Sensory ecology of that prey on

Thesis submitted by Martha Patricia Torres Sánchez

Grupo de Ecofisiología, Comportamiento y Herpetología Departamento de Ciencias Biológicas Universidad de los Andes

Under the Supervision of Professor Adolfo Amézquita, PhD

Dissertation presented in Partial Fulfilment of the Requirements for the Degree of Doctor of Sciences – Biology Universidad de los Andes Bogotá,

August 2019

“Si nos aventuramos en el conocimiento y en la ciencia, lo hacemos tan sólo para regresar mejor equipados para la vida” Johann Wolfgang von Goethe, 1806

Dedication

For my beloved son Martín, thank you for your laughter, for your games and for your caresses, thanks for being here and for making my life happy. For my life partner, Carlos for all the love and unwavering support you have given me. For my mother, who has supported me in everything and has helped me to become the person that I am today. For my family, who were always by my side and heard me talk about my research, even if they did not fully understand why I do what I do. They have all the gratitude and appreciation that I am able to muster.

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Agradecimientos

La parte más difícil de la escuela de posgrado es lograr un equilibrio entre el trabajo y la vida personal. Durante mi tiempo como estudiante de posgrado en la Universidad de los Andes, tuve la suerte de conocer gente que hizo que los momentos de trabajo y vida fueran más productivos y agradables. Estoy inmensamente agradecida con Adolfo Amézquita por apoyar los diferentes caminos que recorrí durante mi doctorado. Me dio suficiente independencia para permitirme construir mi propia senda, y ayudarme a resolver cuando las cosas estaban a punto de salirse de las manos. Gracias por recibir a esta aracnóloga, que nunca se sintió como “mosco en leche” en el GECOH. Sobre todo, gracias por la paciencia y persistencia durante estos años. Adolfo es un editor absolutamente increíble y mi redacción y esta tesis se han beneficiado de ello. A todos los antiguos y actuales miembros del GECOH por su generosa ayuda durante este proceso. Gracias especiales a Pablo Palacios, Diana Motta, Mabel González, Sofía Rojas, Pedro Patricio, Sebastián Di Doménico, Sebastián Gómez, Catalina Orejuela, Santiago Mesa, Roberto Márquez, Iván Beltrán, Manuel Guayara, Leidy Barragán, Vicky Flechas y Javier Méndez por su ayuda durante la recolección de datos de campo y las primeras ideas de este trabajo. Mileidy Betancourt y Diana Galindo me han aconsejado, animado y apoyado – tanto en lo académico como en lo personal– a lo largo de estos años. Su amistad y ayuda han sido especialmente valiosas durante los últimos meses de redacción. Diana Pinto y Camilo Rodríguez hicieron extremadamente productivo y agradable el trabajo de campo. Les doy gracias por su paciencia para enseñarme a reconocer las ranitas y apoyar mis experimentos vibracionales y comportamentales. A mis colegas de la Universidad Central Javier Casas y Mauricio Vergara, quienes diseñaron y facilitaron generosamente equipos para realizar mis experimentos y respondieron el teléfono (¡incluso en navidad!) para solucionar

iii problemas. Les agradezco por empujarme a pensar en nuevas formas de abordar mis preguntas y guiarme a través de los complicados conceptos de la física del sonido. Yeltsin Torres y Gustavo Lozano, estudiantes de ingeniería electrónica (UC) siempre fueron un oído dispuesto, me enseñaron habilidades útiles para la vida (¡como soldar!) y a no tener miedo de la física para medir la vibración con paciencia y buen sentido del humor. A Eileen Hebets de la Universidad de Nebraska en Lincoln (UNL), quien me recibió en su laboratorio durante la pasantía y puso a disposición mía su tiempo y los recursos necesarios para completar con éxito esta etapa del doctorado. Su puerta siempre estaba abierta, ya fuera para charlar sobre mi investigación, el desarrollo de los experimentos y análisis vibracionales, o solo sobre la vida. Allí tuve la oportunidad de conocer a un talentoso grupo de investigadores quienes se convirtieron en amigos de confianza. Agradezco a Rowan McGinley por ser tan increíblemente generoso con su tiempo, por apoyarme y guiarme durante mi estancia en UNL. Rowan, Laura Segura, Colton Watts, Tyler Corey, Bridget Bigner, Laura Gatch y Fiona Grey; me animaron a pensar en la logística y metodologías de muchas ideas de investigación presentes y futuras. Les agradezco su entusiasmo por mi investigación. Goran Mihaijlovik y Juan Carlos Tamayo directores de la Reserva Tanimboca, me brindaron su apoyo logístico para conducir esta investigación. Leonaldo, Sarita, Ramiro, José y Rodolfo proporcionaron un apoyo inestimable durante el trabajo de campo en Leticia. El Amazonas es uno de los lugares más especiales del planeta y lo que lo hace más especial, son las personas verdaderamente increíbles que allí conocí. He tenido experiencias inolvidables y aprendí mucho de su dedicación y grandes corazones. También agradezco a todos los colegas y amigos que han estado de una u otra forma. A Daniel Garavito por su acompañamiento, sus minuciosos y rigurosos comentarios y correcciones.

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Gracias a mi comité de evaluación por sus sugerencias constructivas para mejorar este trabajo. Eduardo Flórez, Jorge Molina y Rodrigo Villemart, ustedes han sido increíblemente generosos y comprensivos, y aprecio su paciencia y visión de este trabajo. Mi investigación no hubiera sido posible sin la asistencia técnica y administrativa y apoyo en el Departamento de Ciencias Biológicas. Mi más grande agradecimiento a mi familia. A mi madre, hermanas y sobrinos por animarme siempre a pensar y soñar en grande. Por su amor y apoyo infinitos a lo largo de estos años, asistiendo en el cuidado de Martín durante los meses lejos de mi hogar. Y, por último, agradezco a mi hijo Martín quien desde el vientre acompañó el trabajo de campo y se convirtió en mi compañero de travesía. A mi esposo Carlos, quien con gran entusiasmo recolectó arañas, observó ranas y transportó materiales y equipos. Me acompañó a lo largo del proceso de escritura, dándome un abrazo después de un día particularmente difícil o estupendo. No tengo palabras para agradecerles por simplemente estar allí y apoyarme incondicionalmente. Mi investigación fue financiada con el apoyo de la Universidad de los Andes a través de los Proyectos Semilla y la Asistencia Graduada, la Universidad Central a través del Programa de Apoyo a Estudios de Posgrado; la Unidad de Diseño, Innovación e Integración de Tecnología (DIT); y el Departamento de Ciencias Naturales y Colciencias a través del proyecto ID#52037. La investigación fue aprobada por el CICUAL de la Universidad de los Andes (Protocolo CFUA 16-014) y se llevó a cabo de conformidad con el Permiso Marco de Recolección de Especímenes de Especies Silvestres de la Diversidad Biológica con Fines de Investigación Científica No Comercial #1386.

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Tabla de contenido Dedication ...... ii

Agradecimientos ...... iii

General Abstract ...... 1

Resumen General ...... 3

General Introduction ...... 6

Thesis Aims and Objectives ...... 9

Study System ...... 10

Literature cited ...... 13

Chapter I: -eating Spiders: An Ecological Accident or a Specialized Guild? ...... 22

Abstract ...... 23

Introduction ...... 24

Methods ...... 26

Data Collection and Search Criteria ...... 26

Sampling the Spatial Overlap Between Spiders and Putative Prey ...... 28

Predation Experiments ...... 29

Results ...... 30

Geographic distribution and pervasiveness in anuran predation ...... 30

Co-occurrence and behavioural interactions between spiders and frogs: How Important are Anuran Predation? ...... 33

To what extent do spiders feed on anurans? ...... 34

Discussion ...... 34

Acknowledgments ...... 39

Literature cited ...... 39

Chapter II: Substrate vibration caused by calling frogs and its role as a cue for predatory spiders ...... 63

Abstract ...... 64

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Introduction ...... 66

Methods ...... 68

Study ...... 68

Transmission properties of natural substrates ...... 69

Substrate type and degradation of seismic cues ...... 72

Substrate Choice ...... 73

Results ...... 75

Signal Characteristics of the Frogs’ Calling Song ...... 75

Frog vibratory signal efficacy on different substrates ...... 76

Substrate Type and Choice ...... 78

Discussion ...... 79

Acknowledgments ...... 82

Literature cited ...... 82

Chapter III: Frog detection by predatory spiders: The role of chemical and seismic cues104

Abstract ...... 105

Introduction ...... 106

Methods ...... 109

Study Animals ...... 109

Spiders response to vibrations produced by frogs ...... 110

Influence of the interaction of chemical and vibratory cues in prey detection ...... 113

Results ...... 115

Characterization of prey vibrations on spider’s response ...... 115

Cue use in prey location: Responses to the chemical and vibrational cues ...... 116

Discussion ...... 116

Acknowledgments ...... 119

Literature cited ...... 119

Concluding remarks ...... 133 vii

Ethics Considerations ...... 136

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General Abstract

The study of sensory ecology, how animals perceive and interpret their environment, can be a powerful tool gain a deeper understanding on how evolution have shaped behaviour, morphology, and ecology. We have a well-founded idea of how spiders perceive and respond to visual, chemical and vibrational signals, in the context of mating and intraspecific aggression, yet we understand very little about how environmental cues are used to detect and recognise their potential prey. There is a growing number of reports of anurans preyed by spiders but the sensory ecology underlying this interaction is almost unknown. In an effort to add to the conceptual framework, I conducted in this thesis reviews, surveys, experiments and analyses around the predator–prey relationship between spiders and frogs. First (1a) I exhaustively reviewed the available and reliable reports of this interaction. I found it to be overrepresented in a small group of spider families, specifically ctenids and theraphosids, but a broad spectrum of anuran families, perhaps less accentuated in toxic frogs. Precisely, because frogs strongly vary in their profitability as prey, from very toxic to relatively harmless, (1b) I first conducted field surveys that confirmed the spatiotemporal overlap between spiders and frogs, and then (1c) tested whether spiders avoid toxic anurans in predation experiments. They did. For the last two and the following aims, I used three Amazonian spider , belonging to the families more often reported to prey on frogs: fera, Ancylometes rufus (Ctenidae) and Avicularia juruensis (Theraphosidae). Spiders possess well developed mechanoreceptors and use seismic signals during courtship and male-male interactions. Because spiders might eavesdrop seismic cues produced by their prey, I experimentally confirmed (2a) that frogs produce seismic cues while they utter advertisement calls. Those vibrations are transmitted within very narrow frequency bandwidths and at very low dominant frequencies (below 100–600 Hz). They also (2b) convey enough information as to discriminate among three tested frog species. Because the information content of seismic cues is probably degraded along the propagation medium, (2c) I further examined the filtering properties of four natural substrates available for spiders and frogs, and tested whether the studied spiders selected microhabitats accordingly. The substrates had indeed drastically different filtering properties and plant leaves was the substrate that best transmitted the seismic cues. The spiders, however, preferred the experimental microhabitats that better mimicked their natural perches rather than the microhabitats that least degraded the seismic cues. Lastly, (3a) I aimed at testing whether frogs actually respond to seismic cues as emitted from calling frogs. A Y-maze playback experiment supported this hypothesis: most tested spiders climbed a plant and approached to the branch transmitting frog vibrations, but just a few reacted when the branch was transmitting white- noise vibrations that sub served as experimental controls. Lastly, to estimate the importance for prey detection of seismic cues compared to other sensory modality, (3b) I conducted a two-choice experiment. Spiders were offered two chambers: one transmitting seismic and chemical cues from a captive frog, and the other transferring only chemical cues. Even though the spiders did not evidence a clear preference in their first reaction, they spent more time in the chamber of bimodal stimuli. This study has evidenced and phylogenetically contextualised the importance of spiders as predators of frogs. It further demonstrates that seismic cues, a by-product of frog calling behaviour, are produced and transmitted best along plant substrates. Perhaps more importantly, it shows that these seismic cues are indeed recognised by predatory spiders, as evidenced by both seismotactic approaches and microhabitat selection. Altogether, our evidence invites to reconsider the role of this predator–prey interaction in structuring ecological communities, explaining biodiversity patterns, and shaping the behaviour, physiology, and morphology of both spiders and frogs.

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Resumen General

El estudio de la ecología sensorial, cómo los animales perciben e interpretan su entorno, puede ser una herramienta poderosa para obtener una comprensión más profunda de cómo la evolución ha dado forma al comportamiento, la morfología y la ecología de los animales. Tenemos una idea bien fundada de cómo las arañas perciben y responden a las señales visuales, químicas y vibratorias, en el contexto del apareamiento y la agresión intraespecífica. Sin embargo, sabemos muy poco acerca de cómo se utilizan las señales ambientales para detectar y reconocer sus posibles presas. Hay un número creciente de informes de anuros cazados por arañas, pero la ecología sensorial que subyace a esta interacción es casi desconocida. En un esfuerzo por agregar al marco conceptual, realicé en esta tesis revisiones, encuestas, experimentos y análisis sobre la relación depredador–presa entre las arañas y las ranas. Primero (1a) revisé exhaustivamente la información disponible y confiable sobre esta interacción. Descubrí que los eventos de depredación estaban sobrerrepresentados en un pequeño grupo de familias de arañas, específicamente cténidos y therafósidos, aunque en un amplio espectro de familias de anuros, quizás menos acentuadas en ranas tóxicas. Precisamente, debido a que las ranas varían mucho en su rentabilidad como presas, desde muy tóxicas hasta relativamente inofensivas, (1b) primero realicé estudios de campo que confirmaron la superposición espaciotemporal entre las arañas y las ranas, y luego (1c) probé si las arañas evitan los anuros tóxicos en la depredación. En los experimentos realizados, lo hicieron. Para los últimos dos capítulos y los siguientes objetivos, utilicé tres especies de arañas amazónicas, pertenecientes a las familias que con más frecuencia se reportan como depredadoras de ranas: Phoneutria fera, Ancylometes rufus (Ctenidae) y Avicularia juruensis (Theraphosidae). Las arañas poseen mecanorreceptores bien desarrollados y usan señales sísmicas durante el cortejo y las interacciones entre machos y hembras. Debido a que el contenido de información de las señales sísmicas probablemente se degrada a lo largo del medio de propagación, (2c) examiné las propiedades de filtrado de cuatro sustratos naturales disponibles para arañas y ranas, y probé si, en consecuencia, las arañas estudiadas seleccionaban microhábitats. Los sustratos tenían propiedades de filtrado drásticamente diferentes y las hojas de las plantas eran el sustrato que mejor transmitía las señales sísmicas. Las arañas, sin embargo, preferían los microhábitats experimentales que mejor imitaban sus perchas naturales en lugar de los microhábitats que menos degradaban las señales sísmicas. Finalmente, (3a) me propuse probar si las arañas responden realmente a las señales sísmicas emitidas por las ranas. Un experimento con reproducción de vibraciones en arena experimental y en forma de Y apoyó esta hipótesis: La mayoría de las arañas probadas escalaron una planta y se acercaron a la rama que transmitía las vibraciones de la rana, pero solo unas pocas reaccionaron cuando la rama transmitía vibraciones de ruido blanco que servían como controles experimentales. Por último, para estimar la importancia de la detección de presas de señales sísmicas en comparación con otra modalidad sensorial, (3b) realicé un experimento de dos opciones. A las arañas se les ofrecieron dos cámaras: una transmitía señales sísmicas y químicas de una rana cautiva, y la otra transmitía solo señales químicas. A pesar de que las arañas no mostraron una clara preferencia en su primera reacción, pasaron más tiempo en la cámara de los estímulos bimodales. Este estudio ha demostrado y contextualizado filogenéticamente la importancia de las arañas como depredadores de ranas. Además, demuestra que las señales sísmicas, un subproducto del comportamiento de llamada de la rana, se producen y transmiten mejor a lo largo de sustratos vegetales. Quizás más importante, muestra que estas señales sísmicas son reconocidas por las arañas depredadoras, como lo demuestran los enfoques sismotácticos y la selección de microhábitats. En conjunto, nuestra evidencia invita a reconsiderar el papel de esta interacción depredador–presa en la estructuración de comunidades ecológicas, explicando los patrones de

4 biodiversidad y configurando el comportamiento, la fisiología y la morfología de las arañas y las ranas.

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General Introduction

Photo by Patricia Torres

Avicularia juruensis in a typical substrate in Tanimboca Reserve, Leticia, Amazonas, Colombia.

The capacity of animals to acquire information from the environment is essential for occupying proper feeding and breeding , which ultimately affects ecological performance and fitness. Both biotic and abiotic cues may guide the animals through an assortment of habitats, and sensory systems should be able to perceive and decode the relevant information. In addition, the use of multiple sensory modalities by predators should be favoured by natural selection, where they increase the probability of detecting profitable prey (Grinsted et al. 2013). The study of the mechanisms that underlie prey detection and recognition is necessary to fully understand individual behavioural decisions and the nature of predator-prey interactions (Uma 2010).

Arachnids have been found to use a variety of senses by combining information from two or more sensory modalities, which allows them to assess environmental information with less ambiguity (Uetz and Roberts 2002, Uma and Weiss 2010, Fenk et al. 2010, Chen et al. 2013). Vision, taste and Photo by Patricia Torres chemical cues have been found to have variable importance among different species. Most spiders, however, are believed to use detection of vibrations both in air and through the substrate as their primary means of detecting prey (Rovner and Barth 1981, Barth 1998, 2002; Foelix 2011).

Spiders are found in virtually all terrestrial (and some aquatic) habitats and, thus, potentially consume a variety of prey (Wise 1995). They receive signals from their prey on virtually a vast variety of substrates with drastically different physical properties. This is particularly noticeable in ctenids and theraphosids, cursorial and relatively mobile species (Elias et al. 2004). Because the type and availability of prey are likely to change throughout ontogeny of spiders, the season of the year and the time of day, sensory and learning abilities are expected to contribute at various spatial scales (Kingsford et al. 2002) to their ecological performance (Niemelä and DiRienzo 2013).

Two major factors must be considered in this context. First, communication via seismic signals is affected by substrate heterogeneity. On the other hand, spiders exhibit multimodal communication that conveys information in more than one sensory modality (Hebets and Papaj 2005, Partan and Marler 2005, Bro-Jørgensen 2010, Gordon and Uetz 2011). Focusing on the specifics of one modality, we may lose the dynamic interplay between modalities (Gordon and Uetz 2011). Despite these restrictions, it is important to consider vibrational communication channels as having the diversity of prey capture signalling strategies among spiders.

Although frogs are not traditionally considered common prey for spiders, there is significant evidence of this interaction (for reviews, see McCormick and Polis 1982, Menin et al. 2005, Toledo 2005, Nyffeler and Pusey 2014, von May et al. 2019). Spiders in a number of species readily capture and eat adult , especially when they are aggregated at breeding sites (Toledo 2005, Wells 2007). Both the coincidence and the complex ecological interactions between them make these groups an interesting system for testing how variation in the sensory capacities of a species can affect the outcome of the interaction. Despite the frequent co–occurrence of spiders and breeding frogs, the sensory ecology of their predator–prey interactions have been rarely addressed (von May 2019). The aim of this paper is the understanding of how variation in the availability of seismic cues affects the outcome of this interaction.

Particularly, I am interested in testing the following hypotheses: Because frogs strongly vary in their profitability as prey, from very toxic to relatively harmless, I hypothesize that (1) prey choice by spiders is based on the

8 profitability of frogs. Because the degradation of seismic information depends upon the microhabitat, I further hypothesize that (2) spiders will select microhabitats that benefit the transmission of seismic signals. Finally, (3) spiders are able to assess seismic cues to locate and attack frogs.

Thesis Aims and Objectives

The general aim of this thesis is to study the dynamic relationship between predatory spiders and their anuran prey, with a focus on how vibrational cues and the physical environment influence the outcome of these interactions. By combining laboratory and field evidence, I tested the aforementioned general hypotheses in a series of interrelated chapters, intended to be manuscripts. Chapter one reviewed all the available and reliable information on predation of anurans by spiders to test (1a) whether those ecological interactions are disproportionally found in some anuran and spider taxa. In the field; (1b) I estimated the degree of co-occurrence between frogs and those spiders most frequently reported to prey on them. Finally, (1c) I experimentally tested whether those spiders discriminate toxic against non-toxic frog prey. Chapter two tested (2a) whether the seismic signals produced during frog calling, and propagated via substrate, convey enough information to discriminate between frog species; and (2b) whether some substrates outperform others in the propagation of seismic signals. In Chapter three, I tested whether my spider research models differ in behavioural attributes that might associate with their role as anuran predators. Specifically, (3a) whether spiders are attracted toward vibratory signals mimicking calling frogs, and (3b) which sensory modality prevails during detection and capture of frogs.

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Study System

Spiders are major predators in forest-floor leaf litter (Weidemann 1976, Schaefer 1991, Wise and Chen 1999). They influence herbivore and detritivore communities by numerous direct and indirect interactions, and play a critical role in the structure and functioning of food webs (McCormick and Polis 1982). In the tropics, spiders are among the most diverse predaceous and exhibit high levels of both family and species richness in this region (Cardoso et al. 2011).

Ctenidae is the most studied family of Neotropical spiders. Some iconic species such as Cupiennius have been used as a model in a wide range of studies on sexual and reproductive behaviour and sensory ecology (for revisions Willemart and Lacava 2017). However, there are still studies on predatory interactions, given the wide variety of prey from ants, to vertebrates, such as bats and anurans (von May et al. 2019). On the other hand, Theraphosidae are among the largest spiders, with sizes exceeding 15 cm (Costa and Pérez- Miles 2002). They are voracious and opportunistic predators, who regularly consume a great variety of vertebrate prey including rodents, birds, , geckos, other lizards and even anurans (Raven 2000). They are considered an important ecological factor as the main predator of numerous food chains (Berge 2003).

Predation by invertebrates upon vertebrates has been well documented in aquatic systems (Horstkotte et al. 2010, Nyffeler and Pusey 2014). Few experimental studies have addressed the role of invertebrates as vertebrate predators of in terrestrial ecosystems (Formanowicz et al. 1981, Rubbo et al. 2001, 2003). Spiders prey on anurans and both the abundance and co- occurrence of these taxa suggest a relevant ecological role of spiders as regulatory mechanisms and selection pressures on populations

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(Greene 1988, Donnelly and Guyer 1994, Vega–Trejo et al. 2013). To fully understand such role, the behavioural ecology of predator–prey interactions between spiders and frogs must be investigated in a rigorous manner.

In this study, I first reviewed literature and the internet in search of the most available and reliable reports of spiders preying on frogs. The analysis of reviewed data allowed me to choose three spider species of the genera Ancylometes, Phoneutria (Ctenidae), and Avicularia (Theraphosidae) as model predators of frogs (Figure 1). They are large nocturnal hunting spiders, and common members of Amazonian spider communities. Phoneutria fera is one of the most abundant large spider species in the Amazonia. They are frequently found perching on large leaves, probably because they can sustain their weight and transmit vibrations efficiently (Barth et al. 1988, Torres–Sánchez and Gasnier 2010). Ancylometes rufus forage mostly on the ground, often near water bodies, where they frequently feed on arthropods and some aquatic vertebrates, e.g., tadpoles, toads and small fishes (Gasnier et al. 2002). Avicularia juruensis is found among leaves of herbaceous and climbing plants, on tree trunks and branches, and on man-made structures (Stradling 1994). It is known to prey on crickets, wax moths, grasshoppers, roaches and small tree frogs (Schultz and Schultz 2009).

All the subsequent observational and experimental data included in the present thesis were thus gathered in the terra-firme forest at the Tanimboca Nature Reserve, Km, 11 km north of the city of Leticia (Colombia) on the Leticia–Tarapacá road (04°07’15.4’’S, 69°57’19.7’’W, 89 masl.). The reserve encompasses 29 hectares of secondary and primary forests, with predominance of platanillo gigante (Phenakospermun guyanense), yarumo (Cecropia scyadophylla), castaño (Scleronema micranthum), caucho (Hevea sp.), palosangre (Brosimum rubescens), and acapu (Minquartia guianensis) (Maldonado 2011). The richness of anurans at Tanimboca surpasses 91

11 species (Castroviejo, sf). Despite the striking diversity of reproductive modes in Amazonian anurans (Hödl 1990), most species are either arboreal frogs that lay eggs on temporary ponds, or terrestrial species that lay eggs outside the water.

I was interested in two particular groups of frog species for my observations and experiments. First, because many spiders are seen preying on frogs at temporary ponds, I principally chose some arboreal frogs (family , genera , Boana, , Osteocephallus and Phyllomedusa) and low vegetation inhabitants (family , Pristimantis) to conduct a spatial overlap analysis and experiments on the role of auditory signals and seismic cues on the spiders’ behaviour. Most of these frogs mostly call from elevated perches above water and lay their eggs directly in the water or on leaves and branches above it. Secondly, because terrestrial frogs encompass from relatively harmless to very toxic frogs, I conducted further experiments using leaf litter frogs ( [Craugastoridae] and Rhinella [Bufonidae]) including a reportedly poisonous species of family Dendrobatidae, Ameerega trivittata (Figure 2). By including both arboreal and terrestrial frogs in this study, I also include the range of habitats where my study spiders are found.

Accordingly, accumulating literature suggests that spiders play an important role as vertebrate predators across Neotropical wet forests (Hayes 1983, Guyer 1988), but no study to date has examined how sensory systems are shaped to influence predatory behaviour in these abundant ctenid spiders in a predator- prey context.

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Literature cited

Barth, F. G., Bleckmann, H., Bohnenberger, J., & Seyfarth, E. (1988). Spiders of the Cupiennius Simon 1891 (Araneae, Ctenidae). Oecologia, 77(2), 194-201. doi:10.1007/bf00379186

Barth, F. G. (1998). The Vibrational Sense of Spiders. Comparative Hearing: Insects Springer Handbook of Auditory Research, 228-278. doi:10.1007/978-1-4612-0585-2_7

Barth, F. G. (2002). Spider senses – technical perfection and biology. Zoology, 105(4), 271-285. doi:10.1078/0944-2006-00082

Berge, B. (2003). Predatory behaviour of theraphosid spiders in Northern Queensland. (Unpublished doctoral dissertation). James Cook University, Queensland, Australia.

Bro-Jørgensen, J. (2010). Dynamics of multiple signalling systems: Animal communication in a world in flux. Trends in Ecology & Evolution, 25(5), 292-300. doi: 10.1016/j.tree.2009.11.003

Cardoso, P., Pekár, S., Jocqué, R., & Coddington, J. A. (2011). Global Patterns of Guild Composition and Functional Diversity of Spiders. PLoS ONE, 6(6). doi: 10.1371/journal.pone.0021710

Castroviejo, S., (n.d.). Anfibios de la Reserva Tanimboca [PDF].

Chen, Y., Liao, C., Tsai, F., & Chi, K. (2013). More than a safety line: Jump-stabilizing silk of salticids. Journal of The Royal Society Interface, 10(87), 20130572-20130572. doi:10.1098/rsif.2013.0572

Costa, F. G., & Pérez-Miles, F. (2002). Reproductive Biology of Uruguayan Theraphosids (Araneae, ). Journal of Arachnology, 30(3), 571-587. doi:10.1636/0161- 8202(2002)030[0571: rbouta]2.0.co;2

Donnelly, M. A., & Guyer, C. (1994). Patterns of reproduction and habitat use in an assemblage of Neotropical hylid frogs. Oecologia, 98,291–302. doi: 10.1007/BF00324217

Elias, D. O., Mason, A. C., Hoy, R. R. (2004). The effect of substrate on the efficacy of seismic courtship signal transmission in the jumping spider Habronattus dossenus (Araneae: Salticidae). Journal of Experimental Biology, 207:4105–4110. doi:10.1242/jeb.01261

Fenk, L. M., Hoinkes, T., & Schmid, A. (2010). Vision as a third sensory modality to elicit attack behavior in a nocturnal spider. Journal of Comparative Physiology A, 196(12), 957- 961. doi:10.1007/s00359-010-0575-8

Foelix, R. F. (2011). Biology of spiders. Oxford: Oxford University Press.

Formanowicz, D., Stewart, M., Karyn Townsend, Pough, F., & Brussard, P. (1981). Predation by Giant Crab Spiders on the Puerto Rican Frog Eleutherodactylus coqui. Herpetologica, 37(3), 125-129. Retrieved from http://www.jstor.org/stable/3891882

Gasnier, T. R., Torres–Sánchez, M. P., Azevedo, C. S. & Höfer, H. (2002). Adult size of eight hunting spider species in central Amazonia: temporal variations and sexual dimorphisms. Journal of Arachnology, 30,146-154. doi:10.1636/0161-8202(2002)030

Gordon, S. D., & Uetz, G. W. (2011). Multimodal communication of wolf spiders on different substrates: Evidence for behavioural plasticity. Animal Behaviour, 81(2), 367-375. doi: 10.1016/j.anbehav.2010.11.003

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Greene, H. W. (1988). Species richness in tropical predators. In F. Almeda & C. M. Pringle (Eds.), Diversity and Conservation of Tropical Rainforest (pp. 259–280). San Francisco, CA: Academic of Science.

Grinsted, L., Pruitt, J. Settepani, V. & Bilde, T. (2013). Individual personalities shape task differentiation in a social spider. Proceedings of the Royal Society B: Biological Sciences, 280, 20131407. doi:10.1098/rspb.2013.1407

Guyer, C. (1988). Food Supplementation in a Tropical Mainland Anole, Norops Humilis: Effects on Individuals. Ecology, 69(2), 362-369. doi:10.2307/1940434 Hayes, M. (1983). Predation on the Adults and Prehatching Stages of Glass Frogs (Centrolenidae). Biotropica, 15(1), 74-76. doi:10.2307/2388005

Hebets, E. A. & Papaj, D. R. (2005). Complex signal function: developing a framework of testable hypotheses. Behavioral Ecology and Sociobiology, 57,197–214. doi:10.1007/s00265-004-0865-7

Hödl, W. 1990. Biology and Physiology of Amphibians Reproductive diversity in Amazonian lowland frogs. In W. Hanke (Ed.). Fortschrine der Zoologie. Band/Vol. 38 (pp. 42–62). Sarsar, NY: Gusrav Fischer Verlag.

Horstkottet, J., Riidiger, R., Plath, M. & Jager, P. (2010). Predation by three species of spiders on a cavefish in a Mexican sulphur cave. Bulletin of British Arachnological Society, 15(2), 55–58. doi:10.13156/arac.2010.15.2

Kingsford, M. J., Leis, J. M., Shanks, A., Lindeman, K. C., Morgan, S. G. & Pineda, J. (2002). Sensory environments, larval abilities and local self-recruitment. Bulletin of Marine Science, 70,309–340. Retrieved from https://escholarship.org/uc/item/4zn2g6jf

Maldonado, A. M. 2011. Tráfico de monos nocturnos Aotus spp. en la frontera entre Colombia, Perú y Brasil: efectos sobre sus poblaciones silvestres y violación de las regulaciones

15

internacionales de Comercio de fauna estipuladas por cites. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 35(135), 225-242. Retrieved March 24, 2019, from http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0370- 39082011000200009&lng=en&tlng=es.

McCormick, S., & Polis, G. A. (1982). Arthropods that prey on vertebrates. Biological Reviews, 57: 29-58. doi:10.1111/j.1469-185X.1982.tb00363.x

Menin, M., Rodrigues, D. & de Azevedo, C. S. (2005). Predation on amphibians by spiders (Arachnida, Araneae) in the Neotropical region. Phyllomedusa, 4(1), 39-47. doi:10.11606/issn.2316-9079.v4i1p39-47

Niemelä, P. T., DiRienzo, N., & Hedrick, A. V. (2012). Predator-induced changes in the boldness of naïve field crickets, Gryllus integer, depends on behavioural type. Animal Behaviour, 84(1), 129-135. doi: 10.1016/j.anbehav.2012.04.019

Nyffeler, M., & Knörnschild, M. (2013). Bat Predation by Spiders. PLoS ONE, 8(3), e58120. doi: 10.1371/journal.pone.0058120

Partan, S., & Marler, P. (2005). Issues in the Classification of Multimodal Communication Signals. The American Naturalist, 166(2), 231-245. doi:10.1086/431246

Raven, R. 2000. Australia’s or whistling spiders. Queensland Museum, Retrieved from http://www.uq.edu.au/~xxrraven/therres.html.

Rovner, J. S., & Barth, F. G. (1981). Vibratory Communication Through Living Plants by a Tropical . Science, 214(4519), 464-466. doi:10.1126/science. 214.4519.464

Rubbo, M. J., Townsend, Jr., V. R., Smyers, S. D., & Jaeger, R. G. (2001). The potential for invertebrate–vertebrate intraguild predation: the predatory relationship between wolf

16

spiders ( pulchra) and ground skinks (Scincella lateralis). Canadian Journal of Zoology, 79(8), 1465-1471. doi:10.1139/cjz-79-8-1465

Schaefer, M. 1991. The animal community: diversity and resources. In E. Röhrig & W. Ulrich. (Eds.), Ecosystems of the world 7. Temperate deciduous forests (pp. 51–120). Amsterdam: Elsevier.

Schultz, S. A., & Schultz, M. J. (2009). The Tarantula Keeper's Guide: Comprehensive Information on Care, Housing, and Feeding. Hauppauge, NY: Barron's Educational Series.

Stradling, D. J. (1994). Distribution and Behavioral Ecology of an Arboreal `Tarantula' Spider in Trinidad. Biotropica, 26(1), 84. doi:10.2307/2389113

Toledo, L. F. (2005). Predation of juvenile and adult anurans by invertebrates: current knowledge and perspectives. Herpetological Review, 36(4), 395-400. Retrieved from www.researchgate.net/publication/289919007

Torres–Sánchez, M. P., & Gasnier, T. R. (2010). Patterns of abundance, habitat use and body size structure of Phoneutria reidyi and P. fera (Araneae: Ctenidae) in a Central Amazonian rainforest. Journal of Arachnology, 38(3), 433-440. doi:10.1636/p08-93.1

Uetz, G. W., & Roberts, J. A. (2002). Multisensory Cues and Multimodal Communication in Spiders: Insights from Video/Audio Playback Studies. Brain, Behavior and Evolution, 59(4), 222-230. doi:10.1159/000064909

Uma, D. B., & Weiss, M. R. (2010). Chemical Mediation of Prey Recognition by Spider‐ Hunting Wasps. Ethology, 116, 85-95. doi:10.1111/j.1439-0310.2009. 01715.x

Vega-Trejo, R., Zúñiga-Vega, J. J., & Langerhans, R. B. (2013). Morphological differentiation among populations of Rhinella marina (Amphibia: Anura) in western Mexico. Evolutionary Ecology, 28(1), 69-88. doi:10.1007/s10682-013-9667-6

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von May, R., Biggi, E., Cárdenas, H., Diaz, M. I., Alarcón, C., Herrera, V., Santa–Cruz, R., Tomasinelli, F., Westeen, E. P., Sánchez–Paredes, C. M., Larson, J. G., Title, P.O. Grundler, M. R., Grundler, M. C., Rabosky, D. & Rabosky, A. R. (2019). Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest. Amphibian and Conservation, 13(1),65–77.

Weidemann, G. (1977). Struktur der Zoozönose im Buchenwald-Ökosystem des Solling. Verhandlungen der Gesellschaft für Ökologie, Göttingen 1976, 59-74. doi:10.1007/978-94-011-5957-9_6

Wells, K. D. (2010). The Ecology and Behavior of Amphibians. Chicago, IL: University of Chicago Press.

Willemart, R. H., & Lacava, M. (2017). Foraging Strategies of Cursorial and Ambush Spiders. In Viera, C., & Gonzaga, M. O. (Eds.). Behaviour and Ecology of Spiders. Contributions from the Neotropical Region. Basingstoke, England: Springer International Publishing.

Wise, D. H. (1995). Spiders in Ecological Webs. Cambridge, England: Cambridge University Press.

Wise, D. H., & Chen, B. (1999). Impact of intraguild predators on survival of a forest-floor . Oecologia,121(1), 129-137. doi:10.1007/s004420050914

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Figure 1. Representative specimens of the studied spider species at the study site. a) Ancylometes rufus, b) Phoneutria fera, c) Avicularia juruensis. d) Ancylometes rufus preying on Dendropsophus (December, 10th 2015), e) Rhinella margaritifera predated by Ancylometes (January, 13th 2016). Photos by Patricia Torres.

Figure 2. Individuals of the anuran genera used as spiders’ potential prey in the predation experiment: a) Boana lanciformis, b) Osteocephallus yasuni c) Phyllomedusa tomocterma, d) Dendropsophus triangulum, e) Scinax ruber, f) Rhinella margaritifera, g) Oreobates quixensis, h) Pristimantis altamazonicus and i) Ameerega trivittata. Photos by Patricia Torres, except Pristimantis (by S. Waters).

a b c

d e

Figure 1

a b

c d e

f g h i Credit: Photo by S. Waters Figure 2

Chapter I Chapter I: Frog-eating Spiders: An Ecological Accident or a Specialized Guild?

Photo by Sofía Rojas

Avicularia juruensis preying on hylid frog goinorum? in Tanimboca Reserve in Leticia, Amazonas, Colombia. December, 18th 2014.

Abstract

Spider predation on frogs has been often reported, yet few studies address the extent, and ecological context of this interaction. I first conducted an exhaustive bibliographic search to learn whether this phenomenon is disproportionally found on some spider and anuran taxa. I created visualizations and conducted network analysis on the distribution of predator- prey interactions. Both analyses revealed that ctenid and theraphosid spiders are particularly prone to preying upon frogs. I thus conducted field surveys to examine the degree of co–occurrence between these spiders (Phoneutria, Ancylometes, Ctenus and Avicularia) and the most common frogs in a terra-fire Amazonian forest. The distribution of encountered individuals was modeled with regard to perch elevation and distance to water (pond, stream) edge. The results revealed a high overlap between frogs (especially Dendropsophus, Scinax, Pristmantis, Osteocephalus, Phyllomedusa, Oreobates and Rhinella) and their putative spider predators, especially Phoneutria and secondarily Ancylometes. Finally, because some frogs bear potent defensive alkaloids or peptides on their skin, I conducted predation experiments to test whether the study spiders discriminate against toxic frogs. The results show that these spiders can prey upon a wide array of arboreal and leaf litter anurans; they also show that, in particular, Ancylometes and Phoneutria spiders attack significantly fewer toxic frogs of the genera Ameerega. Summing up, our review, observational, and experimental data, suggest that spider predation on anurans is a common and ecologically relevant phenomenon that may have led to specific adaptations in both predators and prey. More studies should probably address this topic to gain a more complete overview of the ecology and evolution of tropical spiders and frogs.

Introduction

Spiders are generalist predators, abundant and ubiquitous, and thereby important components of many terrestrial animal communities (Wise 1993, Schmitz et al. 2000, Hurtado–Guerrero et al. 2003, Sørensen 2003). Their diet consists mainly of insects and other arthropods (Nentwig 1987, Foelix 2011). Yet it is known that a number of spiders supplement their diet by occasionally capturing vertebrates (McCormik and Polis 1982, Bleckmann and Lotz 1987). Like other generalist predators, spiders attack a variety of prey that vary in profitability, i.e. the trade-off between their energetic value and the cost of subduing them, overcoming their defensive mechanisms (Pollard 1990, Kneitel and Chase 2004, Nelson and Jackson 2011).

Several factors allegedly affect the attack of vertebrate prey by spiders: e.g. size, mobility, nutritional quality (Eubanks and Denno 2000, Rogers et al. 2012), and abundance (Jeschke and Tollrian 2000). Birds and bats are captured in orb-webs of araneid and nephilid spiders (Cox and NeSmith 2007, Duca and Modesto 2007, Timm and Losilla 2007, Gunnarsson 2008, Brooks 2012, Das et al. 2012, Nyffeler and Knӧrnschild 2013). Fish are prey of several large and semi-aquatic spiders (reviewed by Nyffeler and Pusey 2014) and a number of reports describe and amphibians being preyed on by spiders (Bauer 1990, Raven 1990, Armas 2000, Boistel and Pauwels 2002, Maffei et al. 2010). Anuran predation by spiders has been documented and reviewed in a handful of publications (Menin et al. 2005; Toledo 2005, Toledo et al. 2007, Mafei et al. 2010, von May 2019). There are also many, largely incidental observations without validation of species identity (Toledo 2005, Wells 2007, Foelix 2011). We are not aware of published quantitative analyses on the extent and ecological context of this interaction, despite the significant amount of anecdotical reports and the potential significance of this phenomenon at both

population and community levels (McCormick and Polis 1982, Donnelly and Guyer 1994).

Events of anuran predation by spiders have been reviewed predominantly from neotropical species (Menin et al. 2005, Maffei et al. 2010, von May 2019). The predation risk appears to be high during the breeding season of anurans, when recently metamorphosed froglets leave the water (Toledo 2005). Nonetheless, a number of spider predators readily capture adult amphibians, especially when they are aggregated at breeding sites (Menin et al. 2005, Wells and Schwartz 2007). The intensive use of auditory signals for mate attraction should render anurans conspicuous to spiders, because the spiders might eavesdrop the collateral vibrational cues (Uetz and Roberts 2002, Uma 2010). In addition, amphibians are known for possessing granular glands, which produce and often release chemicals that deter predators from ingesting them. Many frogs and salamanders are indeed known for being aposematic, i.e. for combining deterrent chemicals with conspicuous coloration or odour (Brodie et al 1991, Toledo and Jared 1995, Prates et al. 2012, Brunetti et al. 2019). Few predators have been shown to be able to overcome such defenses (Ringler et al 2010, Lenger et al. 2014). Because spiders do not eat whole prey, they might be able to avoid the toxins accumulated in the frog skins.

Spiders ambush and hunt their victims on the leaf litter and vegetation (Foelix 2011), where they probably co–occur with many frogs and toads. This increases the likelihood of potential encounters, affecting the dynamics of the interaction. Understanding changes in spatial overlap between interacting species, such as predators and their prey, may give a deeper insight into how the distribution of species influences the food web underlying forces. For example, this system is composed of large predatory invertebrate communities, and abundant small vertebrate communities, such as frogs. To better understand I delved into this interaction by conducting a literature analysis,

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field sampling, and field experiments to specifically address: (1) whether those ecological interactions are disproportionally found in some anuran and spider taxa, (2) what the degree of co-occurrence between frogs and the spiders most frequently reported to prey on them is, and (3) whether those spiders discriminate toxic against non-toxic frog prey.

Methods

Data Collection and Search Criteria

To solve the first question, I searched for information on a wide range of and anuran species including tropical, subtropical, and temperate regions around the world. I reviewed the published scientific literature and searched the internet for unpublished, albeit reliable reports. The search was based mainly on Science Direct, Scopus, JSTOR, ProQuest, Springer, EBSCO, Wiley databases, Science Citation Index (isiknowledge.com) and a professional network Research Gate. I also searched on Google Scholar, Google Books, textbooks on spiders and amphibians, theses and dissertations. The internet search on non-scientific sources essentially consisted of contacting bloggers who had posted photographs, videos, and reports about spiders preying on anurans. I particularly asked whether the event was observed/photographed under natural conditions, dates, and places. Some herpetologists and arachnologists contributed with their photographs and valuable and accurate field information. When the animals involved were unidentified, I confirmed at least the genus identity by contacting arachnologists and herpetologists.

I used the following key words in English, Spanish and Portuguese: “frog/anuran predation,” “spider predation,” “spider preying on frogs/anurans,” “spider eating frogs/anurans,” “frog/anuran predation risk,” “spider predatory behaviour,” “spider preying on vertebrates,” “spider caught

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frogs,” “vertebrate predation by .” Every search was carried out in the all, images and videos tabs. During the last six months I have also done haphazard searches on Google Scholar using the keywords listed above. Data with no response by web page author, were not included in the analysis because they do not provide accurate identification on predation events. I also included unpublished data on frog predation by spiders (this study, see Figure 1 in general introduction and cover photo in this chapter). The sources of variations evaluated were predator taxa, prey taxa (Family and when possible, Genus and Species), place of the event and predator sex. The predator hunting mode was classified as sit and wait, active hunters and weavers. The information categories included natural and artificial (models of frogs made of plasticine or clay) risk of predation. Other sources of variation (native or invasive predators, experimental vs. observational studies) were also included.

To describe the frequency of predation events on frogs by spiders with regard to their phylogenetic status, I created heat maps, which enabled the comparison of multiple spider and anuran families simultaneously. For this purpose, I used recently published phylogenies of anurans (Pyron and Wiens 2011, Zhang et al. 2013) and spiders (Garrison et al. 2016), and assembled the corresponding phylogenetic trees using the Mesquite software (Maddison and Maddison 2011). The frequency of predation events was then simultaneously mapped onto both spider and anuran taxa. To formally test whether predation events are disproportionally found in some of this taxa, I first built a null model by randomizing predator–prey interactions with the R package Bipartite 2.13 (Dormann et al. 2008); then, I quantified network structural properties and compared the results with the null model using the null.t.test-function (Peres–Neto et al.2001). The quantitative network describes the intensity of frog–spider association, and is used to calculate the following structural parameters: two-mode clustering coefficient as proposed by Opsahl (2010), which indicates the total value of closed 2-paths over the total value of

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all 2-paths, the generality (G), which indicates the effective mean number of the number of prey species by predator; the vulnerability (V), which is the effective number of predator species per prey; and the selectivity of the network (H2), as a measure of dietary specialization.

Sampling the Spatial Overlap Between Spiders and Putative Prey

To estimate the degree of frog and spider co-occurrence, I conducted field surveys in June 2013, July 2014, and December–January 2015 and 2016. One observer (MPT) walked at night searching for anurans and spiders along three trails in a terra-firme forest at the Tanimboca Private Reserve, 11 km north of the city of Leticia, in the Colombian Amazon. The search was conducted between 20:00 and 01:00 h. and was focused on common frog species, and ctenid and theraphosid spiders, because the analysis of the literature/internet reports had already shown that these spiders were among the most frequently reported predators of anurans. I thus recorded for each encountered spider or frog, the species identity, the size (carapace length for spiders, and snout-to-vent length [SVL] for anurans), and the height above ground of the substrate or perch, and the distance to the nearest pool or stream. Lastly, to estimate the degree of microhabitat co-occurrence between anurans and spiders, I plotted all encountered individuals onto the two- dimensional space created by the variables distance to the nearest (pond, stream) water body and perch height. The distribution of each spider/frog genus was then estimated as the probability of occurrence within the fixed kernel Utilization Distribution UD, (Worton 1989). Fixed (non-parametric) Kernel ranges of 50% (core area) and 95% (representative range) probability of occurrence were calculated using smoothing parameters estimated via the least squares cross-validation procedure (Seaman et al. 1999). The pairwise degree of overlap between spiders and frogs was then estimated as the degree of overlap between the corresponding Kernel distribution ranges.

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Predation Experiments

To test whether spiders discriminate against poisonous frogs, I carried out predation experiments. Based on reviewed observations of natural predation events, I used adult spiders between 10–33 mm of carapace length (CL), and frogs between 21–52 mm of snout-vent length (SVL). Also, I chose as potential predators three spider species in the genera Ancylomentes, Phoneutria (both in the family Ctenidae), and Avicularia (family Theraphosidae) which were among the most frequently reported predators of anurans and were also abundant at the study site. As potential prey, I included the most commonly encountered frogs belonging to nine species of the genera Phyllomedusa, Osteocephalus, Boana, Scinax, Dendropsophus, Pristimantis, Rhinella, Oreobates and Ameerega (as it was shown in the general introduction). Among them, Ameerega was the only genus considered to be poisonous (Daly et al. 2005, Prates et al. 2011) and belonging to the family of poisonous frogs (Dendrobatidae).

Spiders were captured and allowed to settle for 72 hours within individual 60×40×60 cm opaque semi-outdoor cages, enriched with leaf litter, sticks (3- cm), and 1-cm depth soil layer. Food withdrawal is a common procedure meant to homogenize hunger levels among individuals (Persons et al. 2001); I standardized a 24 h period of starving prior to any experiment to induce maximal behavioural response. Food deprivation during less than 10 days appears to cause no detectable detrimental effect on spiders (Barnes et al. 2002). Anurans were kept (maximum for three days) in separate cages with leaf litter material and ad libitum food (Drosophila flies) and water. Each trial started when I presented one prey item to each spider; the frog was released beneath the litter on the opposite side to the spider position. 2013 experiments were conducted under semi–laboratory conditions (25.9± 4.1 °C, 12:12 light- dark cycle, ambient relative humidity 90.3%). The trials were initiated in

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darkness at night time (around 19:00) and the cages were checked the next morning (around 07:00). Any eaten/non eaten frog was recorded and the spider released after being marked to avoid posterior recaptures. After terminating an experiment, any prey that remained alive was removed and the containers were thoroughly rinsed.

To minimize interdependence, the order of the individuals tested was randomized for each predator treatment, and no more than one individual was tested during the same run. Each spider and frog was used only once during the experiment. A second, 12-day period of experiments was conducted in July 2014 to examine the repeatability of the results. Semi–laboratory conditions for these trials were 25± 2.81 °C, 12:12 light-dark cycle, ambient relative humidity 93%). Seventy-six spiders (31 Ancylometes rufus, 27 Phoneutria fera, and 18 Avicularia juruensis) were evaluated. To test the effect of both predators and prey on the occurrence of a predation event (yes or no), I used a Generalized Linear Mixed Model (GLMM) with a binomial link function, where the identity of the spider was used as a random effect. The GLMM analysis was performed through the lme4 package (Bates et al. 2015) in R software (R Core Team c2015).

Results

Geographic distribution and spider pervasiveness in anuran predation

I found of 398 reliable reports of anurans preyed on by spiders. Nearly 70% of them were from tropical regions, and 90% of these were from the neotropics (Figure 1). Less reports were originated in North America (6%), Australia (4%) and eastern and south eastern Asia (1%), and no reports were found from Europe or the Antarctic region. Within the neotropics, most events of anuran predation occurred in lowland tropical forests floors from , Colombia,

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Peru, , Costa Rica and Panama. Regarding habitat, most events were seen near shallow puddles and creeks, in low vegetation, in the leaf litter, and on tree trunks.

Anurans belonging to 97 species and 16 families were reported to be trapped and eaten by spiders. The most frequently attacked frogs (n=171;) were 47 species of tree frogs (family Hylidae). At the level of a single species, I found 12 reports involving the tree frog Dendropsophus minutus (Hylidae) and 10 of the Puerto Rican tree frog Eleutherodactylus coqui (Eleutherodactylidae). Regarding the spiders, 72 spider species belonging to 14 families were reported as preying upon anurans. Most reports (n=195) involved 20 species of wandering spiders (Ctenidae), followed by Pisauridae (n=93 reports of 12 species) and Theraphosidae (n=53 reports of 13 species). Most of them were hunting spiders, particularly in the genera Ancylometes, Phoneutria, and Ctenus (Ctenidae), and Dolomedes (Pisauridae); in contrast, less than 5% of the records involved funnel-web spiders (Dipluridae) and the particularly large orb wavers in the family Araneidae and Nephilinidae. At the level of a single species, I found 20 reports involving the fishing spider Ancylometes rufus, a large semi-aquatic spider with a nocturnal life-style, which is found near ponds or small streams on banks of larger rivers in the tropical forests of Brazil, Colombia, and Ecuador (Höfer et al. 2014).

The predation events were overrepresented in a few spiders×anuran combinations. Anuran-catching spiders belong to the suborders araneomorph and mygalomorph. Most records that included a description of the spiders implicated in anuran predation cited hunting spiders (~95%), with only very few records involving weavers: funnel-web spiders (Dipluridae) and particularly large orb weavers araneids and nephilinids. Wandering spiders (Ctenidae) represented the most diverse family with 34 species, followed by Theraphoside and Pisauridae (18 and 12 species respectively, Fig. 1). Roughly

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half of all reported cases (n=189) that identified the spiders hunting and eating anurans were in the genus Dolomedes (Pisauridae), Ancylometes, Phoneutria and Ctenus (Ctenidae). Although ctenid and pisaurid spiders were the most frequent predators of most anurans (Figure 2), ctenid spiders hunted mainly hylid, eleutherodactylid, leptodactylid, centrolenid, and dendrobatid frogs. In contrast, pisaurid spiders attacked mainly myobatrachid, pipid, and ranid frogs. Otherwise, hylids, centrolenids, leptodactylids eleutherodactylids, craugastorids, and hylodids were the most important prey for all predators, except for two spiders (Ctenizidae and Idiopidae) that captured chiefly myobatrachids. So far, the strongest predator-prey associations occurred between ctenids–hylids and pisaurids–hylids. The majority of hylids captured by spiders represented species that are among the most common frogs in their respective geographic region. There is clear evidence that Ctenidae is an important predator for most groups of frogs (for example, Hylidae and Leptodactylidae), but also the apparent avoidance by Pipidae and Myobatrachidae (Figure 3). The family that more frequently came up as a predator (Ctenidae), showed a general behaviour in relationship with the prey used, while other families of spiders had more specific preferences.

The structure of the network obtained differed significantly from random networks (Jordano et al. 2009) and showed patterns of high connectivity, where Ctenidae and Pisauridae presented a greater number of associated prey, whereas the rest of spider families presented a lower number of predated frogs

(Figure 3). On the other hand, the value of the specialization (H2) is low, indicating greater global specialization of the represented interactions; that is, most of the predation concentrated on a few predators. Within the generated network, there are frogs such as Cycloramphidae, Pipidae and Dicroglossidae, which were only chosen by one predator. The global clustering coefficient of the distributions of prey species across predator species was low (0.12), with a few nodes of the high level connected with many of the lower level, suggesting

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a hierarchical structure (Junker and Schreiber 2008). The generality values indicate that spiders in dataset are consuming a large number of prey, whereas the vulnerability scores suggest that frogs are been predated by few spiders (Table 1). These rates represent the average of effective associations between spiders and frogs, respectively (Blüthgen et al. 2008).

Co-occurrence and behavioural interactions between spiders and frogs: How Important are Anuran Predation?

With regard to the spider and frog co–occurrence in the field, I report 257 encounters: 107 of anurans and 149 of spiders. The encounters occurred within 0–50 m (8.5 ± 0.6 m, mean ± sd) to the nearest water body, and within 0 to 1057 cm (46.3 ± 23.3 m) of perch height. At low elevation and close to the water, the modeled distribution of the Ancylometes spiders overlapped with the frog genera Rhinella, Oreobates, Dendropsophus and Ameerega. At intermediate elevation, the Phoneutria spiders overlapped with most frog genera, with the only exception of Phyllomedusa. At elevations above 2 m, the distribution of Avicularia spiders did not overlap with any frog although, admittedly, it was probably much harder for the observers to detect frogs at this elevation range.

The kernel UD analysis revealed that spiders and frogs did not use the habitat uniformly (Fig. 6). The representative ranges (95% kernel range) of spiders and frogs were similar in size covering a total area of about 0.25 km2 (estimated as the area covered by the three main trails used in the surveys), and showed a continuous representative range extending from 0m to approximately 1.50m in height, and from 0m to around 50m water distance. Within this range there were two core areas (50% kernel range) for spiders and only one for frogs. 95% representative ranges of spiders and frogs showed considerable spatial overlap. The range shared between both predator and prey was of 65% overlap. Almost

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all of the two core areas of spiders (82%) and all of the frogs’ core area were contained within this shared area.

To what extent do spiders feed on anurans?

In the predation experiment, the selected spider species readily attacked and ate anurans, almost entirely; only a pile of bones was left. Ancylometes spiders consumed the largest number of frogs, followed by Phoneutria, which consumed slightly fewer frogs (GLMM, Estimate =-0.7, P= 0.0405), and Avicularia, which consumed significantly less frogs (Estimate =-1.86, P= 0.0002). Regarding the prey, the toxic frogs were much less often consumed than the non-toxic frogs (Estimate =-1.26, P= 0.0001). Also, vegetation frogs (Dendropsophus, Scinax, Pristimantis, Osteocephalus, Boana, and Phyllomedusa) were more often consumed than ground living toads and frogs (Rhinella and Oreobates) (Estimate =2.01, P= 0.0074) (Figure 7).

Discussion

The frequency of reported attacks was differentially distributed across families of both predators and prey: a network analysis of specialization evidenced significant departure from the null hypothesis of random webs. The major spider groups involved in anuran predation events (Ctenidae, Pisauridae and Theraphosidae) possess large strong chelicerae capable of piercing the skin of vertebrates (Marshall 2001, Uzenbaev and Lyabzina 2009) and are equipped with powerful venoms containing hundreds of different neurotoxins, some of which are specific to vertebrate nervous systems (McCormick et al. 1993, Jiang et al. 2013). Also, wandering spiders are often bigger than most spiders and comparatively abundant, which could be related to intraguild pressure and the use of vertebrate prey (Lapinski and Tschapka 2013).

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Specialization (H2) values found for the Bipartite analysis showed heterogeneous levels of association between spiders and frogs. There are frog species preyed on by a few species of spiders, indicating a global concentration of the associations represented in the network (Jordano et al. 2009). Clustering coefficient values found indicate a high nesting level, and therefore, high redundancy in spider–frog interactions (Peres-Neto et al. 2001, Blüthgen et al. 2008, Morris et al. 2014). This redundancy seems to be related to the predator and prey abundance and overlap, because they are more likely to interact if predators face a wide range of prey species. Similarly, abundant prey is more likely to have higher predation pressures (Nielsen and Bascompte 2007).

Field surveys revealed that spiders co–occur with themselves and with frogs in two general habitats and in a vertical segregation. First, semi-aquatic spider species (e.g. Ancylometes) were more often found in the low understory vegetation and in the immediate vicinity of water bodies; they probably avoid desiccation by spending the day in shelters or on wet substrates near the water bodies (Pulz 1983, Young et al. 2005). In those habitats A. rufus cooccurs with very high-water fidelity frogs, such as Dendropsophus; and litter frogs like Oreobates. Although data on spider predation are limited, I reported 4 natural predation events, with D. sarayacuensis and R. margaritifera. Second, Phoneutria and Avicularia were found at different heights perched on the vegetation.

They frequented leaves and tree trunks where they overlap widely with potential prey such as different tree frogs. I found one natural predation event involving Avicularia and probably Scarthyla (Hylidae). Generalist predators are limited mainly by their tolerance to the environmental conditions of the strata or microhabitats (Lapinski and Tschapka 2014), and these species are likely to face a much more variable microclimate that potentially requires specific ecophysiological adaptations (Wise 1993, DeVito et al 2004, Entling et al 2007).

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The wide ranges of height and distance to water found for the species studied, reflect such potential adaptations within the respective microhabitats.

I found that spiders and frogs have a high degree of overlap in the study site, with shared areas used heavily and similarly by both predator and prey. The predominance of foraging activity throughout the core ranges and representative ranges of both groups suggests that predation rates by invertebrates represent an important feeding area in systems with large predatory invertebrate communities and abundant small vertebrate communities, such as frogs (Nordberg et al 2017).

The behavioural experiments confirmed that, especially ctenid spiders, readily attack and consume frogs. An important source of information for many spiders is the vibration transmitted through water or solid substrates (Rovner and Barth 1981; Barth 1998, Hebets and Papaj 2005, Roland and Rovner 1983, Quirici and Costa 2007). Frogs produce vibrational cues not only while walking or jumping, but also while males utter their advertisement calls during the breeding season (see Chapter 3). Also, spiders may be arguably well suited to feed on toxic frogs. The spiders in my experiment left carcasses of skin and bones after feeding on frogs, and frogs are known to store their noxious chemicals in skin glands (Daly et al. 2002, Nelsen et al. 2014). Although spiders may need to increase the prey handling time while consuming toxic frogs (Toledo et al. 2011), this ability would grant access to a significant biomass of prey that is rarely attacked by other predators. This study shows, nonetheless, that spiders avoid or less frequently consume poisonous frogs, suggesting that they have not completely overcome the deterrent effects of some frog alkaloids and peptides.

Wandering spiders are considered to prey predominantly on arthropods (Nyffeler and Birkhofer 2017), but growing evidence suggests that small

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vertebrates may significantly contribute to their dietary niche (Rubbo et al. 2003, Nordberg et al. 2017, this study). Frogs have been speculated to represent a minor proportion of the diet of semiaquatic ctenid spiders (Menin et al. 2005), but I have witnessed many events of frog predation by semiaquatic ctenids in a single night; it occurred at several Amazonian ponds and invariably during the breeding season of anurans (see figure 1 in General Introduction and the cover of this chapter). Thus, anurans may well constitute a seasonal food source for ctenid spiders, perhaps overlooked by most researchers due to the short duration of massive breeding events in pond- breeding frogs. Feeding on frogs may also be particularly advantageous during the mating period of spiders, when the elevated energy and protein requirements of gravid female spiders require increased food intake (Nyffeler and Pusey 2014). It would be interesting to evaluate whether spiders have developed adaptations to take advantage more often of this, probably more nutritious prey (Schmidt et. al 2012).

The evidence obtained in this study is compatible with a strong ecological role of some spider clades as anuran predators. For the time being, the ctenid and theraphosid spiders are considered opportunistic predators of small vertebrates (for example, Rubbo 2003, Menin et al. 2005, Nordberg et al. 2018). Our results suggest otherwise, which could profoundly impact the population dynamics of the frogs they consume. For instance, synchronous metamorphosis may have evolved as a mechanism to satiate predatory terrestrial spiders, as has been suggested for hylid frogs (Donnelly and Guyer 1994, Guyer and Donnelly 2005). Synchronous breeding and the selection of calling perches may have at least partially evolved under similar pressures (see Chapter 3). The species composition and demography of frog communities appears to be more influenced by predators (Magnusson and Hero 1991) than by the abundance of resources (Folt and Reider 2013). The ecological effect of spiders as vertebrate predators may be particularly important in the

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neotropical forests (Hayes 1983, Guyer 1988, Folt and Lapinski 2017). The predation events I analysed here were indeed overrepresented in tropical areas, which may well be related to the tropical and subtropical distribution of many ctenid and theraphosid spiders (Nyffeler and Knörnschild 2013).

Finally, the capture and consumption of anurans by spiders represents a significant departure from the average dietary patterns and predator–prey size ratios reported in the literature (Mayntz and Toft 2001, Mayntz et al. 2005, Schmidt et al. 2012). According to the optimal foraging theory, predators should therefore prefer foods that deliver the greatest value per unit of effort or time expended acquiring them (Schoener 1971, Westoby 1978).

Thus, the ability to consume a wide variety of food types can have significant advantages for survival and persistence. Predators in a wide range of taxa, including invertebrates (Mayntz et al. 2005), supplement their mixed diet through selective predation in a restricted range of prey (Kolh et al. 2015, Potter et al. 2018). Even if frogs were just occasional prey items for spiders, they might represent a substantial nutritional value (Jensen et al. 2011). My results provide descriptive, correlative, and experimental evidence suggesting an ecological interaction with potentially strong effects on both spider predator and anuran prey. I need to further understand the physiological, ecological, and evolutionary implications of this relationship.

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Acknowledgments

This research provides an example of the importance of reporting interesting natural history notes and keeping good field records. The data synthesized to examine the reported patterns would not have been possible without the careful records of others, including amateur naturalists who published their field notes, photographs, and videos. I wish to thank all those scientists who shared with me their own reports and helped us to identify frogs and spiders. For their hospitality and help in the field, I also thank to the staff of the Tanimboca, Leonaldo, Sarita, Ramiro, José, Rodolfo, Juan Carlos Tamayo and Goran. I am grateful as well to Diana Pinto, Camilo Rodríguez, Mileidy Betancourt, Mabel González, Pedro Patricio, Diana Mota, and Pablo Palacios, for their invaluable help in the field. This study was financially supported by the Colciencias grant ID#52037, and by the Faculty of Sciences (Proyecto Semilla to M. P. Torres) at the Universidad de los Andes, Bogotá.

Literature cited

Armas, L. F. (2000). Frogs and lizards as prey of some Greater Antillean . Revista. Iberica de Aracnología, 3,87–88. Retrieved from http://sea- entomologia.org/Publicaciones/RevistaIbericaAracnologia/RIA03/RIA03.htm

Barnes, M. C., Persons, M. H. & Rypstra, A. L. (2002). The effect of predator chemical cue age on chemically-mediated antipredator behaviour in the wolf spider Pardosa milvina (Araneae: Lycosidae). Journal of Insect Behavior. 15, 269–281. doi:10.1023/A:1015493118836

Barth, F. G. (1998). The vibrational sense of spiders. In Hoy, R. R., A. N. Popper & R. R. Fay (Eds.) Springer Handbook of Auditory Research. Comparative Hearing: Insects. (pp.228– 278). New York, NY, Springer

Bates, D., Maechler, M. Bolker, B. & Walker, S. (2015). lme4: Linear Mixed-Effects Models Using Eigen and S4. R package version 1.1-8. http://CRAN.R-project.org/package=lme4.

Bauer, A. M. (1990). Gekkonid lizards as prey of invertebrates and predators of vertebrates. Herpetological. Review, 21, 83–87.

Bleckmann, H., & Lotz, T. (1987). The vertebrate-catching behaviour of the fishing spider Dolomedes triton (Araneae, Pisauridae). Animal Behaviour, 35(3), 641-651. doi:10.1016/s0003-3472(87)80100-8

Boistel, R. & Pauwels, O. S. G. (2002). Oscaecilia zweifeli (Zweifel’s caecilian). Predation. Herpetological Review, 33, 120–121.

Blüthgen, N., Fründ, J., Vázquez, D. P., & Menzel, F. (2008). What do interaction network metrics tell us about specialization and biological traits? Ecology, 89(12), 3387-3399. doi:10.1890/07-2121.1

Brodie, E. D. Jr, Ducey, P. K. & Baness, E. A. (1991). Antipredator skin secretions of some tropical salamanders (Bolitoglossa) are toxic to predators. Biotropica, 23, 58–62. doi: 10.2307/2388688

Brooks, D. M. (2012). Birds Caught in Spider Webs: A Synthesis of Patterns. The Wilson Journal of Ornithology, 124(2), 345-353. doi:10.1676/11-148.1

Brunetti, A. E., Lyra, M. L., Melo, W. G., Andrade, L. E., Palacios-Rodríguez, P., Prado, B. M., Lopes, N. P. (2019). Symbiotic skin bacteria as a source for sex-specific scents in frogs. Proceedings of the National Academy of Sciences, 116(6), 2124-2129. doi:10.1073/pnas.1806834116

40

Chase, J. M., Abrams, P. A., Grover, J. P., Diehl, S., Chesson, P., Holt, R. D., & Case, T. J. (2002). The interaction between predation and competition: a review and synthesis. Ecology Letters, 5(2), 302-315. doi:10.1046/j.1461-0248.2002. 00315.x

Cox, J. A., & Nesmith, C. C. (2007). Acadian Flycatcher caught in the web of a golden silk orb- weaver. Florida Field Naturalist, 35, 46–48. Retrieved from https://sora.unm.edu/node/135315

Daly, J. W., Kaneko, T., Wilham, J., Garraffo, H. M., Spande, T. F., Espinosa, A., & Donnelly, M. A. (2002). Bioactive alkaloids of frog skin: Combinatorial bioprospecting reveals that pumiliotoxins have an arthropod source. Proceedings of the National Academy of Sciences, 99(22), 13996-14001. doi:10.1073/pnas.222551599

Daly, J. W., Spande, T. F., & Garraffo, H. M. (2005). Alkaloids from amphibian skin: A tabulation of over eight-hundred compounds. Journal of Natural Products, 68,1556–1575. doi: org/10.1021/np0580560

Das, K. S. A., Sreekala, L. K., & Abdurahiman, O. (2012). Predation on the Kelaart’s Pipistrelle Bat Pipistrellus ceylonicus Keelart (Chiroptera: Vespertilionidae), by the Reddish Parachute Tarantula, rufilata Pockock (Araneae: Theraphosidae) in Chinnar Wildlife Sanctuary, Kerala, India. Tropical Natural History. 12:257–260. Retrieved from https://www.tci-thaijo.org/index.php/tnh/article/view/103044

DeVito, J., Meik, J. M., Gerson, M. M., & Formanowicz, Jr., D. R. (2004). Physiological tolerances of three sympatric riparian wolf spiders (Araneae: Lycosidae) correspond with microhabitat distributions. Canadian Journal of Zoology, 82(7), 1119-1125. doi:10.1139/z04-090

Dormann, C. F., Gruber, B. &, Fründ, J. (2008). Introducing the bipartite package: analysing ecological networks. Rnews, 8, 8–11. Retrieved from

41

https://www.researchgate.net/publication/228861770_Introducing_the_bipartite_Package_ Analysing_Ecological_Networks

Dormann, C. F., Frund, J., Bluthgen, N., & Gruber, B. (2009). Indices, Graphs and Null Models: Analyzing Bipartite Ecological Networks. The Open Ecology Journal, 2(1), 7-24. doi:10.2174/1874213000902010007

Duca, C., & Modesto, W. (2007). Spider web as a natural trap for small birds. Revista Brasileira de Ornitologia, 15, 615–616. Retrieved from https://www.researchgate.net/publication/235977382_Spider_web_as_a_natural_trap_for_s mall_birds

Entling, W., Schmidt, M. H., Bacher, S., Brandl, R., & Nentwig, W. (2007). Niche properties of Central European spiders: shading, moisture and the evolution of the habitat niche. Global Ecology and Biogeography, 16(4), 440-448. doi:10.1111/j.1466-8238.2006. 00305.x

Eubanks, M. D., & Denno, R. F. (2000). Health food versus fast food: the effects of prey quality and mobility on prey selection by a generalist predator and indirect interactions among prey species. Ecological Entomology, 25(2), 140-146. doi:10.1046/j.1365- 2311.2000. 00243.x

Foelix, R. (2011). Biology of Spiders. OUP USA.

Folt, B., & Reider, K. E. (2013). Leaf-litter herpetofaunal richness, abundance, and community assembly in mono-dominant plantations and primary forest of northeastern. Costa Rica Biodiversity and Conservation, 22, 2057–2070. doi: 10.1007/s10531-013-0526-0

Folt, B., & Lapinski, W. (2017). New observations of frog and lizard predation by wandering and orb-weaver spiders in Costa Rica Phyllomedusa: Journal of Herpetology, 16(2), 269. doi:10.11606/issn.2316-9079.v16i2p269-277

42

Garrison, N. L., Rodriguez, J., Agnarsson, I., Coddington, J. A., Griswold, C. E., Hamilton, C. A. Hedin, M. Kocot, K. M., Ledford, J. M., & Bond, J. E. (2016). Spider phylogenomics: Untangling the Spider Tree of Life. Peer J, 4, e1719. doi; 10.7717/peerj.1719

Gasnier, T. R., De Azevedo, C. S., Torres-Sanchez, M. P., & Höfer, H. (2002). Adult size of eight hunting spider species in central Amazonia: temporal variations and sexual dimorphisms. Journal of Arachnology, 30(1), 146. doi:10.1636/0161-8202(2002)030[0146: asoehs]2.0.co;2

Gunnarsson, B. (2007). Bird Predation on Spiders: Ecological Mechanisms and Evolutionary Consequences. Journal of Arachnology, 35(3), 509-529. doi:10.1636/rt07-64.1

Guyer, C. (1988). Food Supplementation in a Tropical Mainland Anole, Norops humilis: Demographic Effects. Ecology, 69(2), 350-361. doi:10.2307/1940433

Guyer, C., Donnelly. M.A. (2005): Amphibians and reptiles of La Selva, Costa Rica, and the Caribbean slope: A comprehensive guide. (2005). Choice Reviews Online, 42(09). doi:10.5860/choice.42-5274

Hayes, M. P. (1983). Predation on the adults and prehatching stages of glass frogs (Centrolenidae). Biotropica, 15, 74–76. doi: 10.2307/2388005

Hebets, E. A., & Papaj, D. R. (2004). Complex signal function: developing a framework of testable hypotheses. Behavioral Ecology and Sociobiology, 57(3), 197-214. doi:10.1007/s00265-004-0865-7

Höfer, H., T. R. J. Gasnier, and A. Brescovit. 2014. Wandering Spiders of the Amazon. A project of Naturkunde Museum für Karlsruhe. Retrieved from https://www.wandering- spiders.net/phoneutria/introduction

43

Hurtado–Guerrero, J. C., Vasconcelos da Fonseca, C. R. Hammond, P. M., & Stork, N. E. (2003). Seasonal variation of canopy arthropods in Central Amazonia. In Basset, Y., V. Novotny, S. E. Miller, & R. L. Kitching (Eds.). Arthropods of Tropical Forests: Spatio- temporal Dynamics and Resource Use in the Canopy (pp. 170–175). New York, NY, Cambridge University Press.

Jensen, K., Mayntz, D., Toft, S., Raubenheimer, D., & Simpson, S. J. (2011). Nutrient regulation in a predator, the wolf spider Pardosa prativaga. Animal Behaviour, 81(5), 993- 999. doi: 10.1016/j.anbehav.2011.01.035

Jeschke, J. M., & Tollrian, R. (2000). Density-dependent effects of prey defences. Oecologia, 123(3), 391-396. doi:10.1007/s004420051026

Jiang, L., Liu, C., Duan, Z., Deng, M., Tang, X., & Liang, S. (2013). Transcriptome analysis of venom glands from a single fishing spider Dolomedes mizhoanus. Toxicon, 73, 23-32. doi: 10.1016/j.toxicon.2013.07.005

Jordano, P., Vázquez, D. & Bascompte, J. (2009). Redes complejas de interacciones mutualistas planta-animal. In Medel, R., M. A. Aizen, & R. Zamora (Eds.). Ecología y evolución de las interacciones planta-animal: conceptos y aplicaciones (pp. 17–41). Santiago, Chile: Editorial Universitaria.

Junker, B., & Schreiber, F. (2008). Analysis of Biological Networks. New York, NY, Wiley & Sons Inc.

Kneitel, J. M., & Chase, J. M. (2004). Trade-offs in community ecology: linking spatial scales and species coexistence. Ecology Letters, 7(1), 69-80. doi:10.1046/j.1461-0248.2003. 00551.x

Kohl, K. D., Coogan, S. C., & Raubenheimer, D. (2015). Do wild carnivores forage for prey or for nutrients? BioEssays, 37(6), 701-709. doi:10.1002/bies.201400171

44

Lapinski, W., & Tschapka, M. (2013). Habitat use in an assemblage of Central American wandering spiders. Journal of Arachnology, 41(2), 151-159. doi:10.1636/p11-88.1

Lapinski, W., & Tschapka, M. (2014). Desiccation resistance reflects patterns of microhabitat choice in a Central American assemblage of wandering spiders. Journal of Experimental Biology, 217(15), 2789-2795. doi:10.1242/jeb.102533

Lenger, D. R. Berkey. J. K., & M. B. Dugas. (2014). Predation on the toxic Oophaga pumilio (Anura: Dendrobatidae) by decorata (: Collubridae). Herpetology Notes, 7, 83-84

Maddison, W. P., & Maddison, D. R. (2011). Mesquite: a modular system for evolutionary analysis. Version 2.75. Retrieved from http://mesquiteproject.org.

Magnusson, W. E., & Hero, J. (1991). Predation and the evolution of complex oviposition behaviour in Amazon rainforest frogs. Oecologia, 86(3), 310-318. doi:10.1007/bf00317595

Marshall, S. D. (2001). Tarantulas and Other Arachnids. Hauppauge. New York. Barron’s Educational Series, Inc.

Maffei, F., Ubaid, F. K., & Jim, J. (2010). Predation of herps by spiders (Araneae) in the Brazilian Cerrado. Herpetological Notes, 3,167–170. Retrieve from https://www.researchgate.net/publication/259890771_Predation_of_herps_by_spiders_Ara neae_in_the_Brazilian_Cerrado

Mayntz, D. (2005). Nutrient-Specific Foraging in Invertebrate Predators. Science, 307(5706), 111-113. doi:10.1126/science.1105493

Mayntz, D., & Toft, S. (2001). Nutrient composition of the prey's diet affects growth and survivorship of a generalist predator. Oecologia, 127(2), 207-213. doi:10.1007/s004420000591

45

McCormick, K. D., Kobayashi, K., Goldin, S. M., Reddy, N., & Meinwald, J. (1993). Characterization and synthesis of a new calcium antagonist from the venom of a fishing spider. Tetrahedron, 49(48), 11155-11168. doi:10.1016/s0040-4020(01)81803-2

McCormick, S., & Polis, G. A. (1982). Invertebrates that preys on vertebrates. Biological Reviview, 57,29–58. doi: https://www.jstor.org/stable/4222153

Menin, M., Rodrigues, D. D., & Azevedo, C. S. (2005). Predation on amphibians by spiders (Arachnida, Araneae) in the Neotropical region. Phyllomedusa: Journal of Herpetology, 4(1), 39. doi:10.11606/issn.2316-9079.v4i1p39-47

Morris, R. J., Gripenberg, S., Lewis, O. T. & Roslin, T. (2014). Antagonistic interaction networks are structured independently of latitude and host guild. Ecology Letters, 17, 340– 349.

Nelsen, D. R., Nisani, Z., Cooper, A. M., Fox, G. A., Gren, E. C., Corbit, A. G., & Hayes, W. K. (2013). Poisons, toxungens, and venoms: redefining and classifying toxic biological secretions and the organisms that employ them. Biological Reviews, 89(2), 450- 465. doi:10.1111/brv.12062

Nelson, X. J., & Jackson, R. R. (n.d.). Flexibility in the foraging strategies of spiders. Spider Behaviour, 31-56. doi:10.1017/cbo9780511974496.003

Nentwig, W. (1987). The prey of spiders, In W. Nentwig (Ed). Ecophysiology of spiders (pp. 249–263). Berlin. Springer.

Nentwig, W. (2012). Ecophysiology of Spiders. Berlin, Germany: Springer Science & Business Media.

Nielsen, A., & Bascompte, J. (2007). Ecological networks, nestedness and sampling effort. Journal of Ecology, 95(5), 1134-1141. doi:10.1111/j.1365-2745.2007. 01271.x

46

Nordberg, E. J., Edwards, L., & Schwarzkopf, L. (2018). Terrestrial invertebrates: An underestimated predator guild for small vertebrate groups. Food Webs, 15, e00080. doi: 10.1016/j.fooweb. 2018.e00080

Nyffeler, M., & Knörnschild, M. (2013). Bat Predation by Spiders. PLoS ONE, 8(3), e58120. doi: 10.1371/journal.pone.0058120 Nyffeler, M., & Pusey, B. J. (2014). Fish Predation by Semi-Aquatic Spiders: A Global Pattern. PLoS ONE, 9(6), e99459. doi: 10.1371/journal.pone.0099459

Nyffeler, M., & Birkhofer, K. (2017). An estimated 400–800 million tons of prey are annually killed by the global spider community. The Science of Nature, 104(3-4). doi:10.1007/s00114-017-1440-1

Opsahl, T. (2013). Triadic closure in two-mode networks: Redefining the global and local clustering coefficients. Social Networks, 35(2), 159-167. doi: 10.1016/j.socnet.2011.07.001

Peres-Neto, P. R., Olden, J. D., & Jackson, D. A. (2001). Environmentally constrained null models: site suitability as occupancy criterion. Oikos, 93(1), 110-120. doi:10.1034/j.1600- 0706.2001. 930112.x

Persons, M., Walker, S., Rypstra, A., & Marshall, S. (2001). Wolf spider predator avoidance tactics and survival in the presence of diet-associated predator cues (Araneae: Lycosidae). Animal Behaviour, 61(1), 43-51. doi:10.1006/anbe.2000.1594

Potter, T. I., Stannard, H. J., Greenville, A. C., & Dickman, C. R. (2018). Understanding selective predation: Are energy and nutrients important? PLOS ONE, 13(8), e0201300. doi: 10.1371/journal.pone.0201300

Prates, I., Antoniazzi, M. M., Sciani, J. M., Pimenta, D. C., Toledo, L. F., Haddad, C. F., & Jared, C. (2011). Skin glands, poison and mimicry in dendrobatid and leptodactylid amphibians. Journal of Morphology, 273(3), 279-290. doi:10.1002/jmor.11021

47

Pulz, R. (1983). Patterns of evaporative water loss in tarantulas (Araneae. Theraphosidae): Transpiration and secretion. In Eberhard, W. G., Y. D. Lubin, and B. C. Robinson (ed.), The Proceedings of the 9th International Congress of Arachnology, Panama (pp. 197-201. Washington, D.C, Smithsonian Institution Press.

Pyron, R. A., & Wiens, J. J. (2011). A large-scale phylogeny of Amphibia with over 2,800 species, and a revised classification of extant frogs, salamanders, and caecilians. Molecular Phylogenetics and Evolution, 61, 543–583.

Quirici, V., & Costa, F. G. (2007). Seismic sexual signal design of two sympatric burrowing tarantula spiders from meadows of uruguay: Eupalaestrus weijenberghi and Acanthoscurria suina (Araneae, Theraphosidae). Journal of Arachnology, 35(1), 38-45. doi:10.1636/st06- 08.1

R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Retrieve from http://www.R-project.org.

Raven, R. J. (1990). Spider predators of reptiles and amphibia. Memoirs of the Queensland Museum, 29,448. Retrieved from https://www.biodiversitylibrary.org/part/74491

Ringler, M., Ursprung, E., Hӧdl, W. (2010): Predation on Allobates femoralis (Boulenger 1884; Anura: Arombatidae) by the colubrid snake scalaris (Wucherer 1861). Herpetology Notes 3: 201-304

Roland, C., and J. S. Rovner. 1983. Chemical and vibratory communication in the aquatic pisaurid spider Dolomedes triton (Araneae: Pisuaridae). J. Arachnol., 11:77–85.

Rogers, H., Hille Ris Lambers, J., Miller, R., & Tewksbury, J. J. (2012). ‘Natural experiment’ Demonstrates Top-Down Control of Spiders by Birds on a Landscape Level. PLoS ONE, 7(9), e43446. doi: 10.1371/journal.pone.0043446

48

Rovner, J. S., & Barth, F. G. (1981). Vibratory Communication Through Living Plants by a Tropical Wandering Spider. Science, 214(4519), 464-466. doi:10.1126/science.214.4519.464

Rubbo, M. J., Towsend Jr., V. R., Smyers, S. D. & Jaeger, R. G. 2003. An experimental assessment of invertebrate/vertebrate predation: the interaction between wolf spider () and terrestrial salamanders (Ambystoma maculatum). Journal of Zoology 261: 1–5. doi:10.1017/S0952836903003923

Schmidt, J. M, Sebastian, P., Wilder, S. M., & Rypstra, A. L. (2012). The Nutritional Content of Prey Affects the Foraging of a Generalist Arthropod Predator. PLoS ONE, 7(11), e49223. doi: 10.1371/journal.pone.0049223

Schmitz, O. J., Hambäck, P. A., & Beckerman, A. P. (2000). Trophic Cascades in Terrestrial Systems: A Review of the Effects of Carnivore Removals on Plants. American Naturalist, 155(2),141–153.

Schoener, T. W. (1971). Theory of feeding strategies. Annual. Review of Ecology and Systematics, 2,369–373.

Seaman, D. E., Millspaugh, J. J., Kernohan, B. J., Brundige, G. C., Raedeke, K. J., & Gitzen, R. A. (1999). Effects of Sample Size on Kernel Home Range Estimates. The Journal of Wildlife Management, 63(2), 739. doi:10.2307/3802664

Sih, A. (1985). Predation, Competition, and Prey Communities: A Review of Field Experiments. Annual Review of Ecology and Systematics, 16(1), 269-311. doi: 10.1146/annurev.ecolsys.16.1.269

Sørensen, L. L. (2003). Stratification of the spider fauna in a Tanzanian forest. In Basset, Y., V. Novotny, S. E. Miller & R. L. Kitching (Eds.). Arthropods of Tropical Forests:

49

Spatiotemporal Dynamics and Resource Use in the Canopy (pp. 92–101). London, Cambridge University Press.

Timm, R. M., & Losilla, M. (2007). Orb-weaving Spider, Argiope savignyi (Araneidae), Predation on the Proboscis Bat Rhynchonycteris naso (Emballonuridae). Caribbean Journal of Science, 43(2), 282-284. doi:10.18475/cjos. v43i2.a1

Toledo, L. F., Ribeiro, R. S., & Haddad, C. F. (2007). Anurans as prey: an exploratory analysis and size relationships between predators and their prey. Journal of Zoology, 271(2), 170- 177. doi:10.1111/j.1469-7998.2006. 00195.x

Toledo, R. C., Jared, C. (1995). Cutaneous granular glands and amphibian venoms. Comparative Biochemical Physiology, 111, 1–29. doi:10.1016/0300-9629(95)98515-I

Toledo, L. F. (2005). Predation of juvenile and adult anuran by invertebrates: Current Knowledge and perspectives. Herpetological Review, 36(4), 395–400. Retrieve from https://www.researchgate.net/publication/289919007_Predation_of_juvenile_and_adult_an urans_by_invertebrates_Current_knowledge_and_perspectives

Toledo, L.F., Rodrigues Da Silva, N., Dos Santos Araújo, O.G. 2011. Albinism in two Amazonian frogs: Elachistocleis carvalhoi (Microhylidae) and Lithobates palmipes (Ranidae). Herpetology Notes 4: 145-146.

Torres–Sánchez, M. P., & Gasnier, T. R. (2010). Patterns of abundance, habitat use and body size structure of Phoneutria reidyi and P. fera (Araneae: Ctenidae) in a Central Amazonian rainforest. Journal of Arachnology, 38(3), 433-440. doi:10.1636/p08-93.1

Uetz, G. W., & Roberts, J. A. (2002). Multisensory Cues and Multimodal Communication in Spiders: Insights from Video/Audio Playback Studies. Brain, Behavior and Evolution, 59(4), 222-230. doi:10.1159/000064909

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Uma, D. B. (2010). Behavioral ecology of wasp-spider interactions: The role of webs, chemicals, and deception. (Unpublished doctoral dissertation). Georgetown University, Washington, D. C.

Uzenbaev, S. D., & Lyabzina, S. N. (2009). An experimental study of the effects of spider venom on animals. Entomological Review, 89(4), 479-486. doi:10.1134/s0013873809040125 von May, R., Biggi, E., Cárdenas, H., Diaz, M. I., Alarcón, C., Herrera, V., Santa–Cruz, R., Tomasinelli, F., Westeen, E. P., Sánchez–Paredes, C. M., Larson, J. G., Title, P.O. Grundler, M. R., Grundler, M. C., Rabosky, D. & Rabosky, A. R. (2019). Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest. Amphibian and Reptile Conservation, 13(1),65–77.

Wells, K. D., & Schwartz, J. J. (n.d.). The Behavioral Ecology of Anuran Communication. Hearing and Sound Communication in Amphibians, 44-86. doi:10.1007/978-0-387-47796-1_3

Wells, K. D., & Schwartz, J. J. (2007). The behavioral ecology of Anuran communication. In Narins, P. M., A. S. Feng, R. R. Fay, & A. N. Popper. (Eds.). Hearing and Sound Communication in Amphibians (pp. 44–86). New York, NY, Springer Verlag.

Westoby, M. (1978). What are the Biological Bases of Varied Diets? The American Naturalist, 112(985), 627-631. doi:10.1086/283303

Wise, D. H. (1993). Spiders in Ecological Webs. doi:10.1017/cbo9780511623431

Worton, B. J. (1989). Kernel Methods for Estimating the Utilization Distribution in Home- Range Studies. Ecology, 70(1), 164-168. doi:10.2307/1938423

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Young, J., Christian, K., Donnellan, S., Tracy, C., & Parry, D. (2005). Comparative Analysis of Cutaneous Evaporative Water Loss in Frogs Demonstrates Correlation with Ecological Habits. Physiological and Biochemical Zoology, 78(5), 847-856. doi:10.1086/432152

Zhang, P., Liang, D., Mao, R., Hillis, D. M., Wake, D. B., & Cannatella, D. C. (2013). Efficient Sequencing of Anuran mtDNAs and a Mitogenomic Exploration of the Phylogeny and Evolution of Frogs. Molecular Biology and Evolution, 30(8), 1899-1915. doi:10.1093/molbev/mst091

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Table 1. Values of network metrics for the predation events association matrices of different spider–frog interactions. Significant values correspond to p <0.05). All metrics were estimated with the Bipartite package (Dorman et al. 2009).

obs null mean lower CI upper CI t P two-mode cluster coefficient 0.12 0.15 0.12 0.17 2.75 2.2e-02 H2 0.23 0.13 0.11 0.14 -16.08 6.1-08 t-m cluster.coefficient.HL 0.51 0.64 0.62 0.66 17.84 2.4-08 t-m cluster.coefficient.LL 0.46 0.51 0.48 0.55 3.49 6.7e-03 generality.HL 4.97 5.71 5.58 5.83 13.09 3.6e-07 vulnerability.LL 3.96 4.34 4.25 4.44 9.33 6.3e-06

Table 2. Summary output of the GLMM models fitted with a binomial distribution on the attacked/non attacked data. Spider and frog species, and toxicity were used as a fixed factor; and individuals were used as random variables. Std. Estimate Error z value Pr(>|z|) (Intercept) 0.68 0.29 2.31 0.02* speciesAvicularia -1.85 0.49 -3.76 0.00*** speciesPhoneutria -0.70 0.34 -2.04 0.04* frogDen/Sci/Pris/Oste/Hyp/Phy 2.35 0.74 3.17 0.00** frogRhinella/Oreobates 2.01 0.75 2.67 0.00** toxicitytoxic -1.25 0.32 -3.87 0.00*** Signif. codes: 0*** 0.001** 0.01* 0.05" 0.1’ 1 Residual deviance: 231.82 on 196 degrees of freedom AIC: 239.82

Figure 1. Geographic distribution of anuran-catching spiders worldwide. The map depicts the locations were spiders were reported to prey on anurans (pink dots). The size of the dots indicates the number of reports originated from the same geographic region.

Figure 2. Heat map depicting the relative frequency of predation reports with spiders as predators and anurans as prey. Each cell of the heat map represents the base-2 logarithm of the ratio of the estimated number of predation events to its prior expectation, for the spider families (x axis) and anuran families (y axis) branches. The included phylogenies denote evolutionary relationships at the family level. a) prey and b) predators.

Figure 3. Vertical Bipartite Network visualization of reported predation events (N = 398) with spiders as predators (left) and anurans as prey (right). This displays the observed interaction strengths, modelled confidence limits and whether interactions are stronger or weaker than expected for one consumer species at a time. The colours represent the events of predation. The bands correspond to the number of links between prey and predators. The width of the band represents the strength or importance of the interaction between the pair of species.

Figure 4. Distribution of anurans and predator spiders’ perches with regard to elevation and distance to the nearest water body. The distribution ranges are conservative, since they were obtained using the representative (95% kernel range) and 50% (core) fixed Kernel density estimates.

Figure 5. Proportion of different anuran prey over the attack/non attack 12h trials. The bars represent the spider response to different prey items. shown as percentage volumes of major prey categories consumed. Data are based on predation trials of spider species (predator)× frog species (prey). I used 71

individuals of spiders: Ancylometes rufus (n=31), Phoneutria fera (n=27), Avicularia juruensis (n=18). Prey species comprise: Ameerega (n=20), Den/Sci/Pris/Oste/Hyp group (n=49), Phyllomedusa (n=10), Rhinella (n=28). I ran a total of 72 trials for Ancylometes, 44 for Avicularia and 84 for Phoneutria.

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Figure 1.

Figure 2a.

Figure 2b.

Figure 3.

Figure 4

Figure 5.

Chapter II Chapter II: Substrate vibration caused by calling frogs and its role as a cue for predatory spiders

Photo by Patricia Torres

Ancylometes rufus male preying on Dendropsophus sarayacuensis. Tanimboca Reserve in Leticia, Amazonas, Colombia.

Abstract

The ability of spiders to identify and locate prey depends on reliable transfer of substrate-borne vibrations between emitter and receiver. Have been known that an increasing number of spiders take advantage of the anurans, being able to benefit from eavesdropping to seismic signals, a probable by-product of anuran calling. However, localization of a potential prey may be a difficult task due to complex transmission properties of substrate. In the present study, I investigated the vibrational information content of the frogs calls and the transmission properties of different substrates, by simultaneously recording audio and substrate vibrations along frog calling perches. I tested that seismic signals contain enough information to discriminate between three proven frog species (Dendropsophus sarayacuensis, Boana lanciformis and Scinax ruber) that were abundant and often co-existed with cursorial spiders in the Amazon Rainforest. The analyses confirmed that frogs calling from natural perches, produce seismic signals with a narrow frequency bandwidth (below 100-600 Hz) and low dominant frequencies (250 Hz). They also revealed that the seismic signals contain enough information to discriminate between the three frog species. Because the content of the information is highly degraded along the propagation media, I played recorded substrate-borne signals through four natural substrates available for spiders and frogs, and tested if, consequently, spiders of the genera Ancylometes, Phoneutria and Avicularia select these microhabitats. Substrates have drastically different filtering properties depending on the distance. Green leaves and leaf litter passed all frequencies and were the most favourable signalling environment. Trunks strongly attenuated all frequencies with considerable variability between species. Soil showed bandpass properties; attenuating low frequencies. Despite this, spiders preferred the experimental microhabitats that best imitated their natural foraging perches. Altogether, the results support a scenario where spiders would exploit seismic cues not only to locate but also to identify the

frog species that calls. Because anurans vary greatly in the toxicity of their skin chemical defences, and spiders in our study cannot completely overcome them, sensory vibration exploitation could allow spiders to assess the profitability of their prey. Further experiments are needed to test whether the frogs really use this information.

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Introduction

Predator–prey interactions promote an often-neglected arms race with regard to the sensory modalities used to detect and assess each other (Cronin 2005, Otovic and Partan 2009, Davies et al. 2012). The fitness consequences of predation, for both predators and prey, suggest that strong selective forces have acted to shape sensory exploitation (Moore and Biewener 2015, Schmitz 2017) as well as the ability to decode the available information from the ecological opponent (Schmitz 2008, 2017, Sheriff and Thaler 2014). Mating signals are intrinsically conspicuous and often multimodal (Taylor et al. 2011,

Higham and Hebets 2013, Preininger et al. 2013), which allegedly increase the probability to attract potential mates (Uetz G. Roberts 2002, Preininger et al. 2013). However, conspicuousness and multimodality imply that more information is available to potential predators as well (Ratcliffe and Nydam 2008, Halfwerk et al. 2014). Thus, communication signals, the collateral cues, and sensory capabilities, are probably under strong and opposite selective forces (Endler 1992, Zuk and Kolluru 1998).

Spiders often co–occur at relatively high densities with anuran breeding assemblages (McCormick and Polis 1982, Wells 2007). Many anurans prey on spiders yet some spiders have been also reported to prey on anurans (Vitt and Caldwell 2014, García–R. et al. 2015, Das et al. 2012, Nyffeler and Knörnschild 2013, Nyffeler and Pusey 2014) and other small vertebrates as the main mating signal (Wells 2007). A predictable by-product of anuran calling behaviour is substrate vibration and thereby substrate-borne cues (Lewis and Narins 1985, Lewis et al. 2001, Narins et al. 2018), that may well be exploited by these predators. Spiders have particularly well-developed mechanoreceptors that react to substrate vibration (Barth and Geethabali 1982, Barth 2002, Uetz and Roberts 2002, Elias et al. 2004, Hebets and Vink 2007, Uma and Weiss 2010), which makes them particularly apt to eavesdrop the seismic cues produced by

frogs. Despite the frequent co–occurrence of spiders and breeding frogs, the sensory ecology of their predator–prey interactions, have been rarely addressed (von May et al. 2019).

As in other predator–prey systems, the sensory abilities of the receiver and the properties of the propagation medium probably influence the ability of predators to detect and recognize their prey (Endler 1992, Elias et al. 2004, Devetak et al. 2007, Hebets et al. 2008). Natural selection might have favoured the sensory abilities in spiders that maximize the detection and decoding of collateral frog vibratory signals. Since frogs utter species-specific advertisement calls, spiders could also benefit from seismic signals by assessing the profitability of prey, e.g. in relation to body size or frog toxicity. To better understand the evolution of those abilities, we should study both the characteristics of the signal emitted by the sender, and the transmission properties of the substrates used by prey.

Substrate use by spiders is often associated with their ability to perceive vibratory signals emitted by potential prey (Barth 1998, Hill 2009, Virant- Doberlet 2019). One would expect that the ability to select habitats is influenced by the structural components of the habitat. Recent works have shown that spiders are able to aggregate information about their environment and adapt their behavioural responses to these conditions (e.g., prey availability -Szymkowiak et al. 2005, predation risk - Blamires et al. 2007, shelter availability - Rypstra et al. 1999, and associated structural components to the prey - Lubin et al. 1993, Romero & Vasconcellos-Neto 2004). Understanding this process may then shed light on the problem of spider extracting information from vibrational signals produced by frogs.

In the present study, I address three hypotheses with regard to the transmission of signal vibrations from calling frogs: (i) frogs emit collateral

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seismic information that is available to potential predatory spiders; (ii) because calling male frogs probably generate stereotypical vibrations in plants where they sit (Lewis and Narins 1985, Caldwell et al.2010), I hypothesized that collateral seismic cues allow for the discrimination between frog species; and (iii) because information is usually degraded through the propagation medium, I measured the degradation of seismic cues through four frequent substrates for spiders and frogs, and tested whether spiders select microhabitats that benefit the transmission of seismic signals.

Methods

Study animals

The frogs used in the present study were adult males of the species Dendropsophus sarayacuensis, Scinax ruber and Boana lanciformis. These frogs form nocturnal mating aggregations mostly on vegetation over Amazonian wet forest ponds. Males have been observed calling from slightly elevated perches (Toft and Duellman 1979, La Riva et al. 1995) and preliminary surveys have shown some spider attacks (A. Amézquita, personal communication June 15, 2013; this study). In order to better understand why these frogs are relatively frequent prey of spiders, I hypothesized that this courtship display generates a vibrational signal strong enough to be perceived by foraging spiders. Frogs were searched via active sampling at night along trails in Tamimboca Forest Reserve. All these sites were visited during the warmer, rainy months from December–January 2014, 2015, 2016, and January–February 2018. Each located frog was observed during 30–50 seconds using a red-light LED flashlight in order to select the most active calling males for vibration measurements.

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I used adults of three species of spiders selected from preliminary trials: Anylometes rufus, Phoneutria fera, and Avicularia juruensis. They are strictly nocturnal and active spiders in the rainforests of the . Phoneutria can be found on vegetation (frequently on palm trees) and on the leaflitter in primary forest areas (Torres–Sánchez and Gasnier 2010, Queiroz and Gasnier 2017). Ancylometes forages on the ground and low vegetation mainly close to aquatic environments, although it can forage far from water bodies (Gasnier et al. 2002, Moura and Acevedo 2011). Avicularia is an arboreal 'tarantula' living on bushes, tree trunks, branches and palm trees in which it ‘nests,’ also inhabiting herbaceous and low growing vegetation (Stradling 1994). Spiders were collected 3 days before the trials and were initially housed in individual opaque plastic semi-outdoor cages (60×40×60 cm) enclosing moistened leaf litter, small plants and trunks as substrate (3-cm), and 1-cm depth soil layer. During this period spiders were not fed.

Transmission properties of natural substrates

To estimate the amount of information available from frog calls, I simultaneously recorded audio and substrate vibrations along the calling perch. I selected frog males that were actively and spontaneously calling, and recorded each of them until they left the plant or remained silent and motionless during 5 min. Recordings were made on different nights in 2014, 2015 and 2016, between 19 h and 21 h 30 min. Predominant weather conditions in each year were for 2014(24± 2.51 °C, RH 89,9%); 2015 (25± 2.2 °C, RH 89.1%); and 2016 (27± 2.81 °C, RH 87.5%). To record frog calls I used a Sennheiser K6-ME67TM unidirectional microphone attached to Tascam DR- 40 digital recorder (sampling frequencies 44100 Hz at 16-bit resolution), placed ~1.0 m in front of the frog. Simultaneously, I measured vibration signals along the substrates that were naturally used by frogs as calling perches. For this purpose, I used an AP19 accelerometer with flat frequency response from

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0.5–18000 Hz and weighting 0.14 g (AP Technologies, Oosterhout, Netherlands) that was fixed to the calling perch with masking tape at 0.5–2.5 m in height, and about 25 cm away from the calling frog. The transducer was connected with an amplifier/filter apparatus designed for the project, that also recorded any signals resulting from the males’ advertisement calls. After recordings I measured substrate temperature with an Oakton Infrapro 1 infrared thermometer, and I captured frogs to measure body weight (Pocket Pro Balance; Acculab; ±0.01 g) and snout–vent length (SVL) (Vernier Calliper; ±0.001 mm).

The acceleration recordings were later digitized using MATLAB software (©The Mathworks, Inc., Natick, MA, USA), which were stored as uncompressed WAV files (8 kHz sampling rate and 16 bits amplitude resolution). Audio files were transferred to Raven Pro 1.5 software (Bioacoustics Research Program 2014) to be processed and analysed in sonograms and spectrograms. All frequency analyses were conducted using acceleration values of vibratory signals as the input parameter. I applied a bandpass filter (lower limit of 5 Hz and upper limit of 1.5 kHz; Blackman stop band) to decrease background noise. Before the vibration measurements, calls selected were individually normalized (peak −1.0 dB, given 0.05 seconds of fade in/out), in order to avoid biases related to variation on call unit intensity.

The files generated were analysed in the time and frequency domains, allowing variables to be extracted from function of the ‘‘choose measurements’’ menu: "Low frequency (Hz)," "High frequency (Hz)," "Q1 frequency (Hz)," "Dominant frequency (Hz)," "Q1 Time (s)," "Q3 frequency (Hz)," "Q3 Time(s)," "Agg Entropy (u)," "Average Entropy (u)," "Average Power (dB)," "Band With 90% (Hz)," "Centre frequency (Hz)," "Centre Time(s)," "Delta frequency (Hz)," "Delta Power (dB)," "Delta Time(s)," "Duration 90% (s)," "Energy (dB)," "F-RMS Amp (u)," " Frequency 5%(Hz)," "Frequency 95% (Hz)," "IQR Band With (Hz)," "IQR

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Duration(s), " “Maximum Amplitude (u)," "Maximum frequency (Hz)," "Maximum Power (dB)," "Maximum Time(s)," "Minimum Amplitude (u)," "Minimum Time (s)," "Peak Amplitude (u)," "Peak frequency (Hz)," "Peak Power (dB)," "Peak Time(s)," "RMS Amplitude (u)," "Time 5% (s)," "Time 95% (s)". In addition, I calculated call duration, note duration and interval between notes from wave forms obtained. All acoustic recordings were obtained at 16 bits and 44.1 kHz, and were directly downloaded to a Lenovo computer X240 (Realtek High Definition Audio sound card). The WAV files generated were filtered (high- pass filter, cut-off: 250 Hz, Blackman stop band) using RAVEN PRO, 1.5 software (Bioacoustics Research Program 2014). I extracted the same temporal and spectral properties used on vibration analyses.

Although advertisement calls and breeding site selection of anurans are affected by environmental and morphological variables (Gerhardt & Huber, 2002), given the substrate temperature did not change significantly during the measurements, I did not correct temporal variables by substrate temperature. Also, I did not consider it as a variable factor that could affect the vibration cues transmission. I assumed the results would have been similar to those without these control variables. When possible, at least three calls were analysed for each individual and the mean for each variable was calculated. Finally, I evaluated 39 advertisement calls from 13 individuals of D. sarayacuensis, 24 calls from 10 individuals of B. lanciformis, and 21 calls from 8 individuals of S. ruber. The acoustic and the seismic signals were compared using a Discriminant Analysis of Principal Components (DAPC) to estimate the amount of lost information and to test whether species–specific frog signals could be discriminated on the sole basis of the seismic cue. The DAPC was conducted using the R (R Core Team, 2015) package adgenet (Jombart, 2008)

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Substrate type and degradation of seismic cues

To compare the degree of degradation of seismic cues among four types of substrate, I played back the vibrations obtained while frogs were calling (see above) and recorded them again at different distances from the playback source. Playback vibratory stimuli were generated with Matlab (The Mathworks, Natick, MA) using recordings from male D. sarayacuensis and male B. lanciformis signals acquired with accelerometry (AP19 APTechnology International B.V.) in natural substrates. Recordings were obtained from 3 individuals of each frog species and transferred to a Lenovo X240 computer equipped with Audio Media hardware and software (Realtek High Definition Audio) to be processed as indicated above. All measurements were conducted under semi–laboratory conditions in January–February 2018 (25.7± 1.6 °C, 12:12 light-dark cycle, ambient relative humidity 90.1%). Each test was conducted between 19:00 and 02:00 h., and was performed in a plastic board box (90×40×40 cm), which was filled with the one of the test substrates (green leaves, leaf litter, trunk/bark pieces, and soil).

The playback frog stimuli were generated using a mechanical wave driver (Model 39-160 Pasco), that was fastened to an adjustable support so that the vibrator was suspended pointing down. The vibrator was oriented in the same way for recording all substrates, and in direct contact with the substrate to approximate the load applied to the mass of a male frog of D. sarayacuensis (1.3 ± 0.1 g, mean ± SD, n= 18). or of B. lanciformis (4.2 ± 1.7 g, mean ± S.D., n= 13). Audacity (Version 2.3.2; 2014) software was used to construct each 15- s recording to looped mimicking the natural calling frog rate, considering the loop as the vibratory stimulus. I used each recording of 15 s repeatedly to simulate the natural calling speed of the frogs. Both the sound volume of the computer and the volume of the amplifier were on maximum during playback of call vibration cues. The resonant frequency of the wave element was 7 mm

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peak-to-peak, vibrations to 200 Hz, and the resonant impedance was 8 ohms Ω.

The vibration signals were transmitted by assembling a metal rod about 2 mm in diameter to the mounting bolt of the oscillator and connected to an amplifier designed for the project. I recorded the propagated vibrations through the mechanical vibrator’s pin positioned directly on the test substrate, following distances of 10, 20, 30, 40, 50 and 70 cm. Pieces of reflective tape (approx. 25 mm2) were placed in sequence on the substrate, to serve as reference points for the accelerometer measurements. The orientation of these positions varied somewhat from assay to assay and was guided by the shape of the substrate type. For each type of substrate, three replicates per distance were obtained, the oscillator was repositioned for each sample, individual vibrations of a frog species were randomly presented, and fresh substrate material was introduced to incorporate some of the natural variability of the substrates. To measure the characteristics of vibration reduction through the substrate, the distance of 10 cm point (0 dB attenuation) was normalized as a reference, and the signal attenuation was measured by calculate transfer functions for each sample, averaging measure at each position using Matlab (The Mathworks, Natick, MA, USA) and present gain curves for vibration velocity relative to input signal). Signal attenuation was calculated as root mean square (RMS) amplitude of the signal (in dB) at different distances (Elias et al. 2010). The attenuation data obtained were analysed through analysis of covariance (ANCOVA) with substrate as the independent variable, RMS intensity as the dependent variable, and distance as a covariate.

Substrate Choice

For the habitat choice trials, a circular arena 1.50 m in diameter was constructed from plastic board, and radially divided into four equal segments.

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Each segment was fortuitously chosen to be filled with one of the four substrates described above. Then, I collected fresh samples of the substrate material on which spiders were found: green leaves, leaf litter, trunk/bark, and soil; and placed them to a depth of ~3.5 cm. To begin each trial, I placed a spider under a glass vial in a neutral (i.e. no substrate) zone at the centre of the arena, and left it to acclimatize during 20 min. Then, the vial was slowly lifted, and the spider was allowed to wander freely around the arena during 2 h. For each trial, spiders were chosen at random. The experiments were videotaped from above under very dim light (Sony Night–shot camcorder DCR- TRV25, Sony Electronics Inc San Diego, CA 92127 U.S.A); and the videos were later used to note the first substrate visited by the individual, and the relative residence time per substrate during 2 h. All individuals were used only once, and the material substrates were replaced for each trial. All experiments were conducted under semi–laboratory conditions in 2014 (25± 2.81 °C, RH 93%), 2016 (27± 2.81 °C, RH 87.5%) and 2018 (25.6± 4.6 °C, RH 92.5%). Tests were conducted between 20:00 and 03:00 h.

I used Compositional Data Analysis CoDA (Aitchison 1986) to test the null hypotheses of no habitat selection among the four substrate types, and no behavioral differences between the spider species. The individual was used as the sampling unit. Only in one experiment did it occur that a particular substrate was not used at all by the experimental spiders. To include that case in the composition analysis, I rounded that zero with a very low positive value (0.0001), lower than the smallest recorded nonzero proportion (Aebischer et al. 1993). Then, I converted the original compositional data into an 훼– transformation (Alenazi 2019), and processed it through the “Compositions” package (Van de Boogaart and Tolosana–Delgado 2008) in R statistical environment, version 3.10.1 (R Development Core Team, 2018).

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Results

Signal Characteristics of the Frogs’ Calling Song

Male frogs produced substrate vibration during calling on every perch surface where they were found. Acceleration values of the signals, recorded at a distance ~25 cm from the accelerometer, varied from -0.4 to 0.6 ms–2 in D. sarayacuensis, from -0.2 to 0.4 ms–2 in B. lanciformis, and from -0.1 to 0.2 in S. ruber. The three species showed vibrational patterns similar to the acoustic signals, characterized by periodic bursts of vibration energy, and separated by quieter periods, although not as clearly defined as the airborne samples (Figures 1, 2, and 3). In the three species, frog vibrations were typically striking and brief (average 34.9± 1.3 sec for B. lanciformis, 17.2±0,7 sec for D. sarayacuensis, and 1.6±2.5 sec for S. ruber), including a complex temporal patterning with repeated calls and frequent but short notes. Substrate vibrations produced by male frogs had intermediate bandwidths and very low frequencies (~0.05 – ~0.9 kHz). Vibrations from D. sarayacuensis males were narrower. In contrast, those of B. lanciformis and S. ruber were particularly intense with relative broad-band spectral properties.

Regarding minimum and maximum frequencies, D. sarayacuensis averaged 103.9 ± 32.8 Hz (ranging from 84 to 142.5 Hz; n = 22 calls) and 471.9 ± 28 Hz (ranging from 148.4 to 953.1 Hz; n = 22 calls), respectively. B. lanciformis averaged 387.2 ± 102.1 Hz (ranging from 281.1 to 851.6 Hz; n = 18 calls) and 556.7 ± 113 Hz (ranging from 312.1 to 1007 Hz; n = 22 calls). Finally, S. ruber averaged 306.4 ± 52 Hz (ranging from 172 to 485.1 Hz; n = 17 calls) and 712.6 ± 99 Hz (ranging from 601 to 908.9 Hz; n = 17 calls), respectively. Power spectrum for S. ruber and D. sarayacuensis showed a group of peaks of slight amplitude and narrow band (100, 250, 500 Hz and 100, 350 Hz respectively). Meanwhile in B. lanciformis had one peak at 800 Hz.

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DAPC analyses revealed substantial variation among species in main parameters measured (Table 1). In the vibrational DAPC, 67.9% of the variance is explained by ten first PCs of PCA, and two discriminant eigenvalues were retained. The three main components that summarized the variation in the traits measured had a significant effect; PC1 (peak frequency; F34.2 = 3.48, P <

0.0001), PC2 (RMS amplitude; F42.21 = 3.09, P = 0.0005), and PC3 (the duration of call; F32,4= 128.27, p < 0.0001). The vibration signal was different enough to recognize each species of frog, with a slight overlap.). The first discriminant function (DF1) accounted for 73.81% and the second discriminant function (DF2) for 7.59% of the variance conserved. In Figure 4a, Linear Discriminant 1 (LD 1) formed two groups, separating between Dendropsophus, Boana, and Scinax. Linear Discriminant 2 (LD 2) separated among species: above Dendropsophus, below Boana, and Scinax was roughly at the same level with respect to LD 2.

As shown in Figure 4b, airborne component of the calling song DAPC showed 10 axes that represented that more than 78% of the total variance was retained, and two discriminant eigenvalues were preserved. The first discriminant function suggests not separate information values among species. However, despite overlapping of acoustic traits, the species ellipses did not cross the centres.

Frog vibratory signal efficacy on different substrates

Transmission of seismic signals in D. sarayacuencis and, B. lanciformis showed best efficiency on green leaves and leaf litter as compared to soil and bark/trucks, in which they were scarcely detected. Post hoc analysis indicated no difference in attenuation between green leaves and leaf litter, but significant differences were found between leaves with soil and trunks; and leaf litter with trunks, but not for soil in both species (P< 0.05; Table 2). For each factor, a

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significant interaction effect was found (substrate, distance; substrate × distance interaction). In general, attenuation depended on the frequency with overall attenuation increasing at higher frequencies for all substrates. Furthermore, substratum types behaved as low–pass filters, since attenuation was similar for all types at low frequencies (>300·Hz), and the average transfer functions calculated at different distances showed an attenuation increase at higher frequencies (Fig. 6a). For green leaves and leaf litter, the general shape of the gain curves did not change with distance. Although there was a moderate increase in attenuation frequently in leaf litter (Figure. 6b).

Frog vibratory signal efficacy on different substrates

Transmission of seismic signals in D. sarayacuencis and, B. lanciformis showed best efficiency on green leaves and leaf litter as compared with soil and bark/trucks, in which they were scarcely detected. Post hoc analysis indicated no difference in attenuation between green leaves and leaf litter, but significant differences were found between leaves with soil and trunks; and leaf litter with trucks, but not for soil in both species (P< 0.05; Table 2). For each factor a significant interaction effect was found (substrate, distance; substrate × distance interaction). In general, attenuation depended on the frequency with overall attenuation increasing at higher frequencies for all substrates. Furthermore, substratum types behaved as low–pass filters, since attenuation was similar for all types at low frequencies (>300·Hz), and the average transfer functions calculated at different distances showed an attenuation increase at higher frequencies (Fig. 6a). For green leaves and leaf litter, the general shape of the gain curves did not change with distance. Although there was a moderate increase in attenuation frequently in leaf litter (Figure. 6b).

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Substrate Type and Habitat Choice

Forty-two individuals of P. fera, 36 of A. rufus, and 22 of A. juruensis were used in the substrate choice trials. The distribution of the first substrate visited by spiders was significantly different from random for Ancylometes, 58.34% leaf litter substrate (휒2 = 0.34, P= 0.0025), and Avicularia 67.52% trunk/bark substrate (휒2= 1.73, P= 0.001; Figure 4). Phoneutria apparently does not show first choice for any of the offered substrates. When I pooled all individuals of each species, first choice did not depend on sex (female versus male, 휒2= 2.8, P = 0.36). Likewise, the microhabitat upon which individuals per species were observed most often also did not depend on the sex category (휒2 =5.92, P = 0.69).

Analysis of CoDA showed spiders exploited habitats in a non-random manner in all trials. Avicularia selected predominately bark/trunks substrate, Phoneutria chose mainly green leaves (vegetation), and Ancylometes occupied soil substrates (Figure 5). The 훼–ratio approach to regression analysis supports our hypothesis of strong negative association between Phoneutria and Avicularia with soil, as well as of strong positive association between Avicularia with bark/trunks, and Ancylometes with soil. Next, green leaves (vegetation) is significantly tied to Phoneutria but not to Avicularia, as expected (Table 3). Results of the previous regression also showed a negative but not significant relationship between Phoneutria and leaf litter. These data support the hypothesis that spiders are capable of recognizing different substrates and prefer those that transmit seismic signals more effectively. Finally, when I separated females from males to analyze potential effect of sex, I did not find significant differences in female relative residence time between substrates (F2,25 = 1.65, P= 0.041), even given the known low mobility of females compared to males (Salvestrini and Gasnier 2001).

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Discussion

In this study, I conducted an experimental test of whether spiders and frogs provide a model to understand how seismic signals from the prey (affected by substrate heterogeneity) have an effect on the receivers of these signals. The results of this work show that frogs produce notorious vocalizations that can be accompanied by vibrational signals transmitted by substrates where they unfold (Lewis and Narins 1985, Narins 1990, Narins et al. 2018). In this group of organisms, the propagation of sound in the air has been intensively studied (Kelley 2004, Christensen-Dalsgaard 2008, Köhler et al. 2017, but the components transmitted via the substrate have undergone relatively low studies. Some anurans exploit the forest floor as a relatively silent communication channel in which the vibrations derived from the acoustic signals propagate (Narins 1990, Lewis and Narins 2001). Although there is a selective advantage of producing both an airborne and substrate-borne component of an advertising signal (Narins 1990), the trade-off is to be more "detectable" as potential prey for predators. Spiders often use leaves, stems and leaf litter as substrates, through which they transmit and receive seismic signals (Hill 2009, Elias et al. 2010). Then, if a spider approaches a calling frog, it may perceive this signal, orient and attack.

For a frog to be attacked by a spider, its cue must be sensed and recognized. In other words, it must have characteristics that are potentially interpretable as "something predable." Experiments in artificial wave stimuli using insect- generated waves show spiders recognize signals characterized by their high frequency components (greater than or equal to 50 Hz), their irregularity with respect to amplitude modulation and frequency, and their duration, which in many cases exceeds 10 or even 60 s (Bleckmann and Barth 1984; Bleckmann 1985). Results from the frog vibrational signals propagated through the natural substrates suggest that patterns in both of frequency and amplitude

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components contain the necessary information to be sensed by a foraging spider.

In this study, I observed vegetation, leaf litter, soil and trunks that represent the most common substrates in the natural habitat of these spiders. Because the seismic components of potential prey are critical for survival (Elias et al. 2003, 2004), it follows that the transmission properties of the substrates are crucial. Therefore, the transmission properties entered were consistent with the selection of habitat. At distances where the spider is naturally capable of recognizing prey, the filtering characteristics of each substrate were different. Considering the signal bandwidth of the animal, leaves and litter are the most suitable for transmitting frequency information while signals on the ground and trunks transmit with significant distortion. Therefore, if this information is important, spiders should inhabit these substrates more frequently. Although my results show dependence on the substrate, with the sample size and the available information, I did not find statistical evidence for a substrate choice associated with the filtering properties. The spiders of the three species tended to prefer the substrates where they are habitually found, rather than the substrate that showed the best transmission properties of the vibratory signal of the frogs. This pattern could be consistent with a scenario where spiders choose substrates with both prey and shelter (Barth et al. 1988). Experiments on two Cupiennius species showed a significant preference for bromeliad plants, which included places to hide and where prey was present. Plants in this group not only offer hiding places but are also good conductors of the vibrations that are so important in a spider's life (Barth et al. 2002). My results suggest these spiders do not orient themselves by a single environmental parameter, automatically acquiring a whole set of factors that are associated with that parameter. Conversely, they perceive and take into account several factors at once.

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Spiders as predators deal with the effects that the channel imposes on them (Bleckmman and Lotz 1989, Uetz et al. 2013, Chung and Elias 2014, Elias and Mason 2014). In more natural conditions, it is likely that there are many other environmental factors that influence the choice of microhabitats and movement patterns such as the presence/abundance of prey, predators and conspecifics, humidity levels, light levels, among others (Hebets et al. 2008, Wiley 2009). For example, the substrate may vary considerably through the season as conditions such as humidity and composition of the leaf litter (Hebets and Vink 2007). Given the sympatric occurrence of these spider species, several authors suggest differences in their use of habitat and limiting of resources (Gasnier et al. 2002, Torres–Sánchez and Gasnier 2010, Lapinski and Tschapka 2013). The differential use of substrates found, suggest that substrate–type influences communication and predatory behaviour in these spiders. Furthermore, the high diversity of prey found in these habitats, can make the recognition of cues more complex than in environments with lower diversity (Portela and Gasnier 2012). My experimental design did not control for odour and although it did not appear to pose a problem, future studies should attempt to control this variable. The choice of the right habitat is a process of fundamental significance for all animals, as it is one of the main factors determining their probability of survival. The performance of sensory systems, then, must also be evaluated in this context. In addition, further study is needed to understand the scale at which these predators respond to different habitat features. The question of whether spiders in the field can adopt strategies favouring opportunities for predation on particular substrates is open. Future work will address this possibility.

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Acknowledgments

To my colleagues at the Central University Javier Casas and Mauricio Vergara, who designed and provided the equipment to carry out my experiments. Yeltsin Torres and Gustavo Lozano, students of electronic engineering (Universidad Central) helped with the data that had to be processed in Matlab. Rowan MacGinley helped with the attenuation analysis and suggested other ways to address this data. For your hospitality and help in the field, I also thank the staff of Tanimboca, Leonaldo, Sarita, Ramiro, Jose, Rodolfo, Juan Carlos and Goran. Diana Pinto, Camilo Rodriguez, Mileidy Betancourt, Mabel Gonzalez, Pedro Patricio, Diana Mota and Pablo Palacios, helped and encouraged me in the fieldwork. This study was funded by the Facultad de Ciencias de la Universidad de los Andes (Proyecto Semilla to MP Torres), the Unidad de Diseño, Innovación e Integración de Tecnología (DIC) of the Universidad Central and by Colciencias Grant ID # 52037.

Literature cited

Aebischer, N. J., Robertson, P. A., & Kenward, R. E. (1993). Compositional Analysis of habitat use from animal radio-tracking data. Ecology, 74(5), 1313-1325. doi:10.2307/1940062

Aitchison, J. (1986). The Statistical Analysis of Compositional Data. London, Chapman and Hall.

Alenazi, A. (2019). Regression for compositional data with compositional data as predictor variables with or without zero Values. Journal of Data Science, 17(1),219–238.

Audacity [Computer software]. (2019). Retrieved from http:// https://www.audacityteam.org/

Barbosa, P., & Castellanos, I. (2005). Ecology of predator-prey interactions. Oxford, Oxford University Press.

Barth, F. G., Seyfarth, E. A., Bleckmann, H., and Schiich, W. (1988). Spiders of the genus Cupiennius Simon 1891 (Araneae, Ctenidae). I. Range distribution, dwelling plants, and climatic characteristics of the habitats. Oecologia, 77,187-193

Barth, F. G. (1998). The vibrational sense of spiders. In Hoy, R. R., & Fay, R. R. (2012). Comparative Hearing: Insects. Berlin, Germany: Springer Science & Business Media. 228-278. doi:10.1007/978-1-4612-0585-27

Barth, F. G. (2002). A Spider’s World. Berlin Heidelberg, Springer-Verlag. doi:10.1007/978- 3-662-04899-3

Blamires, S. J., Thompson, M. B., & Hochuli, D. F. (2007). Habitat selection and web plasticity by the orb spider Argiope keyserlingi (Argiopidae): Do they compromise foraging success for predator avoidance? Austral Ecology, 32(5), 551-563. doi:10.1111/j.1442-9993.2007. 01727.x

Bleckmann, H. (1985). Discrimination between prey and non-prey wave signals in the fishing spider Dolomedes triton. In K. Kahnring & N. Eisner (Eds). Acoustic and Vibrational Communication in Insects, pp. 215-222. Berlin, Parey Verlag.

Bleckmann, H., and Rovner, J. S. (1984). Sensory ecology of a semi-aquatic spider Dolomedes triton. Behavioral Ecology and Sociobiology, 4, 297-301.

Bleckmann, H., and Barth, F. G. (1984). Sensory ecology of a semiaquatic spider (Dolomedes triton). II. The release of predatory behaviour by water surface waves. Behavioral Ecology and Sociobiology, 14, 303-312.

83

Bioacoustics Research Program. (2014). Raven Pro: Interactive sound analysis software (Version 1.5). The Cornell Lab of Ornithology, Ithaca, NY.

Caldwell, M. S., McDaniel, J. G., & Warkentin, K. M. (2010). Is it safe? Red-eyed treefrog embryos assessing predation risk use two features of rain vibrations to avoid false alarms. Animal Behaviour, 79(2), 255-260. doi: 10.1016/j.anbehav.2009.11.005

Christensen-Dalsgaard, J. (2008). Amphibian bioacoustics. Handbook of Signal Processing in Acoustics, 1861-1885. doi:10.1007/978-0-387-30441-0_102

Chung-Huey, W., and D. O. Elias. (2014). Vibratory noise in anthropogenic habitats and its effect on prey detection in a web-building spider. Animal Behaviour, 90, 47-56. doi: 10.1016/j.anbehav.2014.01.006.

Cronin, T. W. (2005). The visual ecology of predator–prey interactions. In P. Barbosa & I. Castellanos (Eds.), Ecology of Predator–prey Interactions (pp. 105–138). Oxford, Oxford University Press.

Das, K. S. A., L. K. Sreekala, and O. Abdurahiman. (2012). Predation on the Kelaart’s pipistrelle bat, Pipistrellus ceylonicus Kelaart (Chiroptera: Vespertilionidae), by the reddish parachute tarantula, Poecilotheria rufilata Pocock (Araneae: Theraphosidae), in Chinnar Wildlife Sanctuary, Kerala, India. Tropical Natural History, 12(2), 257-260. Retrieved from https://www.tci-thaijo.org/index.php/tnh/article/view/103044

Davies, N. B., Krebs, J. R., & West, S. A. (2012). An introduction to behavioural ecology. Oxford, Wiley-Blackwell.

Devetak, D., Mencinger-Vračko, B., Devetak, M., Marhl, M., & Špernjak, A. (2007). Sand as a medium for transmission of vibratory signals of prey in antlions Euroleon nostras (Neuroptera: Myrmeleontidae). Physiological Entomology, 32(3), 268-274. doi:10.1111/j.1365-3032.2007. 00580.x

84

Elias, D. O. (2003). Seismic signals in a courting male jumping spider (Araneae: Salticidae). Journal of Experimental Biology, 206(22), 4029-4039. doi:10.1242/jeb.00634

Elias, D. O. (2004). The effect of substrate on the efficacy of seismic courtship signal transmission in the jumping spider Habronattus dossenus (Araneae: Salticidae). Journal of Experimental Biology, 207(23), 4105-4110. doi:10.1242/jeb.01261

Elias, D. O., A. C. Mason, & Hebets, E. A. 2010. A signal-substrate match in the substrate- borne component of a multimodal courtship display. Current Zoology, 56,370–378.

Endler, J. A. (1992). Signals, signal conditions, and the direction of evolution. The American Naturalist, 139, S125-S153. doi:10.1086/285308

García–R. J. C., C. E. Posso–Gómez, H. Cárdenas–Henao. (2015). Diet of direct-developing frogs (Anura: Craugastoridae: Pristimantis) from the Andes of western Colombia. Acta Biológica Colombiana, 20(1),79–87.

Gasnier, T. R., De Azevedo, C. S., Torres-Sanchez, M. P., & Höfer, H. (2002). Adult size of eight hunting spider species in central amazonia: temporal variations and sexual dimorphisms. Journal of Arachnology, 30(1), 146. doi:10.1636/0161- 8202(2002)030[0146: asoehs]2.0.co;2

Gerhardt, H. C., & Huber, F. (2002). Acoustic communication in insects and anurans: Common problems and diverse solutions. Chicago: University of Chicago Press.

Halfwerk, W., Dixon, M. M., Ottens, K. J., Taylor, R. C., Ryan, M. J., Page, R. A., & Jones, P. L. (2014). Risks of multimodal signaling: bat predators attend to dynamic motion in frog sexual displays. Journal of Experimental Biology, 217(17), 3038-3044. doi:10.1242/jeb.107482

85

Hebets, E. A., & Vink, C. J. (2007). Experience leads to preference: experienced females prefer brush-legged males in a population of syntopic wolf spiders. Behavioral Ecology, 18(6), 1010-1020. doi:10.1093/beheco/arm070

Hebets, E. A., Elias, D. O., Mason, A. C., Miller, G. L., & Stratton, G. E. (2008). Substrate- dependent signalling success in the wolf spider, Schizocosa retrorsa. Animal Behaviour, 75(2), 605-615. doi: 10.1016/j.anbehav.2007.06.021

Higham, J. P., & Hebets, E. A. (2013). An introduction to multimodal communication. Behavioral Ecology and Sociobiology, 67(9), 1381-1388. doi:10.1007/s00265-013-1590-x

Hill, P. S. (2009). How do animals use substrate-borne vibrations as an information source? Naturwissenschaften, 96(12), 1355-1371. doi:10.1007/s00114-009-0588-8

Jombart, T., Devillard, S. & Balloux, F. (2010). Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genetics, 11, 94. doi:10.1186/1471-2156-11-94

Jones, M. C., & Aitchison, J. (1987). The Statistical analysis of compositional data. Journal of the Royal Statistical Society. Series A (General), 150(4), 396. doi:10.2307/2982045

Kelley, D. B. (2004). Vocal communication in frogs. Current Opinion in Neurobiology, 14(6), 751-757. doi: 10.1016/j.conb.2004.10.015

Köhler, J., Jansen, M., Rodríguez, A., Kok, P. J., Toledo, L. F., Emmrich, M., Vences, M. (2017). The use of bioacoustics in anuran : theory, terminology, methods and recommendations for best practice. Zootaxa, 4251(1), 1. doi:10.11646/zootaxa.4251.1.1

La Riva, I. D., Marquez, R., & Bosch, J. (1995). Advertisement calls of eight Bolivian hylids (Amphibia, Anura). Journal of Herpetology, 29(1), 113. doi:10.2307/1565094

86

Lapinski, W., & Tschapka, M. (2013). Habitat use in an assemblage of Central American wandering spiders. Journal of Arachnology, 41(2), 151-159. doi:10.1636/p11-88.1

Lewis, E. R., & Narins, P. M. (1985). Do frogs communicate with seismic signals? Science, 227(4683), 187-189. doi:10.1126/science.227.4683.187

Lewis, E. R., Narins, P. M., Cortopassi, K. A., Yamada, W. M., Poinar, E. H., Moore, S. W., & Yu, X. (2001). Do male White-Lipped frogs use seismic signals for Intraspecific communication?1. American Zoologist, 41(5), 1185-1199. doi:10.1668/0003- 1569(2001)041[1185: dmwlfu]2.0.co;2

Lubin, Y., Ellner, S., & Kotzman, M. (1993). Web relocation and habitat selection in desert widow spider. Ecology, 74(7), 1915-1928. doi:10.2307/1940835

McCormick, S., & Polis, G. A. (1982). Invertebrates that preys on vertebrates. Biological Reviview, 57, 29–58. doi: https://www.jstor.org/stable/4222153

MATLAB and Statistics toolbox release. (2018a). The MathWorks, Inc. Natick. Massachusetts. United States.

Moore, A., & Biewener, A. (2015). Outrun or Outmaneuver: Predator–Prey interactions as a model system for integrating biomechanical studies in a broader ecological and evolutionary context. Integrative and Comparative Biology. 55(6), 1188–1197.

Moura, M. R., & Azevedo, L. P. (2011). Observation of predation of the giant fishing spider Ancylometes rufus (Walckenaer, 1837) (Araneae, Ctenidae) on Dendropsophus melanargyreus Cope, 1877 (Anura, Hylidae). Biota Neotropica, 11(4), 349-352. doi:10.1590/s1676-06032011000400028

Narins, P. M. (1990). Seismic communication in Anuran Amphibians. BioScience, 40(4), 268- 274. doi:10.2307/1311263

87

Narins, P. M., Meenderink, S. W., Tumulty, J. P., Cobo-Cuan, A., & Márquez, R. (2018). Plant-borne vibrations modulate calling behaviour in a tropical amphibian. Current Biology, 28(23), R1333-R1334. doi: 10.1016/j.cub.2018.10.056

Nyffeler, M., & Knörnschild, M. (2013). Bat predation by spiders. PLoS ONE, 8(3), e58120. doi: 10.1371/journal.pone.0058120

Nyffeler, M., & Pusey, B. J. (2014). Fish predation by semi-aquatic spiders: A global pattern. PLoS ONE, 9(6), e99459. doi: 10.1371/journal.pone.0099459

Otovic, P., & Partan, S. (2009). Multimodal signaling in animals. Encyclopedia of Neuroscience, 1095-1105. doi:10.1016/b978-008045046-9.01860-x

Preininger, D. M., Boeckle, A., Freudmann, I. Starnberger, M. Sztatecsny, and W. Hödl. 2013. Multimodal signaling in the small Torrent Frog ( saxicola) in a complex acoustic environment. Behavioral Ecology and Sociobiology, 67(9), 1449–1456.

Queiroz, M., & Gasnier, T. (2017). Strong negative effect of diurnal rainfall on nocturnal activity of a wandering spider in Central Amazonia. Revista de Biología Tropical, 65(3), 1152. doi:10.15517/rbt. v65i3.29435

Ratcliffe, J. M., & Nydam, M. L. (2008). Multimodal warning signals for a multiple predator world. Nature, 455(7209), 96-99. doi:10.1038/nature07087

Romero, G. Q., & Vasconcellos-Neto, J. (2004). Spatial distribution patterns of jumping spiders associated with terrestrial bromeliads. Biotropica, 36(4), 596-601. doi:10.1111/j.1744-7429. 2004.tb00353.x

Rubenstein, D. I. (1987). An introduction to behavioural ecology (2nd edn). Trends in Ecology & Evolution, 2(11), 346-347. doi:10.1016/0169-5347(87)90114-5

88

Rypstra, A. L., Carter, P. E., Balfour, R. A. E., & Marshall, S. D. (1999). Architectural features of agricultural habitats and their impact on the spider inhabitants. Journal of Arachnology, 27, 371–377.

Salvestrini, F. M., & Gasnier, T. R. (2001). The Activity of juveniles, females and males of two hunting spiders of the genus boana(Araneae, Ctenidae): Active males or inactive females? Journal of Arachnology, 29(2), 276-278. doi:10.1636/0161-8202(2001)029[0276: scdita]2.0.co;2

Schmitz, O. J. (2008). Effects of predator hunting mode on grassland ecosystem function. Science, 319(5865), 952-954. doi:10.1126/science.1152355

Schmitz, O. (2017). Predator and prey functional traits: understanding the adaptive machinery driving predator–prey interactions. F1000Research, 6, 1767. doi:10.12688/f1000research.11813.1

Shen, S. (n.d.). The statistical analysis of compositional data. doi:10.5353/th_b3123037

Sheriff, M. J., & Thaler, J. S. (2014). Ecophysiological effects of predation risk; an integration across disciplines. Oecologia, 176(3), 607-611. doi:10.1007/s00442-014-3105-5

Stradling, D. J. (1994). Distribution and behavioral ecology of an arboreal `Tarantula' spider in Trinidad. Biotropica, 26(1), 84. doi:10.2307/2389113

Szymkowiak, P., Tryjanowski, P., Winiecki, A., Grobelny, S. E Konwerski, & S. (2005). Habitat differences in the food composition of the wasp–like spider Argiope bruennichi (Scop.) (Aranei: Araneidae) in Poland. Belgian Journal of Zoology, 35, 33–37.

Taylor, R. C., Klein, B. A., Stein, J., & Ryan, M. J. (2011). Multimodal signal variation in space and time: how important is matching a signal with its signaler? Journal of Experimental Biology, 214(5), 815-820. doi:10.1242/jeb.043638

89

Toft, C. A., & Duellman, W. E. (1979). Anurans of the lower Río Llullapichis, Amazonian Perú: a preliminary analysis of community structure. Herpetologica, 35, 71-77.

Torres–Sánchez, M. P., & Gasnier, T. R. (2010). Patterns of abundance, habitat use and body size structure of Phoneutria reidyi and P. fera (Araneae: Ctenidae) in a Central Amazonian rainforest. Journal of Arachnology, 38(3), 433-440. doi:10.1636/p08-93.1

Tsagris, M. T., Preston, S., & Wood, A. T. A. (2011), “A Data-based power transformation for compositional data”, in Proceedings of the 4th Compositional Data Analysis Workshop, Girona, Spain

Uetz, G. W., & Roberts, J. A. (2002). Multisensory cues and multimodal communication in spiders: Insights from video/audio playback studies. Brain, Behavior and Evolution, 59(4), 222-230. doi:10.1159/000064909

Uma, D. B., & Weiss, M. R. (2010). Chemical mediation of prey recognition by spider-hunting wasps. Ethology, 116(1), 85-95. doi:10.1111/j.1439-0310.2009. 01715.x

Van den Boogaart, K. G., & Tolosana-Delgado, R. (2008). “compositions”: A unified R package to analyze compositional data. Computers & Geosciences, 34(4), 320-338. doi: 10.1016/j.cageo.2006.11.017

Vitt, L. J., & Caldwell, J. P. (2013). Herpetology: An Introductory biology of Amphibians and Reptiles. Cambridge, MA: Academic Press. von May, R., Biggi, E., Cárdenas, H., Diaz, M. I., Alarcón, C., Herrera, V. Santa–Cruz, R. Tomasinelli, F., Westeen, E. P., Sánchez–Paredes, C. M., Larson, J. G., Title, P.O., Grundler, M. R., Grundler, M. C., Rabosky, D. & Rabosky. A. R. (2019). Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest. Amphibian and Reptile Conservation, 13(1),65–77.

90

Wells, K. D. (2007). The Ecology and Behavior of Amphibians. Chicago, University of Chicago Press.

Zuk, M., & Kolluru, G. R. (1998). Exploitation of sexual signals by predators and parasitoids. The Quarterly Review of Biology, 73(4), 415-438. doi:10.1086/420412

91

Table 1. Principal component analysis summarizing variation in collateral vibrational information of advertisement calls of three frog species analysed: D. sarayacuencis, B. lanciformis and S. ruber.

Call vibration parameters PC1 PC2 PC3 Peak Freq (Hz) -0.05 0.11 7.43 RMS amplitude -0.00 0.00 -1.8e duration of call -0.37 -0.55 -4.4e IQR BW (Hz) 0.00 -0.05 -1.2e Delta Freq (Hz) 0.00 -0.00 5.2e Delta Power (dB) 0.00 -0.00 -9.81 Eigenvalue 3.60 2.30 1.12 %of variance explained 35.60 32.60 31.84

Table 2. ANCOVA analysis of the influence of variables on substrates attenuation (substrate and frog species are categorical variables).

Estimate Std.Error t value Pr(>|t|) (Intercept) 5.89 282451 26432 5.2e-14*** substrate 0.64 0.89 0.67 0.47** distance 0.68 0.84 1107 0.01 RMS intensity 0.01 0.81 0.13 0.91 substrate×distance -0.94 0.17 -5371 4.1e-05*** substrate×RMS intensity -0.76 0.15 -3642 0.00*** distance×RMS intensity -0.73 0.62 -1792 0.29 substrate×distance×RMS intensity 0.63 0.54 0.78 0.83 Signif. codes: 0‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘1 Multiple R-squared: 0.7276, Adjusted R-squared: 0.6746

Table 3. Summarized results from substrate type regressions with compositional response for spider residence time on each substrate type. Compositional data use the α-transformation to deal with presence of zeros according to Tsagris et al. (2011). Free parameter α = 0 corresponds to the log ratio transformation, and α = 1 corresponds to a linear transformation of the data. Significant regression parameters (at α = 0.01) in bold.

Response log(litter): Estimate Std. Error t value Pr(>|t|) (Intercept) 0.34 0.59 0.58 0.55 Subject0avi -2.30 0.94 -2.45 0.01* Subject0pho -1.39 0.87 -1.5 0.11 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 Residual standard error: 3.734 on 96 degrees of freedom Multiple R-squared: 0.3498, Adjusted R-squared: 0.3363 F-statistic: 25.82 on 2 and 96 DF, p-value: 1.0e-09

Response log(soil): Estimate Std. Error t value Pr(>|t|) (Intercept) 0.42 0.51 0.81 0.41 Subject0avi -3.15 0.81 -3.84 0.00*** Subject0pho -2.77 0.76 -3.62 0.00*** Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 Residual standard error: 3.25 on 96 degrees of freedom Adjusted R-squared: 0.44 Multiple R-squared: 0.46 F-statistic: 41.02 on 2 and 96 DF, p-value: 1.3e-13

Continue Table 3. Summarized results from substrate type regressions with compositional response for spider residence time on each substrate type. Compositional data use the α-transformation to deal with presence of zeros according to Tsagris et al. (2011). Free parameter α = 0 corresponds to the log ratio transformation, and α = 1 corresponds to a linear transformation of the data. Significant regression parameters (at α = 0.01) in bold.

Response log(trunk): Estimate Std. Error t value Pr(>|t|) (Intercept) -3.20 0.44 -7.18 1.4e-0*** Subject0avi 6.52 0.71 9.18 8.3e-5*** Subject0pho 1.32 0.66 2.00 0.04* Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 Residual standard error: 2.818 on 96 degrees of freedom Multiple R-squared: 0.59, Adjusted R-squared: 0.58 F-statistic: 70.31 on 2 and 96 DF, p-value: < 2.2e-16

Response log(veg): Estimate Std. Error t value Pr(>|t|) (Intercept) -0.03 0.63 -0.05 0.95 Subject0avi 0.89 1.00 0.88 0.37 Subject0pho 1.76 0.94 1.87 0.02* Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 Residual standard error: 4.00 on 96 degrees of freedom Multiple R-squared: 0.27, Adjusted R-squared: 0.26 F-statistic: 18.53 on 2 and 96 DF, p-value: < 1.5e-07

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Figure 1. Vibrational and acoustic signals of an advertisement call of Dendropsophus sarayacuensis from Tanimboca Reserve, those available for the spiders. (a) waveform of both signals, (b) spectrogram, and (c) power spectrum showing the relative amount of energy in vibrational signal. Spectrogram configuration with FFT size = 4,096 samples and 75% window overlap.

Figure 2. Waveform of vibrational and acoustic signals (a), spectrogram (b) and power spectrum (c) of an advertisement call composed by a sequence of notes of Boana lanciformis, those available for the spiders in Tanimboca Reserve. Spectrogram configuration with FFT size = 4,096 samples and 75% window overlap. of a vibrational signal. (b) and (c) show just vibrational signals.

Figure 3. Vibrational and acoustic oscillograms of of Sinax. ruber from Tanimboca Reserve (a). Vibrational spectrogram (b) and power spectrum (c) showing the relative amount of energy in vibrational signal. Spectrogram configuration with FFT size = 4,096 samples and 75% window overlap. This information is available for foraging spiders.

Figure 4. Discriminant analysis of principal components DAPC (Adegenet; Jombart et al. 2008), including 39 temporal and spectral components of a) vibration and b) acoustic signals. The plots show the clustering patterns of three frog species: D. sarayacuensis (20 individuals), B. lanciformis (21 individuals) and S. ruber (14 individuals). traits (dots) and species (coloured ellipses) are plotted within the orthogonal space defined by the first two PCA eigenvalues (inserts).

Figure 5. Mosaic plots associating spider species and first choice through habitat types in the habitat selection experiments in Tanimboca Reserve. Rectangles are proportional to observed frequencies and colour reflects the magnitude and significance of residuals from contingency table tests. Habitat types included are vegetation, leaf litter, soil, and wood/trunk of saplings.

Figure 6. Proportions of individual spider relative residence time selection by substrate type. Habitats are arranged from most to least preferred for each species. Colour bars indicate habitat utilization by each individual, and is coloured by the proportion of substrate types used by spiders. Proportions are estimated from absolute numbers of individuals and the time spent by each spider in each habitat, not scaled by total cohort size.

Figure 7. Root mean square (RMS) attenuation of D. sarayacuensis signals across natural substrates. Relative dB was calculated using the shortest measured point to stimulus (10 cm) as a reference (0 dB). Leaf and leaf litter transmit with significantly less attenuation than soil and bark/trunks. a) results for vibration (RMS) according to the distance are shown, b) overall attenuation at different frequencies

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Figure 1a Figure 1b Figure 1c

(Ku))

(KU)

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Amplitude Amplitude

Amplitude

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Time (s) Time (s) Time (s)

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Figure 2a.

Figure 2a

Figure 3

Figure 4.

Number of individuals Figure 5.

Chapter III Chapter III: Frog detection by predatory spiders: The role of chemical and seismic cues

Photo by Patricia Torres

Ancylometes bogotensis female preying on hylid frog D. sarayacuensis in Tanimboca Reserve. January 5, 2016.

Abstract

The ability of predators to identify and locate prey often benefits from eavesdropping the transfer of information between prey sender and receiver. Spiders are widely known for using seismic signals in communication whereas frogs are best known for the use of auditory signals in similar contexts. Spiders have been often observed preying upon frogs around and above the ponds where frogs aggregate for mating. I tested here the hypothesis that spiders detect, recognize, and approach the seismic cues produced during anuran calling. For that purpose, I used two experiments. 1) A Y-maze trial tested whether spiders climbed up a branch transmitting frog vibrations, compared to silent branches and to branches transmitting white-noise vibrations. 2) A two–choice experiment tested whether frogs prefer microhabitats with bimodal (chemical + seismic) cues from live frogs rather than microhabitats with only chemical frog cues. The spiders differentially approached the branches transmitting frog vibrations, and there was no effect of the frog or spider species involved. On the other hand, although spiders did not show any evident microhabitat preference with regard to frog stimuli, they spent more time where bimodal cues were available. Our results strongly support that spiders exploit the acoustic communication system of frogs, by eavesdropping the collateral seismic cues. They also suggest that this predator–prey interaction has been important in evolutionary shaping spider and perhaps frog behaviour.

Introduction

Many spiders identify and locate their prey using the seismic cues generated by them and transmitted throughout a solid substrate (Markl, 1983, Gogala, 1985, Barth, 2002, Čokl and Virant–Doberlet, 2003). Seismic cues are often produced by potential prey during locomotion (Virant-Doberlet et al. 2006, Devetak et al. 2007), as collateral which renders prey detection more heavily dependent on the movement of prey than on the movement of the very predator. Several researches also show that spiders do distinguish between vibrations caused by their environment, potential prey, and mates (reviewed by Hergenröder and Barth 1983a, b; Barth 2002). Field studies prove that spiders receive seismic signals that widely vary in frequency and amplitude (Devetak et al. 2007), but the detection and recognition capacity of spiders is naturally constrained by the sensory properties of their receptors and the transmission properties of the propagation medium. Most evidence suggests, however, that prey capture is more often elicited by broadband seismic cues (Barth 2002).

A number of experimental studies have demonstrated the ability of arthropods to accurately locate a source of seismic cues (reviewed by Virant-Doberlet et al., 2006; Hill, 2009), although the underlying mechanisms remain poorly known (e.g. Cupiennius salei, Hergenröder and Barth 1983a, b). Spiders possess vibration receptors on all of their legs, which makes them particularly suitable for directional detection of vibrations (Virant-Doberlet et al. 2006). Between legs (i.e. receptors) differences in the amplitude and arrival time of seismic cues represent the most evident source of directional information for receivers (Virant-Doberlet et al. 2006), particularly when they remain stationary (Barth and Geethabali 1982, Hergenröder and Barth 1983a, b).

Non web-weaving spiders are found in most terrestrial and many aquatic habitats, and therefore exposed to seismic cues propagated through diverse substrates; plants are however the most common substrate (Barth 1998, Cokll and Virant-Doberlet 2003). Plants are complex structures with regard to vibration transmission (Michelsen et al. 1982, Barth 1998, Magalet al. 2000, Cocroft et al. 2006, Polajnar et al. 2013, 2014), and degradation in both the spectral and time domains (Michelsen et al. 1982, Elias et al. 2004, 2010, Hebets et al. 2008). The loss of information during signal (or cue) transmission might compromise the ability of predators to detect, identify, and locate the potential prey, as has been observed in many other animals (Deventak et al. 2007, Blamires et al. 2011, Virant-Doberlet et al. 2011). Given plants act as frequency filters for the signals traveling through them (Michelsen et al. 1982), we assume that selection will favour predators that integrate multimodal cues (Elvidge and Brown 2012) emitted by their potential prey. Multimodal signals may compensate for environmental constraints on communication, as signals in different modalities vary in efficacy.

By integrating multisensory cues (Partan and Marler 1999, Uetz and Roberts 2002, Hebets and Papaj 2005), spiders could improve their ability to detect, identify, and locate potential prey, thereby enhancing their ecological performance as predators (Duellman and Trueb 1994, Toledo 2005, Wells 2007). While the integration of multimodal information has been studied in the context of courtship and mating by many spiders (Elias et al. 2010, Higham and Hebets 2013, Girard et al. 2015, Uetz et al. 2015, 2016, 2017, Stoffer and Uetz 2017), its role during predatory spider–frog interactions remains poorly known (Punzo and Preshkar 2002, Long et al. 2016).

Spider foraging and predation involves multiple behaviours and multiple signalling modalities: vibration reception, perception of prey odours which may bear a chemical signal (Rypstra et al. 2018, Penfold et al. 2017). Many animals

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release volatile chemicals into the aerial environment, or less volatile chemicals that adhere to substrates. If appropriate sensory systems are coupled, they become odours used for communication with conspecifics (Brunetti et al. 2019). Many of these scents are designed to persist, and thereby provide collateral information that can be perceived by unintended recipients. Spiders, for instance, could eavesdrop chemical signals produced by potential prey (Allan et al 1996). Several studies have illuminated the effect of chemical cues from predators on foraging activity in spiders that do not build webs to capture prey (Punzo 1997; Persons & Rypstra 2001; Persons et al.2002).

Although the literature on spider chemical communication is not nearly as extensive, spiders have well-developed chemical senses, and have long been known to respond to chemical cues and pheromones (Foelix 2011). Spiders use contact receptors or taste hairs found on the tarsi and pedipalps to detect chemical cues (Foelix, 1970, 2011; Trabalon 2013). These receptors are suspected to be tip pore sensilla (Barth 2002, Trabalon 2013). An adult spider can detect both volatile chemicals and substrate-deposited chemical cues through direct contact with the environment (Trabalon, 2013). The ability of spiders to detect kairomones allows spiders to detect prey from a distance, avoid encounters with predators, and select appropriate foraging sites (Nelson & Jackson 2011, Uhl 2013).

In previous chapters, I have shown that frog males produced vibrational information while calling for mates; also, that the seismic information available for foraging spiders suffices to allow discrimination among frog species. Moreover, I found that plant leaves were both the most often selected substrate, and the one that best transmits the seismic cues. Here, I use behavioural experiments to examine the response of spiders to both seismic and chemical cues produced by (or mimicking) frogs. Specifically, my research questions are: a) Are spiders attracted toward seismic cues that mimic calling

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frogs and propagate through vegetation? And b) do spiders integrate or, alternatively, prioritize a sensory modality (seismic or chemical) during detection and approach to frogs’ potential prey? The answer to these questions can shed light on how spiders extract and integrate multimodal information in its poorly known role of anuran predators.

Methods

Study Animals

Adult spiders of Ancylometes rufus, Phoneutria fera, and Avicularia juruensis, were investigated in the vibrational playbacks, and in sensory modality trials. I searched for and collected spiders 3 d before the trials’ beginning, in a nocturnal survey on terra–firme forests at the Tanimboca Private Reserve. Each individual was housed separately in opaque plastic containers (96 L volume approx.) with leaf litter, small plants and trunks as substrate. Every morning they were moistened by sprinkling rainwater. Given the nocturnal habits of these spiders, I conducted all experiments during night time, under dim light and moist conditions. During this period, spiders were not fed. For each experiment set, spiders were randomly assigned to the treatments. I visited all these sites during the warmer, rainy months from December– January 2014, 2016, and January–February 2018.

In the study about the effect of chemical cues on spider predatory behaviour, I used adult males of the species Oreobates quixensis (Craugastoridae). It is a medium-sized brown toad with a granular back with scattered warts (Padial and De la Riva 2008). This toad is a terrestrial species of primary and secondary tropical rainforest and is found in clearings, open areas and banana plantations (Padial et al. 2012). In general, anuran species produce and detect chemical signals which are available to potential predators (Byrne and Keogh

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2007; Woodley 2010; Hamer et al. 2011). In addition, my previous predation experiments showed this toad was consumed by all spider species. Frogs were searched for via active sampling at night along trails in Tamimboca Forest Reserve. All these sites were visited during the warmer, rainy months from December–January 2014, 2016, and January–February 2018. Each located frog was collected and was kept (maximum for three days) in a separate cage with leaf litter material and ad libitum food (Drosophila flies) and water.

Spiders response to vibrations produced by frogs

Because calling males probably generate stereotypical vibrations in plants where they sit (Lewis and Narins 1985, Caldwell et al. 2010), I hypothesized that this display generates a vibrational signal strong enough to be perceived by foraging spiders, given that plants are the most common signalling substrate or invertebrates (Barth 1998, Cökl and Virant-Doberlet 2003, Cocroft and Rodriguez 2005). Spiders in this research have been seen preying on frogs in different Amazonian plant species. In addition, in the previous chapter, I found plant leaves were the most efficient substrate to conduct frog call vibratory signals. Hence, I performed a Y-maze experiment to test whether spiders recognize and react to vibrational cues that mimic vibrations produced during calling by the hylid tree frogs Dendropsophus sarayacuensis, Sinax ruber and Boana lanciformis. In preliminary surveys and colleagues’ observations, it was checked that these frogs were indeed attacked by spiders.

Frog vibration stimuli were obtained by recording with an accelerometer (see Chapter 2) the substrate vibrations produced during calling by each of six males per frog species. The obtained recordings were transferred to a Lenovo computer equipped with Audio Media hardware and software. Using sound- editing software, each 15-s recording was looped mimicking the natural calling rate of the frogs, and the loop used as the vibratory stimulus. The amplitude

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of the frog vibrations could not be increased to match the amplitude of the vibrations produced during calling, because of a loss of compliance between the leaf and the shaker at higher levels. Thus, the amplitude of the playback vibrations was about 3 – 5 dB lower than the naturally produced vibrations. Each of the six individual vibrations of a frog species was randomly presented to five pre-test spiders, to represent the natural variation in the signals used by mating frogs.

The white noise vibration was selected as experimental control, because it represents a novel stimulus that should not elicit an adaptive response from spiders. A positive response to white noise would indicate that there is no specific information content within the frog vibrations, i.e. that spiders react to any temporarily patterned vibration. The white noise was generated using Raven Pro 1.5 software (Bioacoustics Research Program 2014). I created five white noise signals, and paired them with the duration of the vibration of a male frog. All white-noise stimuli were filtered out below 5 Hz (Blackman stop band) and given 0.05 seconds of fade in and fade out. To control for potential covariation in the stimulus amplitude, both the frog and the white noise vibrations were normalized to reach its peak amplitude at -1 dB. They were then saved as WAV files at 8 kHz sampling rate and 16 bits amplitude resolution in MATLAB software (©The Mathworks, Inc., Natick, MA, USA).

I chose three plant species as substrate. This plant type is frequently used by P fera and A. rufus, and occasionally by A. juruensis (pers. obs.). In addition, the predation events that I (and other colleagues) have reported on the study site have also occurred in these species: Anthurium sp. (Araceae), Monotagma laxum (Marantaceae) and Bactris sp. (Arecaceae) with petiole diameters raging 1.8± 0.7 cm for Anthurium, 2.1± 1cm for Monotagma, and 1.2±1.5 cm for Bactris. These plants present slightly different geometries, have large leaves and hiding places, important characteristics related to capacity to transmit

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vibrational cues (Barth 2002, Torres–Sanchez and Gasnier 2010). In preparation for the Y-maze trials, each plant was denuded of all but two petioles and the associated leaflets; an asymmetric Y was thus formed by the two uppermost and fully developed petioles. One branch of the Y consisted of the lower of the two petioles, and the second branch consisted of the main stem and the uppermost petiole. The bottom of the stem was put in a plastic container, and filled with soil from the collection site to prevent withering.

The container was then assembled flush with the center of a circular arena (~120 cm), and was placed on an elastic material to decrease the effect of vibration. To control for directional biases that might result during the experiment, each assay was repeated after rotating the plant 180°. Also, to minimize visual asymmetries between the branches, I placed white disks (17 cm in diameter) around but not touching the petioles on each side of the plant. To better mimic the natural situation, one randomly chosen branch was “silent”, whereas the other transmitted a vibrational signal, either obtained from a frog or synthesized as white noise. Each spider was thus tested twice, once with frog vibration and once with white noise vibration that served as experimental control. In addition, to better mimic the natural variation in substrate that the spiders might find in the field, the plants used in the experiment, fortuitously vary in branch and limb diameters.

To conduct the playback experiments, the output signal of the computer was transferred to a mechanical shaker (Model 39-160 Pasco), connected to an amplifier designed for the project, and then transmitted to the plant branch by resting a metal rod about 2 mm in diameter. Pieces of reflective tape (approx. 25 mm2) were placed on the experimental leaf, to serve as reference point for the accelerometer measurements. The orientation of these positions varied somewhat from assay to assay in relation to species differences. A positive response was declared when a spider arrived to the leaf from where the

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vibrations were played back. A negative response was declared when the spider arrived to the opposite branch. Lastly, individuals were declared non- responsive, and included as such in the analyses, when they remained on the plant but did not reach the end of either branch during a maximum time of 10 min. A different plant of each species with very similar characteristics was used for each replicate.

All measurements were conducted under semi–laboratory conditions during December–January 2014 (24.7± 2.511 °C, RH 89,9%), December–January 2016 (27± 2.81 °C RH 87,5 %), and January–February 2018 (25.6± 4.6 °C, RH 92.5%). Each trial was conducted between 19:00 and 02:00 h. Finally, I tested 35 individuals of P. fera, 34 of A. rufus, and 24 of A. juruensis. To test whether branch selection was predictable from the presence (vs absence) of the stimulus, the frog species, and the spider species, I built a generalized mixed linear model (GLMM) with a binary link function, using the identity of individual frogs and spiders as random effects.

Influence of the interaction of chemical and vibratory cues in prey detection

To test whether spiders integrate or prioritize seismic or chemical cues during detection and approach to frogs, I conducted two-choice experiments on a rectangular arena. The arena (120 × 60 × 40 cm) was built from opaque plastic board (AGRIPAK SRL, 1976), and divided into three compartments (Fig. 1). The central chamber was intended to contain the spider and was separated from the two lateral chambers by vertically sliding doors. In the lateral chambers, two alternative stimuli were randomly assigned: one consisting of vibrational + chemical stimuli from an alive frog, whereas the other consisted of only chemical stimuli. The whole arena floor was enriched with substrate, leaf litter obtained from the habitat where spiders were collected of the spiders. To

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provide directional seismic stimuli, the arena was mounted a piece of non- conductive carpet foam and, in turn, on inflated tires. In this way, the main source of seismic cues should be transmitted through the substrate and originated in one of the lateral chambers.

To provide chemical and seismic stimuli, I used adults of Oreobathes quixensis that were removed from their confinements 24 h before each experiment. Two frogs were randomly chosen and placed within hanging plastic cages, one per each lateral chamber. The thread supporting each cage had no contact with the arena, thus avoiding the transmission of olfactory cues from caged frogs. At the time to initiate the experiment, the spider was introduced to the central chamber, covered with a plastic container, and allowed to acclimatize during 20 min. The trial began by releasing one of the frogs from its suspended cage, and then slightly lifting both doors, which allowed access of the spider to both lateral chambers. The caged frog released only chemical cues, while the free frog released both chemical and seismic cues, the latter due to hopping on the substrate. The initial purpose was for the frogs to vocalize, given the results of the experiments in the previous chapters. In this scenario it was necessary to include air-borne variable. Then, I collected individuals that generated the vibratory stimulus through their movement through the sand in this context.

For each spider, I recorded the first selected chamber, as well as the latency to this first choice. The duration of each test was 120 min. To control possible biases from the emitted odours in each side, the arena might become saturated with the chemical released by the two frogs, thus impeding the spider to recognize the odour gradient. Therefore, I used an experimental arena that lacked a roof, which impeded excessive concentration of chemicals around the spider.

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Both the frogs and the position of each stimulus were randomized for each spider. To remove residual odour cues, the test arena was rinsed with 80% ethanol between trials and fresh substrate was used for each test. To minimize cumulative effects due to the repeated experience, each spider was tested only once. Finally, I tested 37 individuals of P. fera, 43 of A. rufus, and 22 of A. juruensis. I used generalized linear mixed-effect models (GLMM) to test prediction of multimodal signal choice. Laboratory data were analysed as binomial-transformed proportions of choosiness, and the latency to first choice. The full model consisted of one fixed (treatment) and (identity of spider) as random factor.

Results

Characterization of prey vibrations on spider’s response

The behaviour of responsive spiders included orientation, slow approach, and climbing up the plant up to the end of one of the branches. In general, frog vibrational cues evoked much more responses of the spiders than white noise vibrations (Figure 2). Among the spiders that responded, most selected the branch transmitting frog vibrations: 85% in Ancylometes, 70% in Avicularia and 63% in Phoneutria, Figure 3). The preference for frog stimuli was indeed statistically significant (Table 1). I did not find any evidence supporting that the three species of spiders reacted differentially to the vibrations of different frog species: A. rufus (휒2 = 2.626, df = 2, P = 0.757), nor Avicularia juruensis (휒2= 2.47, df = 2, P = 0.781), nor Phoneutria fera (휒2 = 2.26, df = 2, x1 = 0.732). Also, there were no differences in the response rates among the three spider species (table 1; 휒2-test, df. =1, P =).

On the other hand, the latency of spiders’ reactions was much shorter when exposed to frog vibrations compared to control noise (휒2 = 18.03, df = 2, p <

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0.01). However, white noise did not affect spider latency to respond to prey (White noise: 휒2= 5 0.99, p= 5 0.32).

Cue use in prey location: Responses to the chemical and vibrational cues

Regarding the eventual integration of seismic and chemical cues, the analysis revealed differences in the first selected chamber among spiders. In particular Phoneutria and Ancylometes presented significantly opposite behaviour. Phoneutria chose unimodal (chemical) stimuli more frequently, while Ancylometes preferred the chamber with bimodal (chemical + vibratory) stimuli. Avicularia showed no evidence of preference. In relation to residence time, all spiders spent more time in the chamber with bimodal stimuli (Table 3).

Discussion

There is abundant evidence that spiders use multiple modes of communication, including seismic, that are restricted by distance, environment, among other factors (Parten and Marler 1999, Hebets and Papaj 2005, Higham and Hebets 2013). The studies have also demonstrated the ability of spiders to localize the source of vibrations, although there is little information about the underlying mechanisms (for reviews, see Virant- Doberlet et al., 2006; Hill, 2009). My results evidence that spiders not only locate vibrations but also recognize them as originated by potential prey and react accordingly. Lohrey et al. (2009) had already shown that wolf spiders eavesdrop cues from birds as substrate-borne vibrations and they can use them to distinguish between potential threats. One completely ignored aspect of these abilities is whether they are based on learning or instead inherited by the spiders. In any case our data support that frog vibrational signals could be associated with the availability of food by the spiders (Kondoh 2010).

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Another important factor to consider is filtering properties of the various plants. My results indicate no effect of different species that I used. Indeed, a few authors suggested similar patterns (Barth et al. 1988, Cocroft and Rodríguez 2005), although this similarity was not clarified in detail. On the other hand, signals could adapt to transmit through particular plants. Although I did run playback through the plants spiders do not use, a study by Bell (1980) showed that artificial stimuli approximating the vibrational signals of tree crickets (Orthoptera: Gryllidae) transmitted with less attenuation through the stems of plant species used by calling crickets than through the stems of plant species the rickets did not use.

The use of multimodal signalling for communication in some spiders allegedly reflects selection pressures for successful spacing or mating across a wide range of environments (Hebets et al. 2002). Spiders have also been found to use chemical stimuli to detect prey (Persons and Rypstra 2000, Hostettler and Nentwig 2006, Johnson et al. 2011). The spiders I studied here (Ancylometes, Phoneutria and Avicularia) inhabit tremendously complex environments on the spatial scale, which also change over time. Selection pressures might have well favoured individuals that combine several sensory modalities to detect and pursue profitable prey. In the present study I obtained convincing evidence that spiders are able to eavesdrop the collateral vibrations produced during frog calling. The relative importance of chemical versus bimodal (chemical + seismic) cues for the first choice, however, varied among spider species. This result is ambiguous to interpret. I cannot infer that most spiders use olfactory cues for prey detection. We cannot even declare that some genera prioritize chemical cues, while others require bimodal cues, because I did not replicate the experiment in several species of each genus.

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On the other hand, our data show that all spiders significantly chose the chamber that offered bimodal cues (vibration+chemical). This result further supports the importance of seismic cues in attracting predatory spiders (see Chapter 2). It is known that environmental cues originated from prey playing an important role in the selection of foraging sites (Persons & Uetz 1996; Scharf & Ovadia 2006). Although our spiders were ambiguous with regard to their first choice, they spent more time in chambers where seismic cues were available. An explanation to be further tested is that spiders needed some time to evaluate the three chambers and then spend more time at the patch (chamber) where food appeared to be more abundant; the evaluation of patch quality (i.e., food availability) is particularly important for the not so mobile predators before selecting foraging sites (Uetz 1992). This is especially relevant in a complex environment in which the distribution of prey varies unpredictably in time and space (Persons & Uetz 1996).

Finally, the variation inherent to vibrational cues is often large and, therefore, I need further experiments to disentangle how spiders decode the relevant prey information from the seismic background. As many other researchers have expressed, spiders provide an ideal model to study the sensory ecology of vibration, both as a communication signal and as a prey cue. I believe that the study of multimodal signalling will reveal different scenarios under which signals have evolved, and will help us understand the evolution of the form and function of these signals and complex responses

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Acknowledgments

For designed and facilitated equipment to carry out my experiments to Javier Casas and Mauricio Vergara from Universidad Central. For assistance with the data processed in Matlab to Yeltsin Torres and Gustavo Lozano, students of electronic engineering (UC). I would like to thank you to the Tanimboca staff, Leonaldo, Sarita, Ramiro, José, Rodolfo, Juan Carlos and Goran. I am grateful as well to Diana Pinto, Camilo Rodríguez, Mileidy Betancourt, Diana Mota, and Pablo Palacios, for their invaluable help in the field. This study was financially supported by the Faculty of Sciences (Proyecto Semilla to M. P. Torres) at the Universidad de los Andes. The Unidad de Diseño, Innovación e Integración de Tecnología (DIC) at the Universidad Central, and by the Colciencias grant ID#52037.

Literature cited

Amo, L., López, P., & Martín, J. (2004). Chemosensory Recognition of Its Lizard Prey by the Ambush Smooth Snake, Coronella austriaca. Journal of Herpetology, 38(3), 451-454. doi:10.1670/177-03n

Barth, F. G. (2002). A Spider’s World. doi:10.1007/978-3-662-04899-3

Byrne, P., & Keogh, J. (2007). Terrestrial toadlets use chemosignals to recognize conspecifics, locate mates and strategically adjust calling behaviour. Animal Behavior, 74,1155–1162. doi: org/10.1016/j.anbehav.2006.10.033

Blamires, S. J., Chao, Y., Liao, C., & Tso, I. (2011). Multiple prey cues induce foraging flexibility in a trap-building predator. Animal Behaviour, 81(5), 955-961. doi:10.1016/j.anbehav.2011.01.022

Brunetti, A. E., Lyra, M. L., Melo, W. G., Andrade, L. E., Palacios-Rodríguez, P., Prado, B. M., Lopes, N. P. (2019). Symbiotic skin bacteria as a source for sex-specific scents in frogs. Proceedings of the National Academy of Sciences, 116(6), 2124-2129. doi:10.1073/pnas.1806834116

Caldwell, M. S., McDaniel, J. G., & Warkentin, K. M. (2010). Is it safe? Red-eyed treefrog embryos assessing predation risk use two features of rain vibrations to avoid false alarms. Animal Behaviour, 79(2), 255-260. doi: 10.1016/j.anbehav.2009.11.005

Cocroft, R. B., & Rodríguez, R. L. (2005). The behavioral ecology of Insect Vibrational Communication. BioScience, 55(4), 323. doi:10.1641/0006-3568(2005)055[0323: tbeoiv]2.0.co;2

Cocroft, R. B., Shugart, H. J., Konrad, K. T., & Tibbs, K. (2006). Variation in Plant Substrates and its Consequences for Insect Vibrational Communication. Ethology, 112(8), 779-789. doi:10.1111/j.1439-0310.2006. 01226.x

Devetak, D., Mencinger-Vračko, B., Devetak, M., Marhl, M., & Špernjak, A. (2007). Sand as a medium for transmission of vibratory signals of prey in antlions Euroleon nostras (Neuroptera: Myrmeleontidae). Physiological Entomology, 32(3), 268-274. doi:10.1111/j.1365-3032.2007. 00580.x

Elias, D. O. (2004). The effect of substrate on the efficacy of seismic courtship signal transmission in the jumping spider Habronattus dossenus (Araneae: Salticidae). Journal of Experimental Biology, 207(23), 4105-4110. doi:10.1242/jeb.01261

Elvidge, C. K., & Brown, G. E. (2012). Visual and Chemical Prey Cues as Complementary Predator Attractants in a Tropical Stream Fish Assemblage. International Journal of Zoology, 2012, 1-7. doi:10.1155/2012/510920

120

Foelix, R. F. (1970), Chemosensitive hairs in spiders. Journal of Morphology, 132, 313-333. doi:10.1002/jmor.1051320306

Foelix, R. (2011). Biology of Spiders. OUP USA.

Girard, M. B., Elias, D. O., & Kasumovic, M. M. (2015). Female preference for multi-modal courtship: multiple signals are important for male mating success in peacock spiders. Proceedings of the Royal Society B: Biological Sciences, 282(1820), 20152222. doi:10.1098/rspb.2015.2222

Hamer, R., Lemckert, F. L., Banks, P. B. (2011). Adult frogs are sensitive to the predation risks of olfactory communication. Biology Letters, 7, 361–363. doi:10.1098/rsbl.2010.1127

Hebets, E. A., & Papaj, D. R. (2004). Complex signal function: developing a framework of testable hypotheses. Behavioral Ecology and Sociobiology, 57(3), 197-214. doi:10.1007/s00265-004-0865-7

Hebets, E. A., Elias, D. O., Mason, A. C., Miller, G. L., & Stratton, G. E. (2008). Substrate- dependent signalling success in the wolf spider, Schizocosa retrorsa. Animal Behaviour, 75(2), 605-615. doi: 10.1016/j.anbehav.2007.06.021

Herberstein, M. E. (ed) Spider behaviour. Flexibility and versatility. Cambridge, Cambridge University Press.

Hergenrder, R., & Barth, F. G. (1983). The release of attack and escape behavior by vibratory stimuli in a wandering spider (Cupiennim salei keys.). Journal of Comparative Physiology? A, 152(3), 347-359. doi:10.1007/bf00606240

Hostettler, S., & Nentwig, W. (2006). Olfactory information saves venom during prey-capture of the hunting spider Cupiennius salei (Araneae: Ctenidae). Functional Ecology, 20(2), 369-375. doi:10.1111/j.1365-2435.2006. 01103.x

121

Johnson, A., Revis, O., & Johnson, J. C. (2011). Chemical prey cues influence the urban microhabitat preferences of Western black widow spiders, Latrodectus hesperus. Journal of Arachnology, 39(3), 449-453. doi:10.1636/hi11-19.1

Lewis, E. R., & Narins, P. M. (1985). Do Frogs Communicate with Seismic Signals? Science, 227(4683), 187-189. doi:10.1126/science.227.4683.187

Lima, S. L. (2002). Putting predators back into behavioral predator–prey interactions. Trends in Ecology & Evolution, 17(2), 70-75. doi:10.1016/s0169-5347(01)02393-x

Long, S. M., Leonard, A., Carey, A., & Jakob, E. M. (2015). Vibration as an effective stimulus for aversive conditioning in jumping spiders. Journal of Arachnology, 43(1), 111-114. doi:10.1636/s14-49.1

Magal, C., Schöller, M., Tautz, J., & Casas, J. (2000). The role of leaf structure in vibration propagation. The Journal of the Acoustical Society of America, 108(5), 2412-2418. doi:10.1121/1.1286098

Manning, A., & Dawkins, M. S. (1998). An Introduction to Animal Behaviour. Cambridge, England: Cambridge University Press.

Michelsen, A., Fink, F., Gogala, M., & Traue, D. (1982). Plants as transmission channels for insect vibrational songs. Behavioral Ecology and Sociobiology, 11(4), 269-281. doi:10.1007/bf00299304

Nentwig, W. (ed.). Spider ecophysiology, pp. 125-140. Berlin, Springer

Nelson, X. J., Jackson, R. R. (2011a). Flexibility in the foraging strategies of spiders. In:

Padial, J., Chaparro, J., Castroviejo-Fisher, S., Guayasamin, J., Lehr, E., Delgado, A., Vaira, A., & Teixeira, R. (2012). A revision of species diversity in the Neotropical genus Oreobates

122

(Anura: Strabomantidae), with the description of three new species from the Amazonian slopes of the Andes. American Museum Novitates, 3752, 55 doi:10.1206/3752. 23752

Penfold, S., Webb, J. K., & Dayananda, B. (2017). Chemical cues influence retreat-site selection by flat rock spiders. Behaviour, 154(2), 149–161. doi:10.1163/1568539x- 00003415

Polajnar, J., Kavčič, A., Kosi, A., & Čokl, A. (2013). Palomena prasina (Hemiptera: Pentatomidae) vibratory signals and their tuning with plant substrates. Open Life Sciences, 8(7). doi:10.2478/s11535-013-0188-z

Polajnar, J., Eriksson, A., Lucchi, A., Anfora, G., Virant-Doberlet, M., & Mazzoni, V. (2014). Manipulating behaviour with substrate-borne vibrations - potential for insect pest control. Pest Management Science, 71(1), 15-23. doi:10.1002/ps.3848

Rypstra, A. L., Schlosser, A. M., Sutton, P. L., & Persons, M. H. (2009). Multimodal signalling: the relative importance of chemical and visual cues from females to the behaviour of male wolf spiders (Lycosidae). Animal Behaviour, 77(4), 937–947.doi: 10.1016/j.anbehav.2008.12.026

Stoffer, B., & Uetz, G. W. (2017). The effects of experience with different courtship modalities on unimodal and multimodal preferences in a wolf spider. Animal Behaviour, 123, 187- 196. doi: 10.1016/j.anbehav.2016.10.033

The Ecology and behavior of Amphibians. (2009). Austral Ecology, 34(1), 116-116. doi:10.1111/j.1442-9993.2008. 01952.x

Toledo, R., & Jared, C. (1995). Cutaneous granular glands and amphibian venoms. Comparative Biochemistry and Physiology Part A: Physiology, 111(1), 1-29. doi:10.1016/0300-9629(95)98515-i

123

Trabalon, M. (2013). Chemical communication and contact cuticular compounds in spiders. In

Uetz, G. W., & Roberts, J. A. (2002). Multisensory Cues and Multimodal Communication in Spiders: Insights from Video/Audio Playback Studies. Brain, Behavior and Evolution, 59(4), 222-230. doi:10.1159/000064909

Uetz, G. W., Roberts, J. A., Clark, D. L., Gibson, J. S., & Gordon, S. D. (2013). Multimodal signals increase active space of communication by wolf spiders in a complex litter environment. Behavioral Ecology and Sociobiology, 67(9), 1471-1482. doi:10.1007/s00265-013-1557-y

Uetz, G. W., Stoffer, B., Lallo, M. M., & Clark, D. L. (2017). Complex signals and comparative mate assessment in wolf spiders: results from multimodal playback studies. Animal Behaviour, 134, 283-299. doi: 10.1016/j.anbehav.2017.02.007

Uetz, G., Clark, D., & Roberts, J. (2016). Multimodal Communication in Wolf Spiders (Lycosidae)—An Emerging Model for Study. Advances in the Study of Behavior, 117- 159. doi: 10.1016/bs.asb.2016.03.003

V.Kardong, K., Lavín-Murcio, P., & Smith, T. (2000). Persistence of trailing behavior: cues involved in poststrike behavior by the rattlesnake (Crotalus viridis oreganus). Behaviour, 137(6), 691-703. doi:10.1163/156853900502295

Virant-Doberlet, M., King, R. A., Polajnar, J., & Symondson, W. O. (2011). Molecular diagnostics reveal spiders that exploit prey vibrational signals used in sexual communication. Molecular Ecology, 20(10), 2204-2216. doi:10.1111/j.1365-294x.2011. 05038.x

Wiens, J. J. (1993). Herpetology. An Introductory Biology of Amphibians and Reptiles. G. R. Zug. 1993. Academic Press, San Diego, xii + 527 pp. $50.00 (cloth). Systematic Biology, 42(4), 592-596. doi:10.1093/sysbio/42.4.592

124

Woodley, S. (2010). Pheromonal communication in amphibians. Journal of Comparative Physiology, 196,713–727. doi: 10.1007/s00359-010-0540-6

Zorovic, M., Cokl, A., & Virant-Doberlet, M. (2005). Use of Substrate Vibrations for Orientation. Insect Sounds and Communication, 81-97. doi: 10.1201/9781420039337.ch5

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Table1. Probability of eliciting approach behaviour in A. rufus, A. juruensis, and P. fera spiders with vibrational stimuli from different frog species that differ in the peak frequency. P values test comparisons among frog species (last column) or among spider species (last row).

Peak frequency (Hz) D. sarayacuensis S. ruber B. lanciformis P-value within species A rufus (%) 54 44 37 0.78 A. juruensis (%) 39 36 51 0.73 P. fera (%) 35 33 43 0.76 p- value between species 0.71 0.43 0.36

Table 2. Summary of the binomial generalized linear mixed model (GLMM) with regard to the effect of frog vibrations (compared to white-noise vibrations) in eliciting spider approach in a Y maze experiment.

Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -1.57 0.22 -6.87 6.3e-12*** stimulus frog 1.45 0.28 5.15 2.5e-07*** Signif.codes:0*** 0.001** 0.01* 0.05‘’ 0.1‘ Residual deviance: 328.89 on 281 degrees of freedom AIC: 332.89

Table 3. Summary of the binomial generalized linear mixed model (GLMM) with regard to the effect of stimulus modality (vibration; vibration+chemical) in eliciting spider first selection in a two-choice experiment.

Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -15.40 0.25 -5.93 3.0e-09*** stimuluschemical 0.89 0.33 2.67 0.00** stimulusvibration+chemical 14.62 0.32 4.47 7.6e-06*** Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 Residual deviance: 367.50 on 303 degrees of freedom AIC: 373.5

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Figure 1. Schematic representation of multimodal experiment design. Test arenas used in prey recognition trials (a) spiders were assayed in a partitioned container, which was cleaned of odours between trials. Each spider was given twenty minutes to acclimatize before the trial began.

Figure 2. Proportions of individual spider responses to vibrational playbacks. Each vertical bar corresponds to the individuals that responded positively or negatively to the noise or frog stimulus. Width of each vertical column indicates relative abundance of each species, and height of each rectangle indicates relative frequency of response within frog and noise stimulus.

Figure 3. Mosaic distribution representing the relative frequency of observed combinations of the number of spider responses to multimodal behavioural experiments. Proportions are estimated from absolute numbers of individuals, not scaled by total spiders. The area of boxes is proportional to the relative frequency of each spider × stimulus combination.

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cm

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Figure 1.

90 cm

Figure 2.

Figure 3.

Concluding remarks

Photo by Patricia Torres

Phoneutria fera female resting outside from individual cage

Spiders are well adapted to gather information from their environment using various sensory modalities. Perceiving and adequately responding to cues on prey are especially important since the failure of prey recognition can result in decrease in fitness and, ultimately death. Given that prey availabilities can vary stochastically, predators often exhibit behavioural flexibility and may be exposed to varying densities of nutritionally profitable and unprofitable prey. A predator should aim to capture the most profitable prey in the environment even if this prey may be costly to a predator. Spiders can consume vertebrates more often than expected. However, this interaction has not been properly studied. In this dissertation, I synthesized patterns of anurans trapped by spiders using an integrative approximation (Chapter one). I found that the events of predation are disproportionately concentrated in a few families of spiders especially ctenids and hylids, suggesting a potential adaptation to capture frogs beyond chance. The few reported cases of toxic frogs involved in depredation, matched the results of the predation experiments, since the spiders avoiding this type of frogs. I found that spiders exhibited spatial patterns of association with resident frogs in ways consistent with aggregations of conspecific attraction during study time that coincided with breeding frog season. In Chapter two my main hypothesis was whether spiders can detect prey relying mainly on vibratory cues, collateral vibration signals from frog calls could be available to them. Vibrations caused by prey contain a very narrow band energy spike in the spectra between 100 and 600 Hz. In addition, I found seismic cues propagate through the substrates spontaneously chosen by frogs with different characteristics associated to each species. Finally, I found that substrate composition influences the selection by spiders and affects the transmission of frog vibrations, being plant and leaf litter the substrates that best transmit these signals. This pattern seems to be consistent with the habitat choice results, under a scenario where spider receptivity is dependent on the relative spectral properties of frog signals, specifically low-frequency content and not overall signal intensity. In Chapter

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three, I performed an experimental study to obtain the information on availability and spider utilization of frog vibrational cues. In playback tests, I found that a frog vibrational signal was an important factor influencing foraging and predatory behaviour of spiders as a directional cue and caused positive responses in the three spider species. Furthermore, I examined the role of chemical vs. vibration+chemical cues on spider predatory behaviour. The results of my behavioural experiments suggest chemical+vibratory cues, rather than only chemical, mediate prey recognition by spiders. Interactions between predators and prey are not only responsible for a significant amount of the current evolutionary diversity, but also drive the transfer of energy within food webs and the functioning of ecosystems. In a series of novel and innovative experiments, I have shown how an event that seemed isolated constitutes a complex dynamic and an interesting challenge for the understanding of how natural selection shapes predator–prey interactions. Accurate predictions require a detailed understanding of the complexity of how prey interacts with predators and the role that biological and physical background habitats play in these crucial interactions.

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Ethics Considerations

All animal handling was carried out in accordance with the current laws of Colombia, especially Law 84 of December 27, 1989, which adopts the National Statute for the Protection of Animals, creates contraventions, and regulates the procedure and jurisdiction. The work carried out during this study was in accordance with the protocol for the use and care of the animals to CICUAL related to “Proyecto Semilla” (Universidad de los Andes). I provided an accurate description of all procedures used. All efforts were made to ensure the welfare, and reduce stress of the animals; with the addition of personal care. All persons who were in contact with animals have the general/manipulation of living organisms and involves minimal risk to researchers. Euthanasia was not planned, but was practiced on animals with loss of well-being for the purpose of the study. Possible complications such as bites, did not compromise the integrity or health of people who manipulated spiders.

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