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Ostrich 2016, 87(3): 199–207 Printed in South Africa — All rights reserved
OSTRICH
ISSN 0030-6525 EISSN 1727-947X http://dx.doi.org/10.2989/00306525.2016.1216903
The influence of food abundance, food dispersion and habitat structure on territory selection and size of an Afrotropical terrestrial insectivore William D Newmark1* and Thomas R Stanley2 Natural History Museum of Utah, University of Utah, Salt Lake City, Utah, USA US Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA * Corresponding author, email:
[email protected] 1
2
Most tropical insectivorous birds, unlike their temperate counterparts, hold and defend a feeding and breeding territory year-around. However, our understanding of ecological factors influencing territory selection and size in tropical insectivores is limited. Here we examine three prominent hypotheses relating food abundance, food dispersion (spatial arrangement of food items), and habitat structure to territoriality in the Usambara Thrush Turdus roehli. We first compared leaf-litter macro-invertebrate abundance and dispersion, and habitat structure between territories and random sites. We then examined the relation between these same ecological factors and territory size. Invertebrate abundance and dispersion were sparsely and evenly distributed across our study system and did not vary between territories and random sites. In contrast, habitat structure did vary between territories and random sites indicating the Usambara Thrush selects territories with open understorey and closed overstorey habitat. Invertebrate abundance and dispersion within territories of the Usambara Thrush were not associated with habitat structure. We believe the most likely explanation for the Usambara Thrush’s preference for open understorey and closed overstorey habitat relates to foraging behavior. Using information-theoretic model selection we found that invertebrate abundance was the highest-ranked predictor of territory size and was inversely related, consistent with food value theory of territoriality.
Influence de la nourriture en termes d’abondance et de répartition, et de la structure de l’habitat sur le choix et la taille des territoires chez un insectivore terrestre afro-tropical La plupart des oiseaux insectivores tropicaux, à l’inverse de ceux des zones tempérées, maintiennent et défendent un territoire d’alimentation et de reproduction tout au long de l’année. Toutefois, les facteurs écologiques qui influencent le choix et la taille des territoires chez les insectivores tropicaux restent mal compris. Nous examinons ici trois importantes hypothèses liant l’abondance de la nourriture, sa répartition (disposition spatiale des éléments de nourriture) et la structure de l’habitat à la territorialité chez le Merle de Roehl Turdus roehli. Nous avons en premier lieu comparé l’abondance et la dispersion des macro-invertébrés de la litière de feuille ainsi que la structure d’habitat entre les territoires et des sites aléatoirement sélectionnés. Nous avons ensuite examiné la relation entre ces mêmes facteurs écologiques et la taille des territoires. L’abondance et la répartition des invertébrés s’avèrent faiblement et uniformément distribuées au sein de la zone étudiée, et ne présentent pas de différence entre les territoires et les sites aléatoirement choisis. En revanche, la structure de l’habitat entre les territoires et les autres sites présente des variations, montrant que le Merle de Roehl sélectionne les territoires disposant de sous-bois dégagés et de couverts denses. L’abondance et la répartition d’invertébrés au sein des territoires des Merles de Roehl ne sont pas associées à la structure de l’habitat. Le comportement de recherche alimentaire du Merle de Roehl fournit l’explication la plus probable à sa préférence pour les sous-bois ouverts et les couverts denses. A l’aide de modèles (information-theoretic model selection), l’abondance d’invertébrés s’avère le meilleur prédicteur de la taille du territoire, les deux étant inversement proportionnels et de ce fait en cohérence avec la théorie de la valeur alimentaire liée à la territorialité. Keywords: endangered species, food value hypothesis, habitat structure hypothesis, leaf-litter macro-invertebrates, resource dispersion hypothesis, structural cues hypothesis Online supplementary material: Supplementary data for this article are available at http://dx.doi.org/10.2989/00306525.2016.1216903
Introduction Among tropical understorey insectivores, terrestrial insectivores are particularly sensitive to forest fragmentation, loss and disturbance (Johns 1986; Newmark 1991; Stratford – and Stouffer 1999; Şekercioglu et al. 2002; Peh et al. 2005;
Newmark 2006). Yet our understanding as to ecological factors influencing space use and selection among tropical understorey insectivores in general and tropical terrestrial insectivores in particular is quite limited.
Ostrich is co-published by NISC (Pty) Ltd and Taylor & Francis
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Among tropical insectivorous bird species, unlike their temperate counterparts, most species hold and defend a feeding and breeding territory year-round rather than only during the breeding season (Buskirk 1976; Stutchbury and Morton 2001). In addition, territorial boundaries for most tropical insectivores are highly stable over a bird’s lifetime with few individuals shifting or claiming a neighbor’s territory (Greenberg and Gradwohl 1986; Woltmann and Sherry 2011). Here we assess three prominent non-mutually exclusive hypotheses relating food abundance, food dispersion and habitat structure to territory selection and size in an Afrotropical insectivorous bird. We then subsequently examine whether food abundance and dispersion are associated with habitat structure, because habitat structure has been proposed as a mechanistic explanation for the frequently observed inverse relation between food abundance and territory size (Smith and Shugart 1987; Marshall and Cooper 2004). We conduct this analysis at two spatial scales, the habitat patch and territory, because food abundance, dispersion and habitat structure can vary with spatial scale (Wiens et al. 1987; Wiens 1989; Orians and Wittenberger 1991; Eide et al. 2004; Chalfoun and Martin 2007). Indeed, multispatial scale analyses of territoriality are critical for identifying and assessing tradeoffs and interactions among ecological factors structuring territoriality in animals (Smith and Shugart 1987; Orians and Wittenberger 1991; Burke and Nol 1998; Eide et al. 2004). We first test the ‘food value hypothesis’, which is based on food value theory (Stenger 1958; Wilson 1975), and which postulates that territoriality is a mechanism to ensure adequate food to successfully raise offspring. Two predictions of the ‘food value hypothesis’ are (1) tropical insectivorous birds should preferentially select territories within a habitat patch containing high food abundance and (2) territory size of tropical insectivorous birds should be inversely related to food abundance. Among insectivorous birds at higher latitudes, there is support for both predictions (Stenger 1958; Holmes 1970; Smith and Shugart 1987; Burke and Nol 1998). We then asses a second prominent hypothesis termed the ‘resource dispersion hypothesis’, which proposes that the spatial dispersion of food resources, i.e. spatial arrangement of food items, influences territoriality. While this hypothesis was originally formulated to explain variation in group size among social animals (Macdonald 1983), it has more recently been proposed as an explanation for territory selection and variation in territory size among non-social animals (Carr and Macdonald 1986; Johnson et al. 2002; Eide et al. 2004). Two predictions of this hypothesis are (1) tropical insectivorous birds should select territories within a habitat patch containing clumped food resources and (2) territory size in tropical insectivorous birds should decrease with an increase in food resource clumping. Evaluations of this hypothesis among birds have been largely restricted to interspecific comparisons of the presence/absence of territoriality (Brown and Orians 1970; Buskirk 1976; however, see Langen and Vehrencamp 1998). Lastly, we evaluate the ‘habitat structure hypothesis’, which relates intraspecific variation in territory selection and
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size among birds to the more general process of habitat selection. This hypothesis proposes that habitat requirements for nesting sites, song perches, foraging sites and/ or predator avoidance drives territory selection and size in birds (Kendeigh 1945; Partridge 1976; Cody 1981; Lima and Valone 1991; Martin 1993; Stratford and Stouffer 2013). Two predictions of this habitat structure hypothesis are (1) tropical insectivorous birds should non-randomly select territories within a habitat patch based on habitat structure (e.g. tree density, shrub density and ground cover) and (2) territory size is a function of habitat structure. More recently, a mechanistic explanation for the frequently observed inverse correlation between food abundance and territory size has been proposed, which postulates that birds respond to habitat structure rather than directly to food availability as a proximate cue of food availability and has been termed the ‘structural cues hypothesis’ (Smith and Shugart 1987; Marshall and Cooper 2004). A prediction of this hypothesis is that food abundance and/or dispersion are directly related within territories to habitat structure, which in turn is inversely related to territory size. Among several temperate insectivorous bird species there is support for the structural cues hypothesis (Smith and Shugart 1987; Marshall and Cooper 2004). Here we examine the influence of food abundance, dispersion and habitat structure on territory selection and size in a globally endangered Afrotropical terrestrial insectivorous bird in north-eastern Tanzania. In this analysis, we first compare invertebrate abundance and dispersion, and habitat structure between territories and random locations to assess which cue(s) the Usambara Thrush Turdus roehli is using to select a territory. We then examine the relation between invertebrate abundance, dispersion, and habitat structure and territory size to assess the relative influence of these ecological factors on territory size. Lastly, we examine the association within territories between food abundance, dispersion and habitat structure, and between habitat structure and territory size. Methods Study area and species The study was conducted in the Amani Nature Reserve in the East Usambara Mountains (05°06′ S, 38°36′ E) in a 640 ha forest block. The elevation of the study site is 1 016 m with mean annual precipitation of approximately 1 720 mm. The forests at this elevation are closed canopy and classified as submontane (Iversen 1991). The Usambara Thrush, which has recently been described as a distinct species within the Turdus olivaceus species complex (Bowie et al. 2005), is restricted to the East and West Usambara and South Pare Mountains in north-eastern Tanzania. Following IUCN Red List criteria, the Usambara Thrush is globally Endangered. The Usambara Thrush (mass = 62.7 g) is a terrestrial insectivore and forages in the leaf litter by slowly hopping and pushing leaves backward with one foot and flicking leaves with its bill (Urban et al. 2007). The Usambara Thrush’s diet comprises insects, molluscs, nematodes, termites, millipedes, spiders, small lizards and fruit (Sclater and Moreau 1933; Clement 2000).
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Radio-tracking and territory delineation We radio-tracked nine Usambara Thrush in the East Usambara Mountains between August and February, which overlaps the breeding and non-breeding seasons for understorey bird species in the East Usambara Mountains (Mkongewa et al. 2013) during 2001, 2005 and 2006 (Table 1). Individual birds were radio-tracked over a single field season. Birds were captured with mist-nets and weighed, measured, number banded and fitted with a transmitter ≤2.6 g (Holohil, Ontario, Canada). For all birds, transmitters weighed 45 m apart with known Universal Transverse Mercator (UTM) coordinates. Coordinates were estimated with a global positioning system (GPS) having an accuracy of 5–10 m. To avoid autocorrelation of radio-tracking data, all birds were relocated at intervals ≥15 min, a period of time sufficient for a bird to potentially fly across its territory (Otis and White 1999). Birds were followed on average for 4–6 h d−1 between 07:00 and 18:30 over 7–130 d. The number of telemetry locations per bird varied from 56 to 397 (Table 1). To determine the number of locations required to estimate 95% of the maximum area utilised by a bird we conducted an incremental analysis using RANGES 7 (Kenward 2001). Results indicated that 13 telemetry locations were sufficient to define home range or territory and thus variation in sample effort among birds should have minimal impact on our estimate of territory size. Tracking sessions over a field season alternated between the morning–early afternoon and early afternoon–early evening. Estimated location coordinates were then entered into Home Range Extension (Rodgers and Carr 1998) in ArcGIS. We calculated a 95% fixed-kernel home range to define the annual feeding and breeding territory of the Usambara Thrush using a least-squares cross-validation smoothing parameter. Spot-mapping conducted between
Table 1: Comparison among nine Usambara Thrush of year radio-tracked, number of telemetry locations, age of bird and territory size
Bird
Year
1 2 3 4 5 6 7 8 9
2001 2005 2005 2005 2006 2006 2006 2006 2006
Number of telemetry locations 56 385 220 298 285 397 327 362 248
Age
Territory size (ha)
Adult Adult Adult Juvenile Adult Adult Adult Adult Adult
11.0 11.3 8.6 27.5 8.6 9.5 4.3 3.8 16.4
November and January over two breeding seasons, 2009–2011, confirmed an overlap in the location of singing birds with the 95% fixed-kernel home ranges. Measurement of habitat structure We assessed habitat structure within the territory for each of the nine radio-tracked birds within six 5 m × 5 m random plots, and at eighty-five 5 m × 5 m random sites in our study area that did not fall within the known territory of any bird. The following vegetation measurements, which have been shown to influence habitat selection in the Usambara Thrush (Newmark et al. 2010), were recorded: (1) density of trees, which are defined as woody vegetation ≥9.6 cm diameter at breast height (dbh), excluding lianas and Maesopsis eminii (an exotic invasive tree that is an indicator of habitat disturbance); (2) density of Maesopsis eminii >1 m in height; (3) density of shrubs, which are defined as woody vegetation 5 mm in length are potential food items. Although avian
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ecologists generally summarise insect food abundance as dry weight biomass (however, see Holmes et al. 1979; – Şekercioglu et al. 2002), to facilitate the rapid processing of a large number of samples in a remote field location without laboratory facilities we summarised invertebrate abundance here as numbers of invertebrates per sample, i.e. density. Stork and Blackburn (1993) have previously shown that tropical forest arthropod abundance and biomass are highly intercorrelated. Given that invertebrates were sampled immediately adjacent to the vegetation plots in the territory of a bird, we assumed that abundance and dispersion of invertebrates were representative of that occurring within the adjacent vegetation plots. All invertebrate samples were collected between October and December 2007. We used a standardised Morisita index (Ip) (Smith-Gill 1975) to quantify spatial dispersion of invertebrates across a plot because this index, unlike several other indices of spatial dispersion, is independent of population density and sample size (Myers 1978; Krebs 1999). The index ranges from −1.0 to +1.0. An Ip of 0.0 indicates random patterns, with uniform patterns below zero and clumped patterns above zero. We used the vegan package (Oksanen et al. 2013) in R 2.12.2 (R Development Core Team 2011) to calculate the index. To obtain a measure of food abundance and dispersion we averaged invertebrate density and dispersion across all plots within the territory of a bird. Statistical analyses We subjected habitat variables to a principal components analysis to create an additional synthetic variable of habitat structure summarised as the first principal component (PC1) of tree, Maesopsis eminii and shrub density, and percentage ground cover. The first principal component, which explained 44% of the total variance in vegetation structure, accounted largely for tree and Maesopsis eminii density and ground cover. For percentage ground cover we arcsine transformed the data to stabilise variances and normalise data (Sokal and Rohlf 1995). We compared food abundance, food dispersion and habitat structure between territories and random sites using t-tests for independent samples and unequal sample sizes under a null hypothesis of no differences. We tested for equality of variances between populations using a ‘Folded F’ test (Steel and Torrie 1980), and if unequal variances were detected we used the Satterthwaite method (Satterthwaite 1946) to calculate t-values and degrees of freedom. Equal and unequal variances were detected and
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as a result reported degrees of freedom of t-tests vary among habitat variables. To assess the influence of food abundance, food dispersion and habitat structure on territory size, we constructed a priori a candidate set of seven plausible univariate and multivariate linear regression models (Table 2). Owing to a low N we excluded interactions among covariates in our candidate model set. For all regression models we evaluated residuals for normality using the Shapiro–Wilk statistic (Shapiro and Wilk 1965) and homogeneity of variance using residual plots. We employed information-theoretic techniques to assess model support using the difference in Akaike’s information criterion corrected for small sample size (∆AICc) to rank candidate models and AICc weights (W) to evaluate the relative support for predictor variables across models (Burnham and Anderson 2002). The ∆AICc and the AICc value of the best model along with model weights provided a measure of the relative strength of evidence for each model. Models with minimum ∆AICc ≤ 7 were considered to have support (Burnham et al. 2011). In assessing the relation between territory size and food abundance, food dispersion and habitat structure, we excluded one immature bird, and the only juvenile bird that was radio-tracked, because it was a statistical outlier. Among many tropical bird species there is extended parental care and delayed dispersal of young with many young birds staying up to a year in their parents’ territory (Russell 2000; Russell et al. 2004). The juvenile had an unusually large territory as a result of an expanded use of its parents’ territory combined with sporadic short- to mediumdistance exploratory forays. Similar ranging behaviour has been described among juvenile White-throated Robin Turdus assimilis in Costa Rica (Cohen and Lindell 2004) and Checker-throated Antwren Myrmotherula fulviventris in Panama (Greenberg and Gradwohl 1997). To assess the association between food abundance, food dispersions and habitat structure, we computed Pearson correlation coefficients (r) and p-values (null hypothesis, r = 0) among food abundance, dispersion, and all habitat structure variables. Values reported in the results are means ± the standard error. Results 95% Fixed-kernel home range For nine Usambara Thrush radio-tracked between 2001 and 2006, mean 95% fixed-kernel home range was 11 ± 2 ha. Among birds, the 95% fixed-kernel home range varied by a factor of seven (range: 4–28 ha) (Table 1).
Table 2: Models of territory size for the Usambara Thrush. All models include an intercept term. W = the model weight, K = the number of estimated parameters in the model, including the intercept and the mean-squared error Model Mean invertebrate abundance Mean invertebrate dispersion Mean habitat structure Mean invertebrate abundance, mean invertebrate dispersion Men invertebrate abundance, mean habitat structure Mean habitat structure, mean invertebrate dispersion Mean invertebrate abundance, mean invertebrate dispersion, mean habitat structure
AICc 29.07 31.45 32.82 38.32 38.34 40.78 56.88
∆AICc 0.00 2.38 3.75 9.25 9.28 11.71 27.81
W 0.68 0.21 0.15
