Factors influencing survival and long-term population viability of New Zealand long-tailed bats (Chalinolobus tuberculatus): Implications for conservation

BIOLOGICAL CONSERVATION

Biological Conservation 126 (2005) 175–185 www.elsevier.com/locate/biocon

Factors influencing survival and long-term population viability of New Zealand long-tailed bats (Chalinolobus tuberculatus): Implications for conservation Moira A. Pryde a, Colin F.J. OÕDonnell a

a,*

, Richard J. Barker

b

Southern Regional Science Centre, Department of Conservation, P.O. Box 13049, Christchurch, New Zealand b Department of Mathematics and Statistics, University of Otago, P.O. Box 56, Dunedin, New Zealand Received 18 October 2004 Available online 14 July 2005

Abstract A population viability analysis is important for the management of endangered populations and requires the estimation of survival parameters. The long-tailed bat (Chalinolobus tuberculatus) is one of only two native terrestrial mammals currently found in New Zealand and is classed as vulnerable. Its viability in temperate beech (Nothofagus) forest, Eglinton Valley, Fiordland, New Zealand was estimated using mark-recapture data collected between 1993 and 2003 using the Program MARK. Survival was estimated based on a total of 5286 captures representing 1026 individuals. Overall annual survival varied between 0.34 and 0.83 but varied significantly among three sub-populations and with sex and age. Females generally had a higher survival rate compared to males; and adults had higher survival relative to juveniles. Survival of all bats was lower in years when the number of introduced mammalian predators was high and when the winter temperature was warmer than average. High numbers of introduced predators occurred during three of the 10 years in the study. Climate change may mean that the conditions that promote high predator numbers may occur more frequently. A preliminary population viability analysis using a projection matrix on the overall adult female population showed an average 5% decline per year (k = 0.95). Increased predator control targeting a range of predators is required in years when their numbers are high in order to halt the decline of this population of long-tailed bats. Population estimates using minimum number alive estimates supported the population estimates derived from Program MARK and a population viability analysis using matrices. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Bats; Chalinolobus; Chiroptera; Mark-recapture; Population viability analysis; Matrix models

1. Introduction The survival rate of a species is one of the key parameters for determining the long-term viability of populations (White et al., 2002). Analysis of the factors influencing survival and population viability are therefore important tools for informed decision-making and improving the management of populations of threatened species (Morris and Doak, 2002; Ralls et al., 2002). *

Corresponding author. Tel.: +64 33713730. E-mail address: [email protected] (C.F.J. OÕDonnell).

0006-3207/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2005.05.006

Monitoring survival of cryptic species such as bats is particularly difficult because only a small portion of the population may be detected in a survey and individuals are difficult to distinguish due to rarity, patchy distribution, their nocturnal behaviour and the difficulties in capturing and counting them (OÕShea and Bogan, 2003). Consequently, while some studies mention the survival rates of different species of bats (Tuttle and Stevenson, 1982), few have reported reliable long-term estimates of survival or the variation in survival between individual species or within populations (Vardon and Tidemann, 2000; Hoyle et al., 2001; Sendor and Simon,

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2003). Increasing our understanding of factors influencing survival is important because 51% of the Microchiropteran bats are either critically endangered, endangered, data deficient, vulnerable or near threatened (Hutson et al., 2001). Advances in technology in the early 1980s has made the study of small Microchiropteran bats easier. Increased availability of inexpensive ultrasonic bat detectors, small radio-transmitters, specialised harp traps and miniaturised infra-red cameras has led to improved knowledge about behaviour, habitat use and distribution (OÕDonnell and Sedgeley, 1994; OÕDonnell, 2001). Likewise, methods for robust analysis of survival and population demography along with availability of appropriate computer software has made analysis of survival more achievable (Seber, 1982; White and Burnham, 1999; White et al., 2002). Bats are the only native terrestrial mammals found in New Zealand. The long-tailed bat (Chalinolobus tuberculatus, Forster 1844, Vespertilionidae) is one of two extant bat species. It is an endemic species belonging to an Australasian genus, which includes six other species, but it evolved in isolation in New Zealand for at least a million years (Daniel, 1990). Long-tailed bats were common throughout New Zealand in the 1800s when Europeans arrived, but by 1900–1930 they were becoming scarce in many districts (OÕDonnell, 2000a). The taxon is classed as Vulnerable by the IUCN and Nationally Endangered by the Department of Conservation in New Zealand (Hutson et al., 2001; Hitchmough, 2002). Management includes a recovery plan with goals of conserving all sub-species of bat throughout the present range and establishing new populations where possible (Molloy, 1995). It is believed that extinction of the species is likely if nothing is done to reverse current perceived population declines (OÕDonnell, 2000a). Recent studies suggest a number of causes of decline, including loss of foraging and roosting habitats through clearance and logging of lowland forests, predation by introduced mammals, birds and wasps, and human disturbance at roost sites (OÕDonnell, 2000a). There are still cases of trees containing roosts being felled for firewood and timber production. However, declines have also been documented in areas with little forest modification, suggesting that other causes, specifically introduced predators, are to blame (OÕDonnell, 2000a). Globally, introduced predators have had a significant impact on the survival of native species (Clavero and Garcia-Berthou, 2005). For example, at least 31% of the extinctions of 104 species of birds on oceanic islands have been ascribed to introduced predators (Groombridge, 1992). In New Zealand, the introduction of 65 non-native mammal species over the last 1000 years has had a catastrophic effect on native fauna (King, 1990). Declines in populations of many hole-nesting forest birds follow periodic irruption of populations of

stoats (Mustela erminea) and ship rats (Rattus rattus) in beech (Nothofagus) forests (Elliott et al., 1996; OÕDonnell et al., 1996; Wilson et al., 1998; Dilks et al., 2003; Moorhouse et al., 2003). Long-tailed bats occupy the same forests and use similar cavities, so are likely at risk from the same predators (Elliott et al., 1996; Sedgeley and OÕDonnell, 1999a). The objectives of this study were to (a) determine factors influencing the survival rate of long-tailed bats in the Eglinton Valley, a beech-dominated valley in Fiordland, New Zealand, (b) estimate the rate of change of the population, and (c) make recommendations regarding which factors should be managed to improve the survival of the species. Our study focused on beech forests where predator numbers fluctuate in relation to food availability (King, 1983). The beech trees flower and seed heavily (mast) at irregular intervals, usually 3–5 years (Wardle, 1984; Schauber et al., 2002). Mast years increase food supply for introduced mice (Mus musculus) and rats, potentially causing an irruption in their populations. This, is turn, results in prolific breeding by stoats, with up to 13 young raised per female in years when rodents are abundant (King, 1990). Understanding the effects of this system on the survival of native species such as bats is essential for improving the long-term management of threatened native species in these forests. Our hypothesis was that survival rates of long-tailed bats would vary with time and be dependent on levels of introduced predators (OÕDonnell et al., 1996; Hubbs and Boonstra, 1997; Knegtmans and Powlesland, 1999; Dilks et al., 2003; Moorhouse et al., 2003). We also hypothesised that survival was dependent on temperature, because animal populations are suspected to have a lower survival rate in the cold season in temperate regions (Davis and Hitchcock, 1965; North and Morgan, 1979; Webb et al., 1996; Speakman and Rowland, 1999) although this relationship may vary among species depending on over-winter hibernation strategies and the protection offered by winter roosting sites (Humphries et al., 2002). C. tuberculatus roosts in tree cavities and reduces its activities significantly in winter but bats will emerge occasionally on warmer nights (OÕDonnell and Sedgeley, 1999; OÕDonnell, 2000b). The breeding season of long-tailed bats is highly synchronised, with a single young produced each year. Female bats tended to congregate in maternity colonies (average 34.7 ± 23.4 bats, range 2–123, n = 178 groups sampled; OÕDonnell and Sedgeley, 1999) to raise young (November–February). The long-tailed bat population in the Eglinton Valley is structured into a series of sub-populations linked rarely by immigration (OÕDonnell, 2000c). The foraging areas of the sub-populations overlapped, but roosting sites were in distinct areas. We expected that survival would vary among different sub-populations. Previous studies, which employed min-

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imum number alive estimates of population size (Thompson et al., 1998), showed that annual productivity did not vary among sub-populations but probability of survival of juveniles in their first year varied annually from 0.26 to 0.88 and was inversely proportional to the size of natal group (OÕDonnell, 2002). The sub-population with the highest survival rate contained reproductive females and juveniles with a significantly better body condition. Differences in roost site and food quality within home range area, varying genetic differences or density dependent mechanisms may explain this differential survival (OÕDonnell, 2002).

2. Methods 2.1. Study area The study was conducted in the lower Eglinton Valley, Fiordland, in the South Island, New Zealand (44°58 0 S, 168°01 0 E). The valley has a flat floor, 0.5–1.5 km wide at 250–500 m a.s.l. with steep mountainous sides, rising to 2000 m a.s.l. Tussock grasslands cover much of the valley floor. Temperate southern beech forest covers glacial outwash fans on the lower slopes, rising steeply to 1000–1200 m at bush-line. Red and silver beech (Nothofagus fusca and N. menziesii) dominate the lower slopes and mountain beech (N. solandri var. cliffortioides) becomes more common with increasing altitude. Under the canopy, the forest is generally open with few under-storey plants except for a ground cover of mosses (Sedgeley and OÕDonnell, 1999a). A highway bisects the valley for its entire length. The climate is cool temperate, with mean monthly minimum temperatures ranging from 1.1 °C in July to 10.7 °C in February. Rainfall is high, ranging from an average monthly 431 mm in winter to 718 mm in spring during the period 1993–2003 (K. Mc Gill, National Institute for Water and Atmospheric Research, person. commun.). 2.2. Bat capture, marking and radio-tracking Long-tailed bats were caught and marked during mid-summer over a 10-year study period (1993–2003). The yearly capture period was over two months (January–February), except in the first three years when it was over five months (spring–late summer, October– February). Our purpose was to catch a sample of bats from each sub-population at least nine times during each summer catching period so that recaptures reached an asymptote (OÕDonnell, 2000c). Bats were caught using 4.2 m2 harp traps (Austbat Research Equipment, Melbourne, Vic., Australia). Initially, traps were placed in areas likely to be used by bats, such as flight paths or foraging areas, so that a sample of bats could be fitted with radio-transmitters (Model BD2A,

177

Holohil Systems, Carp, Ont., Canada) and tracked to the group roosting site. These bats were followed each night until their transmitter fell off (12.7 ± 0.9 (SE) days; OÕDonnell, 2002). Bats shifted to new roosts most days. Roosting cavities were identified each day by observers on the ground watching bats flying into or out of roost trees at dawn or dusk or by climbing and identifying the occupied cavity using a radio receiver (OÕDonnell and Sedgeley, 1999). At a subset of these roost sites (<10%), a harp trap was hoisted in front of the cavity and most bats in a group (88 ± 18.9%) were captured when departing at dusk (Sedgeley and OÕDonnell, 1996; OÕDonnell, 2000c). Adult females and their young were most often caught in a trapping programme focussed on sampling these roost sites, whereas one-year-old females were rarely caught in communal groups, but reappeared in later years when they were breeding. Male bats tended to roost alone, so were rarely caught (OÕDonnell, 2000c). All bats caught were fitted with an individually numbered 2.8-mm band (The Mammal Society, UK; OÕDonnell, 2000c). Age, sex and reproductive status of all bats caught was recorded. Reproductive females were defined as animals with large bare nipples. Nipples remained conspicuous after parturition. Females without visible nipples or with nipples with hair grown over them were classed as non-reproductive. Some females in the early stages of pregnancy may have been misclassified as non-breeders. However, this number was small because all bats captured were banded and subsequent recaptures indicated whether they had bred that season. If phalangeal epiphyses had not fused then the bats were classed as juveniles (Racey, 1974). 2.3. Survival analysis Data from within a summer catching period were pooled into one capture occasion. Capture histories were constructed for 10 occasions in the years 1993– 2003. Program MARK 3.0 (White and Burnham, 1999) was used to model factors influencing variation in over-winter survival. We used the standard Cormack–Jolly–Seber model that is based on live animal recaptures in an open population (Lebreton et al., 1992). The terminology used is apparent survival (phi or /) and recapture probability (p). Apparent survival is the probability of a bat surviving from one year to the next and remaining in the study population. The recapture probability is the probability that a bat alive in the study population, at the time of a particular sample, is caught in that sample (Cooch and White, 2001). We categorised our data into 12 groups because previous studies suggested variation in survival between sub-populations, and with sex and age (OÕDonnell, 2000c). These data groups were adult males, juvenile males, adult females and juvenile females for each of three

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sub-populations (defined as Group 1, Group 2 and Group 3 after OÕDonnell, 2000c). 2.3.1. Assumptions of the Cormack–Jolly–Seber model The group-specific Cormack–Jolly–Seber model has four main assumptions: (1) every animal in a specific group has the same probability of recapture; (2) every animal in a specific group has the same probability of survival from one sample to the next; (3) marks are not lost or missed; (4) all samples are instantaneous and each release is made immediately after the sample. Departure of the data from the underlying assumptions of the model was tested using the parametric bootstrapping goodness-of-fit method available in MARK. The goodness-of-fit test for the combined dataset showed that the data were mildly over-dispersed indicating assumptions 1 and 2 may be violated (c-hat = 1.39, P < 0.001) (Cooch and White, 2001). The data were adjusted for over-dispersion using Program MARK to correct this potential violation (Cooch and White, 2001). Violations of model assumptions 1 and 2 potentially include a transience effect where there is permanent emigration from the study site after first capture (Pradel et al., 1997) and positive or negative trap-response (Pollock et al., 1990). Previous work on long-tailed bats suggests it is unlikely that permanent emigration occurs from the study site after capture (OÕDonnell, 2000c). A trap-response is also unlikely because traps were placed directly in front of roost entrances (Sedgeley and OÕDonnell, 1996). It is more likely that lack of independence in captures resulting from communal roosting (OÕDonnell, 2000c) caused over-dispersion in the data relative to the model (Pollock et al., 1990). Band loss (assumption 3) was negligible and, according to Keen (1988), forearm bands appear to be as permanent as any other marking system for vertebrates. Minimal band damage (1 in 500) was noted throughout the 10-year study period. Annual samples were not instantaneous (Assumption 4), as the sampling periods each year were over several months. Smith and Anderson (1987) reported that if the banding session was lengthy then an attempt should be made to standardise the banding effort among years (see Section 4). 2.3.2. Model construction Model construction followed the information theoretic methods of Burnham and Anderson (2002). Data were analysed for sex (s), age (a), sub-population (Group, g) and time (=year, t) effects, with average minimum winter temperature (temp) and predators (pred) as covariates of time. Predator numbers were indexed using footprint tracking tunnels for rats along standardised transects (Gillies and Williams, 2001). There are strong correlations between footprint tracking and the number of predators present in a forest and tracking indices of >5% indicate that a rat population irruption has oc-

Table 1 Introduced predator population indices in the Eglinton Valley from 1994 to 2004, expressed at footprint tracking rates for rats in November and February (beginning and end of the bat breeding season) Year

1994–1995 1995–1996 1996–1997 1997–1998 1998–1999 1999–2000 2000–2001 2001–2002 2002–2003 2003–2004

Rat footprint tracking rate (%) November

February

0 30 3 0 0 68 62 0 0 0

0 30 2 0 2 27 45 0 0 0

curred (C. Gillies, M. Willans, pers. comm.). The numbers of predators were high in the austral summers of 1995–1996, 1999–2000 and 2000–2001 (Table 1). The model was therefore coded with a 1 for high predator years and a 0 for the other years (Cooch and White, 2001). Weather details were obtained from the nearest National Institute for Water and Atmospheric Research weather station (F47691 – Milford Sound; K. McGill, person. commun.). The average mean minimum temperature was calculated for the winter months (June, July, August). The global model (one that includes all the parameters thought to be important) was therefore defined as /(s*a*g*t) p(s*a*g*t). The global model and a range of alternative models were run using the sin link for interactive models and the design matrix with the logit function for additive models (Cooch and White, 2001). 2.3.3. Model selection Model selection was based on the quasi AkaikeÕs information criterion, corrected for over-dispersion using the c-hat adjustment and small sample size bias (c) (QAICc; Anderson et al., 1998; Burnham and Anderson, 2002; White et al., 2000; Cooch and White, 2001). QAICc uses an information theoretic approach to select the most parsimonious model from a series of candidate models. The best model is the one with the lowest QAICc. Model selection using QAICc seeks a compromise between model fit (deviance) and simplicity (measured by the number of parameters). Increasing the number of parameters in the model reduces the precision of the estimates and therefore the reliability of inference. However, an overly simple model also results in unreliable inference. The difference (D) between QAICc for each model and that for the model with the smallest observed QAICc from the set of models considered was calculated along with the Akaike weight for each model. Burnham and Anderson (2002) suggest as an approximate guide that models with DQAICc < 2 should be

M.A. Pryde et al. / Biological Conservation 126 (2005) 175–185

considered to have substantial support and thus used for making inferences. Models having DQAICc of about 4– 7 have considerably less support and models with DQAICc > 10, essentially have no support. Akaike weights are proportional to the relative likelihood of each model and are useful in suggesting the weight of evidence in favour of any given model being the actual best model in the set. The bigger the DQAICc from the best model, the smaller the weight and the less plausible is the alternative model (Buckland et al., 1997). We also report the differences in the proportions of bats surviving between the best model and alternative models using the odds ratios calculated from the exponential of the beta values (Sokal and Rohlf, 1995) produced by Program MARK. 2.4. Population viability analysis A preliminary population viability analysis was calculated to explore possible consequences of survival estimates on the long-term viability of this threatened species. Data from each sub-population were combined in the analysis because we were interested in determining an overall indicative population trend rather than trends for each sub-population. The average survival for juvenile and adult females produced by the average model in low and high predator years, along with the average proportion of females breeding each year were entered into an age-classified population projection matrix (Leslie matrix). The probability of females breeding was assumed to be 0.04 in their first year, 0.6 in their second and 1.0 in the third and all subsequent years (OÕDonnell, 2002). Sex ratio at birth is equal (OÕDonnell, 2002). The intrinsic rate of increase was calculated; that is, the growth rate associated with these parameters with a population in equilibrium (Caswell, 2001). A sensitivity analysis was performed to determine how proportional changes in model parameters changed the population growth rate (Caswell, 2001). Various scenarios of predator events were then modelled to show long-term effects on the population. The recapture rates for adult females were used to ^ using the equacalculate the estimated population size N ^ tion N ¼ n=^ p, where n is the number of individuals seen and ^p is the estimated re-sighting probability for that survey. An approximate 95% confidence interval for this ^
2p varðN ^ Þ, and estimate is given by N ^Þ ¼ varðN

n2 varð^ pÞ 4 ^ p nð1  ^ pÞ þ 2 ^ p

pared graphically to determine if a simple index such as minimum number alive reflected the population viability analysis (Thompson et al., 1998).

3. Results 3.1. Survival and recapture modelling We made a total of 5286 captures, representing 1026 individuals, from the three sub-populations (Table 2). There was variability in the number of samples from each sub-population per year, with a mean of 9.6 ± 2.6 SD capture sessions per year for Group 1, 5 ± 3.7 for Group 2 and 4.6 ± 2.3 for Group 3. A relatively consistent number of different individual bats was caught per year in Group 1 (mean = 64.9 ± 14.8). In contrast, capture rates for Group 2 were more variable (mean = 52.8 ± 41.3 individuals per year), because low numbers were caught in the last two years of the study, despite repeated sampling effort. Capture rates for Group 3 were also variable (mean = 88.4 ± 50.3 individuals per year), largely because low numbers of bats were caught in the first two years of the study. Only 26 bats (2.5%) switched between sub-populations during the study. The probability of recapture (p) varied with group, time, sex and age (Table 3). Females had a higher recapture rate (range = 0.58–0.95) compared with males (range = 0.17–0.82). Juvenile recapture rate ranged from 0.18 to 0.95 compared with adults (range = 0.17–0.97). All of these factors influenced survival (social group, year, sex, age, predators and over-winter temperature). Four additive models clearly described survival parameters better than the global model, with models 1 and 2 having the greatest weight (w) (Table 3). Both models 1 and 2 indicated that survival was lower in years with high predator numbers. Although there was also evidence for an effect of high over-winter temperatures reducing survival (model 1), this effect was not compelling, as shown by the small DQAICc value between models 1 and 2 and a minor difference in the likelihood

Table 2 Total captures and number of individual bats caught from three subpopulations between 1993 and 2003 in the Eglinton Valley, New Zealand Females

Males

Total captures

No. of individuals

Group 1 Group 2 Group 3

1658 1032 1264

163 162 227

547 253 532

146 108 220

Total

3954

552

1332

474

ðWilliams et al., 2002:503Þ.

Population size was also calculated using the minimum number alive each year from the capture histories of females. These two population estimates were com-

179

Total captures

No. of individuals

180

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Table 3 The top four models along with the original global model (No. 5) describing factors affecting survival and recapture probability of long-tailed bats in the Eglinton Valley using Program MARK and the combined dataset: / = survival; p = recapture; g = sub-population (1, 2, 3); a = age (juvenile, adult); t = time; s = sex (male, female); pred = predator levels; temp = temperature

1. 2. 3. 4. 5.

Model

QAICc

DQAICc

w

n.p.

Qdev

/(g + a + s + pred + temp) p(g + a + s + t) /(g + a + s + pred) p(g + a + s + t) /(g + a + s + t) p(g + a + s + t) /(g + a + s + temp) p(g + a + s + t) /(g*a*s*t) p(g*a*s*t)

2373.85 2374.78 2382.82 2410.07 2539.87

0 0.93 8.97 36.22 166.02

0.61 0.38 0.01 0 0

20 19 26 19 186

779.41 782.39 776.07 817.68 572.46

Quasi AkaikeÕs information criterion (QAICc), differences in QAIC (DQAIC), AkaikeÕs weight (w), number of parameters (n.p.) and deviance (Qdev).

ratio test (v2 = 2.97, d.f. = 1, P = 0.08). Therefore, model averaging (Cooch and White, 2001) was undertaken to account for the weightings of each model. Average annual survival rates ranged from 0.52 to 0.83 per year for females and 0.34–0.69 for males (Fig. 1). Survival was higher for females than males, higher for adults than juveniles and lower in high predator years (1996, 2000 and 2001). Model 1 (including temperature) shows that survival was higher when it was cooler and model averaging indicated that juvenile survival rate increased more than for adults in cooler temperatures. The odds of survival were 2.09 (SE = 0.30) times higher for females than males, 0.64 (SE = 0.11) times that of adults for juveniles (i.e., 36% lower), multiplied by 0.88 (SE = 0.06) for each 1-unit increase in temperature (i.e., 12% lower), and in a high-predator year were 0.37 (SE = 0.06) times the odds in a low-predator year (i.e., 63% lower).

3.2. Population viability analysis The average survival rates of female long-tailed bats in high and low predator years using model average estimates were 0.79 and 0.59, respectively, for adults and 0.72 and 0.47 for juveniles. A four-age class Leslie matrix produced a population growth rate, k, of 1.03 in years with low predator rates and 0.79 in those with high predator numbers. If the frequency of occurrence of years with high predator numbers continues at the current rate (3 times/10 years), we predict that the population will decline on average 5% per year (k = 0.95), leading to a high probability of extinction in the next 50 years. The model indicated that effective predator control will avert this decline (Fig. 2). A sensitivity analysis showed that the model was most sensitive to the survival and productivity of adult females. Estimates of population size calculated either using the recapture rates from Program MARK or estimates of minimum number alive follow a trend similar to the predictors derived from the population viability analysis (Fig. 3). All three methods indicate that the population of female long-tailed bats is steadily declining.

4. Discussion 4.1. Limitations of data Two factors influenced the precision of the survival estimates and the level of inference of our models. First, the capture period varied among years. In the first three years it was over five months, whereas for the majority of the study it was two months. The number of new adult bats captured steadily increased over the first three years of the study, but few new adults were caught after that (OÕDonnell, 2000c). In subsequent years the majority of adults were marked, and new captures were generally young of the year. Although the study could have been improved if the sampling time was standardised and as short as possible (Smith and Anderson, 1987), the variable sample periods are acceptable because there was relatively low mortality during the sampling periods themselves (Hargrove and Borland, 1994). The second factor influencing precision was that female bats were caught at maternity colonies where they congregate with the young; therefore captures of adults were not independent. Over-dispersion adjustments were made to these data to account for lack of independence in adults, resulting in inflated variances, which reduced the overall level of inference achievable (Pollock et al., 1990). Despite these limitations, our analysis provides useful results, which can be used to guide management of long-tailed bats in the future. There was strong support for our conclusion that the population was declining, based on all three techniques we used for estimating trend (survival analysis, minimum number alive and population viability analysis). 4.2. The influence of predation The hypothesis that survival would vary with time and predator population levels was supported. In the Eglinton Valley, introduced rats occurred in high numbers in three years out of the 10 years studied. In most years, the density of these predators was low, because food is limited. However, their numbers irrupt in response to periodic beech masting and the subsequent massive increase in food availability (King, 1983;

M.A. Pryde et al. / Biological Conservation 126 (2005) 175–185 1

181

A. Adult males

0.8 0.6 0.4 0.2 0

1

B. Adult females

0.8 0.6

Survival

0.4 0.2 0

1

C. Juvenile males

0.8 0.6 0.4 0.2 0

1

D. Juvenile females

0.8 0.6 0.4 0.2 0 1994

1995

1996

1997

1998

1999

2000 2001

2002

Year

Group 1

Group 2

Group 3

Fig. 1. (A–D) Model average annual overwinter survival (±SE) of male and female long-tailed bats from three sub-populations in the Eglinton Valley, New Zealand from 1993 to 2003. Survival was lower when there were high numbers of introduced predators (years 1996, 2000 and 2001).

OÕDonnell and Phillipson, 1996; Dilks et al., 2003). Using the survival figures generated from model averaging, the projected long-tailed bat population exhibits a rate of decline which leads to a high probability of extinction within 50 years. Our analysis shows the importance of controlling introduced predators during irruption years, in forests where long-tailed bats occur. In the Eglinton Valley, there has been low-intensity control of stoats since 1998 with a line of Fenn traps at 200m intervals along the length of the valley. This level of trapping was enough to protect kaka (Nestor meridionalis), a forest parrot, from being preyed upon in the

short term, compared with uncontrolled forests (Moorhouse et al., 2003). In contrast, Fenn trapping did not lower rat numbers appreciably in irruption years and rats remained serious predators of small forest birds such as mohua (Mohoua ochrocephala) (Dilks et al., 2003), and by inference, long-tailed bats. 4.3. Difference between sexes Survival of female long-tailed bats in the Eglinton Valley was higher than the survival of males. Differential survival between the sexes has been recorded in a

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roptera estimated an adult survival rate of between 70% and 80% (Tuttle and Stevenson, 1982), which is similar to the estimates for long-tailed bats in the Eglinton Valley when there were low numbers of introduced predators present.

No of females

900 800

predicted trend (with management)

700

current trend (without management)

600 500 400

4.4. Influence of age structure, social group and temperature

300 200 100 0 1

3

5

7

9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49

Year

Fig. 2. Simulation of trends in numbers of female long-tailed bats in the Eglinton Valley over 50 years, showing the current trend (without management and the actual starting populations of ca. 200 females) and the predicted trend if there is effective management. 250

No of females

200

150

100

MARK

50

0

1995

1996

MNA

1997

PVA

1998

1999

2000

2001 2002

Year Fig. 3. Three methods of population estimation of adult female longtailed bats in the Eglinton Valley, Fiordland from 1995 to 2002. MARK uses the recapture rates from Program MARK (see Section 2), MNA is the minimum number alive per year, and PVA uses the survival rates from MARK combined with productivity rates in a matrix model. All methods combine the data for the three sub-populations.

number of bats, although survival of females is higher than males in some species, but lower in others (Humphrey and Cope, 1976; Keen and Hitchcock, 1980; Gerell and Lundberg, 1990; Hoyle et al., 2001). Both male and female long-tailed bats, including lactating females, enter torpor frequently (Webb, 1998). Differential survival of male and female long-tailed bats is understandable because males tend to roost alone, often at high altitude and so would be subject to different environmental conditions than females. In contrast, females and the young of the year roost in communal groups at low altitudes in more fertile productive forests, so will experience warmer conditions and accrue significant energetic benefits from clustering (Roverud and Chappell, 1991; OÕDonnell and Sedgeley, 1999; Sedgeley and OÕDonnell, 1999a,b; Sedgeley, 2001). In addition, if males arouse from torpor in winter more often than females in order to copulate then energy demands may be higher, as in similar Australian species (Phillips and Inwards, 1985; Tidemann, 1993). Early studies of Chi-

Survival of bats appears to vary with age in this and other studies, with adult survival being higher than that of juveniles (Vardon and Tidemann, 2000; Hoyle et al., 2001; Sendor and Simon, 2003). Previous studies of long-tailed bats have shown that younger bats have greater mortality in their first two years. Lower survival in juveniles may also be related to lower body mass and condition (OÕDonnell, 2002). Shorter-term studies have also shown a difference in the overall survival between the three sub-populations in the Eglinton Valley (OÕDonnell, 2002). Average juvenile survival varied inversely with group size. This was thought to be related to poorer quality roosting cavities, harsher climatic conditions and reduced food availability in the larger sub-populations, which lived farther up the Eglinton Valley and at higher altitude. Sub-population (g) was also important in the models produced; however, there were not enough data to elucidate variation between the individual groups fully. Breeding success and foraging by long-tailed bats appear to be limited by colder temperatures in the Eglinton Valley during summer (OÕDonnell, 2002). However, we had no support for our hypothesis that survival would be reduced in colder temperatures. On the contrary, model 1 suggested that over-winter survival was reduced in years when temperatures were higher and model averaging indicated that juveniles were most sensitive to temperature. Two explanations are plausible. Firstly, warm winter temperatures may cause bats to be more active than normal; either waking them from torpor or while remaining in torpor, functioning at higher metabolic rates than usual. Either behaviour would result in using-up valuable fat supplies during a time when food resources are relatively scarce, hence increasing the risk of mortality (Webb et al., 1996). This may affect juveniles more that adults as they have lower body masses and are likely to be less experienced at foraging than adults. Secondly, the result may be an artefact of, or an interaction with, abundance of predators. High levels of beech seedfall and increased over-winter survival of rodents are both increased by warmer than average temperatures (Schauber et al., 2002). 4.5. Implications for conservation Mark-recapture analysis appears to be a useful technique for assessing survival parameters in rare and cryp-

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tic bats. The resulting estimates can then be used in population assessments, such as predicting the intrinsic rate of population change using matrix models. The main inference from the study was the risk of predation by introduced mammals to the three sub-populations of long-tailed bats in the Eglinton Valley. The sensitivity analysis of the matrix model showed that the population change was most sensitive to adult female survival and productivity, thus maternity roosts should be the focus of attention for predator control. If the current rate of predator irruption years continues, there is a high probability that the population of bats in the Eglinton Valley will be extinct within 50 years. To combat this will require predictions of when years with high predator numbers are about to occur and then control rats and stoats effectively in those years. Introduced predators are a widespread problem in New Zealand contributing to declines in numerous indigenous species (King, 1990). Likewise such predators are a major cause of decline in bats generally (Mickleburgh et al., 1992; Hutson et al., 2001). Recent surveys have failed to find long-tailed bats, or found them in much reduced numbers, at 75% of sites surveyed (Griffiths, 1996; OÕDonnell, 2000a; Alexander, 2001). Temperatures and the frequency of beech masting are increasing in New Zealand. These conditions promote high predator numbers and are likely to occur more frequently in the future as climate changes (Richardson et al., 2005). It is worth noting that minimum number alive estimates were similar to population estimates derived from recapture rates in Program MARK and to the predictors from the population viability analysis (Fig. 3). A correlation between population estimates and minimum number alive has been reported in other small mammal studies (Hanley and Barnard, 1999; Ruscoe et al., 2001). Thompson et al. (1998) suggested that minimum number alive was only useful as a population estimate if there were constant recapture probabilities over time; otherwise the technique is essentially an index of population. If, however, it can be shown that the index closely follows the population estimate, and the estimate is assumed to reflect actual population, then minimum number alive may be useful for detecting population trends, despite more robust estimates being gained by using Program MARK. Thus, in the case of long-tailed bats in the Eglinton Valley, minimum number alive may be a cost-effective option for measuring population trends, but limitations such as lack of confidence intervals must be acknowledged. However, analysis by Program MARK also gave robust estimates of survival that helped to determine the cause of the decline, leading to informative management advice; results which would not have been available simply using minimum number alive alone. Although our study relates to only a small population of bats, declines are probably occurring in bat populations elsewhere in New Zealand where predator num-

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bers are high, and predator control is likely needed in these areas as well. At Hanging Rock, South Island, New Zealand, a mark-recapture study over five years indicated an average 9% decline per year was occurring (Lettink and Armstrong, 2003). The factors influencing this population of bats are more complex than in the Eglinton Valley, because the numbers of bats are smaller and threats include habitat degradation as well as predators. To improve survival of bat populations in such areas, other conservation methods are needed in addition to predator control, including trialling roost boxes and habitat protection and restoration. Continuing to monitor long-tailed bats using long-term mark-recapture methods in areas where they are managed will help to assess whether management techniques are effective. Integrated predator control in areas with bats will likely provide protection for small native bird species as well as bats, and may serve as an example of what could be achieved in other areas.

Acknowledgements Thanks to the more than 80 people who assisted with catching bats over the last 10 years. Particular thanks go to J. Sedgeley, B. Ebert, B. Lawrence, M. Lettink, C. Ryan, and W. Simpson. K. McGill provided the climate data and G. Elliott and I. Westbrooke provided statistical advice and analysis. The Project was funded by Department of Conservation Science Investigations 1578 and 2504, the New Zealand Lottery Grants Board, Telecom New Zealand and WWF New Zealand with approval from the Department of Conservation Animal Ethics Committee using tried and proven capture and handling techniques. Terry Greene, Lynette Clelland, Mark Brigham and an anonymous referee provided useful comments on the manuscript.

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