Behav Ecol Sociobiol (2013) 67:311–320 DOI 10.1007/s00265-012-1451-z ORIGINAL PAPER Hierarchical patch choice by an insectivorous bat through prey availability components D. Almenar & J. Aihartza & U. Goiti & E. Salsamendi & I. Garin Received: 24 January 2012 / Revised: 7 November 2012 / Accepted: 7 November 2012 / Published online: 20 November 2012 # Springer-Verlag Berlin Heidelberg 2012 Abstract Food availability does not only refer to the abundance of edible items; accessibility and detectability of food are also essential components of the availability concept. Constraints imposed by a habitat’s physical structure on the accessibility and detectability of food have been seldom treated simultaneously to the abundance of prey at the foraging patch level in observational studies. We designed a research that allowed decoupling the effects of microhabitat structure and prey abundance on foraging patch selection of the trawling insectivorous long-fingered bat (Myotis capaccinii). The use of different patches of river was surveyed by radiotelemetry during three periods of the bat’s annual cycle, and prey abundance was accordingly measured in and out of the hunting grounds of the tracked bats by insect traps emulating the species’ foraging. Bats preferentially used river stretches characterised by an open course and smooth water surfaces, i.e. they used the most suitable patches in terms of prey accessibility and detectability, respectively. In addition, prey abundance in the selected river stretches was higher than in others where bat activity was not recorded, although the latter also offered good access and prey detection possibilities. Bats also shifted foraging stretches seasonally, likely following the spatiotemporal dynamics of prey production over the watershed. We suggest that the decisions of bats during the patch choice process fitted a hierarchical sequence driven first by the species’ morphological specialisations and ability to hunt in unobstructed spaces, then by the detectability of prey on water surfaces and, finally, by the relative abundance of prey. Communicated by C. Voigt D. Almenar : J. Aihartza : U. Goiti : E. Salsamendi : I. Garin (*) Zoologia eta Animali Zelulen Biologia Saila, UPV/EHU, Sarriena z/g, 48940 Leioa, The Basque Country e-mail: inazio.garin@ehu.es Keywords Patch selection . Foraging . Prey availability . Chiroptera . Myotis capaccinii Introduction Foraging patch selection has received much theoretical attention within the field of behavioural ecology, and its study was originally approached by models predicting the decisions that foraging animals should make in patches with variable food abundance (i.e. MacArthur and Pianka 1966; Fretwell and Lucas 1970; Fretwell 1972; Charnov 1976). Original models have been refined to incorporate the effect of prey’s demographic and behavioural response, predator learning or behavioural plasticity among others, so that more realistic spatial predator–prey relationships could be depicted (e.g. Abrams 2007; Okuyama 2009; Scharf et al. 2012). A common practice is to assume the availability of food in a given patch as solely dependent on its abundance; however, the accessibility and detectability of the food to the animal are also essential components of resources’ actual availability (Holmes and Schultz 1988; Hall et al. 1997). While abundance indicates the absolute number of food items in a defined space (density), accessibility and detectability relate to the animal’s capability to reach and handle food items and to its ability to discriminate food items from the non-edible background, respectively. The participation of the environmental physical attributes that impose some limitation to prey access and detection in the spatial decisions of predators has been already revealed in a number of species (Rice 1983; Whelan 2001; Butler and Gillings 2004; Hopcraft et al. 2005; Jones et al. 2006; Siemers and Güttinger 2006; Chan et al. 2009). Furthermore, where the prey abundance and the structural features of the environment have been investigated, the patch choice process seems to be driven by access and detection rather than abundance of prey (e.g. Kelsey and Hassall 1989; Getty and Pulliam 1993; 312 Uiblein et al. 1995; Bennetts et al. 2006; Andruskiw et al. 2008; Greenville and Dickman 2009; Rainho et al. 2010; Hagen and Sabo 2011; but see Olsson et al. 2001). Nevertheless, the effect of abundance, accessibility and detectability on foraging patch selection is seldom teased apart in observational studies (Holmes and Schultz 1988; BenoitBird et al. 2011), which to some degree may explain the failure to unveil the widely accepted relationship between predator patch choice and prey numbers. In fact, assessing the abundance of natural prey in addition to structural features of the environment is usually a formidable task and measuring it at the precise foraging patch of wild animals is rarely affordable. A feasible ecological model to study patch selection with consideration to the multilevel nature of prey availability may be offered by echolocating bats. The roles of prey detectability (e.g. Neuweiler 1989; Safi and Siemers 2010) and accessibility (e.g. Norberg and Rayner 1987; Rainho et al. 2010) are relatively well known for insectivorous bats that rely on echolocation to catch their prey. Besides, current radio-tracking techniques allow researchers to accurately define individual foraging grounds despite their nocturnal habits and flight and in turn to estimate the abundance of prey actually accessible to and detectable by bats (e.g. Almenar et al. 2008). Furthermore, trawling bats represent an excellent choice to study the influence of availability on patch selection by insectivorous bats, as their foraging behaviour is well defined. Bats in this group share several morphological traits and hunting styles (Norberg and Rayner 1987; Fenton and Bogdanowicz 2002), taking their main prey directly from the water surface (or immediately above it) in a stereotyped manner known as ‘trawling’ behaviour (Jones and Rayner 1988; Kalko and Schnitzler 1989; Kalko 1990; Jones and Rayner 1991; Britton et al. 1997), by which they obtain water-related arthropods (emerging, floating or flying level with the surface; Vaughan 1997; Funakoshi and Takeda 1998; Limpens et al. 1999; Law and Urquhart 2000; Flavin et al. 2001). Production rates of these kinds of prey would unlikely show a demographic response to bat predation; hence, measurements of relative abundance can be plausibly correlated with the encounter rate. In addition, foraging in these bats is specialised with regard to techniques and microhabitats, limiting dietary shifts between alternative prey and, accordingly, promoting estimation of the effective profitability in the foraging patches. Detection of prey is facilitated by the ‘mirror effect’ of sound travelling over flat surfaces (Siemers et al. 2001, 2005; Greif and Siemers 2010). This acoustical effect explains why breaking or cluttering of the water surface is a major constraint on foraging by these bats (von Frenckell and Barclay 1987; Boonman et al. 1998; Rydell et al. 1999; Warren et al. 2000; Almenar et al. 2006). In addition, the group shows limited flight manoeuvrability in structurally complex environments, driving the bats to open spaces for commuting and hunting (Norberg and Rayner 1987). Behav Ecol Sociobiol (2013) 67:311–320 The long-fingered bat (Myotis capaccinii, Bonaparte 1837) is a trawling bat that dwells in caves (Spitzenberger and von Helversen 2001) distributed throughout the Mediterranean basin and South-western Asia (Hutson et al. 2001). It forages almost exclusively on aquatic habitats, showing a preference for rivers (Almenar et al. 2006, 2009). The present study aims to understand patch selection by foraging animals, under the assumption that patch use by insectivorous bats will fit the expectations of general patch selection models (Fretwell and Lucas 1970; Fretwell 1972). We specifically tested whether, within the limits imposed by prey detection and accessibility, the foraging activity of M. capaccinii will concentrate in patches with higher abundance of prey. To do so, we removed the effect of physical constraints on the patch choice process using a two-step approach: we first identified the environment’s physical features that locally constrained patch choice and then we compared prey abundance between patches with and without recorded hunting but similar in physical attributes of microhabitat structure. We thereby minimised the distorting effect of the physical features on the measures of prey abundance. Materials and methods Study area, bat population and study period The study area is located in the eastern Iberian Peninsula (39°04′ N–0°35′ W) and spreads over 3,850 km2 of the lower basin of the Xúquer River. This area includes several tributaries, among which the Albaida and Sellent rivers are the most important. The water flow shows Mediterranean seasonality, with lower levels during mid and late summer. Rivers are managed via a large dam (called Presa de Tous), many weirs (locally known as ‘assuts’) and a vast network of irrigation canals. There are also many ponds (about 3/km2). Aquatic habitats cover 1.2 % of the study area; of these, the calm smooth-surfaced waters that are the preferred foraging habitat of long-fingered bats account for 72 % (Almenar 2008). A large floodplain (20–50 ma.s.l.) mainly covered by orange groves comprises approximately two thirds of the study area. The remaining area is hilly (maximum altitude, 600 ma.s.l.) and mainly covered by Mediterranean post-fire scrublands and pinewoods. For a full description of the study area, refer to Almenar et al. (2009). Two roosts in the area are inhabited consistently every year by large groups of M. capaccinii during the breeding season. The main roost is a limestone cave with a variable colony size through the season: 81 M. capaccinii during pre-breeding, 219 during lactation and 113 during weaning of 2004. More than 100 individuals inhabit the second roost during lactation, located 8.4 km from the first. Both roosts are shared with other bat species (Rhinolophus euryale, Rhinolophus mehelyi, Behav Ecol Sociobiol (2013) 67:311–320 Myotis blythii, Myotis myotis, Myotis emarginatus, Myotis nattereri and Miniopterus schreibersii). Fieldwork was carried out in 2004 and performed during three periods corresponding to three phases in the bats’ annual cycle: pre-breeding (9 to 30 April), lactation (24 May to 11 June) and weaning (1 to 17 July). 313 Table 1 Capture date and radio-tracking effort of 45 long-fingered bats during the three periods of the present study Study period Capture date Characteristic Days Fixes Pre-breeding 4-9-04 AF AF AM AM AF AF AF AM AM AF AM AF AM 3 4 4 8 5 2 4 6 5 3 3 1 2 41 36 43 132 60 31 140 89 78 50 43 19 14 AM AM AF L AM L L L L L L AM P L L AF L JF 5 1 2 4 3 3 4 1 4 1 4 2 2 2 1 1 2 5 38 17 17 7 30 2 47 22 13 20 36 50 33 7 41 23 50 89 JM JF JM JF AF AF AF JM JF JF JF JM AF AF 4 7 5 3 5 3 3 2 5 3 2 4 3 3 64 64 53 23 74 56 69 6 5 36 38 7 40 27 Identification of foraging locations Foraging patches were identified by radio-tracking. We captured bats twice per period when they returned to the main roost after nightly foraging, using a harp trap (modified from Tuttle 1974). In total, 62 bats were radio-tagged, sexed, aged and weighed. After clipping the fur between their shoulder blades, we equipped the bats with a 0.45-g PIP II radio transmitter (Biotrack Ltd., Dorset, UK) using Skinbond surgical adhesive (Smith and Nephew, Largo, FL, USA). The transmitter represented a load of <5 % of the bat’s weight (Aldridge and Brigham 1988), except for 11 cases, mostly juveniles, in which it reached 6.3 %; no abnormal behaviour was observed in these individuals. Capture, manipulation and tagging were performed with permission from the Valencian Government. Bats were (as much as possible) continuously tracked from emergence to return. Up to six teams searched for bats simultaneously, using either 1000-XRS radio receivers (Wildlife Materials, Carbondale, IL, USA) or FT-290RII units (A. Wagener Telemetrieanlagen, Köln, Germany) and three-element Yagi antennae. Mobile teams tracked bats by car or on foot and were guided to foraging sites by up to three observers at stationary vantage points. The stationary observers received radio signals from a wider spatial range than mobile trackers, and their searching scope encompassed both aquatic and terrestrial habitats. Mobile teams focused on the tracking of up to three bats each night. Only those fixes obtained through homing-in (White and Garrot 1990) by the mobile teams were analysed. We failed to gather any fix of nine individuals (three per period). Each period, the 15 bats with the most foraging locations were selected for analyses among tracked individuals (Table 1). When bats flew directly and quickly between the roost and a foraging site or between two separate foraging sites, we considered them to be commuting. Continuous movements to and fro over a location were considered as foraging. Because bats were able to commute to distant foraging sites in 10 min (DA, personal observation), we used a time interval of 10 min between consecutive fixes to avoid spatial autocorrelation. Fixes were mapped in the field on orthoimages or 1:10,000 topographic maps and then transferred into a Geographical Information System (ArcView 3.2, ESRI, Redlands, CA, USA). 4-17-04 Lactation 5-24-04 6-4-04 Weaning 7-1-04 7-10-04 AF adult female, AM adult male, L lactating female, P pregnant female, JF juvenile female, JM juvenile male, Days number of days with radiolocations, Fixes total number of fixes gathered on rivers 314 Classification of patches Patch use was investigated along the rivers, which were the preferred and most used habitat unit by the studied population (individual foraging activity was 92 % on average; Almenar et al. 2009). A colonial minimum convex polygon (MCP; White and Garrot 1990) encompassing all the radiolocations limited the area of foraging activity. To define patches, we first divided the river network into physically homogeneous sectors, distinguishing between sectors with open smooth waters vs. sectors with open rippled surfaces and/or covered by dense reed vegetation. These features were known to affect the preferences of foraging M. capaccinii (Almenar et al. 2006, 2009; Biscardi et al. 2007). Then, we arbitrarily subdivided the homogeneous stretches into 100-m-long stretches. The 100-m measure was chosen on the basis of the approximate distance of the bats’ characteristic to and fro repetitive flight pattern during foraging (Ahlén 1990; Kalko 1990; DA, personal observation). Because the length of homogeneous stretches was not an exact multiple of 100 m, 11 % of them did not reach 100 m. These shorter patches had low impact on the outcome of the analysis, as only 4.7 % of them were used by bats and the test results did not change with their removal from the analysis. A patch was classified as used during any of the three study periods if at least 1 h of foraging activity was recorded there during that period. We set this limit to avoid the inclusion of patches used for exploration. Among the patches without foraging activity of radio-tracked individuals, we chose those used during any of the other two periods—that is, with confirmed suitable structural features for foraging—and classified them as potential patches. Since the rivers’ physical features remained unaltered during the three periods, we reduced the likelihood of any seasonal change of use to occur due to a response of the physical attributes of the patch. Measures of arthropod abundance Although some M. capaccinii populations are known to eat fish in the wild (Aihartza et al. 2003; Levin et al. 2006; Biscardi et al. 2007), the diet of the surveyed individuals appeared to be exclusively arthropods (Almenar et al. 2008). Arthropod abundance was measured by two different prey capture methods during the nights of radio-tracking. One method emulated the bats’ trawling behaviour by dragging the water surface with a hand net (75×25 cm, 1 mm mesh) for 15 min 1–3 h after sunset. The second method sampled airborne arthropods (adults with aquatic and terrestrial larvae) during the whole night by using a malaise interception trap (height 2 m; Entomopraxis, Madrid, Spain) mounted in a structure with floaters for set-up on the water surface. The arthropods caught by both methods were stored in 70 % Behav Ecol Sociobiol (2013) 67:311–320 ethanol and subsequently counted and identified to the ordinal level. Arthropod abundance was sampled simultaneously in 11 used and 13 potential patches during pre-breeding, 12 used and 6 potential patches during lactation and 16 used and 11 potential patches during weaning. Statistical analyses We compared the frequency of patches with contrasting physical features (open smooth waters vs. open rippled surfaces and/or vegetation coverage) between the used patches (observed frequency) and the patches present at the rivers of the study area as a whole (expected frequency). Disproportion between expected and observed frequencies would indicate that physical features were not used at random. A goodnessof-fit G test was used to compare the frequencies (Sokal and Rohlf 1994). Two variables were analysed for differences in arthropod abundance between used and potential patches: aerial prey (captured by malaise traps) and surface prey (trapped by handnetting). Two factorial analyses of variance (ANOVAs) were performed, with period, usage and interaction term as factors. As the variables approached a log-normal distribution, they were log-transformed for the analyses. The GLM procedure of the software SAS 9.0 was used to complete the hypothesis tests, with 0.05 as the designated significance level. Results Among the 851 patches of the study area, 373 showed open smooth water surfaces and thus were classed as structurally suitable for foraging, whereas the other 478 patches showed water surfaces with entangled vegetation and/or disturbance. A total of 1,880 foraging fixes were gathered at rivers by radio-tracking (95 % of all foraging fixes), averaging 42 per bat (range, 2–140), allowing identification of 49 used patches, with 4 being used during more than one period (Fig. 1). The frequency of patches with open smooth water surfaces was significantly higher in the group of used patches than in the whole study area (73 and 44 %, respectively; G020.33, df01, p<0.0001). Accordingly, 27 % of used patches were classified as cluttered. The patches used by the radio-tracked bats contained more aerial and surface prey than did the potential patches (those physically suitable for hunting but not used) (Table 2; Fig. 2). Only the abundance of aerial prey varied significantly between periods (Table 2; Fig. 2). The significance of the interaction term indicates that the magnitude of difference between used and potential patches during the three periods was the same for surface prey but not for aerial prey. Specifically, the difference in overall aerial prey abundance Behav Ecol Sociobiol (2013) 67:311–320 315 Fig. 1 Maps of foraging radiolocations on rivers of 45 M. capaccinii. The study area is delimited by an MCP (black line) encompassing all the radiolocations (both over and outside rivers). River network is drawn in grey. Foraging fixes on rivers are drawn as black dots. The main roost is represented by a black asterisk and the secondary roost is represented by a grey asterisk. a Pre-breeding, b lactation, c weaning Table 2 ANOVA tables for two prey abundance variables in study area: aerial prey and surface prey Source Df SS MS F Variable: aerial prey abundance (log-transformed) Period 2 10.98 5.49 4.59 Use 1 10.90 10.90 9.11 Period×use 2 8.54 4.27 3.57 Residual 65 77.83 1.19 Variable: surface prey abundance (log-transformed) Period Use Period×use Residual 2 1 2 65 10.09 10.61 5.52 168.16 5.04 10.61 2.76 2.59 1.95 4.10 1.07 p 0.0137* 0.0036* 0.0338* 0.1506 0.0470* 0.3499 Three factors were considered: period (three levels), use (used patch/ potential patch) and interaction term. Asterisk denotes significant difference (p<0.05) between used and potential patches was small during the lactation period (Fig. 2). Regardless of usage by bats, the simulated catch rate by aerial traps was higher during weaning (312.0 prey/trap; SD0290.4), but that by surface traps was higher during lactation (188.5 prey/trap; SD0385.1). Nematoceran dipterans, especially chironomids (including pupae in the surface trap), dominated the overall captures obtained by both trap types during all periods. Aerial catches of nematocerans ranged from 81 % during weaning to 91 % during lactation. The proportion of nematocerans over the surface was lower, ranging from 54 % during weaning to 78 % during lactation. Other arthropod groups were present in lower proportions. Only trichopterans during weaning exceeded 5 % of aerial catches, and only heteropterans (mainly aquatic) and hymenopterans accounted for more than 5 % of surface catches in some period. Prey size composition was dominated by small arthropods. The proportion of large prey was higher for 316 Behav Ecol Sociobiol (2013) 67:311–320 a Geometrical mean of prey abundance 1750 1500 1250 1000 750 500 250 0 Potential Use Pre-breeding Potential Use Lactation Potential Use Weaning b Geometrical mean of prey abundance 800 600 400 200 0 Potential Use Pre-breeding Potential Use Lactation Potential Use Weaning Fig. 2 Variation in prey abundance, estimated by means of two arthropod capture devices in the rivers of study area. Bars represent the geometrical mean, and lines indicate the 95 % confidence interval: a aerial prey, b surface prey. Geometrical mean is used because data approaches lognormal distribution. Note the different scale between a and b surface traps (32 %) than aerial traps (9 %). For both aerial and surface traps, the proportion of larger prey increased from pre-breeding to weaning. Discussion Foraging long-fingered bats (M. capaccinii) showed a disproportionate use of river stretches with increased accessibility and detectability, i.e. open smooth water surfaces. Similarly to other trawling bat species, their hunting is constrained by disturbance of the water surface (Boonman et al. 1998; Rydell et al. 1999; Warren et al. 2000; Siemers et al. 2001). Particularly, entangled weed vegetation in some stretches of our study area hampers the bats’ access to patches that otherwise would likely offer suitable prey production (Almenar et al. 2006), and patches with turbulent flow are likely to reduce search efficiency for prey compared to smooth surfaces (Rydell et al. 1999; Siemers et al. 2005). This pattern of patch selection has also been observed in other populations of M. capaccinii (Biscardi et al. 2007). Nonetheless, overcoming the physical constraints alone does not fully explain foraging patch choice in the long- fingered bat. We found that most selected patches were used by foraging bats only during precise periods and their spatial arrangement changed noticeably through seasons (Fig. 1). Thus, we believe that another factor, which was seasonally variable, could be acting upon patch choice. Prey abundance is the most likely candidate, since our results revealed an association between the usage of patches and the amount of catchable arthropods there. The bulk of the species’ diet is comprised by insects of aquatic larvae, a typically ephemeral prey with spatially and temporarily aggregated emergence from water (e.g. Corbet 1964; Gathmann and Williams 2006). The resulting variability of prey abundance between patches could stem from changes in water temperature (Armitage et al. 1995). Since the predator showed also an irregular spatiotemporal pattern of foraging, presumably the foraging patches could be selected according to their profitability in terms of prey abundance. The diversity of hydromorphological features in the study area probably sustained a continuous, though spatially variable, supply of productive patches throughout the entire season of activity. Goiti et al. (2006) also proposed the importance of internal diversity in foraging habitats to ensure an uninterrupted source of prey for R. euryale. Therefore, both prey abundance and physical structure of the foraging habitat seem to be the leading factors in patch choice of the long-fingered bat. This may be generally applicable to many aerial insectivorous bats, as some authors have already anticipated (Grindal and Brigham 1999; Warren et al. 2000; Kusch et al. 2004; Fukui et al. 2006; Goiti et al. 2008; Akasaka et al. 2009). Conversely, studies that have simultaneously addressed the effect of access, detection and abundance on the patch selection process have usually pointed out a negligible influence of prey abundance. For instance, lions ambush prey at greater numbers in areas where prey catchability is higher rather than where prey is most abundant (Hopcraft et al. 2005); and foraging patch choice of dunlins that use tactile stimuli to locate prey in mud has been claimed to be constrained exclusively by the penetrability of the substrate (a surrogate for accessibility; Kelsey and Hassall 1989). Similarly, bats may be forced to forage in patches that grant unobstructed access to prey despite their lower insect density and similar detectability (Rainho et al. 2010; Hagen and Sabo 2011). However, it must be noted that there is a vacuum of studies that measure prey availability at the precise foraging patch, an unavoidable prerequisite to evaluate fairly the effects of the three components of availability on the patch selection process. This is seldom carried out, but when so, the depicted interplay between the components is similar to that found in our study (Holmes and Schultz 1988; Benoit-Bird et al. 2011), e.g. in birds that glean amidst foliage, the abundance of lepidopteran larvae determines the foraging choice at the leaf level only when the structural features of the foliage and the behaviour of the prey suit the ability of the bird to capture and Behav Ecol Sociobiol (2013) 67:311–320 perceive that kind of prey (Holmes and Schultz 1988). As a corollary, we suggest that accessibility, detectability and abundance of prey represent an effective conceptual framework to dissect and understand the factors contributing to patch selection by animals. Nevertheless, it has to be noticed that competitive interference and risk of predation are additional factors acting upon foraging patch selection (e.g. Brown 1988; Butler et al. 2005; Encarnaçao et al. 2010) and thus they may adjust animal preference to a subset of structural features within the physical attributes that broadly shape access to, detection of and abundance of prey. Specifically, we suggest that a hierarchical process rules patch choice by M. capaccinii, with different foraging decisions at different levels. First, the species’ morphological specialisations tie it to water habitats. Second, bats tend to forage in open spaces where their manoeuvrability is not limited. Third, their foraging occurs preferentially on smooth water surfaces, where prey detection is improved. Finally, bats spread over those patches where prey profitability is higher at any given moment. These kind of hierarchical or multilevel processes, where the results of these decisions are not consistent between levels or scales, are useful to understand the successive foraging decisions. For instance, selection of a given food item is envisaged as the consequence of a multiple scale decision process that starts with habitat selection and ends with the chosen item (Sallabanks 1993; Brown and Morgan 1995). Overall, patch selection seems to be determined by predatory risk at larger scales and by energy intake maximisation at the final steps of the selection process (Senft et al. 1987; Holbrook and Schmitt 1988; Bowers and Dooley 1993; Heithaus and Dill 2006). Our study shows that access to and detection of food may also play a role in a multi-scale decision context for foraging. Precise knowledge on the constraints on perception and locomotion may help to elucidate whether the obtained results apply to other organisms with presumably low predation hazard, such as open air flying bats. Due to our research design, we could have misclassified some patches. Indeed, we cannot be completely certain all the patches classified as potential were not used, as untagged bats might have hunted in them. This fact could have masked any true difference in prey abundance between the used and suitable but actually unused (potential) patches; however, the general difference in prey abundance observed between used and potential patches indicates that either the proportion of misclassified potential patches was very low or the actual differences between these patches were even larger. The larger colony size, the rising spread of individuals across the study area and the low overlap of the hunting sectors of the radio-tracked individuals during lactation (Almenar et al. 2011) may have enhanced the risk of misclassifying patches and, therefore, the chances of overlooking any difference between used and potential patches may have been larger during that period. This flaw could have 317 contributed to the similarity in prey production of used and potential patches during lactation. The selection of foraging patches is intimately related to the information that animals have on their profitability (Giraldeau 1997; Dall et al. 2005). However, the emergence of aquatic insects can hardly be foreseen with precision in space and time (Corbet 1964; Gathmann and Williams 2006), and bats’ past experience alone may not guide their choice of profitable patches at the right moment. In our study, some patches attracted many individuals at the same time, principally during pre-breeding and weaning, which introduces a tantalizing question: Was there any information transfer between individuals? Or did each bat evaluate the profitability of a patch independently? Wilkinson (1992) found some evidence suggesting information transfer about profitable patches between foraging individuals of Nycticeius humeralis. According to this author, some bats with little foraging success could follow other bats to their foraging patches, since prey abundance for this species appears to be spatially heterogeneous and ephemeral. This scenario may also suit our studied population because the prey supply was also heterogeneous in space and time. Eavesdropping on echolocation sounds of other foraging bats has been proposed as a means of information transfer (Barclay 1982; Hickey and Fenton 1990; Jones and Siemers 2011), and Noctilio albiventris, also a trawling bat, apparently uses it to locate sources of prey (Dechmann et al. 2009). The role of eavesdropping in finding profitable foraging grounds is plausible in M. capaccinii. Nevertheless, the probability to spot high densities of prey by eavesdropping seems higher during commuting than during foraging, during seasons when dispersion of prey production is more contagious and in those populations that hunt often in scattered and isolated water bodies like ponds, irrigation pools, reservoirs or lakes (Némoz and Brisorgueil 2008). This study has shown that prey availability may largely explain the patch choice of insectivorous bats. However, this availability must be understood not only as prey abundance but also as detectability and accessibility. The ability of individuals to detect and hunt prey at a given river stretch, which is in turn related to the microhabitat features, affects the patch selection process. Given that the physical structure of the river stretches remained roughly constant throughout the activity period, the fluctuations of prey abundance within and between patches were the cause of the notable variations in the spatiotemporal pattern of the bats’ use of foraging areas (Almenar et al. 2011). Our understanding of the relationship between foraging animals and their surrounding landscape should account for the interaction between microhabitat features and prey abundance. By selecting patches with suitable microhabitats, foraging animals maximise prey detection and accessibility, and by selecting richer patches, they maximise their capture rate as well. 318 Acknowledgments We thank all those who kindly helped us in the field. Kate Johnson proofread the English of the manuscript before submission. We also wish to thank the four anonymous reviewers. This study was part of a LIFE project (LIFE00NAT/E/7337) coordinated by C. Ibáñez, Estación Biológica de Doñana (Consejo Superior de Investigaciones Científicas [CSIC]) and co-funded by the Conselleria de Territori i Habitatge of the Generalitat Valenciana and the European Commission. Support was also provided by the Centro de Protección y Estudio del Medio Natural ‘La Granja de El Saler’, the University of the Basque Country (UPV/EHU, research grant no. 9/UPV 0076.31015849/2004) and the Basque Government. D.A. and E.S. were sponsored by the CSIC and UPV/EHU, and U.G. was sponsored by the Basque Government and UPV/EHU. The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript. Ethical standards This study was performed according to the Environmental Laws and with the authorisation of the Valencian Government. 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