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Identifying Unidirectional and Dynamic Habitat Filters to Faunal Recolonisation in Restored Mine-Pits

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Identifying Unidirectional and Dynamic Habitat Filters to Faunal Recolonisation in Restored Mine-Pits MURDOCH RESEARCH REPOSITORY This is the author’s final version of the work, as accepted for publication following peer review but without the publisher’s layout or pagination. The definitive version is available at http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2664.2012.02152.x/full Craig, M.D, Hardy, G.E.St.J., Fontaine, J.B., Garkaklis, M.J., Grigg, A.H., Grant, C.D., Fleming, P.A. and Hobbs, R.J. (2012) Identifying unidirectional and dynamic habitat filters to faunal recolonisation in restored mine-pits. Journal of Applied Ecology, 49 (4). pp. 919-928. http://researchrepository.murdoch.edu.au/9955/ Copyright: © 2012 The Authors. It is posted here for your personal use. No further distribution is permitted. Running title: Filters to faunal recolonisation in restoration Title: Identifying habitat filters to faunal recolonisation in restored mine-pits List of Authors: Michael D. Craig1,7, Giles E. St J. Hardy1, Joseph B. Fontaine2, Mark J. Garkakalis1,5, Andrew H. Grigg3, Carl D. Grant3, Patricia A. Fleming4 & Richard J. Hobbs2,6 1Address: School of Biological Sciences and Biotechnology, Murdoch University, Murdoch, WA 6150, Australia 2Address: School of Environmental Science, Murdoch University, Murdoch, WA 6150, Australia 3Address: Alcoa World Alumina Australia, Pinjarra, WA 6208, Australia 4Address: School of Veterinary and Biomedical Sciences, Murdoch University, Murdoch, WA 6150, Australia 5Present Address: Astron Environmental Services, Level 1, 620 Newcastle Street, Leederville WA 6007, Australia 6Present address: School of Plant Sciences, University of Western Australia, Nedlands, WA 6907, Australia 7Address correspondence to Michael D. Craig Email: [email protected] Phone: 08 9360 2605 FAX: 08 9360 6303 Pages: 28 (including tables and figures) Tables: 3 Figures: 4 References: 49 Word count: 6948 (Summary – 350 words, Main text – 4920 words, Acknowledgments – 86 words, References – 1308 words, Table legends – 80 words, Figure legends – 204 words) 21 1 Summary 2 1. There is increasing evidence that passive faunal recolonisation of restored areas can take decades or even 3 centuries, reducing benefits to biodiversity from restoration. Thus, there is a need to develop restoration and 4 management strategies that facilitate and accelerate faunal recolonisation. This requires identification of habitat 5 features that act as filters to slow or prevent recolonisation and whether those filters are temporally unidirectional 6 or dynamic. 7 2. We investigated successional patterns of reptiles and mammals in restored mine-pits in south-western 8 Australia to identify potential filters to faunal recolonisation. We sampled reptiles and small mammals using 30 9 trapping grids across each of four restoration ages (4, 8, 12 and 17-years old) and unmined forest, and assessed 10 vegetation structure to identify animal-habitat relationships. 11 3. Mammal communities in restored areas converged on unmined forest communities as restoration matured, 12 and all species recolonised rapidly, indicating there were no filters to mammal recolonisation. In contrast, reptile 13 communities did not converge in the same way indicating there were filters that slowed or prevented reptile 14 recolonisation. We identified three reptile species that were slow, or failed, to recolonise restored areas and a 15 fourth species that rapidly recolonised but disappeared as restoration matured. We identified low coarse woody 16 debris (CWD) volumes and high overstorey stem densities as likely filters; the former is a unidirectional filter that 17 will decrease gradually over long timeframes, possibly centuries, while the latter is a dynamic filter that fluctuates 18 in its intensity over short timeframes of years. 19 4. Synthesis and applications. Our study adds to growing evidence that filters to faunal recolonisation may be 20 widespread in restored areas, with important implications for restoration practices. Firstly, examining individual 21 species may more effectively identify filters than examining community successional patterns. Secondly filters 22 can persist over long timeframes, possibly centuries, so management, such as the provision and accelerated 23 development of CWD, may need to occur over similar timeframes. Lastly, filters can be dynamic and repeated 24 management interventions, such as thinning, may be required to overcome these filters. The growing evidence for 25 filters suggests that facilitating faunal recolonisation is more complex than simply returning vegetation to 26 restoration sites. 22 27 Keywords: restoration, succession, mammal, reptile, lizard, mining, coarse woody debris, vegetation structure, 28 forest, jarrah, Australia 29 Introduction 30 Given past and current levels of habitat clearance and degradation, restoration is likely to become increasingly 31 important in conserving global biodiversity (Hobbs & Harris, 2001). However, given that fauna contribute most of 32 the biodiversity in ecosystems, restored areas will need to support most of the original fauna if they are to be 33 effective (e.g. Thomas, 2009). Despite this, many restoration projects simply revegetate and assume that animals 34 will naturally recolonize; this assumption is called the “Field of Dreams” hypothesis, which states that “if you 35 build it they will come” (Palmer, Ambrose & Poff, 1997). However, evidence is increasing that in some systems 36 not all fauna recolonise restored areas even after several decades (e.g. Martin et al., 2004; Kanowski et al., 2006). 37 Species that fail to recolonise are often specialised and are most vulnerable to habitat clearance and fragmentation 38 (Ryan, 1999; Vesk et al., 2008). Thus, it is likely these species will be lost from landscapes unless restoration can 39 provide suitable habitat within the first few decades. If restoration is to be effective in helping preserve global 40 biodiversity, it should aim to facilitate, accelerate and maintain faunal recolonisation rather than relying on 41 passive recolonisation. 42 A number of recolonisation strategies have been proposed (e.g. Thomas, 2009; Lindenmayer et al., 2010) but their 43 incorporation into restoration planning is still not widespread (Brennan, Nichols & Majer, 2005). This may be due 44 to the lack of a conceptual framework through which to interpret barriers to faunal recolonisation and examine 45 generalities across studies. However, community ecology based assembly rules, which seek to understand how 46 communities assemble and why some species occur in particular places (e.g. Wallem et al., 2010), provide a 47 fertile framework through which to interpret faunal recolonisation of restored areas (e.g. Summerville, Conoan & 48 Steichen, 2006). In particular, trait-filter models, which predict how species’ traits limit species presence within 49 assemblages (e.g. Purcell et al., 2009), could improve our understanding of why some species move from regional 50 species pools into restored areas whereas others do not. 23 51 Although trait-filter models have been widely applied to restored plant communities (e.g. Hough-Snee et al., 52 2011), they have been infrequently used in understanding faunal community assembly (but see Summerville, 53 Conoan & Steichen, 2006). However, the mobility of most terrestrial fauna means that they can respond more 54 rapidly to filters than plants, which are sessile and, often, long-lived. This means filters to faunal recolonisation 55 can be both unidirectional (decreasing gradually over time) or dynamic (fluctuating in intensity over time) 56 depending on whether filters develop over long timeframes (e.g. coarse woody debris) or change rapidly (e.g. 57 canopy cover). Typically, it has been assumed that filters are unidirectional and that once a species has 58 recolonised restored areas they will persist there. However, if filters are dynamic, species may recolonise restored 59 areas but fail to persist. The temporal nature of filters has important implications for management because 60 reducing the effect of unidirectional filters may require only single management inputs, whereas reducing the 61 effects of dynamic filters is likely to require on-going and repeated management inputs. 62 Alcoa of Australia has mined bauxite in the jarrah forest of Western Australia since 1963 and restored its mine- 63 pits since 1966 (Koch, 2007). Long-term research indicates that most vertebrate species in unmined jarrah forest 64 recolonise restored sites (Nichols & Nichols, 2003; Nichols & Grant, 2007), although some species are either 65 unrecorded or recorded very rarely in restored areas, indicating there may be filters to recolonisation. Most of 66 these species are reptiles, which are the slowest vertebrate group to recolonise restored areas (Nichols & Nichols, 67 2003). However, the filters that prevent, or slow, their recolonisation have not been identified so restoration 68 practices cannot be modified to facilitate their return. It is also important to identify successional patterns within 69 restored areas so we can determine whether vertebrates that recolonise persist in restored areas or whether there 70 are temporally dynamic filters. This will, in turn, inform the type, and timeframe, of management strategies in 71 restored areas. 72 Our study examined reptile and small mammal communities in restored mine-pits of varying ages and adjacent 73 unmined forest to investigate vertebrate successional patterns and use them to identify filters to recolonisation. 74 We analysed vertebrate successional patterns at both
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