Vertical Stratification on Insectivorous Bats Ensembles in Central Amazon

Vertical stratification on insectivorous bats ensembles in Central Amazon

Maria Mas Navarro Master student in Biodiversity September 2014

CENTRO DE BIOLOGIA AMBIENTAL (Lisboa) MUSEU DE CIÈNCIES NATURALS DE GRANOLLERS DEPARTAMENT DE BIOLOGIA ANIMAL, UNIVERSTIAT DE BARCELONA

Vertical stratification on insectivorous bats ensembles in Central Amazon

Maria Mas Navarro Master student in Biodiversity September 2014

Directors: Dr. Christoph Meyer and Dr. Carles Flaquer Tutor UB: Dr. Maria José López Fuster

Situdent’s signature Director’s signature Tutor’s signature

Table of contents

Abstract ...... 4 Introduction ...... 5 Material and methods ...... 8 Study area ...... 8 Acoustic surveys ...... 8 Insect availability ...... 11 Vegetation obstruction ...... 11 Statistical analyses ...... 11 Results ...... 12 Discussion ...... 21 Conclusions ...... 24 Acknowledgments ...... 25 References ...... 26 ANNEX ...... 31

Abstract

Tropical Amazonian rainforests are under constant anthropogenic pressure. Of all the types of human activities that affect these forests, forest fragmentation probably has the greatest implications for conservation. Due to the pattern of land-use change the landscape can be considered as a mosaic of recovering and mature forests that encompass structurally and ecologically different habitats. Within these forests, two ecosystems are easily distinguishable: the canopy and the understory. Most of the studies of bat ecology and conservation in the Amazon have focused on the understory, which means that there is a remarkable lack of information about higher forest strata. This study aimed to determine the differences in vertical stratification in the activity of aerial insectivorous bat species in primary and secondary forests. Automatic acoustic detectors used to record bat activity in both strata, while insect availability and vegetation obstruction were assessed as variables to explain bat activity. A total of 90,641 bat passes were recorded and classified. Our results showed specific differences in activity between canopy and understory for 8 out of the total of 24 species (Pteronotus sp. and Centronycteris maximiliani being, respectively, the species most strongly associated with the understory and the canopy). Several species showed the same distribution patterns between strata in both the primary and secondary forests, which could possibly be explained by the old age of the regrowth forest in our study area. Insect availability and vegetation obstruction were weakly correlated to only a few species and so bat distribution is hard to explain either food resource availability or by the difficulty of flight inside the forest. Thus, considering those results, to get a complete view of this bat assemblage we strongly recommend that research focuses on sampling aerial insectivorous bats in both strata. Overall, we believe that bat activity patterns in the canopy are similar in both primary and 30-year-old secondary forests.

Introduction

Tropical Amazon rainforests are the most biodiverse ecosystems in the world and contain a large number of plant and animal species that provide remarkable ecological services (Bradshaw et al., 2009) and natural resources such as wood and minerals (Philips et al., 2008). However, decades of human exploitation of these resources have had detrimental effects on wildlife (Corlett, & Primack, 2008; Hansen et al., 2008).

Due to anthropogenic pressure on tropical forests, a widespread process of habitat fragmentation has occurred that affects not only pioneering plants and tree species (Lovejoy, & Bierragaard, 1990; Benétez-Malvido, & Martínez-Ramos, 2003; Laurance et al., 2007) but also communities of various animal groups such as birds, mammals, reptiles and arthropods (Lovejoy et al., 1984; Bierregaard et al., 1992; Watt et al., 1997; Davies et al., 2000; Gascon et al., 2001; Laurance et al., 2001; Peres, 2001; Estrada- Villegas et al., 2010; Laurance et al., 2010)

During the regeneration of the matrix surrounding forest fragments, pioneering trees such as Vismia and Cecropia are likely to cover many once deforested areas (Laurance et al., 2001; Laurance et al., 2007). This secondary forest and the non- deforested areas (or primary forest) differ largely in terms of (i) tree biomass, (ii) the presence or otherwise of these two pioneering trees and (iii) tree height (in the secondary forest the canopy height is 20 m, while in the primary forest it is on average 30–35 m, with some trees over 50 m) (Lovejoy, & Bierregaard, 1990; Laurance et al., 2001; Benítez-Malvido, & Martínez-Ramos, 2003; Laurance et al., 2011).

It is well known that tropical rainforests usually harbour tall trees and that two physically and biologically distinct areas for aerials foragers tend to exist: canopy and understory (Hecker, & Brigham, 1999, Bernard, 2001). This vertical stratification does not only occur in environmental characteristics but also in plant and animal communities and different functions, such pollination, develop in each of these two strata (Bonaccorso, 1979; Kalko, & Handley, 2001; Pereira et al., 2010).

Neotropical bats play key roles in the ecosystems being incolved in important functions such as seed dispersal, flower pollination and the night-flying insect balance (Law, & Lean, 1999; Medellín, & Gaona, 1999; Kalka et al., 2008; Kunz et al., 2011).

These interactions are carried out by a number of different bat species. Some species have morphological characteristics that enable them to commute in open or in cluttered areas, and a number of evolutionary adaptations have arisen in terms of the chosen foraging habitat (Henry et al., 2004; Scrimegeour et al., 2013). Bats with short wide wings seem to be more manoeuvrable than long-, slim-winged species whose flight is usually faster (Kalkounis et al., 1999; Hodgkison et al., 2004; Jung, & Kalko, 2010) and who fly mostly along forest edges, trails and in open areas.

According to the literature, research on bat vertical stratification in rainforests has mostly been conducted using mist-nets and has been focused mainly on phyllostomid bats that are easier to capture using this technique. Thus, previous studies have no or poor information on aerial insectivorous bats, which are clearly undersampled with mists nets (Kalko, & Handley, 2001; Henry et al., 2004; MacSwiney et al., 2008; Pereira et al., 2010,). Given that aerial insectivorous bats have a greatly evolved echolocation system, mist nets are more easily detectable by them than other species so they can easily avoid them.

Studies of bat assemblages in the Neotropics have to date focused on the ground level, which has led to great discrepancies in our knowledge of canopy and understory bat communities (Kalkounis et al., 1999; Bernard, 2001; Kalko, & Handley, 2001; Scrimgeour et al., 2013).

The most commonly considered strata – canopy and understory – harbour distinct species and activity levels (Bernard, 2001; Kalko, & Handley, 2001; Pereira et al. 2010). To date, studies have usually depended on mist-netting as the main capture method. Only a few authors assessed vertical stratification employing other sanpling techniques such as stable carbon isotopes or acoustic surveying (Rex et al., 2011; Scrimgeour et al., 2013). In fact, acoustic surveys are a relatively new technique in bat studies in the Neotropics. However, in recent years the use of acoustic methods has improved our knowledge given their ability to sample larger areas and their autonomy (O’Farrell, & Gannon, 1999). Ultrasound detectors are useful to detect and study certain rare species in inaccessible habitats where they may be more common than suggested by the literature (MacSwiney et al., 2008).

In successional secondary forest and forest fragments most studies of changes in plant and animal communities have focused on the ground level (Gason et al., 1999; Davies et al., 2000; Laurance et al., 2001), leading to an incomplete and biased picture of the

6 effects of habitat modification on species responses. As Scrimgeour et al. state (2013), a non-detected species is not necessarily absent from the sampling site. The underestimation of certain key species, applied in this vertical stratification scenario, could lead conservationists to take inappropriate management decisions.

More specifically, acoustic surveys are considered to be the most efficient way of studying aerial insectivorous bats (Ochoa et al., 2000; Estrada et al., 2004; Flaquer et al., 2007; MacSwiney et al., 2008; Adams et al., 2009; Meyer et al., 2010). Automatic detectors have become available, which allow that surveys can be carried out without observer presence during surveys; in addition, surveys can now be conducted simultaneously at numerous sampling points (Britzke et al., 2013). The high-intensity echolocation calls of aerial insectivorous bats can now be detected (Rydell et al., 2002). With acoustic surveys, is possible to obtain data about a species’ nocturnal activity pattern, while on the other hand, it is impossible to get individual-specific information. Thus, there are pros and cons that must be considered when deciding this study methodology. In the Neotropics, contrary to what might be thought, most bats have distinguishable echolocation calls and species identification is sometimes easier than in other areas, such as Europe, where this echolocation identification is more evolved (O’Farrell, & Gannon, 1999; Russo et al., 2002).

Despite being a widely used technique for studying bat activity, distribution and presence in Europe and North America (O’Farrell, & Gannon, 1999; MacSwiney et al., 2008), in the Neotropics the use of acoustics in bat studies is still developing. Nowadays, acoustic sampling is more used to study birds than bats and gaps in our knowledge of bat species still remain (Ochoa et al., 2000).

The aims of this project were to evaluate patterns of vertical stratification in aerial insectivorous bats for in two habitats, primary forest and secondary forest, in the Central Brazilian Amazon. We also aimed to test whether or not vegetation obstruction and insect availability, as is well known bat activity increases with insect availability, explain patterns of species distribution with respect to forest strata (understory vs canopy) and habitat type.

Material and methods

Study area

This study was carried out in September–November (dry season) in the reserves of the Biological Dynamics of Forest Fragments Project (BDFFP), which consist of vast areas (approximately 1000 km2) of tropical rainforest in the Brazilian Amazon located 80 km north of Manaus (2024’26’’S, 59043’40’’ W; Brazil) (Annex I). The rainforest is a non- flooded forest that receives 1900–3500 mm of rainfall annually. It is generally flat with just a few stream and gullies, lies at 50-100 m a.s.l., and stands on nutrient-poor sandy soils. The average temperature oscillates around 30ºC (Lovejoy, & Bierregaard, 1990; Gascon et al., 1999; Laurance et al., 2002, 2007, 2011).

The BDFFP area harbours two different types of forest habitats, primary forest and patches of tall secondary forest (=matrix) surrounding a number of experimentally isolated forest fragments. These fragments have previously been used in several other studies to evaluate the edge effect on plants, vertebrates and arthropods (Lovejoy et al., 1984; Bierregaard, & Lovejoy, 1992; Fowler et al., 1993; Gascon et al., 1999; Laurance et al., 2002 2007, 2011) and the effects of habitat fragmentation on community composition and species richness (Lovejoy, & Bierregaard, 1990; Bierregaard, & Lovejoy, 1992; Bernard, 2001; Benítez-Malvido, & Martínez-Ramos, 2003; Sampaio et al., 2003)

Acoustic surveys

Four 2-km-long transects were set up in two different reserves in the BDFFP (two in Dimona and two in Cabo Frio, 500 m apart; Annex I). Each transect started in the secondary forest matrix, and ran through this habitat for 1 km, before crossing into the primary forest, in which the rest of distance(1 km) was sampled. To ensure that the data was as little biased as possible, we did not use old trails for recording as bats may prefer open corridors as flyways given that there is less obstructive vegetation (Kusch et al., 2004), as a consequence of which some rare species could be over-recorded. Instead, transects were newly opened at the beginning of the project.

Song Meter 2 detectors (SM2Bat) with non-directional microphones (SMX-US Ultrasonic Microphone) were used Wildlife Acoustics, Massachusetts) (Britzke, 2003; Brigham et al., 2004; Britzke et al., 2013). A sound-permeable piece of foam was placed over microphones to protect them from branches, rain and wind. In order to

8 record echolocation calls from only the selected habitat (understory or canopy), a plastic sheet was placed over the microphones in the understory and under the microphones in the canopy (Annex I).

The detectors were hung from ropes using a similar system commonly used to arm mist-nets in the canopy (Humphrey et al., 1968). A sling shot, nylon ropes and weights were used to place long ropes up 30m high as part of a vertical structure to which the canopy detectors were fixed (approximately 20m high). The understory SM2s were fixed with a single rope on a tree, at breast height (Fig. 1).

The SM2 were programmed to record from 18.00–06.00 for three consecutive nights at each sampling point (14 detectors per transect). Once the recording ended the detectors were transferred to another survey point. Overall, we had a total of 88 sampling points.

Recording points were separated by 50 m to ensure that sampling locations were independent (Britzke, 2003; Fischer et al., 2009; Britzke et al., 2013). We considered as independent points two locations at which a single bat could not be recorded simultaneously by the two detectors. Nevertheless, to increase point independency, on recording nights, detectors were separated 250 m from each other.

In order to test for point independency, Pteronotus parnelli (Gray 1843), a bat with strongest echolocation call, was released and recorded repeatedly from different distances inside the forest (primary and secondary); the maximum distance that the detectors were triggered was around 20 m.

During each sampling night and at each survey point detectors were placed simultaneously both in the understory and the canopy (seven in canopy and seven more in understory). Canopy habitat was considered as ranging between 20–50 m and the understory around 0–10 m in height. At each sampling point, two detectors were placed simultaneously in both the understory and the canopy.

Figure 1: Schematic drawing indicating the placement of bat detectors (black) and light traps for insect sampling (yellow)

Acoustic analyses

In order to analyze the acoustic data we used ‘bat activity’ as the most appropriate variable. It was measured as the number of bat passes/hour at each sample point since neither the number of individuals nor specific abundance could be properly determined from acoustic data (Plank et al., 2012). Bat passes were standardized, being one pass as one recording file with a maximum length of five seconds and with a minimum of two bat pulses (Adams, 2009; Estrada et al., 2004; Henry et al., 2004; Hodgkison et al., 2004).

Due to the extreme modulation of the echolocation calls of some species or to similarities in call guilds and patterns, calls were sometimes grouped into phonic groups (e.g. Molossus sp. <30 KHz, Cynomops sp., Molossops sp., Eumops sp., Promops sp. and Eptesicus-Lasiurus).

Finally, some bat species such as Pteronotus gymnonotus, P. personatus, Thyroptera sp., Furipterus horrens and all the Phyllostomidae were not included in the statistical analyses due to a lack data.

Avisoft-SASLab Pro V.5.2.01 (Sound Analysis and Synthesis Laboratory, Germany) software was used to analyze the recordings. Species were identified using as references publications with descriptions of echolocation calls (Annex II) and our own

10 unpublished acoustic data of release calls from the same area for almost all the identified species.

Insect availability

Insect availability was quantified by setting insect light traps at the acoustic sampling points. We placed insect traps on different days to the bat detectors in order to avoid bat attraction and external bias (Jung & Kalko, 2010; Adams, 2009). The traps consisted of a LED light (hanging from a plate that protects the trap from the rain) focused down on to a small funnel, where flying insects were trapped in water with a little soap for subsequent collection (Annex I). We used the same ropes as used to place the detectors to hang the traps in the canopy.

The traps were installed for two whole nights from dusk until dawn (18.00–06.00) at each acoustic survey point. Insects were collected and stored in 96% alcohol (Jung, & Kalko, 2010) and afterwards identified to order level in the laboratory. Additionally, body height, width and length of each insect were measured using a millimeter paper. Two variables were considered for analysis: the number of individuals collected (ind.) and their volume (vol.).

Vegetation obstruction

In order to assess vegetation obstruction, eight photographs were taken at night per sampling point, four of the canopy and four of the understory. A Canon 550D camera was used with an external flash (Nissin DI866 model) and a SAMYANG 14mm, F.2.8 lens. The camera was lifted into the canopy using the same rope system as the detectors and insect traps. Photographs were transformed with Photoshop CS6 (California, USA) into black-and-white images; ImageJ V.1.46r (National Institute of Health, USA) was used to calculate the percentage of obstruction (the white part).

Statistical analyses

Generalized Linear Model (GLMs) were used test for differences in species–specific bat activity levels between the understory and canopy, and also to determine which explanatory variables (vegetation obstruction, habitat, height, insects and interaction between habitat and height) were best able to explain the variation of bat activity. In order to account for overdispersion in our count data we chose a Quasi-Poisson family GLM with a log link function (Zuur et al., 2009; Zuur et al., 2010). All analyses were performed with R 3.0.1 (R Core Team 2013, Austria).

Results

A total of 90,641 bat passes were identified in our recordings (representing 31.8% of all analysed data: 288,291 records). Species from 6 bat families were detected during the study, comprising 13 genera, 24 species, and 2 phonic groups (Table 1).

Table 1: Families, genera and bat species recorded. Species marked with (*) correspond to phonic groups.

Family Genus Species

Emballonuridae Saccopteryx S. bilineata S. leptura S. canescens Peropteryx P. kappleri P. macrotis Cormura C. brevirostris Centronycteris C. maximiliani Vespertilionidae Vespertilionidae 2 Vespertilionidae 3 Eptesicus-Lasiurus* Myotis M. riparius M. nigricans M. albescens Mormoopidae Pteronotus P. parnellii 55 kHz P. parnellii 60 kHz P. gymnonotus P. personatus Molossidae Molossus M. molossus Molossus <30 kHz* Molossops Molossops sp. Promops Promops sp. Cynomops Cynomops sp. Eumops Eumops sp. E. auripendulus Thyropteridae Thyroptera Thyroptera sp. Furipteridae Furiptera Furiptera sp.

Vertical stratification

While Pteronotus parnellii 60, Saccopteryx bilineata, the Eptesicus-Lasiurus phonic group, Promops and Vespertilionidae 3 only showed slightly significant differences in activity levels between the canopy and understory, Saccopteryx leptura (Fig.9), Cormura brevirostris (Fig. 13) and Centronycteris maximilani (Fig. 14) showed highly significant differences between forest strata (Table 2). The remaining species (Table 2) showed no significant differences between canopy and understory (Fig.1) (Fig.5) (Fig.6) (Fig.7) (Fig.10) (Fig.13) (Fig.11) (Fig.15) (Fig.16) (Fig.17) (Fig.19) (Fig.20) Over all bat activity, there was a highly significant differences being canopy more concurrent for aerial insectivorous bats (Table 2) (Fig.21)

Habitat–specific differences

Few species – Saccopteryx bilineata, Saccopteryx leptura, Eptesicus–Lasiurus and– showed strongly significant differences in their use of primary forest, while E. auripendulus showed highly significant differences for secondary forest; Cormura brevirostris showed weak significant differences in the use of primary forest.

Relationship between bat activity and other explanatory variables

Likewise, several species (S. bilineata, Eptesicus-Lasiurus, M. molossus, Vespertilionidae 2 and Vespertilionidae 3) showed weakly significant differences in terms of vegetation obstruction, while M. riparius and M. nigricans showed strongly significant differences for this variable and increased their activity whenever there was less obstructive vegetation.

For the activity of M. albescens and Eptesicus-Lasiurus, coleopter (ind.) availability was a weakly significant predictor, while dipter (ind.) was only significant for Eptesicus- Lasiurus. Activity of Vespertilionidae 2 and Vespertilionidae 3 presence was strongly related to coleopter (vol), that of S. bilineata and Eptesicus-Lasiurus was related to dipter (vol.), and that of Eptesicus-Lasiurus and Vespertilionidae 3 to lepidopter (vol.).

Table 2: Results of Quasi-Poisson GLMs on species-specific and total bat activity with explanatory variables (Height, Habitat, interaction Height-Habitat, obstruction, coleroptera, diptera and lepidoptera (ind. – individuals; and vol – volume). Significant values: (***) P ≥ 0; (**) P ≥ 0.001; (*) P ≥ 0.01

Height Habitat Height*Habitat Obstruction Coleoptera(ind.) Species z values P-values z values P-values z values P-values z values P-values z values P-values

Pteronotus parnellii 55 1.796 0.0763 -0.046 0.9638 -0.524 0.6015 -0.119 0.9059 0.748 0.4570

Pteronotus parnellii 60 2.083 0.0406 * 1.466 0.1467 -0.897 0.3726 -0.586 0.5599 0.192 0.8486

Saccopteryx bilineata -2.419 0.01795 * -3.431 0.00097 *** 0.763 0.44805 -2.019 0.04698 * -0.103 0.91825

Saccopteryx leptura -4.135 8.96e-05 *** -2.662 0.00944 ** -0.114 0.90945 0.008 0.99332 1.207 0.23118

Saccopteryx canescens -0.433 0.66590 1.843 0.06912 0.000 0.99966 -0.884 0.37965 -1.389 0.16880

Peropteryx kappleri -1.317 0.192 -0.065 0.948 0.382 0.703 0.120 0.905 -0.104 0.917

Peropteryx macrotis -0.853 0.3960 1.234 0.2211 -0.045 0.9644 1.668 0.0993 -0.565 0.5739

Cormura brevirostris -4.027 0.000131 *** -2.149 0.034780 * 0.435 0.665100 0.146 0.884680 0.758 0.451052

Centronycteris maximilani -2.791 0.00662 ** -0.613 -0.613 0.734 0.46541 1.217 0.22730 0.023 0.98142

Myotis riparius -0.282 0.77870 1.356 0.17919 -1.578 0.11865 3.083 0.00284 ** -0.699 0.48676

Myotis nigricans -1.132 0.26132 1.848 0.06840 -0.207 0.83655 3.045 0.00318 ** 0.042 0.96621

Myotis albescens 0.006 0.9955 0.006 0.9950 -0.007 0.9942 -0.589 0.5578 2.181 0.0322 *

Eptesicus-Lasiurus -2.052 0.043544 * -3.621 0.000523 *** 0.945 0.347532 -2.047 0.044110 * 2.444 0.016830 *

Molossus molossus -0.008 0.9937 -1.622 0.1089 0.000 0.9998 2.157 0.0341 * -1.207 0.2313

Molossus < 30khz -0.011 0.991 -0.273 0.785 0.009 0.993 0.290 0.773 -0.159 0.874

Molossops sp. 0.216 0.830 1.221 0.226 -0.005 0.996 -1.512 0.135 0.886 0.378

Promops sp. -2.454 0.016388 * -1.907 0.060205 -0.008 0.993403 0.055 0.956472 -1.029 0.306613

Vespertilionidae 2 -0.008 0.99374 -1.055 0.29457 0.000 0.99965 2.282 0.02524 * -1.083 0.28208

Vespertilionidae 3 -2.477 0.01544 * -0.051 0.95976 -0.005 0.99617 -2.237 0.02821 * -0.665 0.50777

Eumops sp. -0.010 0.9922 1.223 0.2250 0.008 0.9939 0.669 0.5053 -1.677 0.0977

Eumops auripendulus -0.008 0.99372 2.806 0.00636 ** 0.006 0.99559 -0.684 0.49578 -1.062 0.29161

Total bat activity -3.731 0.000362*** -1.325 0.189199 0.600 0.550214 0.508 0.613125 -0.217 0.828410

Continuation of Table 2

Species Diptera (ind.) Lepidoptera (ind.) Coleoptera(V) Diptera (V) Lepidoptera (V)

z values P-values z values P-values z values P-values z values P-values z values P-values

Pteronotus parnellii 55 1.392 0.1679 0.751 0.4547 0.640 0.5241 -1.666 0.0997 -0.630 0.5309

Pteronotus parnellii 60 1.314 0.1927 0.182 0.8557 0.335 0.7386 -1.468 0.1463 1.506 0.1361

Saccopteryx bilineata 1.554 0.12426 1.334 0.18626 -0.046 0.96352 -2.029 0.04596 * -0.062 0.95077

Saccopteryx leptura -0.885 0.37878 0.073 0.94230 -0.334 0.73924 -0.042 0.96691 -0.555 0.58081

Saccopteryx canescens -0.200 0.84222 -0.401 0.68968 -0.253 0.80088 0.475 0.63632 0.554 0.58089

Peropteryx kappleri -0.654 0.515 0.643 0.522 0.623 0.535 -0.395 0.694 -0.697 0.488

Peropteryx macrotis -1.264 0.2101 -0.334 0.7395 1.350 0.1809 1.653 0.1023 0.219 0.8272

Cormura brevirostris 0.100 0.920952 -1.301 0.197003 1.182 0.240822 -0.455 0.650312 0.300 0.765052

Centronycteris maximilani -0.211 0.83375 0.115 0.90843 0.519 0.60492 0.087 0.93067 -1.155 0.25146

Myotis riparius 0.331 0.74159 -0.252 0.80164 0.378 0.70652 -0.404 0.68726 -0.645 0.52057

Myotis nigricans 0.319 0.75038 1.749 0.08434 1.633 0.10662 -0.760 0.44946 -1.334 0.18611

Myotis albescens -0.233 0.8163 -0.075 0.9407 0.099 0.9216 -0.365 0.7158 1.315 0.1925

Eptesicus-Lasiurus 2.726 0.007928 ** -1.405 0.164162 -1.531 0.129857 -2.936 0.004386 ** 2.133 0.036121 *

Molossus molossus -2.202 0.0307 * 0.706 0.4823 1.346 0.1824 1.120 0.2661 -1.274 0.2066

Molossus < 30khz -0.720 0.474 -0.218 0.828 -0.665 0.508 0.633 0.529 -0.178 0.859

Molossops sp. -0.019 0.985 1.179 0.242 -1.028 0.307 -0.351 0.727 -0.669 0.505

Promops sp. 0.110 0.912465 -1.558 0.123342 -0.175 0.861315 -0.222 0.825009 1.393 0.167568

Vespertilionidae 2 1.629 0.10729 0.012 0.99031 2.186 0.03183 * -1.003 0.31888 -1.304 0.19628

Vespertilionidae 3 -1.807 0.07470 -1.704 0.09241 2.153 0.03447 * 1.134 0.26043 2.432 0.01732 *

Eumops sp. -0.139 0.8897 -0.539 0.5914 1.824 0.0720 0.383 0.7027 0.008 0.9939

Eumops auripendulus -0.715 0.47687 -1.100 0.27487 -0.754 0.45313 1.447 0.15186 1.552 0.12468

Total bat activity 0.033 0.973921 0.127 0.899459 0.645 0.521028 -0.344 0.731514 -0.808 0.421597

Species bar plots grouped in bat families and orders of insects for canopy and understory in primary (MP) and secondary (MS) forest showing mean and standard error (se).

Mormoopidae

Figure 1: Pteronotus parnellii 55 (mean ± se) Figure 2: Pteronotus parnellii 60 (mean ± se)

Emballonuridae

Figure 3: Saccopteryx bilineata (mean ± se) Figure 4: Saccopteryx leptura (mean ± se)

Figure 5: Saccopteryx canescens (mean ± se) Figure 6: Peropteryx kappleri (mean ± se)

Figure 7: Peropteryx macrotis (mean ± se) Figure 8: Cormura brevirostris (mean ± se)

Figure 9: Centronycteris maximiliani (mean ± se)

Vespertilionidae

Figure 10: Myotis riparius (mean ± se) Figure 11: Myotis nigricans (mean ± se)

)

Figure 13: Vespertilionidae 2 (mean ± se) Figure 12: Eptesicus-Lasiurus (mean ± se)

) )

Figure 14: Vespertilionidae 3 (mean ± se)

) 18

Molossidae

Figure 15: Molossus molossus (mean ± se) Figure 16: Molossus < 30kHz (mean ± se)

) )

Figure 18: Promops sp. (mean ± se) Figure 17: Molossops sp. (mean ± se)

) )

Figure 20: Eumops auripendulus (mean ± Figure 19: Eumops sp. (mean ± se) se)

) )

Total bat activity

Figure 21: Total bat activity (mean ± se)

Orders of insects

Figure 22: Abundance of coleopters (mean ± se) Figure 23: Abundance of dipters (mean ± se)

Figure 24: Abundance of lepidopters (mean ± se)

Discussion

When studying aerial insectivorous bats, acoustic surveys are the most effective method than other techniques such as mist-netting due to their ability to avoid them. In fact, according to MacSwiney et al. (2008), acoustic methods detect 30% more of the bat community than mist-netting. Other studies based on acoustic surveys have shown that Neotropical non-phyllostomid bat families are not adequately represented in mist netting studies (Ochoa et al., 2000). Some studies support the idea that acoustic surveys are an effective way of studying insectivorous bats (Estrada-Villegas et al., 2010; Jung, & Kalko, 2010; Meyer et al., 2011). Nevertheless, some important considerations must be taken into account: acoustic surveys, for example, are unable to calculate bat abundance or to separate bat individuals, sexes or ages; furthermore, the vegetation could reflect echolocation calls, thereby attenuating and decreasing bat detectability (Patriquin et al., 2003), and species-specific detectability is still imperfect (Meyer et al., 2011). In this study we tried to correct or minimize these problems and discuss them below.

The fact that most bat studies are carried out only in the understory implies that there is a considerable lack of knowledge on what is happening to canopy bat species, but not only in the Amazon, but also in temperate zones (Hayes, & Gruver, 2000); this is even more problematic in the case of aerial insectivorous bat species since acoustic surveys have only just begun to be used. In fact, several vertical stratification studies have shown a remarkable difference, in terms of species composition, between canopy and understory, but so far have only considered phyllostomid bats (Kalko, & Handely, 2001; Henry et al., 2004; Pereira et al., 2010). Several studies carried out in the eastern Amazon (Handley,1967) show that some species were represented 45 times more in the understory than in the canopy, and that the proportion of pteropodid bats varied 30–100 times between the canopy and the understory (Francis, 1994). Our results basically coincide with this latter author’s findings and provide data that indicates that most insectivorous bat species will be under-represented if canopy habitats are not taken into account. Most of the species that were often recorded in our study are extremely rare or uncommon, or had never been captured by other bat studies carried out at the BDFFP based on mist-netting (López-Baucells, unpublished).

Pteronotus parnellii 60 showed differences in vertical stratification and was commoner in the understory. However, the closely related species Pteronotus parnellii 55 showed no preference for either the understory or the canopy. Despite not being significant,

21 there seems to be a tendency for these bats to forage in the understory in both the primary and the secondary forests (Fig.1; Fig.2); a larger sample size is probably needed if we are to determine whether or not they positively select this stratum. Some studies partially support our results and have also shown that P. parnellii usually commutes near the ground and that their high duty cycle of echolocation allows them to detect their prey in areas cluttered with vegetation (Goldman & Henson, 1977; Herd, 1983; Fenton et al., 1995). Nevertheless, we were unable to detect any relationship with the obstruction. Saccopteryx bilineata, S. leptura, Cormura brevirostris, Centronycteris maximilani, Eptesicus-Lasiurus, and Vespertilionidae 3 were all significantly more frequent in the canopy The fact that some morphologically similar emballunorids such as Saccopteryx canescens, Peropteryx kappleri and P. macrotis did not select for either the understory or canopy could be explained by their rarity and low number of detections, which make data interpretation even harder and somewhat problematic. However, Myotis riparius, M. nigricans, M.albescens and Vespertilionidae 2 all seemed to forage at both heights in the forest. All these species are vespertilionids, where our results have showed a similar distribution between strata.

The activity of a total of six species (Saccopteryx bilineata, Myotis riparius, M. nigricans, Eptesicus-Lasiurus, Vespertilionidae 2 and Vespertilionidae 3) was strongly related to the vegetation obstruction. Although M. riparius, M. nigricans and Vespertilionidae 2 did not show differences between canopy and understory use, they generally preferred more open areas with less dense vegetation (Fig. 12; Fig.13: Fig.18). Only in three species (S. bilineata, Eptesicus-Lasiurus and Vespertilionidae 3) did behaviour seem to be more restrictive: these species selected only the canopies that it seemed to be related with less vegetation obstruction. It is known that some more manoeuvrable species are able to fly in cluttered areas due to their aspect ratio and wing loading, while other species prefer to forage in open areas (Kalkounis et al., 1999; Hodgkison et al., 2004; Jung, & Kalko, 2010; Findley et al., 1972; Norberg, &

Rayner, 1987). If the aspect ratio increases and the wing loading decreases, bats will tend to fly faster (e.g. S. bilineata, Eptesicus-Lasiurus) as the same case with high aspect ratio and high wing loading (Molossidae), while with a low aspect ratio and a high wing loading bats will fly more slowly but with greater manoeuvrability (P. parnellii) (Kalkounis et al., 1999). Our results could be explained by these species-specific differences in wing mophology.

A few species were related to the presence of a particular order of insects. Although bat activity is often assumed to increase with insect availability (Adams et al., 2009), only a few species in this study showed specific insect preferences. Activity of M. albescens and Eptesicus-Lasiurus was related to the number of coleoptera, which are part of their known diet (Whitaker et al., 1980; Aguiar, & Antonini, 2008). Eptesicus- Lasiurus activity was also related with the abundance of diptera; globally only two species (Eptesicus-Lasiurus and Vespertilionidae 3) were related to the volume of lepidotera. Eptesicus-Lasiurus was the only species group whose presence was related to all three insect orders. Coleoptera, diptera and lepidotera (Fig. 22) (Fig.23) (Fig.24) were the most represented insect families in the canopy, which could explain why both Eptesicus-Lasiurus and Vespertiliondiae 3 were related to the higher forest strata.

At the family level, the molossids (Molossus molossus, Molossus <30 Khz, Molossops sp., Cynomops sp., Promops sp., Eumops sp. and E. auripendulus) showed any preference for either of the forest strata, possibly due to a lack of data or to methodological limitations. Molossid species emit low frequency echolocation calls that disperse further and thus, they could be recorded more easily by the detectors in both the canopy and understory, thereby rendering our isolating system inefficient. Furthermore, the Molossidae are specialized for flight in completely open areas, that is, above the canopy or outside the forest. Due to their fast flight (Norberg, & Rayner, 1987), the molossids find it impossible to manoeuvre around any obstructions (Hayes, & Gruver, 2000).

Are there differences in activity between primary and secondary forest? Some species (S. bilineata, S. leptura, C. brevirostris, Eptesicus-Lasiurus and E. auripendulus) were more often recorded in the primary than the secondary forests. The difference in canopy height (higher in the primary forest) could be the principal factor that explains the differences between habitats, as these species will have more space to forage in the primary forests but at the same canopy height is the strata with a high presence of insects.

If we consider the results overall, a clear space separation between the understory and the canopy was discernible for different bat families. The Mormoopids typically commute in the understory strata unlike most emballonurids and molossids, which were only detected in the canopy strata; most vespertilionids (above all, Myotis species), which did not select clearly for either strata.

Implications for conservation

The capacity to assess a community in an ecosystem depends on how well we can describe the assemblages of all taxons. Here we provide evidence that it is essential to consider the whole vertical stratification (both understory and canopy) in both primary and secondary forests if any inventory of aerial insectivorous bat species in tropical rainforests is to be considered complete. Additionally, our results support the previously stated idea that it is more efficient to use acoustic surveys than mist-nets to describe assemblages (O’choa et al., 2000), a finding that should be borne in mind in future research. The fact that the majority of studies have focused to date on the understory and almost never use acoustics as a sampling technique has led to an under- representation of canopy species. The exclusion of canopy data could mean that some species may erroneously be classified as ‘rare’ or even absent from an area. Such false negatives could lead to management work being undertaken and nature conservation budgets may be misallocated. It is vital to have a complete description and understanding of how the whole ecosystem works if we are to adequately protect it.

Conclusions

A clear separation between canopy and understory species was detected; seven species were more often represented in the canopy than in the understory and only a few showed a preference for the understory. The two mormoopid species considered in the study showed a preference for the understory and most emballunorids and all Molossids for the canopy, while most vespertilionids (above all Myotis species) tended to occur in both strata.

The presence of six species was shown to depend on the degree of vegetation obstruction, probably due to their wing morphology. The vegetation obstruction was the variable that explained most of the differences in species-specific distribution between strata.

On the other hand, insect availability was related to the presence of only a very few species. More effort and variation in sampling samples is needed in any further research.

The 30-year-old secondary forests seem to be similar in terms of habitat quality as mature forests for most of the species (i.e. they showed similar patterns of activity); only five species had higher activity levels in the primary forest.

In summary, is essential to evaluate both strata in all studies of aerial insectivorous bats in the Neotropics to avoid underestimating the bat assemblages that are present. Acoustic surveying techniques are the best methods for studying these mammals.

Acknowledgments

We wish to thanks Adrià López Baucells for his help during the field work. All the workers of the Brazilian National institute for Research in the Amazon (INPA) and Smithsonian Tropical Research Institute - Instituto Nacional de Pesquisas da Amazônia to help me to develop this research on bats. And many thanks to Oriol Massana Valeriano, to provide me some pictures from our project.

References

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ANNEX I

Maps of study area

Figure 1: Map of BDFFP project in the Central Amazon. Blue circles denote the two study areas, Dimona and Cabo Frio.

Figure 2: Placement of the two transects at Dimona and Cabo Frio

Bat detectors and light traps

Figure 3: Canopy and understory detectors

Figure 4: Image of an insect light trap

ANNEX II

References for species acoustic identification:

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