Conservation value of forest fragments to Palaeotropical bats

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Conservation value of forest fragments to Palaeotropical bats Matthew J. Struebiga, Tigga Kingstonb, Akbar Zubaidc, Adura Mohd-Adnanc, Stephen J. Rossitera,* a

School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, United Kingdom Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409-3131, United States c Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Malaysia b

A R T I C L E I N F O

A B S T R A C T

Article history:

Forested landscapes in Southeast Asia are becoming increasingly fragmented, making this

Received 18 March 2008

region a conservation and research priority. Despite its importance, few empirical studies

Received in revised form

of effects of fragmentation on biodiversity have been undertaken in the region, limiting

3 June 2008

our ability to inform land-use regimes at a time of increased pressure on forests. We esti-

Accepted 12 June 2008

mated the biodiversity value of forest fragments in peninsular Malaysia by studying frag-

Available online 26 July 2008

mentation impacts on insectivorous bat species that vary in dependence of forest. We sampled bats at seven continuous forest sites and 27 forest fragments, and tested the influ-

Keywords:

ence of fragment isolation and area on the abundance, species richness, diversity, compo-

Chiroptera

sition and nestedness of assemblages, and the abundance of the ten most common

Habitat fragmentation

species. Overall, isolation was a poor predictor of these variables. Conversely, forest area

Nestedness

was positively related with abundance and species richness of cavity/foliage-roosting bats,

Species–area relationship

but not for that of cave-roosting or edge/open space foraging species. The smallest of frag-

Isolation

ments (<150 ha) were more variable in species composition than larger fragments or con-

Malaysia

tinuous forest, and larger fragments retained substantial bat diversity, comparable to

Oil palm

continuous forest. Some fragments exhibited higher bat abundance and species richness than continuous forest, though declines might occur in the future because of time lags in the manifestation of fragmentation effects. Our findings suggest that fragments >300 ha contribute substantially to landscape-level bat diversity, and that small fragments also have some value. However, large tracts are needed to support rare, forest specialist species and should be the conservation priority in landscape-level planning. Species that roost in tree cavities or foliage may be more vulnerable to habitat fragmentation than those that roost in caves. Ó 2008 Elsevier Ltd. All rights reserved.

1.

Introduction

Habitat fragmentation is a major contributor to biodiversity loss (Whitmore, 1997). Nowhere is this more dramatic than in Southeast Asia, where tropical forests are becoming increasingly disturbed and fragmented, and are rapidly being

lost to agriculture (Sodhi et al., 2007). Despite this, only a few detailed studies of fragmentation have been conducted in the region (e.g. Lynam and Billick, 1999; Pattanavibool and Dearden, 2002; Bru¨hl et al., 2003; and Benedick et al., 2006). This paucity of information hinders both our understanding of the consequences of fragmentation for biodiversity in

* Corresponding author: Tel.: +44 2078827528. E-mail addresses: [email protected] (M.J. Struebig), [email protected] (T. Kingston), [email protected] (A. Zubaid), [email protected] (A. Mohd-Adnan), [email protected] (S.J. Rossiter). 0006-3207/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2008.06.009

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Southeast Asia, and our ability to advise stakeholders and land owners on potential mitigation strategies (Meijaard and Sheil, 2007). Fragmentation reduces suitable habitat area and isolates patches within a matrix of modified habitat. Island biogeography theory (MacArthur and Wilson, 1967) predicts that smaller, more isolated fragments support smaller populations, and fewer species than are supported by larger or less isolated fragments. However, a recent synthesis has reported that, while fragment area is a significant predictor of species richness in most studies, the effects of isolation remain ambiguous (Watling and Donnelly, 2006). Species exhibit variable responses to fragmentation. These responses are inconsistent across taxonomic groups, but are more commonly correlated with population size and fluctuation, disturbance sensitivity, matrix use, biogeographic position and rarity (Henle et al., 2004). Area-dependent declines in abundance and species richness can result in predictable local patterns of species extinction, with depauperate smaller fragments harbouring nested subsets of assemblages found in larger fragments (Wright et al., 1998). Thus, to evaluate the long-term conservation value of forest fragments, it is essential to describe species diversity patterns and to elucidate the mechanisms that produce them. Bats constitute the second most species-rich order of mammals (Wilson and Reeder, 2005) and up to half of mammal species in tropical forests (Findley, 1993). In recent decades, bat populations have experienced global declines, a trend linked to extensive, recent habitat loss (Mickleburgh et al., 2002). In Southeast Asia, 20% of bat species are predicted to become extinct by 2100 (Lane et al., 2006). Nonetheless, bats are frequently overlooked in biodiversity assessments and fragmentation research, possibly because they are widely perceived to be at low risk of extinction due to their ability to fly. The perception of bats as low priority subjects for conservation research may be overly optimistic because these animals exhibit combinations of traits that may increase their sensitivity to habitat loss and disturbance. Ecomorphological factors such as wing shape (Schnitzler and Kalko, 2001), behaviours including coloniality and strong site fidelity (Miller-Butterworth et al., 2003) and slow rates of reproduction (Barclay and Harder, 2003) constrain their ecological flexibility. In addition, bats are dependent on the availability of suitable roosting sites. Consequently, populations of species that roost in trees (in hollows and cavities of standing trees, under fallen trees and logs), may be adversely impacted by fragmentation via the direct loss of rare roosting sites in fragments (Schulze et al., 2000) or changes to roost suitability resulting from edge effects (e.g. disturbance levels and microclimate changes; Laurance et al., 2002). These edge effects also have the potential to influence the persistence of bats that roost in foliage (under modified or unmodified leaves), because these types of roost are more exposed to abiotic conditions and disturbance. Similarly, fragmentation can also lead to the separation of cave roosts from foraging habitat (fragments). However, given the natural patchy distribution of caves, and that they typically support large populations of bats, communal cave roosting species are likely to have been selected for greater vagility over evolutionary time. As a re-

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sult, these species typically commute great distances to and from foraging grounds each night (Altringham, 1999), and so may be better adapted to persist in a fragmented landscape than their tree and foliage-roosting counterparts. To date, fragmentation studies of tropical bats have focused almost exclusively on assemblages in the Neotropics (but see Law et al., 1999 for a study in Australia), where bat assemblages in forests are dominated by members of the family Phyllostomidae. These studies have suggested that bat species richness may be largely unaffected by fragmentation (Schulze et al., 2000; Estrada and Coates-Estrada, 2002; Pineda et al., 2005; Faria, 2006; Bernard and Fenton, 2007), though subtle impacts on assemblage structure have been detected (Cosson et al., 1999; Gorresen and Willig, 2004). However, meaningful comparisons between studies are complicated by differences in sampling effort and fragmentation history, as well as variation in potential determinants of assemblage structure in fragments, such as the degree of contrast between fragments and the matrix (low contrast, Estrada and Coates-Estrada, 2002; Pineda et al., 2005; Faria, 2006; versus high contrast, Cosson et al., 1999; Bernard and Fenton, 2007), and the availability and size of forest patches in a landscape (Gorresen and Willig, 2004). Palaeotropical bat assemblages are dominated by members of the families Rhinolophidae and Hipposideridae, and the Vespertilionidae subfamilies Kerivoulinae and Murininae. These species are not present in the Neotropics, and many of them are typically highly adapted for foraging in the clutter of the forest interior (‘narrow-space’ ensemble, sensu Schnitzler and Kalko, 2001). Consequently, these species may be more sensitive to forest loss and exhibit greater avoidance of disturbed and open habitats than Neotropical bats (reviewed in Kingston et al., 2003). Because of this dependence on forest, we expect these species to be adversely affected by deforestation and other forest disturbance events (Lane et al., 2006). We determined the conservation value of forest fragments in the Palaeotropics by using bats as a focal animal group, and quantifying abundance, species richness, diversity, assemblage composition and nestedness in a fragmented landscape in central peninsular Malaysia. We focused on the narrowspace ensemble of insectivorous species due to their predicted vulnerability and because they can be readily captured in forests using a single, standardised sampling technique. Landscapes in Malaysia have undergone major changes over the last century as forests have been rapidly cleared for timber, urbanisation and plantation agriculture (KathirithambyWells, 2005). Increasing demand for plantation products such as oil palm (Elaeis guineensis) places pressures on land owners to increase yields; one way to do this is to increase production area by clearing forest remnants. Hence, we sought to inform these management decisions regarding the value of such remnants at a time of increased pressure on remaining forest habitats. We hypothesised that (1) species richness, abundance and diversity of bats is lower in smaller or more isolated forest fragments than in larger or less isolated fragments; (2) fragmentation effects are stronger in species that roost in tree cavities and/or foliage than in more vagile species that roost in caves and (3) assemblages in smaller or more isolated frag-

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ments represent nested subsets of those in larger or less isolated fragments.

2.

Methods

2.1.

Study landscape

The Krau landscape in central Pahang state (3°40 0 N, 102°10 0 E; Fig. 1) represents 562,060 ha of land and is bounded by continuous forest to the north and west. Historically this landscape has experienced little deforestation, but in recent years (1966– 2002), 39 % of the forest has been felled (DAPM, 2005). Today, large blocks of undisturbed continuous forest remain protected as the Krau Wildlife Reserve and neighbouring Forest Reserves, while 43% of land is covered by rubber (Hevea brasiliensis) and oil palm plantations, surrounding smaller forest fragments. The majority of natural vegetation in the Krau landscape is lowland or hill dipterocarp forest, with associated dominant tree species including Dipterocarpus cornutus, D. baudii, Hopea sangal, Shorea acuminata and S. ovalis, or Anisoptera laevis, D. grandiflorus, S. leprosula, S. cutisii and Vatica cuspidata respectively (Yusof and Sorenson, 2000). The annual 24-h mean temperature is 26 °C, and monthly precipitation typically exhibits two periods of maximum rainfall between September and December, and March and May, separated by two periods of minimum rainfall (Yusof and Sorenson, 2000).

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2.2.

Forests sampled and patch metrics

We sampled bats between May 2002 and June 2007 at 35 lowland forest sites. These comprised five undisturbed sites and two disturbed sites within Krau Wildlife Reserve (S01-S07, mean distance between sites 17 km); and 27 forest fragments varying in size from 3 ha to 11,339 ha (F01-F27, Fig. 1). Fragments were identified from land-use maps (DAPM, 2005) verified by visual interpretation of 2002 Landsat ETM satellite images; they represent the range of forest remnant sizes and land-use histories in the landscape. Fragments were subject to ongoing disturbance: all exhibited evidence of logging as well as hunting of wild pigs (Sus scrofa) and mouse deer (Tragulus spp.). We used ArcView version 3.2 to calculate forest area and two measures of isolation widely used in fragmentation studies (Watling and Donnelly, 2006): the shortest Euclidean distance to nearest continuous forest, and the distance to the nearest forest patch. All metrics were independent from each other (Pearson’s r < 0.3; p > 0.3), and were log transformed to approximate to normal distributions.

2.3.

Bat sampling

We minimised methodological heterogeneity and capture biases (Kingston et al., 2003) by restricting sampling to insectivorous species that are readily captured in the forest under-

Fig. 1 – Locations of sampling sites in the Krau landscape, peninsular Malaysia, including those in continuous forest (S prefix) and forest fragments (F prefix). Dark grey areas represent forest cover in 2002 and light grey areas represent additional forest cover in 1966, both according to Malaysian Ministry of Agriculture maps. White areas consist of a plantation mosaic, primarily oil palm and rubber, but also with substantial areas of durian (Durio spp.) and Acacia spp. Forest cover for all peninsular Malaysia is shown in the inset, and black lines indicate state boundaries.

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storey, conducting fieldwork only in dry seasons, and avoiding periods of heavy rain. Bats were captured using up to fifteen four-bank harp traps positioned across flight paths (trails, logging skids, streams, or swamp beds) each night and then moved to a new position the following day – hence one trap set for one complete night constituted one harp trap night (HTN), following Kingston et al. (2003). Bats were collected and identified following the procedures of Kingston et al. (2006) and were marked either with uniquely numbered forearm bands or wing biopsies, so that recaptures could be recognised and excluded from analyses. Individuals were released within 12 h at the capture point. We classified species into three classes based on dispersal capabilities inferred from wing morphology and roosting ecology. Wing morphology was first used to define species at the level of ensemble by distinguishing bats that forage in narrow spaces (‘narrow-space’ bats, sensu Schnitzler and Kalko, 2001; ‘Strategy I’ bats, sensu Kingston et al., 2003) from those that primarily forage in edges or open spaces (‘Strategy I’ and ‘Strategy III’ bats, sensu Kingston et al., 2003). Species in the narrow-space ensemble were then further partitioned based on their roosting ecology into two classes: (1) tree cavity/foliage-roosting species and (2) cave-roosting species (including rock crevices).

2.4.

Sampling design

The 27 fragments varied substantially in isolation history, as well as in distances to other fragments and to areas of karst limestone, which hosted large populations of cave-roosting bats that dominated assemblages. Because these factors were likely to obscure the effects of fragmentation on bat assemblages, we analysed a subset of 15 fragments, each of which was a minimum of 500 m from other fragments and 2 km from karst sites, and had a sampling effort of at least 15 HTN. Isolation distances for these sites ranged from 2.1 to 11.0 km (mean 6.4 km) from continuous forest, and 0.6 to 2.3 km (mean 1.3 km) from other fragments. For comparisons with undisturbed continuous forest, we classified fragments by size, which ranged across three orders of magnitude: small (mean 70 ha, range 31–102); medium (mean 353 ha, range 251– 443); and large (mean 5410 ha, range 2025–11 339). Data from sites within each size class were then pooled to provide sufficient sample sizes for statistical analyses.

2.5.

Statistical analyses

A suite of analyses was designed to evaluate the effects of forest fragmentation on bat abundance, species richness, diversity, assemblage composition and nestedness. We used the Simpson index as our measure of diversity because this measure is weighted toward common species, and allows for examination of patterns of species dominance, or in its reciprocal form, species evenness. Because of the exploratory nature of our study and extensive debate regarding the use of adjustments for multiple tests in the ecological literature (e.g. Roback and Askins, 2005), we report the exact p-values for all analyses. We tested the influence of fragment area and isolation on assemblage variables (total bat abundance,

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observed and predicted species richness, and diversity), using generalised linear models (GLMs) undertaken in the R-statistical package version 2.5.1 (http://www.r-project.org). This approach focussed on site-level species richness or total bat abundance (i.e. standardised richness or abundance for all species pooled in all traps at each site), and was also used separately to test the influence of fragment metrics on the abundance and species richness for each of the three classes of bats (i.e. edge/open space foraging species, cave-roosting narrow-space species, and tree cavity-foliage roosting narrow-space species). Observed species richness (Sobs) and reciprocal Simpson diversity (1/D, evenness) were derived from sample-based rarefaction curves (Colwell, 2004), and species richness was predicted at a standard number of individuals (200) using the Shen multinomial model (Shen et al., 2003; Chao and Shen, 2003-2005). Square root transformations were used on abundances and predicted species richness to approximate normal distributions without special treatment of zeros (McCune and Grace, 2002). Sample sizes were sufficient to warrant testing the responses in the abundance of the ten most common species to fragment area and isolation. However, the low abundances of these species at some sites limited our ability to detect these responses using the GLM approach. Therefore, we quantified the responses in species abundance to area and both isolation metrics with a procedure that focused on trap-level abundance of these species using a generalised linear mixed-effects model (GLMM) with Poisson error terms. Modelling sites as random effects in GLMMs also controlled for pseudoreplication within a site and accounted for variance attributable to particular sites. All GLMMs were undertaken in R with the lmer function from the lme4 package (Bates, 2008). The three fragment metrics were modelled as fixed effects, sites were modelled as random effects, and the response variable was a species’ abundance in a trap (15 traps per site). p-values were generated from 10 000 Markov chain Monte Carlo (MCMC) simulations using the languageR package (Baayan, 2008). Bat abundance, species richness and reciprocal Simpson diversity (i.e. evenness) among different size fragments and continuous forest were compared using non-parametric Kruskal–Wallis tests with post-hoc pairwise Mann–Whitney U tests. This procedure was also undertaken for the abundances of the ten species for which we had sufficient sample sizes. Estimates of observed species richness and Simpson diversity were partitioned into additive components within sites (a); between sites of similar sizes (b1); and between sites of different sizes (b2), using an individual-based randomisation procedure (Veech and Crist, 2007). Because additive partitioning resulted in a and b components being measured in the same units (Crist et al., 2003), we could assess the relative contributions of size classes of fragments to overall (c) insectivorous bat species richness and Simpson diversity (i.e. dominance) over the Krau landscape. Species abundance distributions within fragment size classes and continuous forest were determined using standardised rank abundance (Whittaker) plots, on which the differences of species rank between the pooled assemblages could be visually inspected. Differences in species abundances distributions between fragment size classes and con-

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tinuous forest were assessed using a v2 randomisation test in Ecosim version 7 (Gotelli and Entsminger, 2007). Because this test uses the same expected abundance values for both observed and simulated data (i.e. 1000 simulations) the results were not sensitive to small expected values arising from rare species. To determine variation in the compositional structure of bat assemblages among sites, we used non-metric multidimensional scaling (NMDS) with the Bray-Curtis dissimilarity index. Bray-Curtis coefficients were based on species abundances, which were square-root transformed to compress values of abundant species relative to those of rare species without the need to adjust zeros (i.e. species absences) (McCune and Grace, 2002). Ordinations were implemented using the software PC-ORD version 5 (McCune and Mefford, 2006) with 500 iterations and 250 runs of both real and randomised data. Because assemblage data are often composed largely of rare or absent species, removing some of these species may enhance the detection of relationships between composition and causal factors, such as fragment metrics (McCune and Grace, 2002). Therefore, we performed several ordinations starting with the inclusion of all species, and then removed subsets of species based on ensemble or rarity. The final ordination was chosen based on reducing stress from additional axes but also retaining enough species for the ordination to remain biologically meaningful. A GLM was used to evaluate whether forest metrics determined the positions of forest sites in ordination space, and hence the compositional differences of bat assemblages between forest sites. Finally we determined the extent to which bat assemblages were nested by calculating nestedness derived from presence–absence matrices of species in fragments. We performed separate analyses using matrices of all bat species and sub-matrices for each of the three classes of bat. The resulting temperature metric T describes the level of ‘heat disorder’, a measure of the distribution of unexpected presences and absences in a matrix. Maximum order, or perfect nestedness, is indicated by a temperature of zero, and significance can be assessed by comparing the observed temperature to a null distribution based on MCMC simulations. We used the binary matrix nestedness calculator (BINMATNEST, Rodrı´guez-Girone´s and Santamarı´a, 2006), an algorithm that overcomes limitations of other calculators concerning the reordering and packing of matrices, the definition of the isocline of perfect order, and the appropriateness of null models used to assess significance. BINMATNEST provides three alternative null models on which to assess significance, with model 3 being the most conservative according to the authors. We therefore used this model to evaluate significance, and based our p-values on 5000 simulated matrices. To determine if the maximally nested matrix produced an ecologically meaningful nested arrangement, in terms of forest fragmentation, the order of forest fragments in the maximally nested matrix was correlated (Spearman rank coefficient) with forest fragments ordered by area or isolation, as surrogates of fragmentation intensity. Hence, a significant correlation coefficient would suggest a nested arrangement that resulted from the fragmentation process (Rodrı´guez-Girone´s and Santamarı´a, 2006).

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3.

Results

We captured a total of 10 343 insectivorous bats of 46 species from 1830 HTN over seven sites in continuous forest and 491 HTN over 27 fragments (Appendix 1). Of the 7488 individuals captured in continuous forest, tree cavity/foliage-roosting and cave-roosting narrow-space species represented a similar proportion of all bats captured: 47% of individuals (21 species) were tree cavity/foliage-roosting; 52%, (12 species) were caveroosting; and 1% (7 species) were edge/open space foragers. Conversely, of the 2857 individuals captured in fragments, the proportion of tree cavity/foliage-roosting species was lower (26% 17 species), while that of cave-roosting species (68% 12 species) and edge/open space foraging species (6% 9 species) was higher. Only six individuals were recaptured between sites, all of which were cave-roosting species (Table 1). No species were recorded in every fragment, but four species (Rhinolophus affinis, R. lepidus, R. trifoliatus and Murina suilla) were widespread (present in >70% of fragments and all continuous forest sites). Sixteen species were uniformly rare (< 1% of captures in both continuous and fragment forest sites, Appendix 2) and six (Coelops robinsoni, Hipposideros armiger, Harpiocephalus mordax, Kerivoula krauensis, Murina rozendaali and Myotis siligorensis) were only recorded in continuous forest. Three species captured in fragments (Hesperoptenus blanfordi, Hipposideros lylei and Scotophilus kuhlii) were absent from our surveys in continuous forest, but have been recorded in that habitat by other studies reviewed in Kingston et al. (2006).

3.1.

Patterns of abundance and assemblage composition

More bats were captured in larger fragments than smaller fragments (Fig. 2; Table 2), but there was no response in total or ensemble abundance based on either measure of fragment isolation. Fragment area explained the majority of variation in total bat abundance (72.7% Fig. 2a), with measures of isolation consistently removed from GLMs. When partitioning this relationship by ensemble and roosting class, area explained variation in abundance of tree cavity/foliage-roosting bats (54.5% Fig. 2b), but not for cave-roosting bats (Fig. 2c) or edge/open space foraging bats (Fig. 2d). There was no response to fragment isolation exhibited by any ensemble or roosting class. The total bat abundance of the smallest fragments was significantly lower than continuous forest (Kruskal–Wallis v2 = 11.78, p = 0.008; all pairwise Mann–Whitney comparisons, U < 0.001, p = 0.009), but abundance in medium and large fragments was similar to continuous forest (U = 7.0–11.0, p > 0.05). When considered by roosting class, fewer tree cavity/foliageroosting bats were captured in fragments of all size classes compared to continuous forest sites (v2 = 10.73, p = 0.013; all pairwise analyses, U > 1, p < 0.05). However, for cave-roosting and edge/open space foraging bats no differences between size classes were detected (v2 = 5.38, p = 0.15; and v2 = 5.01, p = 0.17, respectively). Species abundance distributions were unequal across fragment size classes (observed v2 = 913.17, simulated v2 = 111.18 ± 13.08, p < 0.0001; Fig. 3). Kerivoula intermedia was among the most dominant tree cavity/foliage-roosting spe-

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Table 1 – Individuals recaptured in forest fragments in the Krau landscape during this study, with the Euclidean distance between sites of capture and recapture Species Hipposideros cervinus Rhinolophus affinis Rhinolophus stheno

Sex and reproductive conditiona #A $ A PL #A $AP $ A PL #A

Identity band number MBCRU A6251 MBCRU A8593 MBCRU A5326 MBCRU B2183 THK 34227 MBCRU A6546

Site captured

Site recaptured

Distance between sites (km)

S05 S05 S05 S01 F17 S05

F10 F12 F09 F08 F18 F10

12.5 10.7 10.4 4.9 1.9 10.9

a A, mature adult; PL, post-lactating; P, pregnant.

Fig. 2 – Relationships between insectivorous bat abundance (a–d) or species richness (e–h) and forest area, for ensembles of bats with different roosting/foraging ecology. Black circles indicate forest fragments and grey circles indicate continuous forest sites. Regression models performed using fragment sites only. Fragment F15 was identified as an outlier with a hyperabundance of cave-roosting species and so was excluded from regressions.

cies in continuous forest (rank = 2) and large fragments (rank = 1), but was much rarer in medium (rank = 19) and small fragments (rank = 20). In contrast, Rhinolophus affinis was a rare cave-roosting species in continuous forest (rank = 18), but was much more abundant in fragments (ranks from large fragments to small = 3, 1, 3). For species-level analyses of abundance significantly fewer bats were captured in fragments compared to continuous forest for two tree cavity/foliage-roosting species – K. intermedia (v2 = 9.11, p = 0.028) and K. papillosa (v2 = 11.99, p = 0.007). These results were also supported by GLMM models, which showed that more individuals of these species were captured in traps set in larger fragments than in smaller fragments (K. intermedia, p = 0.010; K. papillosa, p < 0.0001), and that both isolation metrics were not significant predictors of abundance. Similarly, species abundance of two cave-roosting species,

Hipposideros cervinus and H. larvatus, was greater in larger fragments than smaller fragments (p = 0.005 and p = 0.014 respectively), but also increased with greater distance from continuous forest (p = 0.030 and p = 0.032 respectively). The six other common species (tree cavity/foliage roosting: Murina suilla, Rhinolophus trifoliatus; and cave-roosting: H. bicolor 131, H. bicolor 142, R. affinis, R. lepidus) exhibited no response in abundance to any fragment metric (p > 0.1).

3.2.

Species richness and diversity

Smaller fragments typically supported fewer bat species than larger fragments or continuous forest. Significant positive relationships existed between species richness and log-area using observed and predicted species richness (r2 = 0.309, p = 0.01, Fig. 2e; and r2 = 0.324, p = 0.02 respectively). When ob-

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Table 2 – Landscape metric and insectivorous bat assemblage characteristics for fragment and continuous forest sites used for analyses Forest class and site

Landscape metrics Area (ha)

a

Assemblage characteristics b

Isolation (km)

Nearest forest (km)

N

c

Sobsd

S200e

1/Df

Small fragments F03 RTP Lembah Klau F09 Paya Parit F11 Ulu Rugan F22 Desa Bakti F25 Jambu Rias

100 31 122 107 32

7.4 5.0 8.8 5.6 4.6

2.3 0.6 1.7 2.1 1.2

39 41 23 42 20

10 11 5 12 7

11.8 27.3 8.9 17.0 7.4

4.7 6.3 3.2 6.1 6.3

Medium fragments F06 Klau Kecil F08 Paya Luas F10 Hutan Kerdau F14 Kampung Lebu F15 Rumpun Makmur

443 353 319 400 251

3.7 2.1 8.1 7.4 4.6

1.4 1.0 0.6 2.3 1.8

63 43 71 77 157

17 11 14 17 19

19.1 12.7 19.8 18.9 20.4

10.7 6.8 5.4 8.2 7.0

Large fragments F01 Kemasul 1 F02 Kemasul 2 F21 Belungu F23 Klau Besar F24 Jengka

2883 11 339 5225 5581 2025

7.7 7.5 11.0 5.5 7.6

0.6 1.2 1.8 0.7 0.6

65 113 104 91 112

15 17 14 17 13

19.8 18.3 18.9 19.5 14.5

4.2 8.8 4.2 9.1 4.9

Continuous forest S01 Kuala Lompat S02 Lubuk Baung S03 Kuala Serloh S04 Kuala Gandah S05 Jenderak Selatan

137 137 137 137 137

– – – – –

67 66 49 61 162

16 13 11 16 12

20.0 16.6 11.9 19.4 12.5

10.0 7.9 7.4 8.0 3.5

a b c d e f

000 000 000 000 000

– – – – –

The shortest straight-line distance to continuous forest. The shortest straight-line distance to the nearest forest fragment. Number of individuals captured in 15 harp traps set on trails in a site. Number of observed species. Predicted number of species at the 200 individual abundance level using the model proposed by Shen et al. (2003). Reciprocal Simpson index – higher values indicate a more diverse assemblage with even species abundances.

served species richness was considered separately for each ensemble and roosting class, only tree cavity/foliage-roosting bats exhibited a positive response to log-area (Fig. 2f–h). No significant relationships existed between reciprocal Simpson diversity (i.e. evenness) and any of the fragment metrics. Fewer species were recorded in small fragments than continuous forest (v2 = 10.73, p = 0.013; U = 2.00, p = 0.027), but fragment size classes were similar in terms of predicted species richness (v2 = 7.20, p = 0.066), or reciprocal Simpson diversity (v2 = 4.45, p = 0.217). Additive partitioning revealed that species richness of bats within sites, between sites of similar size, and between sites of different size, contributed almost equal proportions to the overall insectivorous bat species richness (a = 36.8%; b1 = 35.7%; b2 = 27.7%). However, the majority of species dominance, as measured by Simpson diversity, was attributed to within sites (a = 89.7% b1 = 6.9%; b2 = 3.3%) suggesting that sites were highly dominated by common species.

3.3.

Bat assemblage composition

The final NMDS ordination of species dissimilarity among sites consisted of two axes and was based on a matrix that included all bats except for the edge/open space foraging ensemble (27 species, stress = 16.7, (Fig. 4)). Other ordinations

based on assemblages with all species, or with rare species excluded, had higher stress (20.0) and so were less reliable, but showed a similar pattern. The final ordination represented 82% of variation in dissimilarity, and showed that small fragments (<150 ha) were atypical of the pattern of assemblage structure at other sites based on their wide scatter on the ordination plot (Fig. 4). Hence, bat species composition in small fragments was more variable than that in larger fragments or continuous forest. Forest area was the sole predictor of assemblage composition described by NMDS axis 1, which represented the majority of variation in dissimilarity (r2 = 0.430, p = 0.001). There was no such relationship between the scores of other axes with area or isolation. Hence, larger sites, including those in continuous forest and large fragments, were more similar to each other in terms of bat species composition than smaller sites.

3.4.

Nestedness of species assemblages

When all bat species were considered in the analysis assemblages were significantly nested (observed T = 25.29, expected T = 44.77 ± 4.04, p < 0.001), and the rank order of forest fragments in the maximally nested matrix was strongly negatively correlated with forest fragments ordered by area (rs = 0.639, p = 0.001). Tree cavity/foliage roosting bats were

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Fig. 3 – Rank abundance (Whittaker) plots for insectivorous bats in three size classes of forest and continuous forest in the Krau landscape. Species are ranked according to the abundance of each species (n) and the total abundance of all species for each forest class (N). Species codes are in Appendix 2.

Fig. 4 – Nonmetric multimensional scaling (NMDS) ordination for Bray-Curtis species dissimilarity of insectivorous bat assemblages in 15 forest fragments and five continuous forest sites in the Krau landscape. A 2dimensional ordination that excluded edge/open space species was the best solution (stress = 16.7), and represented the majority of species (27) and variance in dissimilarity (82%). Points are scaled to log transformed forest area, the sole significant predictor of assemblage composition. Grey points represent sites in continuous forest and black points represent forest fragments.

also significantly nested when assessed separately (observed T = 20.00, expected T = 36.81 ± 5.23, p < 0.001), and the rank order of fragments exhibited a similar negative relationship with fragment area (rs = 0.693, p = 0.001). Cave-roosting bats exhibited nested subsets, but were not as strongly nested as other groups of bats (observed T = 17.22, expected T = 34.06 ± 6.54, p < 0.01), and no significant correlation between fragment rank and area was evident (rs = 0.261, p = 0.174). No nested pattern was evident for edge/open space foraging bats (observed T = 14.69, expected T = 21.20 ± 6.71, p = 0.216), and no correlation was observed between the nested rank order of fragments and either measure of isolation for any of the matrices (p > 0.1). Hence, nested analyses suggested that bat assemblages in smaller fragments were subsets of those in larger fragments, that this was more evident for tree cavity/foliage-roosting and cave-roosting narrow-space bats, and that fragment area rather than isolation played a causal role in this nested structure.

4.

Discussion

We recorded diverse insectivorous bat assemblages and found evidence that fragmentation has negative effects on bat abundance, species richness and assemblage composition. Overall bats responded to changes in fragment area, but not isolation, and assemblages in small fragments were nested subsets of those in large fragments. Moreover, tree

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cavity/foliage-roosting species appeared more susceptible to fragmentation than cave-roosting species or edge/open foraging species. We found that fragment area, but not fragment isolation, influenced assemblage-level abundance, species richness, composition and nestedness rankings of bat species, in agreement with the majority of fragmentation studies (Watling and Donnelly, 2006). At the level of individual species, we also found that the abundance of four species (Hipposideros cervinus, H. larvatus, K. intermedia and K. papillosa) responded positively to increases in fragment area; however, contrary to expectations, the abundance of two of these (H. cervinus and H. larvatus) also increased with greater isolation distance from continuous forest. Given that both of these species roost in caves, we suggest that this response was an artefact of the distribution of caves; several large cave systems are known in the east and west of the Krau landscape, but only a few small caves are known near the continuous forest sites, and none of these support large bat populations. Thus it is likely that, at least for some cave-roosting species, their roosts are simply of sufficient distance from continuous forest for bats not to be recorded in great numbers at the sites we studied. This notion is also supported by the greater abundance rankings of the cave-roosting species H. larvatus, Rhinolophus affinis and R. lepidus in fragments compared to continuous forest (Fig. 3). Our inability to detect a clear effect of fragment isolation on bat assemblage structure might reflect the comparatively limited distribution in values of isolation distance compared to area in the study (see Watling and Donnelly, 2006). However, we also suspect that the lack of an impact of isolation is real, and is attributable to several aspects of the study area and focal species. First, the Krau landscape is characterised by a low level of matrix contrast. The structural contrast between fragments and matrix determines the extent to which animals can move across fragment boundaries, and is highly dependent on a species’ vagility and its perception of habitat (see Ewers and Didham, 2006). In an example of extreme matrix contrast, Meyer and Kalko (in press) studied land-bridge islands in Panama and found that island (fragment) isolation, rather than area, was linked to patterns of nestedness in bat assemblages. In Krau, the more hospitable matrix consisting of plantations and village gardens is likely to be more easily traversed by bats. Indeed, the tolerance of a species to different habitats defines its effective isolation, which might differ from that described by Euclidean distances, and so further complicate our ability to detect isolation effects (Ricketts, 2001). The extent to which isolation impacts assemblage structure in fragments will also be influenced by the history of the landscape. Fragmentation is usually an ongoing process, and although this process began in the Krau landscape ca. 50 years ago, it has been much more recently that most changes have occurred. In addition, the rate of fragmentation has been much faster in some areas than others. Thus, there might be a delay in the realisation of isolation effects, with current patterns dominated by the effects of area, which will reflect both the prey base available to insectivorous bats, as well as viable roosting opportunities for tree cavity/foliage roosting species.

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Perhaps the most obvious explanation for a lack of isolation effect is that the bats studied are sufficiently vagile to cover distances between the fragments. However, we advocate caution in drawing this conclusion for several reasons, not least because while empirical studies demonstrate that some of the bat species recorded are highly mobile, the vagility of several groups appears to be more limited. Indeed, edge/ open space foraging bats, together with several species in our cave-roosting class, may be able to commute between forest patches, as well as utilise matrix habitats. The relatively small, long and narrow wings characteristic of these species (Kingston et al., 2003) result in high wing loading and high aspect ratios, which have been linked to fast energy-efficient flight (Norberg and Rayner, 1987). Radio-tracking studies have shown that cave-roosting rhinolophid and hipposiderid species can commute several kilometres in a single night (e.g. H. speoris, Pavey et al., 2001; R. hipposideros, Bontadina et al., 2002), and recapture data from our study (Table 1) confirm that dispersal distances can exceed the distances between some fragments. In contrast, bat species in our tree cavity/foliage roosting class appear to be more restricted to areas around available roosts in forest fragments. These species are characterised by low wing loading and low aspect ratios (Kingston et al., 2003), associated with slow, manoeuvrable but energetically expensive flight that is suited to clutter but poorly adapted to long distances (Norberg and Rayner, 1987). This prediction is well supported by banding records from the Krau Wildlife Reserve; of 3900 bat recaptures, none of the recapture distances for tree cavity/foliage roosting species exceeded 1 km (Sujarno-Kudus, 2006). Moreover, radiotracking studies of four of these species (Kerivoula papillosa, Hipposideros ridleyi, Rhinolophus sedulus and R. trifoliatus) have revealed that home ranges are limited to < 100 ha and do not extend beyond forest boundaries (Allen, 2005; Fletcher, 2006). In light of such empirical evidence, we speculate that the combined effects of low matrix contrast, heterogeneous fragmentation rates and variation in bat species vagility are likely to have ameliorated the impacts of isolation for at least some of our study species. Area-dependent relationships with species richness, nestedness and assemblage structure suggest that in our study area large tracts of forest are needed to conserve intact bat assemblages. Nonetheless, the greatest differences in assemblage structure were among the smallest fragments, and many of the medium- and large-sized fragments (>300 ha) retained substantial bat diversity, in come cases equalling or even exceeding that of continuous forest sites. In fact, additive partitioning revealed that almost a third of bat species richness at the landscape level was generated by diversity between sites of different size classes (i.e. b2), which was a similar contribution to that of species richness from within sites (i.e. a). Although this suggests that smaller fragments have substantial value for bat diversity when considered together at the landscape level, again, there are several reasons to be cautious. First, most sites were highly dominated by common species that were relatively mobile; the greatest component of Simpson diversity (i.e. species dominance) was attributed to individual sites, and species abundance distributions in fragments indicated that dominant bats were frequently cave-roosting species. Second, species

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predicted to be vagile contributed most to the differences in assemblage composition between small fragments. In particular, there was no nested pattern for edge/open space foraging bats, the nestedness of cave-roosting bats could not be predicted by fragment area, and some small fragments were seen to host edge/open space foraging species that were not recorded elsewhere during the study (Hesperotenus blanfordi and Scotophilus kuhlii). Third, our analyses have not fully accounted for the rare specialist bat species known to occur in peninsular Malaysia, which are likely to be at a greater risk of extinction than common generalists (Davies et al., 2004). Although 11 of the 46 species we captured are IUCN red-listed (Appendix 2), these were typically found in larger fragments and continuous forest. Despite a large cumulative sampling effort over the landscape, six species were only found in continuous forest; three of these (Coelops robinsoni, Harpiocephalus mordax and Murina rozendaali) are red-listed, and one (Kerivoula krauensis) has only recently been described, is currently considered endemic to Krau Wildlife Reserve, and has not yet been assessed by the IUCN. Finally, because of the recent history of fragmentation in some parts of the Krau landscape, crowding effects are likely to be substantial over the short term (see Ewers and Didham, 2006). Hence, many small and isolated fragments may still owe an extinction debt (Tilman et al., 1994), at least for the few cavity/foliage roosting species that currently persist in them, and the long-term responses of bat assemblages to fragmentation in Malaysia may yet be realised. This study represents one of the first to date of bats and fragmentation in the Palaeotropics, with the vast majority of previous tropical fragmentation research having been undertaken in the Neotropics. Comparisons between our results and those of other studies of bats and fragmentation are not only complicated by the fundamental differences of bat assemblage composition between the Neo- and Palaeotropics, but also by fragmentation history. Studies in naturally fragmented landscapes in the Neotropics suggest that fragmentation has had limited impact on bat assemblages, with species richness and composition remaining similar between fragments and continuous forest (Montiel et al., 2006; Bernard and Fenton, 2007). However, in historical examples of fragmentation, processes are likely to have selected for species traits that confer resistance to habitat change (Balmford, 1996), and hence patterns in these landscapes do not necessarily predict those that arise from more rapid human-induced fragmentation. In some cases, subtle impacts on assemblage structure have often been detected in these situations, and researchers have suggested characteristics that may influence the resilience of bat species to fragmentation. In Guatemala, for example, the most abundant bats in fragments were found to be typically large frugivores (Schulze et al., 2000), while in French Guiana they were large frugivores that were also canopy specialists (Cosson et al., 1999). In a study of insectivorous bats in Australia, resilient species appeared to be fast flying, poorly manoeuvrable species (Law et al., 1999)ßand in a detailed study of land-bridge islands in Panama, edge-sensitivity was suggested to be the key influence on vulnerability (Meyer et al., 2008). However, single traits are often poor predictors of species sensitivity to frag-

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mentation, and profiles describing groups of traits that may act synergistically may be more accurate (Davies et al., 2004; Henle et al., 2004). In this regard, our study suggests that multiple traits correlated with roosting ecology (e.g. vagility, population size, foraging behaviour, see Altringham, 1999) might have important roles in determining the differential responses of bat species to fragmentation.

4.1.

Conservation implications

The ability of bats to fly calls into question whether these animals are a poor model group to infer the impacts of land-use change, or on which to base landscape management policies. Despite this, few empirical studies have compared the responses of bats to land-use changes with different taxa within the same landscape. The exceptions, based exclusively in the Neotropics, have demonstrated that different animal groups vary in their response to land-use change, and that the response of bat assemblages is not shared by other taxa, which typically are more heavily affected (Pineda et al., 2005; Barlow et al., 2007; Gardner et al., 2008). In fact, Amazonian bat assemblages were similar amongst secondary forests and plantations, a response that exhibited the poorest congruence with other groups of vertebrates, invertebrates and plants (Gardner et al., 2008), and which was related to their high vagility (Barlow et al., 2007). However, this finding might have arisen because analyses were conducted on all bat species at the assemblage level. Our study suggests that, in the Palaeotropics at least, not all bat species are as mobile as might be perceived, and that partitioning assemblage analyses based on foraging or roosting strategies may improve our ability to detect responses to land-use changes. Studies of bats and other animal groups in the same disturbed Palaeotropical landscapes are needed to elucidate how the responses of tree cavity/foliage roosting bats compare to those of other taxa. Our study supports the view that larger fragments contain more species, with assemblages resembling those in ‘intact’ natural habitats. Therefore, conservation strategies in Palaeotropical landscapes should favour large areas of forest, at least for conserving bat populations. Large fragments in the Krau landscape are currently managed for timber production as part of the Permanent Forest Estate, echoing trends elsewhere in Malaysia; they are therefore likely to remain in the landscape given their size and economic value. Small and medium sized fragments, however, are typically afforded low conservation and economic status and their long-term fate rests in the hands of plantation managers, local landowners and the state government. Our study suggests that fragments > 300 ha can support considerable bat diversity. In addition, although small fragments do not appear to support the rare, specialist species of most conservation concern, they contribute substantially to landscape-level bat diversity, and may also facilitate the movements of some species across managed landscapes. By comparison, a preliminary study of bat diversity in rubber and oil palm plantations suggests that these plantation types host a much more depauperate bat fauna compared to forest (Danielsen and Heegaard, 1995). With demonstrated predation impacts on arthropod popula-

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tions in agricultural areas (Williams-Guille´n et al., 2008), insectivorous bats have an ecosystem value that could benefit plantation managers. Hence, protecting large tracts of forest, while retaining some forest fragments in plantations should form an integral part of landscape planning, and has the potential to both benefit plantation management and bat conservation.

Acknowledgements We are grateful to Christoph Meyer and an anonymous reviewer for critical suggestions that greatly improved the manuscript. Thanks to the Economic Planning Unit of the Malaysian Government for granting us permission to conduct bat research in Malaysia, and the Malaysian Department of Wildlife and National Parks (DWNP), the Pahang

1 4 1 ( 2 0 0 8 ) 2 1 1 2 –2 1 2 6

State Forestry Department, the Federal Land Development Authority (FELDA), and numerous private landowners for allowing us access to research sites. Thanks also to Paul _ Banks, Monika Bozek, Christine Fletcher, Joanne Kelly, LeeSim Lim, Juliana Senawi, Rakhmad Sujarno Kudus, Anthony Turner and Zamiza Zainal for assistance with fieldwork, and to Richard Nichols and Philippa Lincoln for statistical advice. Research in fragments was funded by a PhD studentship awarded to MJS from the Natural Environment Research Council UK, and a grant from Bat Conservation International/US Forest Service. Research in Krau Wildlife Reserve was supported by grants to TK from Lubee Bat Conservancy, National Science Foundation (NSF # 0108384, DEB & East Asia and Pacific Program), Earthwatch Institute, and National Geographic (Committee for Research & Exploration; Conservation Trust).

Appendix 1 Fragment and continuous forest sites visited in the Krau landscape, peninsular Malaysia, between May 2002 and June 2007, with a summary of bat survey results Site name

Surrounding land-usea

Area (ha)

Isolation (km)b

Nearest forest (km)c

Trap nights

Nd

Sobse

A, O A, O O, R O A R, O, G O O, R, G R, O, G R, O, G O, R C, O O O, G R, G C, G, R R, G, O R, G R, G O O, R A, P O, R O, R O, R O, R R F F F F

2883 11 339 100 1838 551 443 1356 353 31 319 122 161 44 400 160 93 32 115 100 300 5225 107 5581 2025 32 35 3 137 000 137 000 137 000 137 000

7.7 7.5 7.4 2.5 18.1 3.7 12.3 2.1 5.0 8.1 8.8 6.9 3.0 7.4 4.6 5.5 6.3 6.6 13.4 14.7 11.0 5.6 5.5 7.6 4.6 3.6 10.8 – – – –

0.6 1.2 2.3 1.9 1.2 1.4 0.6 1.0 0.6 0.6 1.7 0.4 1.3 2.3 1.8 0.6 0.5 0.3 0.7 0.7 1.8 2.1 0.7 0.6 1.2 1.1 0.6 – – – –

28 40 27 27 14 38 15 16 15 29 15 14 9 21 14 16 22 17 14 13 22 16 17 19 16 8 5 330 356 355 356

137 220 90 97 18 120 483 44 43 93 23 30 11 85 219 33 75 42 35 202 107 43 358 105 20 122 2 998 1491 614 1194

16 19 12 14 5 20 15 11 11 16 5 10 5 17 20 10 19 13 9 8 16 12 19 13 7 12 2 29 28 30 25

F, Fragment; S, Continuous forest (KWR) F01 F02 F03 F04h F05 F06 F07g F08 F09 F10 F11 F12h F13f F14h F15 F16 F17 F18 F19f,h F20g F21 F22 F23h F24 F25 F26 F27 S01 S02 S03 S04

Kemasul 1: 3°23 0 N, 102°11 0 E Kemasul 2: 3°26 0 N, 102°08 0 E RTP Lembah Klau: 3°42 0 N, 101°58 0 E FELDA Jenderak: 3°37 0 N, 102°19 0 E Bukit Besar: 3°22 0 N,102°15 0 E Klau Kecil: 3°47 0 N, 101°53 0 E Gunung Senyum: 3°41 0 N, 102°27 0 E Paya Luas: 3°42 0 N, 102°19 0 E Paya Parit: 3°41 0 N, 102°23 0 E Hutan Kerdau: 3°39 0 N, 102°25 0 E Ulu Rugan: 3°36 0 N, 102°20 0 E Dato’ Shariff: 3°40 0 N, 102°23 0 E Kampung Gun: 3°33 0 N, 101°58 0 E Kampung Lebu: 3°38 0 N, 101°56 0 E Rumpun Makmur: 3°43 0 N, 102°23 0 E Tebing Tinggi: 3°51 0 N, 102°23 0 E Bukit Dinding: 3°49 0 N, 102°24 0 E Bukit Ketupat: 3°48 0 N, 102°24 0 E Paya Perak: 3°36 0 N, 102°26 0 E Batu Sawar: 3°39 0 N, 102°28 0 E Belungu: 3°44 0 N, 102°33 0 E Desa Bakti: 3°48 0 N, 102°28 0 E Klau Besar: 3°75 0 N, 101°89 0 E Jengka: 3°59 0 N, 102°47 0 E Jambu Rias: 3°45 0 N, 102°10 0 E Karak: 3°41 0 N, 102°05 0 E Tasek Chatin: 3°47 0 N, 102°35 0 E Kuala Lompat: 3°43 0 N, 102°17 0 E Lubuk Baung: 3°43 0 N, 102°13 0 E Kuala Serloh: 3°40 0 N, 102°10 0 E Kuala Gandah: 3°36 0 N, 102°09 0 E

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Appendix 1 (continued) Site name

Surrounding land-usea

Area (ha)

Isolation (km)b

Nearest forest (km)c

Trap nights

Nd

F F, G F, G

137 000 137 000 137 000

– – –

– – –

370 39 24

1766 821 604

Sobse

F, Fragment; S, Continuous forest (KWR) S05 S06 S07

Jenderak Selatan: 3°38 0 N, 102°17 0 E Lembah Klau: 3°42 0 N, 102°03 0 E Perlok: 3°49 0 N, 102°13 0 E

27 15 17

a Land-use surrounding the site in order of increasing area. A, Acacia plantation; O, oil palm plantation; P, pine plantation; R, rubber plantation; C, cleared land; F, forest; G, mixed gardens. b The nearest straight-line distance to continuous forest. c The straight-line distance to the nearest forest fragment. d Total number of individuals captured at a site, including recaptures from other sites, but excluding those within a site. e Observed species richness for all insectivorous bat species. f Sites in which surveys were influenced by heavy rain. g The Gunung Senyum fragment (F07) contains an outcrop of karst limestone with very large abundances of cave-roosting bats, which skewed analyses for both this fragment and the nearest neighbour Batu Sawar (F20). Hence, these fragments were excluded from subsequent analyses on these grounds. h Fragments of reduced area since 2002 due to recent or current forest clearance. Area estimates are corrected based on observations on the ground and inspection of local forest maps if available.

Appendix 2 Bat species surveyed in the Krau landscape during this study FAMILY/Taxon

Species code

Red list statusa

Landscape distributionb

Ensemblec

No. continuous sites occupied(Nmax = 7)d

No. fragments occupied(Nmax= 27)d

MEGADERMATIDAE Megaderma spasma

Msp

R

T

5

1

NYCTERIDAE Nycteris tragata

Ntr

R

T

7

7

EMBALLONURIDAE Emballonura monticola

Emo

R

E

5

2

RHINOLOPHIDAE Rhinolophus affinis Rhinolophus lepiduse Rhinolophus luctus Rhinolophus macrotis Rhinolophus robinsoni Rhinolophus sedulus Rhinolophus stheno Rhinolophus trifoliatus

Raf Rle Rlu Rma Rro Rse Rst Rtr

W W R R R

C C T T C T C T

7 7 3 1 4 5 7 6

22 22 6 2 2 13 17 23

HIPPOSIDERIDAE Coelops robinsoni Hipposideros armiger Hipposideros bicolor 131f Hipposideros bicolor 142f Hipposideros cervinus Hipposideros cineraceus Hipposideros diadema Hipposideros doriaee Hipposideros galeritus

Cro Har Hb31 Hb42 Hce Hci Hdi Hdo Hga

T C C C C C C T C

4 1 7 7 7 4 7 4 1

0 0 18 13 19 5 17 5 3 (continued on next page)

NT W

NT

A A

R NT

R R

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Appendix 2 (continued) FAMILY/Taxon

Hipposideros larvatus Hipposideros lylei Hipposideros ridleyi VESPERTILIONIDAE Glischropus tylopus Harpiocephalus mordax Hesperoptenus blanfordi Kerivoula hardwickii Kerivoula intermedia Kerivoula krauensise Kerivoula minuta Kerivoula papillosa Kerivoula pellucida Miniopterus medius/schreibersiig Murina aenea Murina cyclotis Murina rozendaali Murina suilla Myotis ater Myotis horsefieldi Myotis ridleyi Myotis siligorensis Phoniscus atrox Phoniscus jagorii Scotophilus kuhlii Tylopus pachypus Tylopus robustula

Species Red list Landscape Ensemblec No. continuous No. fragments code statusa distributionb sites occupied(Nmax = 7)d occupied(Nmax= 27)d Hla Hly Hri

Gty Hmo Hbl Kha Kin Kkr Kmi Kpa Kpe Msc Mae Mcy Mro Msu Mat Mho Mri Msi Pat Pja Sku Tpa Tro

NT VU

F

VU

A F R

NT nc NT

NT VU VU

NT

A

R A W

R A R R F R R

C C T

3 0 5

13 1 7

E T E T T T T T T E T T T T E E E E T T E E E

0 2 0 2 7 4 1 7 7 0 3 7 4 6 1 3 5 1 6 1 0 1 1

8 0 1 1 13 0 1 19 15 6 1 4 0 23 8 1 4 0 8 2 1 2 0

a IUCN red list status following review by the Southeast Asian Mammal Databank (http://www.ieaitaly.org/samd/. Accessed 31 March 2008): NT, Near Threatened; VU, Vulnerable; nc, not yet classified. b Landscape distribution of species based on presence and abundance at sites in continuous and fragmented forest. W, widespread, present in at least 70% of fragments, and all continuous forest sites; R, rare, comprise < 1% of combined captures from all sites; A, absent from fragments; and F, absent from continuous forest. c T, cavity/foliage-roosting narrow-space species; C, cave-roosting narrow-space species; E, edge/open space foraging species. d The number of sites occupied does not control for the different trapping effort applied to each site. Therefore absence at a site does not necessarily reflect true absence. e Kingston et al. (2003) included R. lepidus as R. refulgens, H. doriae as H. sabanus, and K. krauensis as K.sp. We follow the updated nomenclature in: Simmons (2005) Chiroptera, In: Wilson DE, Reeder DM (eds) Mammal species of the World: a taxonomic and geographic reference. John Hopkins University Press, Baltimore, pp 312-529, and Francis, C.M., Kingston, T., Zubaid, A., 2007. A new species of Kerivoula (Chiroptera: Vespertilionidae) from peninsular Malaysia. Acta Chiropterologica 9, 1–12. f Hipposideros ‘bicolor’ comprises two phonic types with mean echolocation call frequencies of 131 kHz and 142 kHz. They differ genetically enough to warrant treatment as separate taxa and can be distinguished in the hand by subtle differences in noseleaf shape, forearm length and tibia length (Kingston et al., 2006). g Miniopterus individuals captured could not be reliably identified by external measurements to medius or schreibersii. The red list status is Least Concern for M. medius, and Near Threatened for M. schreibersii.

R E F E R E N C E S

Allen, D. 2005. Foraging ecology of Kerivoula papillosa. MSc thesis, University of East Anglia, Norwich. Altringham, J.D., 1999. Bats: Biology and Behaviour. Oxford University Press, Oxford. Baayan, R.H., 2008. The languageR package for R: data sets and functions with ‘‘Analyzing linguistic data: A practical introduction to statistics’’, version 0.92, .

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