determining corridor use than plant species per se. Powerline corridors have the potential to create a mixture of different successional stages, enhancing habitat availability for many species. However, the intensity of current management needs to be reduced and an integrated approach to management needs to be undertaken if powerline corridors are to continuously provide habitat for native small mammal species. © 2008 Elsevier B.V. All rights reserved.

1. Introduction Powerline and other utility corridors have been established in many natural ecosystems throughout the world. These corridors have been subject to criticism due to their potential to fragment the ecosystems they bisect (Goosem and Marsh, 1997), and because they may facilitate the movement of weeds and pest species into these ecosystems (e.g. Gates, 1991; Goosem and Marsh, 1997). Traditionally, powerline corridor management focused on keeping the vegetation in an early-successional stage to minimize the risk of damage to the overhead lines by tall-growing woody vegetation (Brown, 1995). Internationally the focus has begun to shift towards management of corridor vegetation in a fashion that is more sympathetic to the integrity of the ecosystems through which they run (Hurst, 1997; Smallidge et al., 1996). Recent initiatives in the United States (e.g. Project Habitat) have made managing util-

∗ Corresponding author. Tel.: +61 3 9251 7625; fax: +61 3 9251 7626. E-mail addresses: [email protected] (D.J. Clarke), [email protected] (J.G. White). 1 Present address: School of Biological Sciences, University of Southampton, Bassett Crescent East, Southampton SO16 7PX, UK. 0169-2046/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.landurbplan.2008.04.009

ity corridors for wildlife conservation a priority (Hurst, 1997) with integrated vegetation management (IVM) techniques being developed to provide habitat for wildlife while still minimizing the risks posed by high growing vegetation (e.g. Hurst, 1997; Smallidge et al., 1996). In Australia however, powerline corridors are still maintained as low, early-successional habitats because vegetation and consequent fuel load are perceived to pose a risk to the structure, function and integrity of transmission lines (Clarke et al., 2006). This style of management does not take account of Australian (e.g. Clarke et al., 2006; Goldingay and Whelan, 1997; Macreadie et al., 1998) and international studies (e.g. Chasko and Gates, 1982; Hanowski et al., ¨ ¨ ¨ 1997; Smallidge et al., 1996) that 1993; Kylakorpi and Garden as, have highlighted that utility corridors can create habitat for a range of rare and endangered species. To avoid creating corridor habitat that is only suitable for opportunist or early-successional species, it is important to have an intimate knowledge of how small mammal populations recover from management events. Managers therefore need an understanding of: 1. how the vegetation recovers post-management, 2. the timing of recolonisation of the corridor by wildlife,

D.J. Clarke, J.G. White / Landscape and Urban Planning 87 (2008) 108–116

3. the point at which the corridor becomes functional habitat for particular species, 4. the vegetation characteristics that drive species responses, and 5. the point at which corridor vegetation becomes an unacceptable fire risk. This study investigates the effects of powerline corridor vegetation management in the form of slashing, on: (1) the timing of small mammal recolonisation; (2) the vegetation characteristics that drive small mammal responses; and (3) the point where corridor resources are sufficient to provide functional habitat for native species. 2. Methods Three permanent sites were established along a powerline corridor in southern Victoria, Australia. Sites incorporated both the powerline corridor (100–120 m wide) and the adjacent forest vegetation, and spanned 125 m × 300 m (3.75 ha). Management of the corridor focuses on slashing the entire corridor at one time, generally on a 3-year cycle with emergent saplings spotsprayed where necessary between slashing periods. Wet gully areas where machinery cannot access are typically left unmanaged. Areas that are too steep for the slashing machinery to access are commonly cleared of all vegetation via blading with a bulldozer. The majority of the corridor vegetation was slashed to a height of approximately 5 cm in September 2000. The detection of the near-vulnerable broad-toothed rat Mastacomys fuscus, by Macreadie et al. (1998) within one section of the powerline corridor however, led to the protection of vegetation from complete vegetation removal between one set of pylons (approximately 500 m × 100 m) since 1994. This area consisted of a low-growing shrub–sedge–grass community and served as a reference site for the study. Two sites were established in corridor sections which were slashed in September 2000 (herein referred to as M1 and M2) and a reference site was selected in the area of the corridor that had not been slashed since 1994. The reference site was however, spot-sprayed with dicot specific herbicides and emergent trees were manually removed in the period following slashing in 1994. Only one reference site was selected as no other areas, which had been protected from slashing, and/or the use of broadcast herbicides existed along the corridor. A comparison of the vegetation communities within the corridor using a one-way analysis of similarity (ANOSIM) and a similarities of percentages (SIMPER), demonstrated that the underlying community of the reference site however, was representative of the communities found along the length of the corridor. Native grasses, shrubs and sedge species, in particular Gahnia sp. accounted for a high percentage of within site similarity across all three corridor sections. Live trapping sampled terrestrial small mammal communities from January 2001 to January 2004. A trapping grid consisting of 102 “Elliot” aluminium folding traps (10 cm × 10 cm × 33 cm) (Elliott Scientific, Upwey, Victoria) was set at each site. Thirty traps in the corridor and 36 traps in the adjacent forest on each side of the powerline corridor, were placed 20 m apart in 17 transects each comprising of six traps, with transects spaced at 25 m intervals. Five transects were set in the powerline corridor, with the edge transects at least 3 m from the corridor–forest edge, and six transects were set in each side of the adjacent forested areas, with the first transects set within 1 m of the corridor–forest edge. Traps were baited with a mixture of peanut butter, rolled oats, honey, tuna oil and linseed oil, set for five consecutive nights and cleared each morning. Captured animals were identified to species. Repro-

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ductive condition, head–body measurements and location were recorded. Female rodents were assumed to be breeding if perforate and pregnant if nipples were enlarged or lactating. Rodent males were said to be reproductive if testes were enlarged. Marsupials with pouch young, or an open pouch were classified as breeding. The bush rat Rattus fuscipes, swamp rat Rattus lutreolus and broadtoothed rat M. fuscus, were ear tagged, and all other species were ear notched to indicate first capture or recapture. Trapping was conducted once a month from January 2001 until May 2002 and every 2 months thereafter until January 2004, totalling 35,190 trap nights over the study. Vegetation structural complexity was surveyed at each trap location at five random positions in a 2 m × 2 m quadrat, using a 2 m high pole divided into 10 cm increments, placed vertically at ground level. The number of vegetation contacts with the pole in each height increment was counted up to a maximum of 10 contacts. These structural complexity values were averaged for each trap station and multiplied by 10 to produce a percent value for each height increment. In a 2 m × 2 m quadrat at all trap locations, percentage cover of life forms and the dominant plant species were estimated for shrubs, sedges, ferns, moss, native and introduced grass, leaf litter, canopy cover, and bare ground. The species, height and number of midstorey and overstorey trees, including diameter at breast height (DBH) were recorded within a 5 m radius of each trap location. Fallen logs were counted and grouped into small, medium, large, or very large categories. Forest vegetation was surveyed annually in 2001, 2002 and 2003. Vegetation surveys within the corridor were conducted after management early in 2001, and then bi-annually in 2002, 2003 and 2004. To assess the recovery of vegetation post-management, the vegetation data was averaged within transects for each survey period. The data for the adjacent forest sections either side of the corridor remained separated to give two datasets for the forest and one for the corridor, for each site and survey period. Principal component analysis (PCA) used VARIMAX rotation to reduce multicolinearity between the structure variables in the corridor only, and produced factors with eigenvalues over 1. These factors were used in species abundance models to assess small mammal responses to vegetation recovery in the corridor following management. Species trap success were calculated separately for forest and corridor habitats for each trip and standardised to 100 trap nights for consistency across habitats and for ease of analysis of the low captures of animals in the corridor. Overall trap success between the reference and managed sites was assessed with a Mann–Whitney U test, using pooled data across the managed sites. Trap success between the corridor and forest for the common species were examined using non-parametric Wilcoxon Signed Rank Tests. We used PCA with a VARIMAX rotation to produce factors with eigenvalues over 1, to assess the general patterns in small mammal recolonisation of the corridor following management, and of the successional trajectory within the whole study area. Although Fox (1990) suggested the use of pooled annual data to study small mammal succession to avoid seasonal fluctuations in species abundances masking successional patterns of the community, the small mammal data used in the PCA were pooled across 6-month intervals to coincide with the bi-annual vegetation surveys and in an effort to detect fine-scale changes in small mammal community succession. This resulted in seven ‘time since management intervals’ in the corridor: 0.5 years (2 trapping sessions), 1.0 years (4 trapping sessions), 1.5 (5 trapping sessions), 2.0 years (5 trapping sessions), 2.5 years (3 trapping sessions), 3.0 years (3 trapping sessions) and 3.5 years (2 trapping sessions). Captures within the corridors of M1 and M2 were pooled, and forest data from all sites were pooled, before being standardised to 100 trap nights to

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account for unequal trapping sessions across each 6-monthly interval. The data were pooled for clarity and to produce only one set of estimates for early- and late-succession. Chi-square test of homogeneity using Yates’ correction assessed differences in the frequencies of males and females in the corridor small mammal community only. Frequencies included the number of captures for agile antechinus Antechinus agilis, dusky antechinus A. swainsonii and house mouse Mus domesticus and known to be alive (KTBA) estimates for R. fuscipes, R. lutreolus and M. fuscus. To assess small mammal response to vegetation succession, abundances (defined as KTBA) of the commonly trapped species were modelled against vegetation variables. Models for A. agilis, A. swainsonii and M. domesticus used the number of captures as the abundance measure in the models. Small mammal data were from the month the vegetation surveys were conducted and only the corridor data were modelled. Fox (1990) demonstrated that small mammals do not respond to temporal changes, but rather to vegetation succession of an area. Consequently, there may be a time lag between vegetation recovery and mammal recolonisation of an area. Comparisons of time-lagged global models and non-lagged global models were therefore initially conducted for each species to test for any lag effects in small mammal responses to vegetation recovery. Model variables were time-lagged by 6 months from the animal data, using hierarchical partitioning to select the most influential habitat variables on animal abundance. The data were modelled using the information-theoretical approach described by Burnham and Anderson (2002). Akaike Information Criterion corrected for small sample sizes and overdispersed data (QAICc) was applied to models showing overdispersion. Dispersion was estimated by examining the differences in residual deviance and residual degrees of freedom for all global models, and where necessary the variance inflation factor (ˆc) was adjusted. QAICc was used to model data for A. swainsonii. Data were not overdispersed for any of the other species and AICc was used. All subsets of the models were analysed using generalized linear models assuming a Poisson distribution. Akaike differences (i ), weight (wi ) and evidence ratios (wi /wj ) determined the level of support for each model in the set. Weighted model averaging based on 5000 bootstrapped samples was used for all models to give unconditional model variances when the Akaike weight suggested no single model was clearly the best (wi > 0.9) (Burnham and Anderson, 2002). Mann–Whitney U test, Wilcoxon Signed Rank Tests, principal components analysis and tests of homogeneity were conducted in SPSS and model selection was undertaken using R statistical packages (Ihaka and Gentleman, 1996), using algorithms to calculate AICc, QAICc, bootstrap frequencies, and model averaged estimates.

Hierarchical partitioning analysis was also undertaken in R, using the hier.part package (Walsh and Mac Nally, 2003). 3. Results During the study 5939 captures of 2778 individual small mammals occurred. These captures represented eight native and one introduced species and occurred in both the forest and corridor habitat types (Table 1). Trap success varied greatly between the managed and unmanaged corridors, with much higher success occurring in the unmanaged area (Mann–Whitney U test, Z = −10.49, p < 0.01). Native small mammal abundance was lower in the managed corridors and the abundance of the introduced M. domesticus was highest in this habitat. Of the six common species trapped across the study, R. fuscipes was the least abundant in the recently managed corridors, with only two captures recorded. M. domesticus, A. swainsonii and R. lutreolus had the highest abundance in this habitat (Table 1). Overall, the corridor habitat was less suitable for A. agilis (Z = −7.214, p < 0.01), A. swainsonii (Z = −6.242, p < 0.01) and R. fuscipes (Z = −6.194, p < 0.01), who had significantly higher trap success in the forest when compared to the corridor. In contrast M. domesticus (Z = −4.026, p < 0.01) and M. fuscus (Z = −4.791, p < 0.01) were trapped more in the corridor. R. lutreolus (Z = −0.423, p > 0.05) had similar trap success in both habitat types (Table 1). 3.1. Small mammal relative abundance and recolonisation of the corridor The abundance of all small mammals in the corridors was initially low after management. M. domesticus dominated the managed corridors until R. lutreolus began to recolonise 1.5 and 2 years after management (M2 and M1 respectively). However, individual R. lutreolus, A. agilis and A. swainsonii were trapped infrequently prior to this time (Fig. 1). A. swainsonii recolonised the corridor 1.5 and 2.5 years following management (M2 and M1 respectively), while it was 2 and 3.5 years before numbers of M. fuscus began to increase (M1 and M2 respectively). R. fuscipes and A. agilis were trapped in very low numbers in the managed corridors, suggesting the habitat in the managed corridor is unsuitable for these species in early- or mid-succession. The reference corridor had an established community of all five native species, and was dominated by R. lutreolus, A. swainsonii and the near threatened M. fuscus. Lower captures of A. agilis, R. fuscipes and the introduced M. domesticus occurred at this site. M. domesticus numbers were relatively low in this corridor demonstrating their replacement by native mammals (Fig. 1).

Table 1 Trap success (per 100 trap nights) of terrestrial small mammal species in corridor habitats and adjacent forest habitats, at all sites Species

Number of captures M1 Forest

M. domesticus R. lutreolus M. fuscus A. swainsonii R. fuscipes A. agilis C. nanus I. obesulus P. nasuta Total captures

0 1.3(8) 0 12.5(241) 7.9(22) 25.0(396) 0.3(6) 0 >0.1(1) 774

M2 Corridor 6.2(41) 7.7(14) 3.2(2) 2.2(11) 0 0.3(2) 0 0 0 126

Forest >0.1(1) 33.6(100) 0 44.2(764) 41.2(79) 28.5(493) 0.2(3) 0.2(4) 0 2557

Reference site Corridor 8.1(58) 5.0(10) 0.3(1) 5.4(39) 0.3(2) 2.1(15) 0 0 0.3(1) 154

Forest 0 8.8(16) >0.1(1) 34.7(576) 20.2(44) 30.5(506) 2.8(46) 0.2(3) 0 1614

Corridor 1.4(10) 30.6(42) 16.5(18) 25.9(179) 10.1(10) 17.2(119) 0.1(1) 0.1(1) 0 714

Numbers in the parentheses indicate number of individuals known to be alive (KTBA) for R. lutreolus, M. fuscus, and R. fuscipes, and number of captures for all other species. All sites included 72 traps in forest habitat and 30 traps in corridor habitat.

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Fig. 2. Small mammal succession highlighting the community change and species replacement, with increased time since management. Factor 1 is representative of late-succession showing high abundance of R. fuscipes, A. agilis, and A. swainsonii, and absence or reduced abundance of M. domesticus. Factor 2 is indicative of mid-succession, showing high abundances of R. lutreolus, and M. fuscus with lesser contributions from A. swainsonii. The solid circle represents early-successional habitat, the dotted circle represents mid-successional habitats, and the dashed circle represents late-successional or forest habitats. Arrows indicate the postmanagement trajectory of small mammal communities.

Fig. 1. The change in small mammals in the corridor and forest habitats based on pooled trap success across 6 month intervals, standardised to 100 trap nights. Time since management is based on the time since the managed sites corridor vegetation was slashed to a height of 5 cm in September 2000, and when the reference corridor vegetation was last heavily managed in 1994. Data is pooled for the corridors of sites M1 and M2 to give estimates for regeneration age <3.3 years, the corridor of the reference site was used for regeneration between 6.5 and 9.3 years and the data was pooled across all forests for forest estimates.

Interspecific competition may also be important to the internal trajectory of the small mammal community in the corridor (Fig. 1). M. domesticus were numerically dominant in the initial 3 years after management however, numbers were reduced at 6.5–9.3 years after management when M. fuscus abundance had increased (Fig. 1a), suggesting these species may compete for resources. A similar pattern was also seen between R. lutreolus and R. fuscipes with R. lutreolus showing numerical dominance over R. fuscipes initially and 6.5–9 years after management (Fig. 1c). PCA produced a clearer pattern of the temporal pathway of succession in the small mammal communities, highlighting the distinction between the managed corridors, unmanaged corridor and forest communities (Fig. 2). PCA produced two factors with eigenvalues over 1 accounting for 67% of the variation in the small mammal data. Factor 1 indicates a high positive contribution from A. agilis (0.889), R. fuscipes (0.857) and A. swainsonii (0.698). M. domesticus had a high negative contribution to factor 1 (−0.712).

Factor 2 indicated a high positive contribution from M. fuscus (0.873) and R. lutreolus (0.726). A. swainsonii showed a weak positive relationship with this factor (0.399). For the first 3 years post-slashing the early-successional community is dominated by M. domesticus, whose abundance decreases over time. The community in corridor vegetation that was left unmanaged for 6–9 years represented a mid-successional stage with increases in the native species R. lutreolus and M. fuscus, and to a lesser degree A. swainsonii. The forest communities represent a late-successional community with R. lutreolus largely replaced by R. fuscipes, and both antechinus species (Fig. 2). Adult males of all species were generally the first individuals to recolonise the managed corridors (Fig. 3), resulting in significantly more males in the corridor community in M. domesticus (M1: 2 = 8.81, d.f. = 1, p < 0.01; M2: 2 = 3.92, d.f. = 1, p < 0.05), A. swainsonii (M1: 2 = 7.36, d.f. = 1, p < 0.01; M2: 2 = 4.83, d.f. = 1, p < 0.05), and A. agilis (M2: 2 = 9.31, d.f. = 1, p < 0.01) (Fig. 3a). Sex-bias was not observed in the R. lutreolus population (M1: 2 = 0.00, d.f. = 1, p > 0.05; M2: 2 = 1.47, d.f. = 1, p > 0.05) (Fig. 3b). Generally, in small mammal populations, males are the main dispersers and therefore it would be expected that the first individuals to explore the managed corridor would be male. The reference corridor community also demonstrated significantly higher male abundances of M. domesticus (2 = 6.40, d.f. = 1, p < 0.05), A. swainsonii (2 = 5.10, d.f. = 1, p < 0.05), and A. agilis (2 = 14.88, d.f. = 1, p < 0.01) (Fig. 3c). M. fuscus however, had higher occurrences of females in the population at this site (2 = 3.86, d.f. = 1, p = 0.05) (Fig. 3d), suggesting the corridor forms optimal habitat for this species. There was no significant sex bias in R. lutreolus (2 = 0.00, d.f. = 1, p > 0.05), or R. fuscipes (2 = 0.04, d.f. = 1, p > 0.05) populations at this site (Fig. 3d). Successful colonisation of an area requires the establishment of females in the population and results suggests the corridor initially supported a breeding population of M. domesticus 2 years after management until the end of the study, although numbers of this species decreased dramatically in the last 6 months of the study (Fig. 3a). The first adult females of native species began to colonise the managed corridors around 2.5 years after management, when pregnant females of all three rodent species appeared in the com-

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Fig. 3. The sex and age community dynamics of small mammals in the corridor with increased time since management in the managed sites for (a) M. domesticus, A. agilis and A. swainsonii and (b) R. lutreolus, M. fuscus and R. fuscipes and in the reference site for (c) M. domesticus, A. agilis and A. swainsonii and (d) R. lutreolus, M. fuscus and R. fuscipes. Data is pooled across 6 month intervals and based on the number of captures for M. domesticus, A. agilis and A. swainsonii and known to be alive estimates (KTBA) for R. lutreolus, M. fuscus and R. fuscipes. Time since management is based on the time since the managed sites corridor vegetation was slashed to a height of 5 cm in September 2000 (a and b), and when the reference corridor vegetation was last heavily managed in 1994 (c and d).

munity (Fig. 3b). R. lutrelous reproduced in the managed corridor the following year, and while the number of female M. fuscus also increased, no pregnant females were detected the following year. One pregnant A. swainsonii appeared in the corridor around 1.5 years after management, and the population continued to contain adult females and to reproduce for the remainder of the study. Adult females of all native species were generally trapped across each 6month interval within the reference corridor, and annual breeding cycles were recorded across all species (Fig. 3d), demonstrating that the corridor provides continuous functional habitat for a breeding community if some structural complexity is maintained after management.

3.2. Small mammal abundance and vegetation recovery models PCA on the corridor vegetation structure variables produced four factors with eigenvalues above 1, accounting for 77.59% of the variance in the structure data. Factors 1 and 2 were representative of low vegetation (<60 cm and 60–110 cm respectively), and factors 3 and 4 depicted higher vegetation structure (110–140 cm and 140–180 cm respectively). Time-lagged species models had virtually all of the support based on Akaike weights (>0.99), when compared to non-lagged variables, showing that the small mammal community was not responding instantaneously to vegetation change in the corridor. No one model was clearly the best (>0.90) in the candidate set for any species, and model averaging was used for each set of species models. All variables selected for the species models had high stan-

dard errors in comparison to the model averaged coefficients, and may show the non-linearity of vegetation recovery, and the complexity of the relationship between vegetation regeneration and small mammal succession (Wilson et al., 1990).

3.2.1. Mus domesticus The cover of wiry baurea Baurea rubioides, golden bush-pea Pultenaea gunnii, Hakea sp., Gahnia sp. and bare ground were the factors chosen for M. domesticus. Four models had some support based on Akaike weights, all of which included B. rubioides and Gahnia sp. (Table 2). The most supported model from Akaike weights (wi = 0.228) was the global model. However, this model had a very low bootstrapped weight (i = 0.034). Bootstrapped weights indicated changes in Gahnia sp., and the two shrub variables B. rubioides, and Hakea sp., were influencing M. domesticus habitat use the most (i = 0.194). The global model was supported as the best in the candidate set by the log-likelihoods and by model averaging, as the differences between the conditional and unconditional standard errors were low (Table 3). Summed Akaike weights show the importance of B. rubioides (0.87), bare ground (0.84) and Hakea sp. (0.83) to M. domesticus abundance. Gahnia sp. (0.60) and P. gunnii (0.58) had a lower summed weight. The positive association of M. domesticus with B. rubioides and Gahnia sp. (Table 3) however, may be a response to increased cover afforded by these species across the corridor in general, rather than to any association with the plant species. The positive response of M. domesticus to bare ground is indicative of this species being an early coloniser of newly disturbed areas. The negative Hakea sp. coefficient may demonstrate

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Table 2 Time-lagged AICc based model selection for M. domesticus, R. lutreolus, M. fuscus, A. agilis and R. fuscipes, based on species abundances −log(L)/ˆc

Species

Model

M. domesticus

P. gunnii + B. rubioides + Gahnia sp. + bare ground + Hakea sp. B. rubioides + Gahnia sp. + bare ground + Hakea sp. B. rubioides + Gahnia sp + Hakea sp. P. gunnii + B. rubiodes + Gahnia sp.

R. lutreolus

Structure 60–110 cm + Structure <60 cm + Moss + Leptospermum sp. + Hakea sp. Structure 60–110 cm + Structure <60cm + Moss + Leptospermum sp.b Structure 60–110 cm + Structure <60 cm + Mossb

M. fuscus

Structure <60 cm + G. dicarpa + Logs + Banksia sp. Structure <60 cm + Logs + Banksia sp. Structure <60 cm + G. dicarpa + introduced grass + Logs + Banksia sp. Structure <60 cm + G. dicarpa + Banksia sp. Structure <60 cm + Banksia sp.

A. swainsonii

Structure <60 cm + Banksia sp. Structure <60 cm Structure <60 cm + P. esculentum + Banksia sp. Structure <60 cm + Banksia sp. + Hakea sp. Structure <60 cm + Hakea sp. Structure <60 cm + P. esculentum Structure <60 cm + P. esculentum + P. gunnii + Banksia sp.b

A. agilis

Structure <60 cm + P. esculentum + sedge species P. esculentum + sedge species Structure <60 cm + P. esculentum + native grass + P. gunnii + sedge species Structure <60 cm + P. esculentum + P. gunnii + sedge species

R. fuscipes

P. esculentum + other fern species + Leptospermum sp. + Acacia sp. + introduced grass P. esculentum + other fern species + Leptospermum sp. + Acacia sp. P. esculentum + other fern species + Acacia sp.b P. esculentum + Leptospermum sp. + Acacia sp. + IGb

K

AICc

i

wi

␲i

−65.7 −66.9 −68.2 −68.8

5 4 3 3

144.22 144.40 144.70 145.99

0.000 0.185 0.486 1.771

0.228 0.207 0.178 0.093

0.034 0.168 0.194 0.089

– 1.10 1.28 2.45

−92.7 −108 −98.6

5 4 3

198.00 203.00 206.00

0.000 4.310 7.280

0.812 0.094 0.021

0.514 0.110 0.133

– 8.64 38.67

−48.8 −50.5 −48.3 −50.7 −51.9

4 3 5 3 2

108.00 109.00 110.00 110.00 110.00

0.000 1.200 1.360 1.650 1.800

0.247 0.135 0.125 0.108 0.101

0.117 0.158 0.010 0.102 0.224

– 1.83 1.98 2.28 2.44

3a 2a 4a 4a 3a 3a 5a

170.00 170.00 171.00 171.00 172.00 172.00 173.00

0.000 0.439 0.970 1.306 1.692 1.904 2.772

0.170 0.136 0.105 0.088 0.073 0.066 0.043

0.218 0.137 0.193 0.084 0.045 0.080 0.102

– 1.25 1.62 1.93 2.33 2.58 3.95

−52.3 −53.8 −50.8 −52.0

3 2 5 4

113.00 114.00 114.00 115.00

0.000 0.755 1.355 1.514

0.296 0.203 0.150 0.139

0.297 0.260 0.170 0.039

– 1.46 1.97 2.13

−25.2 −26.6 −28.6 −27.5

5 4 3 4

63.20 63.80 65.50 72.20

0.000 0.542 3.303 8.934

0.334 0.255 0.106 0.004

0.076 0.108 0.172 0.197

– 1.31 3.15 83.50

−123 −125 −122 −122 −124 −124

wi /wj

A. swainsonii abundance data were overdispersed and QAICc was used for model selection. The species, model, maximized log-likelihood (log(L)/ˆc), number of parameters (K), Akaike Information Criterion corrected for small sample sizes (AICc) and Quasi-Akaike Information Criterion corrected for small sample sizes QAICc for A. swainsonii, AICc/QAICc differences (i ), Akaike weights (wi ), bootstrap selection frequencies (i ) and evidence ratios (wi /wj ) are shown for the best models. Models with substantial support based on AICc/QAICc ranking from model averaging, are shown in descending order. The variance inflation factor (ˆc) for A. swainsonii was 1.5. a This total includes the estimation for the overdispersion parameter ˆc. b Bootstraps indicated this model should be considered as a contributing model.

M. domesticus preference for early-successional habitat, as Hakea sp. abundance increased in the unmanaged corridor over time. P. gunnii abundance was also high within the unmanaged corridor and the negative coefficient may reflect the low abundance of M. domesticus at this site rather than an association with this species (Table 3). 3.2.2. Rattus lutreolus Two structure variables (<60 cm and 60–110 cm), two shrubs (Leptospermum sp. and Hakea sp.), and the cover of moss were the factors selected for R. lutreolus. The global model was the best in the set to describe R. lutreolus response to vegetation succession (Tables 2 and 3), and therefore, all variables had high summed Akaike weights. Structure below 60 cm (0.99) and between 60 cm and 110 cm (0.95), moss (0.98) and Leptospermum sp. (0.98) had the highest summed weight, while Hakea sp. (0.88) had a comparatively lower weight. R. lutreolus responded positively to all variables in the models (Table 3) which emphasizes the importance of structure and damp areas to this species. All of the plant variables in the R. lutreolus models increased noticeably over time in the managed corridors, in particular Leptospermum sp. and moss. These results suggest R. lutreolus habitat requirements are more indicative of mid-successional habitat and corridor vegetation is unsuitable in the early stages after management. 3.2.3. Mastacomys fuscus M. fuscus models included low structure (<60 cm), logs and the abundance of introduced grasses, pouched coral fern Gleichenia dicarpa and Banksia sp. A number of models were viable to describe M. fuscus response to vegetation recovery in the corridor

(Tables 2 and 3). Low structure (0.91), Banksia sp. (0.89) and logs (0.70) made strong contributions to M. fuscus occurrence, while G. dicarpa (0.63) and introduced grass (0.32) contributed less. M. fuscus abundance had a positive relationship with low structure and G. dicarpa (Table 3), possibly emphasizing M. fuscus reliance on cover and shelter from predators. Introduced grasses, logs and Banksia sp. all contributed negatively to M. fuscus numbers, although the large standard errors for Banksia sp. suggest a complicated relationship (Table 3). The negative association with introduced grass and logs may reflect M. fuscus preference for some structural complexity, which introduced grass generally lacks, while logs may reduce the availability of cover, shelter and nesting sites, by reducing the cover of native grasses M. fuscus use as their main food resource and for nest building. Introduced grass decreased at both the managed sites over time however, Banksia sp. increased at the reference site and M2, and G. dicarpa only increased over time in the reference site. M. fuscus models suggest structure and cover are the most important components in their habitat requirements. This species is known to recolonise an area only when these factors are sufficient. 3.2.4. Antechinus swainsonii The cover of three shrubs Banksia sp., P. gunnii and Hakea sp., and one fern, austral bracken Pteridium esculentum plus low structure (<60 cm) were the factors selected for A. swainsonii. Six models had support based on Akaike weights, although loglikelihoods were conflicting as to the most likely model in the set (Tables 2 and 3). Low structure (1.0) was the most important variable for A. swainsonii. Summed Akaike weights for all other variables were comparatively low; Banksia sp. (0.55), Hakea sp. (0.35), P. esculentum (0.31) and P. gunnii (0.27). A. swainsonii demonstrated a

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Table 3 Model averaged coefficients, unconditional and conditional standard errors, for all variables selected in small mammal models Species

Variable

M. domesticus

P. gunnii B. rubioides Gahnia sp. Bare ground Hakea sp.

R. lutreolus

Coefficient

Standard errors

Contribution

Z-score

Unconditional

Conditional

−0.170 0.029 0.043 0.012 −0.633

0.132 0.023 0.037 0.023 0.707

0.146 0.020 0.035 0.029 0.705

9.60 36.46 25.44 6.45 22.04

−1.26 2.86* 2.78* 1.02 −1.13

Structure 60–110 cm Structure <10–60 cm Moss Leptospermum sp. Hakea sp.

0.372 0.548 0.094 0.076 0.064

0.178 0.179 0.032 0.036 0.043

0.161 0.165 0.032 0.031 0.035

20.30 17.20 17.70 23.30 21.60

2.09* 3.45* 3.41* 2.53* 2.82*

M. fuscus

Structure <10–60 cm G. dicarpa. Introduced grass Logs Banksia sp

0.595 0.137 −0.020 −0.839 −29.464

0.239 0.146 0.004 1.070 3.99 + 03

0.249 0.139 0.068 1.208 4.64 + 03

31.60 32.90 13.90 10.90 10.70

1.99* 2.14* −0.89 −1.14 −0.01

A. swainsonii

Structure <10–60 cm P. esculentum P. gunnii Banksia sp. Hakea sp.

0.656 −0.033 −0.016 −0.246 0.033

0.138 0.017 0.010 0.134 0.027

0.141 0.026 0.019 0.157 0.040

63.85 12.49 4.50 9.24 9.92

4.64* −1.27 −0.82 −1.57 0.83

A. agilis

Structure <10–60 cm P. esculentum Native grass P. gunnii Sedge species

0.644 −0.656 −0.037 −0.051 −0.139

0.230 0.249 0.015 0.024 0.033

0.276 0.280 0.024 0.037 0.044

18.30 24.60 11.30 12.20 33.70

2.29* −2.34* −1.51 −1.38 −3.15*

R. fuscipes

P. esculentum Other fern species Leptospermum sp. Acacia sp. Introduced grass

2.77 + 03 0.363 0.306 1.24 + 04 0.210

2.96 + 03 0.319 0.323 1.28 + 04 0.238

18.80 44.89 15.81 7.97 12.54

−0.004 2.37* −1.68 −0.003 −1.31

−12.034 0.756 −0.542 −39.329 −0.310

Conditional standard errors are conditional on the best selected model. Results from hierarchical partitioning are also shown, with the independent contribution, Z-scores and significance (based on the upper 0.95 confidence limit Z ≥ 1.65), of each variable to species abundance. * Statistical significance based on the upper 0.95 confidence limit (Z ≥ 1.65).

positive relationship to low structure and the cover of Hakea sp., but the species responded negatively to P. esculentum, Banksia sp., and P. gunnii (Table 3). P. esculentum and P. gunnii were both indicative of early-succession at M1, decreasing in abundance over time. P. esculentum however, increased over time at M2 and may have resulted in areas of unsuitable habitat for A. swainsonii. Models for A. swainsonii emphasize that vegetative structure is the most important habitat requirement for this species and suggest that earlysuccessional corridor habitat will not be suitable for this species. 3.2.5. Antechinus agilis Low structure (<60 cm), the abundance of native grass, sedge species, P. esculentum, and P. gunnii were the variables selected for A. agilis. Four models had some support based on Akaike weights and bootstraps (Tables 2 and 3). Summed Akaike weights show that P. esculentum (1.0) and sedge species (0.98) were most influential on A. agilis abundance and that low structure (0.59), P. gunni (0.4) and native grasses (0.28) contributed less. A. agilis demonstrated a positive relationship with low structure and a negative relationship to all other variable (Table 3), reflecting a preference for late-successional habitat, as native grass, sedge species, P. esculentum, and P. gunnii all had high abundances in the corridor. 3.2.6. Rattus fuscipes Leptospermum sp., Acacia sp., P. esculentum, other fern species and introduced grasses were the variables selected for R. fuscipes. No structure variable was selected for this species, which demonstrates that R. fuscipes preference for structurally complex habitats were absent in the recovering corridor. Three models had some sup-

port based on Akaike weights and bootstraps (Table 2). Summed Akaike weights suggested that cover of P. esculentum (0.99), Acacia sp. (0.94), other ferns (0.86) and Leptospermum sp. (0.77) were most influential on R. fuscipes abundance. Introduced grass (0.58) had a comparatively lower summed weight. R. fuscipes only responded positively to the abundance of other fern species. All other variables had a negative relationship with this species (Table 3). R. fuscipes is known to prefer wet areas, and ferns are indicative of wet, later-successional habitat. Acacia sp., P. esculentum and introduced grasses were prolific in the early-successional stages of the corridor, and it is not unexpected that R. fuscipes would respond negatively to these species. These models clearly indicated that the corridor does not provide suitable microhabitat for this late-successional species. 4. Discussion There were clear differences between the small mammal communities of the recovering corridors, reference corridor and forest. The habitat accommodation model proposed by Fox (1982) suggests population densities vary during different successional stages due to changes in resource availability, and will decrease as optimal conditions and successional stage change. The communities in the corridor vegetation appear to adhere to such a model. As the vegetation regenerated through early- to late-succession, the small mammal community changed from one dominated by M. domesticus, through one with high abundances of R. lutreolus, M. fuscus and to a lesser extent, A. swainsonii, to a forest community of A. agilis, R. fuscipes and A. swainsonii. This successional trajectory is

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Fig. 4. A model showing the successional gradient of the small mammal community within the corridor and forest. Solid lines indicate the current management cycle, where after 3 years management occurs in the form of slashing and resources are removed from the small mammal community dominated by M. fuscus and R. lutreolus. The ecosystem becomes degraded and the small mammal community reverts back to one dominated by introduced M. domesticus. Dotted lines represent a proposed management strategy where a combination is used of mosaic slashing in high-growing vegetation and manual cutting or selective herbicide to remove emergent midstorey saplings and problem plants in low-growing vegetation. This would maintain resources for a native small mammal community, increase intervals between management and increase the community’s resistance to invasion by the introduced M. domesticus.

similar to those seen in fire succession studies, where M. domesticus was the first species to recolonise recently disturbed areas (e.g. Fox, 1983; Fox et al., 2003; Wilson and Moloney, 1985), followed by R. lutreolus or a dasyurid species (Fox, 1983) depending on factors such as other species present, the density of vegetation (Fox and Fox, 1984; Monamy and Fox, 2000), and the intensity of disturbance (Fox and Fox, 1984). Driessen (1999) also found M. fuscus colonised burnt areas within 2 and 3 years following fire, which is consistent with the present study. Small mammal species contributing to the early, mid- and late-successional communities reflect the temporal changes in vegetation composition. Species such as B. rubioides and P. esculentum were prolific in early post-management stages, and M. domesticus was positively associated with B. rubioides, while P. esculentum negatively contributed to the abundances of three later-successional species R. fuscipes, A. agilis and A. swainsonii. Similarly, the corridor community was colonised by Banksia sp., Leptospermum sp., and Hakea sp. in mid-succession, when the abundances of R. lutreolus, M. fuscus and A. swainsonii began to increase. A. swainsonii, A. agilis and R. fuscipes require complex habitat (Barnett et al., 1978; Bennett, 1993; Strahan, 1991), indicative of a late-successional stage, which is not available in the corridor. It was not surprising therefore, that these species demonstrated negative associations with shrub species, which had high abundances in the corridor. Interspecific competition may also be a driving factor for the compositional changes seen in the small mammal community over time. Maitz and Dickman (2001) found that intense competition between R. lutreolus and R. fuscipes resulted in R. fusicpes partial exclusion from the better microhabitats. It is possible in the present study that R. lutreolus restricted R. fuscipes access to resources in the corridor. Interspecific competition may also explain the population responses of M. fuscus and M. domesticus, with the heathland specialist (Happold, 1989) partially excluding the generalist M. domesticus from the corridor over time. Structural complexity is a good indicator of small mammal abundance (Catling et al., 2001), and was important in four of the six species models. Only M. domesticus and R. fuscipes models did not include vegetation structure, highlighting both that the requirement of R. fuscipes for high structural complexity was absent in the corridor, and that M. domesticus was associated with newly disturbed areas (Fox et al., 2003; Wilson and Moloney, 1985). The

models suggest that small mammal abundance is influenced by cover and shelter from predators rather than plant species per se. Batzli et al. (1999) also suggested the quality of food and cover was the most important habitat component for voles. Fox and Fox (1984) also demonstrated that recolonisers must wait for suitable food and shelter resources to regenerate following a disturbance, but cautioned that small mammal succession does not necessarily parallel vegetation succession, especially if there are “pulses” in vegetation growth. This theory was supported in the present study, where there was at least a 6-month time lag in small mammal species response to vegetation changes. The large standard error for many model variables also most likely suggests that vegetation regeneration was not linear, and that the relationship between vegetation recovery and small mammal succession is complex, even when time lag is accounted for. Wolff (1999) stressed the importance of female immigration if colonisation of patches is to be successful. Evidence of annual breeding cycles of R. lutrelous, M. fuscus and A. swainsonii in the recently managed corridor sections 2.5 years after management, suggests that the managed corridor population is able to maintain a viable breeding community of these three species. The low captures of R. fuscipes and A. agilis however, demonstrate this is not the case for R. fuscipes or A. agilis populations in such a modified habitat. Evidence of annual breeding cycles of all species in the reference site show that if structural complexity is maintained in the corridor it can support a viable small mammal community for a continuous time period. Sources of recolonisation of the corridor were largely unknown. Some individuals moved into the corridor from the surrounding forest, demonstrating its importance as a source population. Although there is a danger of source–sink dynamics occurring between the corridor and forest populations if the corridor requires constant immigration from the surrounding forest to be maintained (Batzli et al., 1999), the presence of pregnant females in the corridor suggests the corridor can sustain a breeding population of small mammals. 4.1. Implications for management The current approach to powerline corridor management, which focuses on complete vegetation removal along the entire length of the corridor using short rotations (usually 3 years) main-

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tains powerline habitat in a degraded state. It allows populations of introduced M. domesticus to thrive by removing resources at a time when native populations are beginning to recover and depress M. domesticus populations (Fig. 4). Current management practices increase recolonisation times by forcing small mammals to wait for sufficient levels of resources to regenerate. It took 2.5 years post-management before corridor habitat was suitable for a breeding native small mammal community, which is essential if the corridor is to provide functional habitat. Current management however, reduces resources back to unsuitable levels on a 3-year cycle (Fig. 4), severely limiting the amount of time the corridor can support a native small mammal community. The 6-month time lag in small mammal response to vegetation recovery exacerbates management effects. Management needs to maintain threshold levels of habitat cover if colonisation times are to be reduced (Fox et al., 2003). Creating refuge areas in the corridor in high growing vegetation through mosaic slashing, would maintain threshold vegetation levels and help the small mammal community recover quickly from management, while keeping biomass and fire risk low. Lindenmayer et al. (2005) suggested that small mammal populations are more likely to survive a disturbance event if patches of suitable habitat remain. An integrated approach to corridor management using a combination of mosaic slashing in high growing vegetation and spot-spraying or manual removal of problem plants in low-growing vegetation would maintain a mid-successional small mammal community, and minimize disruption to resources for native species (Fig. 4). This approach would also reduce the need for slashing in the short term, allow an increase in rotation times, and reduce management costs. The near threatened M. fuscus was one of the first native species to recolonise the corridor post-management. However, the low reproduction rate of this species compared to other native rodents (Green and Osborne, 2003), in combination with the suppression of M. fuscus populations during management, may mean populations recover to pre-management levels slowly. This stresses the importance of using an integrated management approach to maintain source populations not only of M. fuscus, but all native small mammal species. It is essential to shift the current cycle of a corridor comprising a degraded system lacking native small mammals, to one rich in native species. An integrated approach to management is the way forward. Acknowledgements Thank you to the Parks Victoria Research Partners Scheme and Deakin University, School of Life and Environmental Sciences for funding the study. Special thanks to the Parks Victoria Rangers at the Gembrook office for their additional funds, support and interest across the study and to the many people who helped with fieldwork, especially Meghan Cullen and Kate Pearce. We gratefully acknowledge the suggestions and ideas provided by Barry Fox and an anonymous reviewer. References Barnett, J.L., How, R.A., Humphreys, W.F., 1978. The use of habitat components by small mammals in eastern Australia. Aust. J. Ecol. 3, 277–285. Batzli, G.O., Harper, S.J., Lin, Y.K., Desy, E.A., 1999. Experimental analyses of population dynamics: scaling up to the landscape. In: Barrett, G.W., Peles, J.D. (Eds.), Landscape Ecology of Small Mammals. Springer-Verlag, New York, pp. 107–174. Bennett, A.F., 1993. Microhabitat use by the long-nosed potoroo, Potorous tridactylus, and other small mammals in remnant forest vegetation of south-western Victoria. Wildl. Res. 20, 267–285.

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