Agriculture, Ecosystems and Environment 233 (2016) 140–146
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Agriculture, Ecosystems and Environment
journa l homepage: www.elsevier.com/locate/agee
Nocturnal bird composition in relation to habitat heterogeneity in
small scale oil palm agriculture in Malaysia
a a,b,c, a,b
Muhammad Syafiq Yahya , Chong Leong Puan *, Badrul Azhar ,
a a
Sharifah Nur Atikah , Amal Ghazali
a
Faculty of Forestry, Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor, Malaysia
b
Biodiversity Unit, Institute of Bioscience, Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor, Malaysia
c
Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Republic of Singapore
A R T I C L E I N F O A B S T R A C T
Article history:
Received 5 May 2016 The expansion of oil palm cultivation is recognised as a major cause of tropical biodiversity loss. In
Received in revised form 27 August 2016 contrast to large-scale plantations, oil palm smallholdings being more heterogeneous may support
Accepted 9 September 2016
greater biodiversity. This study examined the effects of local and landscape level variables on the
Available online xxx
composition of nocturnal bird species in Malaysian oil palm smallholdings. Using visual and aural point
sampling, we made 1408 encounters with nine owl and two nightjar species. The Biota-Environment-
Keywords:
Stepwise matching analyses (BEST) indicated four predictor variables (three local variables; number of
Nocturnal birds
crop species, widths of roads and trenches, and one landscape variable; distance to the nearest main
Oil palm smallholding
road) significantly influenced the community assemblages of nocturnal bird species in the smallholdings.
Habitat heterogeneity
Generalized Linear Models (GLMs) further indicated seven predictor variables (numbers of palms and
Community assemblage
houses, widths of roads and trenches, distances to the nearest forest and house, as well as palm height)
Malaysian owls
significantly influenced the abundances of certain nocturnal species. These findings not only improve our
understanding on habitat preference of nocturnal birds in the Sunda region but also support the
argument that habitat complexity in cultivated areas may aid in biodiversity conservation, at least for
nocturnal birds.
ã 2016 Published by Elsevier B.V.
1. Introduction Malaysia and Indonesia are two leading countries in the global
palm oil trade (FAO, 2015). By 2005, the two countries accounted
Originating from West and Central Africa, oil palms (Elaeis for about 83% of the world’s palm oil production and dominated
guineensis) have been planted on a vast scale throughout many 89% of the global exports of palm oil (Brown and Jacobson, 2005).
developing countries in humid tropical regions (Wakker et al., Currently, Malaysia alone contributes about 39% of global palm oil
2004; Koh and Wilcove, 2007, 2008; Corley and Tinker, 2008; production and 44% of the world exports (MPOC, 2012). To date, oil
Fitzherbert et al., 2008; Tan et al., 2009). Triacylglycerol (or palm palm cultivation makes up 77% of the total agricultural area of
oil) derived from the palms is a main ingredient for a huge variety Malaysia covering about 15% of the total 33 million ha land area of
of edible, cosmetic and industrial products (Pearce, 2008) and it the country (MPOC, 2012). In Malaysia, there are two main types of
has become a major component of the national economy in many oil palm management, namely plantations and smallholdings.
developing countries (e.g. Malaysia, Indonesia and Brazil) (Koh and Plantations are industrial scale monoculture planting systems of
Wilcove, 2008; Shuit et al., 2009). In Southeast Asia, millions of typically more than 500 ha. They are managed mostly by
hectares of forested land have been converted into oil palm companies or government owned corporations. On the other
cultivation over the last few decades (Koh and Wilcove, 2007; hand, smallholdings are owned by local farmers who practice
Groom et al., 2008). small-scale planting strategies involving intercropping with other
cultivated plants, within an area sometimes as little as 5 ha (Ismail
et al., 2003; Azhar et al., 2011; Jambari et al., 2012).
Undeniably, the existence of this monoculture landscape has
altered the biological communities that were present before
* Corresponding author at: Faculty of Forestry, Universiti Putra Malaysia, 43400
UPM, Serdang, Selangor, Malaysia. cultivation was established. Yet, in spite of rigorous agricultural
E-mail addresses: [email protected], [email protected] (C.L. Puan). management, even homogeneously structured, big oil palm
http://dx.doi.org/10.1016/j.agee.2016.09.003
0167-8809/ã 2016 Published by Elsevier B.V.
M.S. Yahya et al. / Agriculture, Ecosystems and Environment 233 (2016) 140–146 141
plantations have been shown to serve as habitat for some fauna particularly in smallholdings that practice intercropping. Both
species (Azhar et al., 2011; Jambari et al., 2012). Despite the local and landscape level structure found in smallholdings are
number of species found in oil palm cultivation being far below different from those of large-scale plantations (Azhar et al., 2011,
that found in natural forests, oil palm cultivation supports 2015). Hence, this study examined the effects of local and
considerable species numbers, e.g. in the case of birds (Koh, landscape level variables on the composition and abundance of
2008; Azhar et al., 2011, 2014a; Jambari et al., 2012), mammals nocturnal bird species in oil palm smallholdings in Peninsular
(Azhar et al., 2014b) and insects (Krooss and Schaefer, 1998; Malaysia, with prior knowledge on the occurrence of these birds in
Wickramasinghe et al., 2004; Koh, 2008; Turner and Foster, 2008). these areas (Atikah et al., 2013).
Such findings indicate the possibility of cultivated areas function-
ing either as a main or an alternative habitat for species which are 2. Methods
able to adapt to this environment.
Unusual features of the oil palm agro-ecosystem give its 2.1. Study sites
nocturnal avifauna special interest. An abundant year-round oil-
rich crop can attract many rodents, e.g. squirrels and treeshrews by We conducted the study in the oil palm smallholdings
0 00
day, which are replaced by high population densities of various rat (approximately 5300 ha) located at Banting (2 47 48 N,
0 00 0 00 0 00
species by night (Wood, 1968; Medway, 1983; Puan, 2013). Oil 101 31 10 E), Tanjung Karang (3 24 24 N, 101 15 26 E) and Sabak
0 00 0 00
palms contain almost no cavities suitable for hole-nesting owls and Bernam (3 50 50 N, 100 53 19 E), Selangor state, Peninsular
hence opportunities for predatory birds are constrained by the Malaysia (Fig. 1). The three sites were selected for this study to
scarcity of nest sites. Further, the continuous canopy of palm fronds increase the range of potential habitat variability sampled. On
may interfere with typical bird foraging methods and there are average at each site, there were about 20–30 smallholders who
risks from management practices such as rodent poisoning (Puan, individually owned an area that ranged from 1 to 50 ha. All study
2013). Previous studies in Malaysian oil palm plantations have sites were located in the western part of Peninsular Malaysia and
suggested that Common Barn-owls (Tyto alba) may provide had similar topographical features (a flat coastal area with an
biological control of rats in oil palm plantations (Lenton, 1984; altitude ranged from 4 to 11 m above sea level and the surrounding
Hafidzi and Naim, 2003; Puan et al., 2012; Puan, 2013 Puan, 2013). landscape matrices comprised mangrove forests, peat swamp
Besides Barn-owls, oil palm plantations frequently serve as forests and/or paddy fields). The study sites were primarily planted
habitats for other owls, i.e. Spotted Wood-owl (Strix seluputo) with oil palms which were intercropped with banana (Musa spp.),
and Sunda Scops-owl (Otus lempiji) (Puan, 2013), and a study coconut (Cocos nucifera) and/or jackfruit (Artocarpus heterophyllus),
conducted in oil palm smallholdings in Malaysia recorded several and other subsistence crops. Unlike large scale plantations, the
other species that are more typically associated with forest planting systems employed by the smallholders varied resulting in
habitats (i.e. Brown Wood-owl (Strix leptogrammica) and Dusky a non-uniform pattern of palm age (1–15 years old), palm spacing
Eagle-owl (Bubo coromandus) (Atikah et al., 2013). This raises and arrangement as well as openness of understory stratum and
questions about nocturnal avian community structure, the relative availability of frond piles. Palm stands of three years old and above
importance of predators and insectivores in such a habitat, the typically start producing fruit bunches throughout the year. The
significance of oil palm cultivation as supplemental habitat for average daily temperature and humidity were similar at all sites
otherwise forest-dependent species, and the effects of landscape and ranged from 24 to 33 C and 65 to 70%, respectively (MET,
scale influences such as distance from forest. Other than food 2014). There were roads (being frequently used by smallholders to
availability (Atikah et al., 2013), local and landscape level habitat transport fruit bunches and/or carry out daily activities) and
structure may influence the composition of nocturnal birds trenches (as part of the irrigation system that was usually
Fig. 1. Location of study sites; (A) Sabak Bernam, (B) Tanjung Karang and (C) Banting.
142 M.S. Yahya et al. / Agriculture, Ecosystems and Environment 233 (2016) 140–146
waterlogged, depending on the season) within the smallholdings. Hempstead, United Kingdom). To examine the relationship
There were also residential areas located within the study areas between species abundance and predictor variables, we per-
with basic infrastructure (i.e. roads, schools, etc.). formed Generalized Linear Models (GLMs) to develop predictive
models for four nocturnal bird species (i.e. Large-tailed Nightjar,
2.2. Survey of nocturnal birds Sunda Scops-owl, Spotted Wood-owl and Common Barn-owl) due
to larger data collected for these species. We regressed the
A total of 90 points were established (30 points in each of the abundance of the selected species as response metrics against all
three study sites). The points were pre-determined through Google predictor variables. Poisson distribution, logarithm as link
Earth software (Google Inc.) based on systematic sampling with a function, and sites were incorporated as grouping factors for
random starting point, similar to previous studies at the same sites each modeling process. We reported the slope values for each
(Ghazali et al., 2016; Syafiq et al., 2016). By using a portable GPS significant predictor variable.
(Garmin), we recorded the coordinates and altitudes of the survey We determined the most parsimonious models by using
points. Points were located more than 800 m apart in order to avoid Information Theoretic (IT) approach by considering all possible
double counting (Takats et al., 2001). At each sampling point, subset regression analyses. The best models for each selected
surveys were conducted for three times from January to April 2014 species were selected by choosing the minimum value of Akaike’s
and repeated for another three times from June to August 2014 in Information Criterion (AIC). The values of corrected AIC (AICc)
order to increase the encounters with targeted birds. These periods were then calculated and the values of AIC differences (Di), relative
covered both breeding and non-breeding seasons of the focal likelihoods (RL), and Akaike weight (Wi) were derived from the
species. The surveys were conducted from 1900 to 0200 h daily, corrected AIC values.
weather permitting or otherwise, the survey was resumed the next
night. On each night, for safety and species validation reasons, two 3. Results
experienced surveyors simultaneously stayed at each sampling
point for ten minutes to detect birds through sight and/or 3.1. Bird composition and diversity indices
vocalization. Due to low visibility, the presence of nocturnal birds
was mostly detected by their vocalization, similar to other studies We recorded a total of 11 species (1408 encounters) of nocturnal
(Gerhardt, 1991; Takats and Holroyd, 1997; Takats et al., 2001; birds from three families (Caprimulgidae, Tytonidae and Strigidae)
Delport et al., 2002; Newton et al., 2002; Kemp et al., 2009). No call (Table 1) and no other bird species were recorded. This includes
playbacks were used in this study. nine owl and two nightjar species out of the total 14 owl and four
nightjar species resident in Peninsular Malaysia (MNS, 2012).
2.3. Measurements of local and landscape level variables Throughout the study, we recorded all the species that had been
recorded by previous research conducted in the oil palm small-
We measured and estimated five local level variables at each holdings located in Selangor state, Peninsular Malaysia (Atikah
sampling point within 30 m radius: (i) average height of oil palms et al., 2013), all of which are listed as Least Concern species (IUCN,
(HP) measured in m from the highest frond using a Haga altimeter; 2014).
(ii) number of oil palms (NP); (iii) number of crop species (NC); and The most abundant species were Large-tailed Nightjar (Capri-
(iv) widths of trenches (WT) and roads (WR), which were found at mulgus macrurus; 25.82% of the total encounters), followed by
all sampling points were measured in m using a measuring tape. Spotted Wood-owl (24.74%), Sunda Scops-owl (19.73%), Common
Four landscape level variables measured at each sampling point Barn-owl (5.75%), Savanna Nightjar (Caprimulgus affinis; 1.14%),
include: (i) number of human houses (NS) at 100 m radius; (ii) Oriental Bay-owl (Phodilus badius; 0.85%) and Buffy Fish-owl
distances to the nearest forest patch (DF), (iii) main road (DR), and (Ketupa ketupu; 1.08%; Table 1), all of which are species of open and
(iv) human house (DS) measured in m. We used the ruler tool in semi-open habitats, except for the Oriental Bay-owl which tends to
Google Earth Pro (Google Inc., USA) to measure these variables. be associated with a more wooded habitat (König et al., 1999;
Wells, 1999; Robson, 2000). We also recorded four nocturnal
2.4. Statistical analyses species which were associated with forest habitats, i.e. Barred
Eagle-owl (Bubo sumatranus; 0.05% of the total encounters), Dusky
We used the Shannon Wiener (H’) indices to measure the Eagle-owl (0.05%), Brown Wood-owl (0.74%), and Brown Boobook
diversity of nocturnal bird species in oil palm smallholdings. We (Ninox scutulata; 0.11% of the encounters based on vocalization;
applied bootstrap estimation on the diversity index by 100 King, 2002). The diversity index of nocturnal birds in the oil palm
permutations to increase the precision of the calculations. Both smallholdings was 3.359, or 4.731 0.004 based on bootstrap
non-permutated and permutated estimation values of the indices estimation.
were reported.
We used Similarity Percentages test (SIMPER) to examine 3.2. Bird abundances, community assemblages and influencing factors
species' contribution into the community assemblages, followed
by Biota-Environment-Stepwise matching analyses (BEST) SIMPER indicated that Spotted Wood-owl (with 36.88%
(Clarke and Ainsworth, 1993) to determine variables that contribution to similarity), Large-tailed Nightjar (29.79%) and
contributed into the community assemblage of the nocturnal Sunda Scops-owl (24.11%) were the highest contributing species
birds in oil palm smallholdings. For SIMPER, we reported the with the cumulative percentage of 90.78% of the community
contribution of each nocturnal species recorded to the commu- assemblage. BEST indicated model with four variables (i.e. distance
nity assemblage. For BEST, we reported the correlation coefficient, to the nearest main road, number of crop species, widths of roads
r and predictor variables which were selected through the most and trenches) were the most parsimonious model (r = 0.134).
parsimonious model. Both SIMPER and BEST were performed GLMs indicated that four local level variables (i.e. average
using Primer-e Version 6 (Primer-e Ltd., Ivybridge, United height of oil palms, number of oil palms, widths of the roads and
Kingdom). trenches) significantly influenced the abundance of specific
Prior to modeling work, a correlation was performed to detect nocturnal birds (P < 0.05) in the smallholdings. The average height
multicollinearity among all the predictor variables, if any, by of oil palms was positively and significantly affected the abundance
using GenStat 12th edition (VSN International Ltd., Hemel of Spotted Wood-owl (slope = 0.537) whereas it was negatively and
M.S. Yahya et al. / Agriculture, Ecosystems and Environment 233 (2016) 140–146 143
Table 1
Nocturnal bird species recorded in oil palm smallholdings in Banting, Tanjung Karang and Sabak Bernam, Peninsular Malaysia.
Family Species Number of encounters Mean observations per point Species contribution (%)*
Banting Tanjung Sabak Total
Karang Bernam
Caprimulgidae Large-tailed Caprimulgus 230 138 86 454 5.04 29.79
Nightjar macrurus
Savanna Nightjar Caprimulgus affinis 20 0 0 20 0.22 N/A
Tytonidae Common Barn-owl Tyto alba 36 36 29 101 1.12 N/A
Oriental Bay-owl Phodilus badius 0 10 5 15 0.16 N/A
Strigidae Spotted Wood-owl Strix seloputo 122 134 179 435 4.83 36.88
Sunda Scops-owl Otus lempiji 182 92 73 347 3.86 24.11
Buffy Fish-owl Ketupa ketupu 9 3 7 19 0.21 N/A
Brown Wood-owl Strix leptogrammica 1 8 4 13 0.14 N/A
Brown Boobook Ninox scutulata 1 1 0 2 0.02 N/A
Dusky Eagle-owl Bubo coromandus 0 1 0 1 0.01 N/A
Barred Eagle-owl Bubo sumatranus 0 0 1 1 0.01 N/A
Total 601 423 384 1408 90.78
*
Species-specific contribution in community assemblage derived from SIMPER.
significantly associated with the abundances of Large-tailed recorded fewer birds at sampling points located near or on the
Nightjars (slope = –0.108) and Sunda Scops-owls (slope = –0.155). main roads, which may have been due to disturbance (e.g. as a
On the other hand, the number of oil palms positively and result of vehicle movements; Goosem, 2007). We observed that
significantly affected the abundance of the Sunda Scops-owls the traffic at major roads can be particularly high and noisy in the
(slope = 0.023). Width of roads was negatively and significantly evening. Wider roads may also expose the birds to potential
correlated to the abundance of Large-tailed Nightjars (slope = – predators such as stray dogs which were found in the study
0.117) and Sunda Scops-owls (slope = –0.096). The abundance of areas. However, the underlying reasons for such a relationship
Common Barn-owls was positively and significantly affected by between these birds and the roads deserves further investigation.
width of trenches (slope = 0.126). We found that three predictor variables (i.e. palm height,
GLMs showed that all landscape variables (i.e. number of distance to human houses, and width of trenches) significantly
houses, distance to the nearest forest and distance to human influenced the abundance of large bodied nocturnal birds in the
houses), except for distance to the nearest main road, significantly smallholdings. GLMs performed on data for Spotted Wood-owl
influenced the abundance of selected nocturnal bird species. The suggested that its abundance increased significantly with the
number of houses in a radius of 100 m from the sampling points height of oil palms but significantly decreased with the number of
negatively and significantly affected the abundance of Large-tailed houses. This demonstrated the importance of mature palms (six
Nightjars (slope = –0.086), Sunda Scops-owl (slope = –0.094) and years and above in this case with an average height of 7–8 m) as
Spotted Wood-owls (slope = –0.060). The distance to the nearest perching and hunting spots for the owl. We also suspect that palms
forest negatively and significantly affected abundance of Large- with such height may facilitate the owl’s hunting with respect to
tailed Nightjars (slope = –0.145). Lastly, the distance to the nearest the openness of the hunting territory and/or flight paths. In fact,
house positively and significantly influenced the abundance of during the survey, we often observed these owls perching on tall
Sunda Scops-owls (slope = 0.429). palms. Such behaviour can also be observed for other large diurnal
The model with four predictor variables (average height of oil raptors (i.e. Brahminy Kite (Haliastur indus) and Black-shouldered
palms, width of roads, distance to the nearest forest and number Kite (Elanus axillaris)) which are also associated with agro-
of houses per 100 m radius) was the most parsimonious model ecosystem habitat. We recorded fewer Spotted Wood-owls at
for Large-tailed Nightjar, with the minimum AIC of 93.76 areas with a higher density of human houses which may be related
2
(AICc = 94.47, R = 60.01) (Table 2). The most parsimonious model to the higher level of human disturbance (i.e. higher traffic
for Spotted Wood-owl had two predictors (average height of oil intensity and noise pollution). We found that the abundance of
palms and number of houses per 100 m radius) with the Common Barn-owls increased with the width of the trenches. The
2
minimum AIC of 85.57 (AICc = 89.85, R = 22.87). The combination abundance of this species was lower than that of the Spotted
of five predictor variables (average height of oil palms, number of Wood-owl. The reasons for this are not known, however, we
oil palms, width of roads, distance to the nearest house from the suspect that there may be an interspecific interaction between the
survey point and number of houses within a 100 m radius) two species (Puan, 2013). This hypothesis awaits further investi-
produced the most parsimonious model for the Sunda Scops-owl gation.
2
with the minimum AIC of 96.21 (AICc = 97.22, R = 53.24). For For small bodied birds, we found that five predictor variables
Common Barn-owl, the model with one predictor variable (width (i.e. number of palms, palm height, distance to house, number of
2
of trenches) and the minimum AIC of 91.52 (AICc = 91.66, R = 9.41) residential houses and width of roads) had a significant influence
was selected. on abundance. GLMs indicated that the number of Sunda Scops-
owls increased significantly with the number of palms and
4. Discussion distance to human houses, but decreased with palm height and
the width of roads. For the Large-tailed Nightjar, GLMs suggested
Our results suggest that the distance to the nearest main road that places with shorter oil palms, narrow roads, far away from
along with widths of roads and trenches may act as potential forested areas and with a lower number of human houses would
landscape barriers to some nocturnal bird species. In fact, we positively influence the abundance of the bird. Lower average
144 M.S. Yahya et al. / Agriculture, Ecosystems and Environment 233 (2016) 140–146
Table 2
Results of GLMs with all possible subset regression models and the most parsimonious models (in bold; at a 5% significance level) determined based on the smallest values of
Akaike’s Information Criterion (AIC) for respective species (AICc, Di, and Wi are the corrected AIC, AIC differences; and Akaike weight, respectively).
2
Model No. of terms Term(s) R AIC AICc Di Relative Likelihoods Wi
7 8
Sunda 1 DS 27.76 127.92 127.965 30.745 2.11 10 5.983 10
5 6
Scops-owl 2 WR + DS 34.40 118.53 118.668 21.446 2.20 10 6.253 10
3 4
3 HP + NS + S 42.58 108.50 108.779 11.557 3.09 10 8.779 10
1 2
4 HP + WR + DS + S 47.95 101.29 101.760 4.538 1.03 10 2.923 10
1 1
5 HP +WR+ DS + NS + S 51.75 96.77 97.480 0.258 8.79 10 2.50 10
1
6 HP+ NP + WR + DS + NS + S 53.24 96.21 97.222 0.000 1.00 2.90 10
1 1
7 HP + NC + NP + WR + DS + NS + S 53.77 97.30 98.666 1.444 4.86 10 1.38 10
1 2
8 HP + NC + NP + WR + DF + DS + NS + S 54.26 98.47 100.248 3.026 2.20 10 6.25 10
2 2
9 HP + NC + NP + WR + WT + DF + DS + NS + S 54.43 100 102.250 5.028 8.10 10 2.30 10
2 3
10 HP + NC + NP + WR + WT + DF + DR + DS + NS + S 54.53 102.00 104.785 7.563 2.30 10 6.471 10
2 2
Spotted 1 S 12.60 96.16 96.205 6.356 4.17 10 1.86 10
1 1
Wood-owl 2 NS + S 19.58 90.95 91.088 1.239 5.38 10 2.40 10
1
3 HP + NS + S 22.87 89.57 89.849 0.000 1.00 4.46 10
1 2
4 HP+ NP +NS + S 23.19 91.23 91.701 1.852 3.96 10 1.86 10
1 2
5 HP + NP + DF + NS + S 23.69 92.72 93.434 3.585 1.67 10 7.44 10
2 2
6 HP + NP + DF + DSNS + S 24.11 94.29 95.302 5.453 6.54 10 2.92 10
2 3
7 HP +NP + DF + DR + DS + NS + S 24.22 96.17 97.536 7.687 2.14 10 9.60 10
3 3
8 HP+ NP + WR + DF + DR + DS + NS + S 24.30 98.08 99.858 10.009 6.70 10 3.00 10
3
9 HP + NC + NP+ WT+ DF + DR + DS + NS + S 24.37 100.01 102.260 12.411 2.01 10 9.02 10 4
4
10 HP + NC + NP + WR + WT + DF + DR + DS + NS + S 24.38 102.00 104.785 14.936 5.71 10 2.55 10 4
1 1
Common 1 WT 4.35 92.18 92.225 0.568 7.53 10 2.12 10
1
Barn-owl 2 WT + S 9.41 91.52 91.658 0.000 1.00 2.81 10
1 1
3 WR + WT +S 10.77 92.25 92.529 0.871 6.47 10 1.82 10
1 1
4 NC + NP + WT+ S 13.01 92.19 92.661 1.003 6.06 10 1.70 10
1 2
5 NC + NP + WR + WT+ S 14.23 93.07 93.784 2.126 3.45 10 9.71 10
1 2
6 NC + NP + WR + WT+ DS + S 14.73 94.61 95.622 3.964 1.38 10 3.87 10
2 2
7 NC + NP + WR + WT+ DF + DR + S 14.86 96.46 97.826 6.168 4.58 10 1.29 10
2 3
8 NC + NP + WR + WT+ DF + DR + DS + S 15.27 98.11 99.888 8.230 1.63 10 4.60 10
3 3
9 HP + NC + NP + WR + WT + DF + DR + DS + S 15.34 100.04 102.290 10.632 4.89 10 1.90 10
3 4
10 HP + NC + NP + WR + WT + DF + DR + DS + NS + S 15.39 102.00 104.785 13.127 1.40 10 3.97 10
11 12
Large- tailed 1 DR 29.37 144.87 144.915 50.441 1.11 10 6.36 10
7 8
Nightjar 2 DR + WR 39.86 125.95 126.088 31.614 1.37 10 7.80 10
4 4
3 DF + NS + S 49.59 110.55 110.829 16.355 2.81 10 1.60 10
2 2
4 HP+ DF + NS + S 55.47 100.81 101.281 6.806 3.33 10 1.90 10
1
5 HP + WR + DF + NS + S 60.01 93.76 94.474 0.000 1.00 5.71 10
1 1
6 HP + WR + WT+ DF + NS + S 60.34 95.10 96.112 1.638 4.41 10 2.51 10
1 1
7 HP + NC+ WR + WT+ DF + NS + S 60.66 96.47 97.836 3.362 1.86 10 1.06 10
2 2
8 HP + NC+ WR + WT+ DF + DR + NS + S 60.81 98.17 99.948 5.473 6.48 10 3.70 10
2 2
9 HP + NC+ WR + WT+ DTF + DR + DS + NS + S 60.88 100.03 102.280 7.806 2.02 10 1.15 10
3 3
10 HP + NC + NP + WR + WT + DF + DR + DS + NS + S 60.89 102.00 104.785 10.311 5.769 10 3.294 10
Variables; DF – distance to the nearest forest; DR – distance to the nearest main road; DS – distance to the nearest house; HP – average height of oil palms; NC – number of crop
species; NP – number of oil palm; NS – number of houses per 100 m radius; S – site; WR – width of roads; WT – width of trenches.
height of palms is expected to make the area more accessible for 5. Management and conservation implications
the Large-tailed Nightjar that prefers to hunt in open or partly
open habitat (Wells, 1999), allowing easier visual or auditory This study helps fill in the knowledge gaps on the ecology of the
detection of prey, and greater maneuverability with fewer lesser known nocturnal birds in Malaysia, particularly in the
obstructions in flight. During this study, Large-tailed Nightjars context of oil palm agro-ecosystem. Even though the number of
were usually seen foraging close to the ground level along the forest associated species remained low in numbers throughout the
sides of narrow roads. On the other hand, young palms (prior to study, the observed nocturnal community in smallholdings (11
trunk formation) with their dense below-canopy appearance species) represents a substantial proportion of the Malaysian
may influence many aerial insects both in terms of their numbers nocturnal avifauna, with evidence of community structure
and flight pattern (Wood et al., 1973; Corley and Tinker, 2008). according to body size, diet, and local and landscape level habitat
Such an environment may provide a suitable hunting ground and variables.
cover from predators for the Sunda Scops-owl, which tends to be In the oil palm agro-ecosystem, with the majority of the land
more common in disturbed habitat with similar habitat features being planted with a single crop species, an ideal habitat is created
(i.e. dense undergrowth; Robson, 2000; Najmi-Hanis et al., 2016). for the proliferation of some insect and rodent populations due to
Likewise, it is believed that higher palm density also provides the the abundance of food sources (Wood, 1968). The abundance of
same foraging opportunity for this bird. However, the underlying insects emerging at night in oil palm smallholdings is likely to
interspecific relationships among the large and small bodied support plentiful nocturnal insectivores, which may in turn be
bird species in the smallholdings and whether there is a presence beneficial to farmers by means of biological control of insects as
of intraguild predation and/or competition among the species suggested by Koh (2008) for diurnal birds in Sabah, East Malaysia.
(Puan, 2013; Michel et al., 2016) require further study. In our study, all the three commonest nocturnal birds (Spotted
Wood-owl, Sunda Scops-owl and Large-tailed Nightjar) feed on
M.S. Yahya et al. / Agriculture, Ecosystems and Environment 233 (2016) 140–146 145
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This study was part of a larger nocturnal bird study in Malaysia
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funded by the Ministry of Higher Education Malaysia through (7157), 993–994.
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Fundamental Research Grant Scheme (Project No.: 07-01-13-
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