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Longer-term response to experimental manipulation of fallen timber on forest floors of floodplain forest in south-eastern Australia
Forest Ecology and Management 229 (2006) 155–160 www.elsevier.com/locate/foreco
Longer-term response to experimental manipulation of fallen timber on forest floors of floodplain forest in south-eastern Australia Ralph Mac Nally * Australian Centre for Biodiversity: Analysis, Policy and Management, School of Biological Sciences, Monash University, Melbourne 3800, Australia Received 8 February 2006; received in revised form 27 March 2006; accepted 27 March 2006
Abstract There often are substantial accumulations of fallen timber (logs, large boughs) in many woodlands and forests around the world. However, fallen timber has become a target for removal for use as fuel or for management actions, such as fuel-reduction burning. Many silvicultural practices, such as fast harvesting rotations, coppicing and debris burning prior to re-sowing/re-planting, lead to much reduced fallen-timber loads. Many studies show the ecologically important role fallen timber plays, so its removal is likely to have adverse ecological outcomes. It has previously been shown that a specialized forager on fallen timber, the brown treecreeper Climacteris picumnus, responded strongly over a shortterm (20 mo) to a meso-scale (34 ha) manipulation of fallen-timber loads in river red gum Eucalyptus camaldulensis forest in northern Victoria, Australia [Mac Nally, R., Horrocks, G., Pettifer, L., 2002a. Experimental evidence for beneficial effects of fallen timber in forests. Ecol. Appl. 12, 1588–1594]. There were substantially more birds in all treatments in which loads were increased to 40 Mg/ha or more, elevated from averages of ca. 20 Mg/ha across the southern Murray-Darling Basin. Sites were revisited 3 years after the manipulation was conducted and I show here that the changes in density have been sustained. These results suggest that increased fallen-timber loads 40 Mg/ha are preferred by the vulnerable treecreeper, and that the bird’s responses reported previously were not transient. These elevated densities may translate into increased reproductive success of the treecreepers because larger groupings in this and related cooperative breeders produce more young. I conclude by outlining options for management of fallen timber to provide greater chances of viability for the species. # 2006 Elsevier B.V. All rights reserved. Keywords: Bayesian models; Brown treecreeper; Eucalyptus camaldulensis; Habitat manipulations; River red gum; Woody debris; WinBUGS
1. Introduction Many human activities directly or incidentally alter habitat characteristics, and hence quality, for organisms. Identifying and ameliorating these changes underlie much of the work done in conservation biology and wildlife management (Baker, 1997; Stewart et al., 2003). Definitive demonstrations of habitat-structural impacts on species occurrence or demography require field experiments at appropriate spatial and temporal scales (Mac Nally, 1997). Habitat manipulations have been used relatively infrequently compared with more indirect methods, such as statistical modeling (Mac Nally et al., 2002a). This probably reflects prohibitive workloads in constructing large, replicated experiments and difficulties in
* Tel.: +61 3 9905 5642; fax: +61 3 9905 5613. E-mail address: [email protected]. 0378-1127/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2006.03.024
maintaining manipulated habitats over periods long enough to demonstrate ecologically important effects. There are relatively few habitat elements that can be precisely manipulated and also are demonstrably critical for biota. Fallen timber – logs and large boughs – is a habitat element that has many characteristics that make it attractive for manipulative experiments. First, it has been systematically removed from many forests and woodlands around the world, to the detriment of much of the forest-floor dwelling biota (Harmon et al., 1986). Therefore, it is both a critical element from an ecological standpoint but also one that has experienced much modification. Second, few habitat elements are as suited to experimental manipulation as fallen timber because of the precision with which loads (expressed in Mg/ha) can be altered and redistributed. These two facets led to an exploration of how anthropogenically imposed variations in fallen-timber loads affect species’ occurrence and densities in forests. The problem of fallen timber removal is very marked in the forests or the floodplains of south-eastern Australia. Timber on
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the major floodplains of the southern Murray-Darling Basin (MDB) has been pillaged systematically for almost 200 years, first to sustain the demands of river paddle-steamers, then to provide fuel for the major cities and towns of Victoria and, more recently, to yield firewood, building materials and train-track stays (Mac Nally and Parkinson, 2005). Much of the extant forested area is intensively managed for fast-turnover timber production, which means that the age-class structure of trees is deliberately kept youthful, with few large, old trees. The latter are the primary generators of fallen timber through limbabscission and tree-death and collapse. The outcome has been a likely reduction in fallen-timber loads by about 85%, to ca. 19 Mg/ha across the southern MDB (Mac Nally et al., 2002b). In 2002, short-term responses were reported for a vulnerable species of bird (in New South Wales and Victoria) that specializes in foraging on fallen timber (Mac Nally, 1994), the brown treecreeper Climacteris picumnus, to a meso-scale manipulation of fallen timber in a floodplain forest of northcentral Victoria, Australia (Mac Nally et al., 2002a). By mesoscale I mean that the experiment was conducted over 34 1-ha plots; by short-term I mean that responses were monitored for 20 mo following manipulation. One of the primary reasons for the species’ parlous conservation status is loss of fallen timber (Garnett and Crowley, 2000). The results were reasonably conclusive: treecreeper densities were substantially greater in all treatments in which wood-loads exceeded 40 Mg/ha. The experimental system is relatively large-scale (tens of ha) and appropriate to the scales of movement of the treecreeper, which is a relatively sedentary, cooperatively breeding species (Noske, 1980, 1991) with a group home-range of ca. 4.5 ha (Cooper et al., 2002). Many ecological studies, and especially experiments, often involve a mismatch between spatial and temporal scales (Thompson et al., 2001). That is, large spatialscale experiments often are conducted for relatively short periods of time and sometimes vice versa. Although not originally intended within the project plan, additional funding was secured and I report here on new data that extends the monitoring period to 35–40 mo following the manipulation. I show that the initial results have been sustained over a longer time-frame (to >3.5 years), providing greater confidence that the birds recognize and respond to variation in fallen-timber load. The implications of this sustained response are discussed, as is the major remaining problems relating to the management of fallen timber in these floodplain forests.
2. Methods 2.1. Study area The experiment was conducted on Gunbower Island (358420 23S 1448120 13E), which lies between the Murray River and Gunbower Creek near Cohuna, in north-central Victoria, Australia. The island used to flood almost every year, but with more extreme water extractions and flow regulation, flooding now is much rarer (Crabb, 1997). Gunbower Island is intensively exploited for firewood and posts and railway-stays.
2.2. Experimental design Thirty-four 1-ha plots were marked out. Wood-load measurements (average 27 Mg/ha) were conducted prior to manipulation. This consisted of measuring all pieces of fallen timber within the 1 ha plot, taking end diameters and lengths of pieces and computing volumes. These were translated into mass by using the mean density of 0.6 Mg/m3 (Robinson, 1997). The 34 plots were randomly allocated to seven treatments prior to moving the wood, but with some constraints on the random distribution. As much as possible, sites allocated to different treatments were interspersed to reduce possible spatial effects. Five treatments corresponded to loads of 0, 20, 40, 60 and 80 Mg/ha (designated 0, 20, 40, 60 and 80L) of aged fallen wood (10 cm diameter). River red gum is a highly resilient timber that decays slowly (Robinson, 1997), so that most of the fallen timber was of Decay Class I or II (i.e. bark largely intact, structural integrity mostly solid, larger twigs present; Harmon and Sexton, 1996). Following four rounds of pre-manipulation bird surveys beginning in May 1999 (see below), timber was moved in late March 2000. On all of these plots, fallen timber already on the plots was disturbed so that all timber was dislodged from previous footings. There was an undisturbed control treatment (designated UC) in which no equipment or persons traversed plots during wood moving. The other treatment was the imposition of 40 Mg/ha of tree crowns onto plots (40H). The 40H treatment emulates current silvicultural practices, which involve the felling of a river red gum tree, removal of the bole for timber, and the deposition of the crown for up to 3 years before harvesting the main branches for firewood. Thus, new fallen timber in these production forests often is in the form of crowns. Existing timber was removed from these plots and fresh crowns deposited. There were four replicate plots for each treatment, apart from 0L, for which there were six. In all manipulated plots, timber was evenly distributed over the whole ha (100 m 100 m). The middle 50 m 50 m part of each plot was marked with metal stakes and formed the focus for bird surveys. One thousand Mg of timber was repositioned during this operation, requiring six persons for 8 days, hydraulic tandem trailers, a bulldozer and a log-harvesting machine (Mac Nally, 2001). 2.3. Bird survey schedule and method There were 18 rounds of surveys, each consisting of a 7-day period, in the following months: May, July and October 1999, January, May, July and September 2000, January, March, April, July, September and November 2001, January 2002, February, April, May and July 2003. The first four rounds were prior to wood-load manipulations, while the latter 14 followed the experimental changes. The surveys were divided into three periods. The first is the pre-manipulation period, consisting of four surveys. The second period is that consisting of the next 10 surveys over 20 mo, which is regarded as the short-term response period and has been reported (Mac Nally et al., 2002a). Another four
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surveys were completed in 2003, the longer-term response period, with a gap of 13 mo between the last of the secondperiod surveys and the first of this series. These four surveys were conducted 35–40 mo after the manipulations were undertaken. Surveys involved the observer (the same person in all 18 survey rounds) sitting at one corner of the interior square for 45 min and recording all birds active within the half of the square closest to the observer (a right-triangular area of 0.125 ha). While activities of birds outside this small central part of plots were recorded, these data are not considered here. Surveys were conducted either between dawn and 1100 Australian Eastern Time (AET) or from 1400 AET to 1 h before sunset. 2.4. Analyses The data consisted of an array of 30 sites by 18 survey periods. I used a Poisson model to analyse these data (Gelman et al., 1995). Most of the data were small, non-negative values (<5), so the use of a counts distribution like the Poisson seemed reasonable. The model is: Y jðmÞkðnÞ Poissonðm jðmÞkðnÞ Þ; logðm jðmÞkðnÞ Þ ¼ a jðmÞkðn¼1Þ þ a jðmÞkðn 6¼ 1Þ :
(1)
The Ys are assumed to be Poisson-distributed with means m and are the observed numbers in plot j in survey k, with the j(m) indicating that site j belongs to treatment m (viz., 0L, . . ., UC). The k(n) subscript assigns survey k to period n (n = 1 = premanipulation, n = 2 = short-term period, n = 3 = longer-term period). The as for n 2 are multiplicative constants and, when exponentiated, indicate the degree to which numbers of treecreepers increase or decrease relative to the values for the given treatment before manipulation (i.e. n = 1). From these coefficients, one can estimate the average change in numbers of treecreepers in periods 2 and 3 relative to period 1 and relate these to changes in the UC-treatment sites over the same comparisons: DY jðmÞkðn 6¼ 1Þ ¼ ðexpða jðmÞkðn 6¼ 1Þ Þ 1Þ expða jðmÞkðn¼1Þ Þ; @Y jðmÞkðn 6¼ 1Þ ¼ DY jðmÞkðn 6¼ 1Þ DY jðm¼UCÞkðn 6¼ 1Þ :
(2)
The DYs are the estimated net increases in numbers of treecreepers in periods 2 and 3 relative to period 1 for each treatment, while the @Ys are these differences relative to the changes that occurred in the UC-treatment sites over the same periods. Therefore, the @Ys provide changes in numbers corrected for changes in numbers recorded in the control sites. I used the WinBUGS Bayesian analysis software (publicdomain, version 1.4, Spiegelhalter et al., 2003). Noninformative normal priors were used for the a coefficients (0 means, 106 precisions). In all analyses, means and medians of posterior distributions of parameters were similar, indicating symmetric probability distributions. Burns-in of 10,000 and samples of 20,000 were used.
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The outputs of WinBUGS modeling are posterior probability distributions (PPDs) of model parameters and any functions thereof. Therefore, I computed PPDs for the as and @Ys (Eqs. (1) and (2)) and report upon the latter here. One can also compute how much of the PPD for a parameter exceeds 0. For a non-informative prior, where I had no expectation that a parameter would differ from 0, the expected value of PPD is 0.5. The degree to which PPD differs from 0.5 is a measure of the probability that a parameter’s value differs from zero either negatively (<0.5) or positively (>0.5). Also for a noninformative prior, in which the ratio of posterior probabilities for the parameter is unity, the Bayes factor (BF), the ratio of PPD/(1 PPD) in this instance, is a measure of the evidence in favor of the parameter differing from 0 (Jaynes, 2003). Kass and Raftery (1995) argued that BFs exceeding 12 are strong evidence supporting one hypothesis over another (here that the parameter differs from 0), and BFs between 3 and 12 signal positive evidence. BFs < 3 are hardly worth reporting. For negative coefficients, values of PPD will be <0.5 so that PPD/ (1 PPD) < 1. Therefore, one uses the inverse guideline measures of Kass and Raftery (1995) for inferring differences from 0 (i.e. 1/12, 1/3, etc.). This means that PPD < 0.25 and > 0.75 correspond to BFs < 1/3 and > 3, respectively, while PPD > 0.92 or < 0.08 represent BFs > 12 or < 1/12, respectively. 3. Results Total numbers of treecreepers fluctuated substantially through time across Gunbower Island (Fig. 1a). There was substantial variation in densities of treecreepers among treatments before fallen-timber manipulations were done (Fig. 1b). By happenstance, the densities were extremely low in the four sites randomly allocated to the 40H treatment but much greater in the sites randomly allocated to the 20L treatment (Fig. 1b). By inspection, it seems that there were dramatic increases in mean densities for period 2 in treatments 40H, 40L, 60L and 80L, as reported by Mac Nally et al. (2002a). Generally speaking, these increases appear to have been maintained in period 3, at least 3 years after the timber was manipulated (Fig. 1b). Results in Table 1 take into account simultaneous changes in sites of the control treatment (UC), which the differences @Ys (Eq. (2)) were designed to do. These values are changes in density in periods 2 and 3 from to period 1 (pre-manipulation), but made relative to changes in the UC-treatment sites over the same comparisons. For example, in 40L-treatment sites, densities increased by 0.29 birds/(0.125 ha) between periods 2 and 1 more than the density change in the UC sites between periods 2 and 1 (Table 1). Inspection of values for the @Ys suggests that densities increased more than in the control sites in all treatments with wood-loads of 40 Mg/ha, and these increases were sustained in the longer term (Table 1). Increases (in excess of changes in UC sites) typically were 0.3 birds/ (0.125 ha), and as much as 0.63 (Table 1). There was little change in the 20L sites, but a suggestion of a possible weak increase in the longer term in denuded sites (BF = 4.6).
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Fig. 1. (a) Densities of treecreepers summed for all 30 sites (hence total survey area of 4.75 ha) in months elapsed since May 1999. Periods are: pre-manipulation (solid circles), short-term (open squares) and longer-term (closed squares). (b) Mean (+S.E.) of brown treecreepers (birds/(0.125 ha)) for seven experimental treatments, described in text. Three periods are: pre-manipulation (open bars), short-term (coarse hatch) and longer-term (fine hatch). Treatment codes are described in text, but UC indicates the control sites.
Table 1 Results of statistical comparisons of changes in densities of treecreepers in experimental treatments in the two post-manipulation periods relative to changes in the undisturbed control over the same periods (@Y) Parameter
Est.a
S.D.
2.5%
97.5%
PPDb
Bayes factorc
@Y[0L, short] @Y[0L, longer] @Y[20L, short] @Y[20L, longer] @Y[40H, short] @Y[40H, longer] @Y[40L, short] @Y[40L, longer] @Y[60L, short] @Y[60L, longer] @Y[80L, short] @Y[80L, longer]
0.09 0.20 0.12 0.09 0.63 0.63 0.29 0.38 0.33 0.38 0.34 0.52
0.21 0.24 0.22 0.27 0.24 0.27 0.25 0.30 0.24 0.28 0.24 0.29
0.49 0.26 0.55 0.42 0.17 0.10 0.19 0.19 0.16 0.16 0.13 0.02
0.32 0.67 0.31 0.66 1.10 1.18 0.77 0.98 0.81 0.93 0.79 1.11
0.34 0.82 0.28 0.63 1.00 0.99 0.88 0.91 0.92 0.91 0.93 0.97
0.5 4.6 0.4 1.7 Inf. 99.0 7.3 10.1 11.5 10.1 13.3 32.3
a
Mean estimated value from the Bayesian modeling. PPD: posterior probability mass = amount of probability distribution >0. c Bayes factors: >12 indicates compelling evidence that differences are substantial; >3 indicates positive evidence that differences are substantial. b
4. Discussion The precise manipulations of habitat characteristics through alterations of fallen-timber loads allowed a clear demonstration that (1) the brown treecreepers respond to variation in this
habitat element and (2) loads 40 Mg/ha are more likely to be attractive to the treecreepers than lower densities. Previously published results provided strong evidence that the treecreepers preferred sites with such loads (Mac Nally et al., 2002a). Concerns were expressed in that paper that the changes in densities may have been transient and ephemeral re-arrangements of the birds from surrounding parts of the Gunbower Island forest. The latest results reported here provide greater confidence that the birds have a preference for the more heavily laden sites (40 Mg/ha). Two major issues need to be resolved following these confirmed, longer-term findings. The first is whether the changes in density have demographic consequences? For example, does the greater concentration of numbers apparently induced by higher wood-loads lead to: (1) greater foraging efficiency (Stewart et al., 2003), (2) reduced mortality (Stokes et al., 2004), and (3) more breeding attempts and greater success when attempts are made (Walters et al., 1999)? Foraging efficiency per se and mortality rates are difficult to measure, so breeding activity and success are more likely to be feasibly monitored and provide more direct links between changes in habitat preferences and demographic consequences. Detailed demographic studies are prohibitively difficult to do, especially when one seeks to draw inferences for a number of treatments (here seven) and replicates per treatment (here 4). However, Luck (2002) reported on non-experimental evidence that suggested that many attributes of habitat structure are related to fitness measures (e.g. male and fledgling survival, provisioning rate, group size) for a congener of the brown treecreeper, the rufous treecreeper Climacteris rufa, in Western Australia. Among the habitat correlates with fitness measures was density of hollow logs, which I regard as analogous to fallen timber measures considered here. However, breeding information has not been gathered for the Gunbower Island experimental sites for treecreepers or any other birds due to logistic limitations. Monitoring reproductive performance clearly is the next critical step in establishing the utility of different wood-loads to the birds. Is there any evidence at all for demographic consequences of different wood-loads in these sites? Reproduction has been monitored for a small (ca. 20–40 g) species of carnivorous marsupial, the yellow-footed antechinus Antechinus flavipes, in this same set of manipulated sites over the same period (Mac Nally and Horrocks, 2002), which was the reason for the additional research funding. Most of the young were produced in plots with 40 Mg/ha, with none at all in plots with 20 Mg/ha. Therefore, there clearly is an a priori reason to attempt to monitor breeding success in different treatments for the treecreeper. The species is a cooperative breeder, so densities need not necessarily reflect breeding pairs, which are many fewer than in monogamously coupling species (Noske, 1980, 1991). However, Noske (1991) showed that reproductive success was correlated with group size, so that if the increases reported here reflect size of reproductive units, then production of young may be expected to follow the reported changes in densities.
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These results seem compelling for the treecreeper favoring sites of heavier wood-loads than are currently available. The effects might be underestimated because breeding groups of brown treecreepers may range over larger areas than the 1 ha used. For example, Cooper et al. (2002) showed that group areas were 1–10 ha (mean 4.5 ha) in woodlands of New England, New South Wales, Australia. If plots were laden with 40 Mg/ha over areas larger than the 1 ha used, it is likely that the relative increases of birds using the higher-load plots would be even more exaggerated. Assuming that reproductive performance in treecreepers is linked to altered densities through different wood-loads, what are the implications for management? Restoring loads to pre-European-settlement (1788) levels clearly is infeasible logistically, physically and ethically. Full restoration of the 221,000 ha surveyed by Mac Nally et al. (2002b) would require 2.4 107 Mg, which is equivalent to ca. 600,000 mature (1 m diameter-at-breast-height) river red gum trees, or the amount of timber that could be obtained from clear-felling 115,000 ha of forest at current stocking levels; one cannot advocate this course of action. However, results reported here suggest that an approximate doubling of loads to ca. 40 Mg/ha (rather than a five-fold increase to ca. 120 Mg/ha) may be sufficient, which, if translated across the southern MDB, would be a more manageable ca. 4.5 106 Mg. Of course, spatial concentrations of relatively large areas of 40 Mg/ha loads may be enough to provide important increases in the viability of the treecreeper. The problem is one of habitat fragmentation, in which one is unable to restore very large tracts of native vegetation but need to cater for the minimum needs of species (e.g. Lambeck, 1997). The widespread loss of fallen timber may effectively make the existing forests highly fragmented for the brown treecreeper. The treecreepers appeared to respond strongly to the 40 Mg/ ha wood-loads consisting of tree crowns (Table 1). Does this mean that current harvesting practices, which involve leaving crowns after bole removal, usually for about 3 years, are advantageous for the treecreeper? What are more general implications for fallen timber management? While it seems likely that the treecreeper finds the crowns attractive, there are two reasons why one would not wish to depend on this current practice as a general rule. First, the crown remnants usually are harvested for firewood after 3 years. This was not done in the current study because the site was exempted from firewood collection over the duration of the study. Removal of crowns after a few years would disrupt any groups of treecreepers that might have settled on those sites. Second, it is unwise to manage habitat on a single-species basis. While the treecreeper seemed to ‘prefer’ the crowns, the yellow-footed antechinus eschewed crown sites almost to the same degree as denuded sites. For these reasons, it seems that loads 40 Mg/ha of logs and large branches are more likely to be a more generally sound management objective. One final question is whether proximity to other sites of high wood-loads is advantageous compared with more isolated plots? If clusters of more heavily laden sites function synergistically, in the manner or metapopulations of cooperatively
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breeding units (Opdam, 1991; Lindenmayer and Possingham, 1996; Wigley and Roberts, 1997), this may make restoration more feasible than widespread application of 40 Mg/ha across very extensive areas, which is unlikely politically and economically. This may be a way in which management of fallen timber for increasing recruitment of brown treecreepers may be achieved with a substantially lower investment in provision of fallen timber. Acknowledgments The current report was made possible by a generous grant (HSF 02-3) from the Hermon Slade Foundation (http:// www.hermonslade.org.au/background.html), for work on A. flavipes but for which additional work on birds and invertebrates was piggy-backed. The support of the Australian Research Council gratefully is acknowledged through Grant Nos. F19804210 and A19927168 for supporting the original 3year project. I thank Greg Horrocks, Andrew Bennett, Erica Fleishman, Sam Lake and Geoff Brown for contributing to parts of the work. Gary Luck and Hugh Ford provided important comments on the MS. The North-western Region of the Victorian Department of Natural Resources and Environment (Robert Price) was especially cooperative in conducting the manipulation and in providing protection from interference for the sites. This is contribution 85 from the Australian Centre for Biodiversity: Analysis, Policy and Management. References Baker, J., 1997. The decline, response to fire, status and management of the Eastern Bristlebird. Pac. Cons. Biol. 3, 235–243. Cooper, C.B., Walters, J.R., Ford, H., 2002. Effects of remnant size and connectivity on the response of brown treecreepers to habitat fragmentation. Emu 102, 249–256. Crabb, P., 1997. Murray-Darling Basin Resources. Murray-Darling Basin Commission, Canberra. Garnett, S.T., Crowley, G.M., 2000. The Action Plan for Australian Birds. Environment Australia, Canberra. Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D.B., 1995. Bayesian Data Analysis. Chapman and Hall, London. Harmon, M.E., Franklin, J.F., Swanson, F.J., Sollins, P., Gregory, S.V., Lattin, J.D., Anderson, N.H., Cline, S.P., Aumen, N.G., Sedell, J.R., Lienkaemper, G.W., Cromack Jr., K., Cummins, K.W., 1986. Ecology of coarse woody debris in temperate ecosystems. Adv. Ecol. Res. 15, 133–302. Harmon, M.E., Sexton, J., 1996. Guidelines for measurements of woody detritus in forest ecosystems. Rep. No. 20. US LTER Network Office, Seattle. Jaynes, E.T., 2003. Probability Theory: The Logic of Science. Cambridge University Press, New York. Kass, R.E., Raftery, A.E., 1995. Bayes factors. J. Am. Stat. Assoc. 90, 773– 795. Lambeck, R.J., 1997. Focal species: a multi-species umbrella for nature conservation. Cons. Biol. 11, 849–856. Lindenmayer, D.B., Possingham, H.P., 1996. Modelling the inter-relationships between habitat patchiness, dispersal capability and metapopulation persistence of the endangered species, leadbeaters possum, in south-eastern Australia. Landscape Ecol. 11, 79–105. Luck, G.W., 2002. Determining habitat quality for the cooperatively breeding rufous treecreeper, Climacteris rufa. Aust. Ecol. 27, 229–237. Mac Nally, R., 1994. Habitat-specific guild structure of forest birds in south-eastern Australia: a regional scale perspective. J. Anim. Ecol. 63, 988–1001.
160
R. Mac Nally / Forest Ecology and Management 229 (2006) 155–160
Mac Nally, R., 1997. Scaling artefacts in confinement experiments: a simulation model. Ecol. Model. 99, 229–245. Mac Nally, R., 2001. ‘Mesoscale’ experimental investigation of the dependence of riparian fauna on floodplain coarse woody debris. Environ. Manage. Restor. 2, 147–149. Mac Nally, R., Horrocks, G., 2002. Habitat change and restoration: responses of a floodplain forest-floor mammal species to manipulations of fallen timber in forests. Anim. Biodivers. Conserv. 1, 41–52. Mac Nally, R., Horrocks, G., Pettifer, L., 2002a. Experimental evidence for beneficial effects of fallen timber in forests. Ecol. Appl. 12, 1588– 1594. Mac Nally, R., Parkinson, A., Horrocks, G., Young, M., 2002b. Current loads of coarse woody debris on south-eastern Australian floodplains: evaluation of change and implications for restoration. Restor. Ecol. 10, 627–635. Mac Nally, R., Parkinson, A., 2005. Fallen timber loads on southern MurrayDarling basin floodplains: history, dynamics and the current state in Barmah-Millewa. Proc. R. Soc. Vict. 117, 97–110. Noske, R.A., 1980. Cooperative breeding by treecreepers. EMU 80, 35–36. Noske, R.A., 1991. A demographic comparison of cooperatively and noncooperative treecreepers (Climacteridae). EMU 91, 73–86. Opdam, P., 1991. Metapopulation theory and habitat fragmentation: a review of holarctic breeding bird studies. Landscape Ecol. 5, 93–106.
Robinson, R., 1997. Dynamics of coarse woody debris in floodplain forests: impact of forest management and flood frequency. B.Sc. (Hons). Charles Sturt University. Spiegelhalter, D., Thomas, A., Best, N., 2003. WinBUGS Version 1.4. Bayesian Inference Using Gibbs Sampling. MRC Biostatistics Unit, Institute for Public Health, Cambridge, UK. Stewart, K.M., Fulbright, T.E., Drawe, D.L., Bowyer, R.T., 2003. Sexual segregation in white-tailed deer: responses to habitat manipulations. Wildlife Soc. Bull. 31, 1210–1217. Stokes, V.L., Pech, R.P., Banks, P.B., Arthur, A.D., 2004. Foraging behaviour and habitat use by Antechinus flavipes and Sminthopsis murina (Marsupialia: Dasyuridae) in response to predation risk in eucalypt woodland. Biol. Conserv. 117, 331–342. Thompson, J.N., Reichman, O.J., Morin, P.J., Polis, G.A., Power, M.E., Sterner, R.W., Couch, C.A., Gough, L., Holt, R., Hooper, D.U., Keesing, F., Lovell, C.R., Milne, M.C., Molles, B.T., Roberts, D.W., Strauss, S.Y., 2001. Frontiers of ecology. BioScience 51, 15–24. Walters, J.R., Ford, H.A., Cooper, C.B., 1999. The ecological basis of sensitivity of brown treecreepers to habitat fragmentation: a preliminary assessment. Biol. Conserv. 90, 13–20. Wigley, T., Roberts, T., 1997. Landscape-level effects of forest management on faunal diversity in bottomland hardwoods. For. Ecol. Manage. 90, 141–154.
Longer-term response to experimental manipulation of fallen timber on forest floors of floodplain forest in south-eastern Australia Ralph Mac Nally * Australian Centre for Biodiversity: Analysis, Policy and Management, School of Biological Sciences, Monash University, Melbourne 3800, Australia Received 8 February 2006; received in revised form 27 March 2006; accepted 27 March 2006
Abstract There often are substantial accumulations of fallen timber (logs, large boughs) in many woodlands and forests around the world. However, fallen timber has become a target for removal for use as fuel or for management actions, such as fuel-reduction burning. Many silvicultural practices, such as fast harvesting rotations, coppicing and debris burning prior to re-sowing/re-planting, lead to much reduced fallen-timber loads. Many studies show the ecologically important role fallen timber plays, so its removal is likely to have adverse ecological outcomes. It has previously been shown that a specialized forager on fallen timber, the brown treecreeper Climacteris picumnus, responded strongly over a shortterm (20 mo) to a meso-scale (34 ha) manipulation of fallen-timber loads in river red gum Eucalyptus camaldulensis forest in northern Victoria, Australia [Mac Nally, R., Horrocks, G., Pettifer, L., 2002a. Experimental evidence for beneficial effects of fallen timber in forests. Ecol. Appl. 12, 1588–1594]. There were substantially more birds in all treatments in which loads were increased to 40 Mg/ha or more, elevated from averages of ca. 20 Mg/ha across the southern Murray-Darling Basin. Sites were revisited 3 years after the manipulation was conducted and I show here that the changes in density have been sustained. These results suggest that increased fallen-timber loads 40 Mg/ha are preferred by the vulnerable treecreeper, and that the bird’s responses reported previously were not transient. These elevated densities may translate into increased reproductive success of the treecreepers because larger groupings in this and related cooperative breeders produce more young. I conclude by outlining options for management of fallen timber to provide greater chances of viability for the species. # 2006 Elsevier B.V. All rights reserved. Keywords: Bayesian models; Brown treecreeper; Eucalyptus camaldulensis; Habitat manipulations; River red gum; Woody debris; WinBUGS
1. Introduction Many human activities directly or incidentally alter habitat characteristics, and hence quality, for organisms. Identifying and ameliorating these changes underlie much of the work done in conservation biology and wildlife management (Baker, 1997; Stewart et al., 2003). Definitive demonstrations of habitat-structural impacts on species occurrence or demography require field experiments at appropriate spatial and temporal scales (Mac Nally, 1997). Habitat manipulations have been used relatively infrequently compared with more indirect methods, such as statistical modeling (Mac Nally et al., 2002a). This probably reflects prohibitive workloads in constructing large, replicated experiments and difficulties in
* Tel.: +61 3 9905 5642; fax: +61 3 9905 5613. E-mail address: [email protected]. 0378-1127/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2006.03.024
maintaining manipulated habitats over periods long enough to demonstrate ecologically important effects. There are relatively few habitat elements that can be precisely manipulated and also are demonstrably critical for biota. Fallen timber – logs and large boughs – is a habitat element that has many characteristics that make it attractive for manipulative experiments. First, it has been systematically removed from many forests and woodlands around the world, to the detriment of much of the forest-floor dwelling biota (Harmon et al., 1986). Therefore, it is both a critical element from an ecological standpoint but also one that has experienced much modification. Second, few habitat elements are as suited to experimental manipulation as fallen timber because of the precision with which loads (expressed in Mg/ha) can be altered and redistributed. These two facets led to an exploration of how anthropogenically imposed variations in fallen-timber loads affect species’ occurrence and densities in forests. The problem of fallen timber removal is very marked in the forests or the floodplains of south-eastern Australia. Timber on
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the major floodplains of the southern Murray-Darling Basin (MDB) has been pillaged systematically for almost 200 years, first to sustain the demands of river paddle-steamers, then to provide fuel for the major cities and towns of Victoria and, more recently, to yield firewood, building materials and train-track stays (Mac Nally and Parkinson, 2005). Much of the extant forested area is intensively managed for fast-turnover timber production, which means that the age-class structure of trees is deliberately kept youthful, with few large, old trees. The latter are the primary generators of fallen timber through limbabscission and tree-death and collapse. The outcome has been a likely reduction in fallen-timber loads by about 85%, to ca. 19 Mg/ha across the southern MDB (Mac Nally et al., 2002b). In 2002, short-term responses were reported for a vulnerable species of bird (in New South Wales and Victoria) that specializes in foraging on fallen timber (Mac Nally, 1994), the brown treecreeper Climacteris picumnus, to a meso-scale manipulation of fallen timber in a floodplain forest of northcentral Victoria, Australia (Mac Nally et al., 2002a). By mesoscale I mean that the experiment was conducted over 34 1-ha plots; by short-term I mean that responses were monitored for 20 mo following manipulation. One of the primary reasons for the species’ parlous conservation status is loss of fallen timber (Garnett and Crowley, 2000). The results were reasonably conclusive: treecreeper densities were substantially greater in all treatments in which wood-loads exceeded 40 Mg/ha. The experimental system is relatively large-scale (tens of ha) and appropriate to the scales of movement of the treecreeper, which is a relatively sedentary, cooperatively breeding species (Noske, 1980, 1991) with a group home-range of ca. 4.5 ha (Cooper et al., 2002). Many ecological studies, and especially experiments, often involve a mismatch between spatial and temporal scales (Thompson et al., 2001). That is, large spatialscale experiments often are conducted for relatively short periods of time and sometimes vice versa. Although not originally intended within the project plan, additional funding was secured and I report here on new data that extends the monitoring period to 35–40 mo following the manipulation. I show that the initial results have been sustained over a longer time-frame (to >3.5 years), providing greater confidence that the birds recognize and respond to variation in fallen-timber load. The implications of this sustained response are discussed, as is the major remaining problems relating to the management of fallen timber in these floodplain forests.
2. Methods 2.1. Study area The experiment was conducted on Gunbower Island (358420 23S 1448120 13E), which lies between the Murray River and Gunbower Creek near Cohuna, in north-central Victoria, Australia. The island used to flood almost every year, but with more extreme water extractions and flow regulation, flooding now is much rarer (Crabb, 1997). Gunbower Island is intensively exploited for firewood and posts and railway-stays.
2.2. Experimental design Thirty-four 1-ha plots were marked out. Wood-load measurements (average 27 Mg/ha) were conducted prior to manipulation. This consisted of measuring all pieces of fallen timber within the 1 ha plot, taking end diameters and lengths of pieces and computing volumes. These were translated into mass by using the mean density of 0.6 Mg/m3 (Robinson, 1997). The 34 plots were randomly allocated to seven treatments prior to moving the wood, but with some constraints on the random distribution. As much as possible, sites allocated to different treatments were interspersed to reduce possible spatial effects. Five treatments corresponded to loads of 0, 20, 40, 60 and 80 Mg/ha (designated 0, 20, 40, 60 and 80L) of aged fallen wood (10 cm diameter). River red gum is a highly resilient timber that decays slowly (Robinson, 1997), so that most of the fallen timber was of Decay Class I or II (i.e. bark largely intact, structural integrity mostly solid, larger twigs present; Harmon and Sexton, 1996). Following four rounds of pre-manipulation bird surveys beginning in May 1999 (see below), timber was moved in late March 2000. On all of these plots, fallen timber already on the plots was disturbed so that all timber was dislodged from previous footings. There was an undisturbed control treatment (designated UC) in which no equipment or persons traversed plots during wood moving. The other treatment was the imposition of 40 Mg/ha of tree crowns onto plots (40H). The 40H treatment emulates current silvicultural practices, which involve the felling of a river red gum tree, removal of the bole for timber, and the deposition of the crown for up to 3 years before harvesting the main branches for firewood. Thus, new fallen timber in these production forests often is in the form of crowns. Existing timber was removed from these plots and fresh crowns deposited. There were four replicate plots for each treatment, apart from 0L, for which there were six. In all manipulated plots, timber was evenly distributed over the whole ha (100 m 100 m). The middle 50 m 50 m part of each plot was marked with metal stakes and formed the focus for bird surveys. One thousand Mg of timber was repositioned during this operation, requiring six persons for 8 days, hydraulic tandem trailers, a bulldozer and a log-harvesting machine (Mac Nally, 2001). 2.3. Bird survey schedule and method There were 18 rounds of surveys, each consisting of a 7-day period, in the following months: May, July and October 1999, January, May, July and September 2000, January, March, April, July, September and November 2001, January 2002, February, April, May and July 2003. The first four rounds were prior to wood-load manipulations, while the latter 14 followed the experimental changes. The surveys were divided into three periods. The first is the pre-manipulation period, consisting of four surveys. The second period is that consisting of the next 10 surveys over 20 mo, which is regarded as the short-term response period and has been reported (Mac Nally et al., 2002a). Another four
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surveys were completed in 2003, the longer-term response period, with a gap of 13 mo between the last of the secondperiod surveys and the first of this series. These four surveys were conducted 35–40 mo after the manipulations were undertaken. Surveys involved the observer (the same person in all 18 survey rounds) sitting at one corner of the interior square for 45 min and recording all birds active within the half of the square closest to the observer (a right-triangular area of 0.125 ha). While activities of birds outside this small central part of plots were recorded, these data are not considered here. Surveys were conducted either between dawn and 1100 Australian Eastern Time (AET) or from 1400 AET to 1 h before sunset. 2.4. Analyses The data consisted of an array of 30 sites by 18 survey periods. I used a Poisson model to analyse these data (Gelman et al., 1995). Most of the data were small, non-negative values (<5), so the use of a counts distribution like the Poisson seemed reasonable. The model is: Y jðmÞkðnÞ Poissonðm jðmÞkðnÞ Þ; logðm jðmÞkðnÞ Þ ¼ a jðmÞkðn¼1Þ þ a jðmÞkðn 6¼ 1Þ :
(1)
The Ys are assumed to be Poisson-distributed with means m and are the observed numbers in plot j in survey k, with the j(m) indicating that site j belongs to treatment m (viz., 0L, . . ., UC). The k(n) subscript assigns survey k to period n (n = 1 = premanipulation, n = 2 = short-term period, n = 3 = longer-term period). The as for n 2 are multiplicative constants and, when exponentiated, indicate the degree to which numbers of treecreepers increase or decrease relative to the values for the given treatment before manipulation (i.e. n = 1). From these coefficients, one can estimate the average change in numbers of treecreepers in periods 2 and 3 relative to period 1 and relate these to changes in the UC-treatment sites over the same comparisons: DY jðmÞkðn 6¼ 1Þ ¼ ðexpða jðmÞkðn 6¼ 1Þ Þ 1Þ expða jðmÞkðn¼1Þ Þ; @Y jðmÞkðn 6¼ 1Þ ¼ DY jðmÞkðn 6¼ 1Þ DY jðm¼UCÞkðn 6¼ 1Þ :
(2)
The DYs are the estimated net increases in numbers of treecreepers in periods 2 and 3 relative to period 1 for each treatment, while the @Ys are these differences relative to the changes that occurred in the UC-treatment sites over the same periods. Therefore, the @Ys provide changes in numbers corrected for changes in numbers recorded in the control sites. I used the WinBUGS Bayesian analysis software (publicdomain, version 1.4, Spiegelhalter et al., 2003). Noninformative normal priors were used for the a coefficients (0 means, 106 precisions). In all analyses, means and medians of posterior distributions of parameters were similar, indicating symmetric probability distributions. Burns-in of 10,000 and samples of 20,000 were used.
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The outputs of WinBUGS modeling are posterior probability distributions (PPDs) of model parameters and any functions thereof. Therefore, I computed PPDs for the as and @Ys (Eqs. (1) and (2)) and report upon the latter here. One can also compute how much of the PPD for a parameter exceeds 0. For a non-informative prior, where I had no expectation that a parameter would differ from 0, the expected value of PPD is 0.5. The degree to which PPD differs from 0.5 is a measure of the probability that a parameter’s value differs from zero either negatively (<0.5) or positively (>0.5). Also for a noninformative prior, in which the ratio of posterior probabilities for the parameter is unity, the Bayes factor (BF), the ratio of PPD/(1 PPD) in this instance, is a measure of the evidence in favor of the parameter differing from 0 (Jaynes, 2003). Kass and Raftery (1995) argued that BFs exceeding 12 are strong evidence supporting one hypothesis over another (here that the parameter differs from 0), and BFs between 3 and 12 signal positive evidence. BFs < 3 are hardly worth reporting. For negative coefficients, values of PPD will be <0.5 so that PPD/ (1 PPD) < 1. Therefore, one uses the inverse guideline measures of Kass and Raftery (1995) for inferring differences from 0 (i.e. 1/12, 1/3, etc.). This means that PPD < 0.25 and > 0.75 correspond to BFs < 1/3 and > 3, respectively, while PPD > 0.92 or < 0.08 represent BFs > 12 or < 1/12, respectively. 3. Results Total numbers of treecreepers fluctuated substantially through time across Gunbower Island (Fig. 1a). There was substantial variation in densities of treecreepers among treatments before fallen-timber manipulations were done (Fig. 1b). By happenstance, the densities were extremely low in the four sites randomly allocated to the 40H treatment but much greater in the sites randomly allocated to the 20L treatment (Fig. 1b). By inspection, it seems that there were dramatic increases in mean densities for period 2 in treatments 40H, 40L, 60L and 80L, as reported by Mac Nally et al. (2002a). Generally speaking, these increases appear to have been maintained in period 3, at least 3 years after the timber was manipulated (Fig. 1b). Results in Table 1 take into account simultaneous changes in sites of the control treatment (UC), which the differences @Ys (Eq. (2)) were designed to do. These values are changes in density in periods 2 and 3 from to period 1 (pre-manipulation), but made relative to changes in the UC-treatment sites over the same comparisons. For example, in 40L-treatment sites, densities increased by 0.29 birds/(0.125 ha) between periods 2 and 1 more than the density change in the UC sites between periods 2 and 1 (Table 1). Inspection of values for the @Ys suggests that densities increased more than in the control sites in all treatments with wood-loads of 40 Mg/ha, and these increases were sustained in the longer term (Table 1). Increases (in excess of changes in UC sites) typically were 0.3 birds/ (0.125 ha), and as much as 0.63 (Table 1). There was little change in the 20L sites, but a suggestion of a possible weak increase in the longer term in denuded sites (BF = 4.6).
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Fig. 1. (a) Densities of treecreepers summed for all 30 sites (hence total survey area of 4.75 ha) in months elapsed since May 1999. Periods are: pre-manipulation (solid circles), short-term (open squares) and longer-term (closed squares). (b) Mean (+S.E.) of brown treecreepers (birds/(0.125 ha)) for seven experimental treatments, described in text. Three periods are: pre-manipulation (open bars), short-term (coarse hatch) and longer-term (fine hatch). Treatment codes are described in text, but UC indicates the control sites.
Table 1 Results of statistical comparisons of changes in densities of treecreepers in experimental treatments in the two post-manipulation periods relative to changes in the undisturbed control over the same periods (@Y) Parameter
Est.a
S.D.
2.5%
97.5%
PPDb
Bayes factorc
@Y[0L, short] @Y[0L, longer] @Y[20L, short] @Y[20L, longer] @Y[40H, short] @Y[40H, longer] @Y[40L, short] @Y[40L, longer] @Y[60L, short] @Y[60L, longer] @Y[80L, short] @Y[80L, longer]
0.09 0.20 0.12 0.09 0.63 0.63 0.29 0.38 0.33 0.38 0.34 0.52
0.21 0.24 0.22 0.27 0.24 0.27 0.25 0.30 0.24 0.28 0.24 0.29
0.49 0.26 0.55 0.42 0.17 0.10 0.19 0.19 0.16 0.16 0.13 0.02
0.32 0.67 0.31 0.66 1.10 1.18 0.77 0.98 0.81 0.93 0.79 1.11
0.34 0.82 0.28 0.63 1.00 0.99 0.88 0.91 0.92 0.91 0.93 0.97
0.5 4.6 0.4 1.7 Inf. 99.0 7.3 10.1 11.5 10.1 13.3 32.3
a
Mean estimated value from the Bayesian modeling. PPD: posterior probability mass = amount of probability distribution >0. c Bayes factors: >12 indicates compelling evidence that differences are substantial; >3 indicates positive evidence that differences are substantial. b
4. Discussion The precise manipulations of habitat characteristics through alterations of fallen-timber loads allowed a clear demonstration that (1) the brown treecreepers respond to variation in this
habitat element and (2) loads 40 Mg/ha are more likely to be attractive to the treecreepers than lower densities. Previously published results provided strong evidence that the treecreepers preferred sites with such loads (Mac Nally et al., 2002a). Concerns were expressed in that paper that the changes in densities may have been transient and ephemeral re-arrangements of the birds from surrounding parts of the Gunbower Island forest. The latest results reported here provide greater confidence that the birds have a preference for the more heavily laden sites (40 Mg/ha). Two major issues need to be resolved following these confirmed, longer-term findings. The first is whether the changes in density have demographic consequences? For example, does the greater concentration of numbers apparently induced by higher wood-loads lead to: (1) greater foraging efficiency (Stewart et al., 2003), (2) reduced mortality (Stokes et al., 2004), and (3) more breeding attempts and greater success when attempts are made (Walters et al., 1999)? Foraging efficiency per se and mortality rates are difficult to measure, so breeding activity and success are more likely to be feasibly monitored and provide more direct links between changes in habitat preferences and demographic consequences. Detailed demographic studies are prohibitively difficult to do, especially when one seeks to draw inferences for a number of treatments (here seven) and replicates per treatment (here 4). However, Luck (2002) reported on non-experimental evidence that suggested that many attributes of habitat structure are related to fitness measures (e.g. male and fledgling survival, provisioning rate, group size) for a congener of the brown treecreeper, the rufous treecreeper Climacteris rufa, in Western Australia. Among the habitat correlates with fitness measures was density of hollow logs, which I regard as analogous to fallen timber measures considered here. However, breeding information has not been gathered for the Gunbower Island experimental sites for treecreepers or any other birds due to logistic limitations. Monitoring reproductive performance clearly is the next critical step in establishing the utility of different wood-loads to the birds. Is there any evidence at all for demographic consequences of different wood-loads in these sites? Reproduction has been monitored for a small (ca. 20–40 g) species of carnivorous marsupial, the yellow-footed antechinus Antechinus flavipes, in this same set of manipulated sites over the same period (Mac Nally and Horrocks, 2002), which was the reason for the additional research funding. Most of the young were produced in plots with 40 Mg/ha, with none at all in plots with 20 Mg/ha. Therefore, there clearly is an a priori reason to attempt to monitor breeding success in different treatments for the treecreeper. The species is a cooperative breeder, so densities need not necessarily reflect breeding pairs, which are many fewer than in monogamously coupling species (Noske, 1980, 1991). However, Noske (1991) showed that reproductive success was correlated with group size, so that if the increases reported here reflect size of reproductive units, then production of young may be expected to follow the reported changes in densities.
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These results seem compelling for the treecreeper favoring sites of heavier wood-loads than are currently available. The effects might be underestimated because breeding groups of brown treecreepers may range over larger areas than the 1 ha used. For example, Cooper et al. (2002) showed that group areas were 1–10 ha (mean 4.5 ha) in woodlands of New England, New South Wales, Australia. If plots were laden with 40 Mg/ha over areas larger than the 1 ha used, it is likely that the relative increases of birds using the higher-load plots would be even more exaggerated. Assuming that reproductive performance in treecreepers is linked to altered densities through different wood-loads, what are the implications for management? Restoring loads to pre-European-settlement (1788) levels clearly is infeasible logistically, physically and ethically. Full restoration of the 221,000 ha surveyed by Mac Nally et al. (2002b) would require 2.4 107 Mg, which is equivalent to ca. 600,000 mature (1 m diameter-at-breast-height) river red gum trees, or the amount of timber that could be obtained from clear-felling 115,000 ha of forest at current stocking levels; one cannot advocate this course of action. However, results reported here suggest that an approximate doubling of loads to ca. 40 Mg/ha (rather than a five-fold increase to ca. 120 Mg/ha) may be sufficient, which, if translated across the southern MDB, would be a more manageable ca. 4.5 106 Mg. Of course, spatial concentrations of relatively large areas of 40 Mg/ha loads may be enough to provide important increases in the viability of the treecreeper. The problem is one of habitat fragmentation, in which one is unable to restore very large tracts of native vegetation but need to cater for the minimum needs of species (e.g. Lambeck, 1997). The widespread loss of fallen timber may effectively make the existing forests highly fragmented for the brown treecreeper. The treecreepers appeared to respond strongly to the 40 Mg/ ha wood-loads consisting of tree crowns (Table 1). Does this mean that current harvesting practices, which involve leaving crowns after bole removal, usually for about 3 years, are advantageous for the treecreeper? What are more general implications for fallen timber management? While it seems likely that the treecreeper finds the crowns attractive, there are two reasons why one would not wish to depend on this current practice as a general rule. First, the crown remnants usually are harvested for firewood after 3 years. This was not done in the current study because the site was exempted from firewood collection over the duration of the study. Removal of crowns after a few years would disrupt any groups of treecreepers that might have settled on those sites. Second, it is unwise to manage habitat on a single-species basis. While the treecreeper seemed to ‘prefer’ the crowns, the yellow-footed antechinus eschewed crown sites almost to the same degree as denuded sites. For these reasons, it seems that loads 40 Mg/ha of logs and large branches are more likely to be a more generally sound management objective. One final question is whether proximity to other sites of high wood-loads is advantageous compared with more isolated plots? If clusters of more heavily laden sites function synergistically, in the manner or metapopulations of cooperatively
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breeding units (Opdam, 1991; Lindenmayer and Possingham, 1996; Wigley and Roberts, 1997), this may make restoration more feasible than widespread application of 40 Mg/ha across very extensive areas, which is unlikely politically and economically. This may be a way in which management of fallen timber for increasing recruitment of brown treecreepers may be achieved with a substantially lower investment in provision of fallen timber. Acknowledgments The current report was made possible by a generous grant (HSF 02-3) from the Hermon Slade Foundation (http:// www.hermonslade.org.au/background.html), for work on A. flavipes but for which additional work on birds and invertebrates was piggy-backed. The support of the Australian Research Council gratefully is acknowledged through Grant Nos. F19804210 and A19927168 for supporting the original 3year project. I thank Greg Horrocks, Andrew Bennett, Erica Fleishman, Sam Lake and Geoff Brown for contributing to parts of the work. Gary Luck and Hugh Ford provided important comments on the MS. The North-western Region of the Victorian Department of Natural Resources and Environment (Robert Price) was especially cooperative in conducting the manipulation and in providing protection from interference for the sites. This is contribution 85 from the Australian Centre for Biodiversity: Analysis, Policy and Management. References Baker, J., 1997. The decline, response to fire, status and management of the Eastern Bristlebird. Pac. Cons. Biol. 3, 235–243. Cooper, C.B., Walters, J.R., Ford, H., 2002. Effects of remnant size and connectivity on the response of brown treecreepers to habitat fragmentation. Emu 102, 249–256. Crabb, P., 1997. Murray-Darling Basin Resources. Murray-Darling Basin Commission, Canberra. Garnett, S.T., Crowley, G.M., 2000. The Action Plan for Australian Birds. Environment Australia, Canberra. Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D.B., 1995. Bayesian Data Analysis. Chapman and Hall, London. Harmon, M.E., Franklin, J.F., Swanson, F.J., Sollins, P., Gregory, S.V., Lattin, J.D., Anderson, N.H., Cline, S.P., Aumen, N.G., Sedell, J.R., Lienkaemper, G.W., Cromack Jr., K., Cummins, K.W., 1986. Ecology of coarse woody debris in temperate ecosystems. Adv. Ecol. Res. 15, 133–302. Harmon, M.E., Sexton, J., 1996. Guidelines for measurements of woody detritus in forest ecosystems. Rep. No. 20. US LTER Network Office, Seattle. Jaynes, E.T., 2003. Probability Theory: The Logic of Science. Cambridge University Press, New York. Kass, R.E., Raftery, A.E., 1995. Bayes factors. J. Am. Stat. Assoc. 90, 773– 795. Lambeck, R.J., 1997. Focal species: a multi-species umbrella for nature conservation. Cons. Biol. 11, 849–856. Lindenmayer, D.B., Possingham, H.P., 1996. Modelling the inter-relationships between habitat patchiness, dispersal capability and metapopulation persistence of the endangered species, leadbeaters possum, in south-eastern Australia. Landscape Ecol. 11, 79–105. Luck, G.W., 2002. Determining habitat quality for the cooperatively breeding rufous treecreeper, Climacteris rufa. Aust. Ecol. 27, 229–237. Mac Nally, R., 1994. Habitat-specific guild structure of forest birds in south-eastern Australia: a regional scale perspective. J. Anim. Ecol. 63, 988–1001.
160
R. Mac Nally / Forest Ecology and Management 229 (2006) 155–160
Mac Nally, R., 1997. Scaling artefacts in confinement experiments: a simulation model. Ecol. Model. 99, 229–245. Mac Nally, R., 2001. ‘Mesoscale’ experimental investigation of the dependence of riparian fauna on floodplain coarse woody debris. Environ. Manage. Restor. 2, 147–149. Mac Nally, R., Horrocks, G., 2002. Habitat change and restoration: responses of a floodplain forest-floor mammal species to manipulations of fallen timber in forests. Anim. Biodivers. Conserv. 1, 41–52. Mac Nally, R., Horrocks, G., Pettifer, L., 2002a. Experimental evidence for beneficial effects of fallen timber in forests. Ecol. Appl. 12, 1588– 1594. Mac Nally, R., Parkinson, A., Horrocks, G., Young, M., 2002b. Current loads of coarse woody debris on south-eastern Australian floodplains: evaluation of change and implications for restoration. Restor. Ecol. 10, 627–635. Mac Nally, R., Parkinson, A., 2005. Fallen timber loads on southern MurrayDarling basin floodplains: history, dynamics and the current state in Barmah-Millewa. Proc. R. Soc. Vict. 117, 97–110. Noske, R.A., 1980. Cooperative breeding by treecreepers. EMU 80, 35–36. Noske, R.A., 1991. A demographic comparison of cooperatively and noncooperative treecreepers (Climacteridae). EMU 91, 73–86. Opdam, P., 1991. Metapopulation theory and habitat fragmentation: a review of holarctic breeding bird studies. Landscape Ecol. 5, 93–106.
Robinson, R., 1997. Dynamics of coarse woody debris in floodplain forests: impact of forest management and flood frequency. B.Sc. (Hons). Charles Sturt University. Spiegelhalter, D., Thomas, A., Best, N., 2003. WinBUGS Version 1.4. Bayesian Inference Using Gibbs Sampling. MRC Biostatistics Unit, Institute for Public Health, Cambridge, UK. Stewart, K.M., Fulbright, T.E., Drawe, D.L., Bowyer, R.T., 2003. Sexual segregation in white-tailed deer: responses to habitat manipulations. Wildlife Soc. Bull. 31, 1210–1217. Stokes, V.L., Pech, R.P., Banks, P.B., Arthur, A.D., 2004. Foraging behaviour and habitat use by Antechinus flavipes and Sminthopsis murina (Marsupialia: Dasyuridae) in response to predation risk in eucalypt woodland. Biol. Conserv. 117, 331–342. Thompson, J.N., Reichman, O.J., Morin, P.J., Polis, G.A., Power, M.E., Sterner, R.W., Couch, C.A., Gough, L., Holt, R., Hooper, D.U., Keesing, F., Lovell, C.R., Milne, M.C., Molles, B.T., Roberts, D.W., Strauss, S.Y., 2001. Frontiers of ecology. BioScience 51, 15–24. Walters, J.R., Ford, H.A., Cooper, C.B., 1999. The ecological basis of sensitivity of brown treecreepers to habitat fragmentation: a preliminary assessment. Biol. Conserv. 90, 13–20. Wigley, T., Roberts, T., 1997. Landscape-level effects of forest management on faunal diversity in bottomland hardwoods. For. Ecol. Manage. 90, 141–154.