Opportunism and cognition in birds
Lima Kayello
Department of Biology
McGill University
Montréal, QC, Canada
Submitted April 2013
A thesis submitted to McGill University in partial fulfillment of the requirements of the degree of Master of Science
© Lima Kayello 2013
ACKNOWLEDGEMENTS
I would like to thank my M.Sc. supervisor, Louis Lefebvre, for his relentless support, encouragement and enthusiasm throughout my candidacy. He has helped me grow as a researcher, and more so as a critical and analytical thinker. With his guidance and reinforcement, I was able to professionally develop my oral and written communication skills. Louis, with his love for telling stories through a still frame, has also inspired me to participate in projects outside my academic/work life and make time for things I enjoy. I am very grateful to the members of the Lefebvre lab, Jean-Nicolas Audet and Simon Ducatez for their contributions in the field and the laboratory, as well as their aid in data collection and analysis. I thank my supervisory committee members, Dr. David Bird and Dr. Andrew Hendry, for their helpful comments throughout the progress of my thesis. Special thanks to Dr. Bird and his team at the Faculty of Agricultural and Environmental Sciences for their help with field advice and equipment. I have gained a tremendous amount of practice and experience netting, extracting and banding birds at the McGill Bird Observatory with the guidance and supervision of an amazing group of professional birders and volunteers. Getting into this project, I had no experience with bird research and conservation, let alone catching, handling and banding any animal. Therefore, I am extremely grateful to Gay McDougall Gruner, Simon Duval and Marcel Gahbauer for their field advice. Special thanks to Gay and Simon for sharing extremely helpful fielding practice and for teaching me the proper techniques of mist netting, bird banding and handling. Their undying love and dedication towards bird monitoring and conservation is ever so contagious, and I have been bitten by the bird love-bug ever since. Blandine Doligez and Laure Cauchard, thank you for your patience and field advice, and for guiding me through the initial stages of my field season in Barbados. Frank Cézilly, the Cézilly lab and Melanie Couture, thank you for your volunteered time and efforts in support of the project. I would also like to express my gratitude towards the staff of the Bellairs Research Institute for their help throughout this study. This work could not have been done without the financial support provided by Natural Sciences and
2 Engineering Research Council (NSERC Canada) graduate scholarship to LK and NSERC Discovery Grant to LL. Last but not least, a special thank you to my mother, Huda Al Zaben, my brother, Rami Kayello, and my boyfriend, Taha Zein, for believing in me and encouraging me to strive to for the best in all aspects of life.
3 ABSTRACT
Animals vary in their response to the distribution of resources in time and space. Opportunistic foraging is evident in many species and has indirectly been shown to be linked to measures of cognition such as innovation and problem solving. However, in the field of cognitive ecology, the operationalization and empirical use of opportunism is problematic. In chapter 1, I review the concept of opportunism in the zoological literature and propose an operational definition. The review suggests that many definitions of the concept are not useful, in particular those that equate it with generalism or use it to describe random choice in foraging. With the operational definition I propose ('latency to switch to a new, abundant, food source'), the relationship between ecological flexibility and cognition is then addressed through a small-scale comparative study in chapter 2. Here, the purpose is to determine if an opportunistic species will perform better at problem solving, and have lower neophobic tendencies, than a less opportunistic species. The study compares two sister species of Thraupidae with different foraging strategies: the Barbados bullfinch (Loxigilla barbadensis), an opportunistic forager, and the black-faced grassquit (Tiaris bicolor), a conservative forager. In the field, I carried out focal observations along with opportunism and neophobia experiments. In captivity, wild-caught individuals were run through a set of behavioural and cognitive tests, which included a neophobia test and a problem-solving obstacle removal task. Results show that although both species share overlapping foraging modes, territorial habits and neophobic tendencies, the Barbados bullfinch is much more opportunistic, bolder and better at problem-solving than the black-faced grassquit.
4 RÉSUMÉ
Les animaux diffèrent dans leurs réponses à la distribution spatiale et temporelle des ressources. Plusieurs espèces manifestent un mode opportuniste de quête alimentaire et des preuves indirectes suggèrent que l'opportunisme est associé à des mesures de cognition telles que l'innovation et la résolution de problèmes. Toutefois, dans le domaine de l'écologie cognitive, la définition et l'opérationalisation de l'opportunisme pose problème. Dans le premier chapitre de ce mémoire, je fais une revue de littérature du concept d'opportunisme et j'en propose une définition opérationelle. La revue suggère que plusieurs acceptions du concept sont peu utiles, en particulier celles qui le confondent avec le concept de 'genéralisme' et celles qui lui donnent le sens de 'capture au hasard' de proies. A partir de la définition opérationelle que je propose ('la latence d'exploitation d'une nouvelle et abondate source de nourriture'), la relation entre l'opportunisme et la cognition est testée au chapitre 2 dans une étude comparative à petite échelle. Je prédis qu'une espèce opportuniste sera plus rapide à résoudre un problème alimentaire et sera moins néophobe qu'une espèce conservatrice. L'étude compare deux espèces génétiquement très proches, le sporophile de la Barbade (Loxigilla barbadensis), une espèce opportuniste, et le sporophile cici (Tiaris bicolor), une espèce conservatrice. J'ai effectué sur le terrain des observations focales et des expériences sur l'opportunsime et la néophobie. En captivité, j'ai soumis des individus piégés sur le terrain à des tests de néophobie et d'enlèvement d'obstacle pour atteindre de la nourriture. Les résultats révèlent que le sporophile de la Barbade est plus opportuniste, moins néophobe et meilleur à résoudre le problème que le sporophile cici, mais que ni sa territorialité ni son mode d'alimentation sur le terrain ne diffèrent suffisamment de celui du sporophile cici pour expliquer les différences de cognition.
5 TABLE OF CONTENTS
ACKNOWLEDGEMENTS ...... 2
ABSTRACT ...... 4
RÉSUMÉ ...... 5
TABLE OF CONTENTS ...... 6
LIST OF TABLES ...... 8
LIST OF FIGURES ...... 9
THESIS FORMAT ...... 13
CONTRIBUTIONS OF CO-AUTHORS ...... 13
GENERAL INTRODUCTION ...... 14
CHAPTER 1: Opportunism and its relation to generalism and other ecological determinants of cognition...... 15
Abstract ...... 16 1. Ecological correlates of cognition ...... 17 a. Environmental variables ...... 17 b. Animal traits that vary with environmental variables ...... 19 2. Opportunism and generalism ...... 21 a. Are they the same thing? ...... 21 b. The many uses of the term ‘opportunism’: a review ...... 23 c. Quantifying opportunism and generalism ...... 26 d. The operational definition used in this thesis ...... 30 Acknowledgements ...... 31 References ...... 31 Tables ...... 44
6 Connecting statement ...... 49
CHAPTER 2: Opportunism, Neophobia and Problem-solving in Sister Taxa from the Family Thraupidae, the Barbados Bullfinch Loxigilla barbadensis and the Black-faced Grassquit Tiaris bicolor ...... 50
Abstract ...... 51 Introduction ...... 52 Field study ...... 54 o Methods ...... 54 § Food provisioning and neophobia experiments ...... 55 § Field Observations ...... 57 Results ...... 58 o Response to food provisioning and novel objects in the field ...... 58 o Field Observations on social foraging ...... 59 Experiments in captivity ...... 59 o Subjects and Maintenance ...... 59 o Test Procedures ...... 60 § Neophobia in captivity ...... 61 § Problem-solving: Obstacle removal task ...... 61 Results ...... 62 o Neophobia ...... 62 o Problem-solving: Obstacle removal task ...... 63 Discussion ...... 63 Acknowledgements ...... 68 References ...... 68 Figures ...... 74
GENERAL SUMMARY AND CONCLUSION ...... 82
References ...... 84
APPENDIX 1 ...... 85
7 LIST OF TABLES
Table 1. ‘Opportunism’ in the literature. Listed are the top 60 most cited articles published in peer-reviewed journals through the Web of Science, placed in five assigned categories. The associated definition in context of the article is provided. (*Indicates articles placed in more than one assigned category)…………………….... 44
8 LIST OF FIGURES
Figure 1. Response to food provisioning in the field. Mean ± SEM time to arrive
(seconds) during (A) trials without familiarization (Ntrials= 6) and (B) trials with familiarization (Ntrials= 6) …………………………………………………..…………... 74
Figure 2. Response to field neophobia experiment. Mean ± SEM of time to arrive
(seconds) of the first of each species. Bf: Bullfinch, Gq: grassquit. (NBF=8, NGQ=8) .… 75
Figure 3. Number of focal bullfinches and grassquits foraging on different substrates. Categories for foraging include the substrate upon which the focal individual foraged; on the ground, in the trees (arboreal), or at anthropogenic or provisioned sites.
(NBF=61, NGQ=68) ……………………………………...... ………..… 76
Figure 4. Problem-solving task. Lid-flipping task; subject must remove the lid to gain access to the seeds………………….………………………………………....………… 77
Figure 5. Levels for shaping to learn lid removal. Subjects that failed the problem- solving task were presented with progressively more difficult levels of the task: (A) level 0, apparatus open and the lid placed on the side; (B) level 1, half of the opening of the apparatus covered by the lid placed bottom-up; (C) level 2, three-quarters of the apparatus covered, lid bottom-up; (D) level 3, the apparatus fully covered, lid bottom-up; level 4, apparatus fully covered, lid bottom-down (see Figure 1) …………....…...…… 78
Figure 6. Results of captive neophobia experiment. Mean ± SEM latency (seconds) to feed without novel object (Shyness – light-gray bar) and with novel object (dark-grey bar) for bullfinches and grassquits. Neophobia (NEO dark-grey bar) calculated by removing the shyness in the latency to feed in the presence of a novel object. (NBF=30,
NGQ=15) ………………………………………………………………………………... 79
Figure 7. Problem-solving in bullfinches and grassquits. Mean ± SEM number of trials to first completion of the obstacle removal task by the bullfinches (NBF=30). None of the grassquits (NGQ=15) completed the task. A maximum of 16 trials were assigned to non-solvers ………………………...………………………………………....………… 80
9 Figure 8. Shaping for obstacle removal task. Difference between bullfinches (grey squares, NBF=3) and grassquits (black diamonds, NGQ=15) in proportion of birds that pass the learning criterion for 4 levels of the obstacle removal task. Error bars represent SEM…………………………………………………………………………………….. 81
Appendix 1.A.: Arrival and feeding latencies of Barbados birds at provisioned sites
Figure 1. Latency to arrive at provisioned site with no familiarization. Latency ±SEM (seconds) of the first of six species to arrive at the provisioned site. Tb: Tiaris bicolor (black-faced grassquit), Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove) ………..…...… 86
Figure 2. Latency to feed at provisioned site with no familiarization. Latency ±SEM (seconds) of the first of six species to feed at the provisioned site. Tb: Tiaris bicolor (black-faced grassquit), Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove) ……………....………… 87
Figure 3. Latency to arrive at provisioned site with familiarization. Latency ±SEM (seconds) of the first of six species to arrive at the provisioned site. Tb: Tiaris bicolor (black-faced grassquit), Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove) ……………….……...… 88
Figure 4. Latency to feed at provisioned site with familiarization. Latency ±SEM (seconds) of the first of six species to feed at the provisioned site. Tb: Tiaris bicolor (black-faced grassquit), Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove) …………….....……...… 89
10 Appendix 1.B.: Opportunism’s correlation with data from literature
Figure 5. Relationship between rank innovation frequency and rank latency to arrive. Innovation frequencies (data from Overington et al. 2009 database) plotted against rank latency of arrival of the Barbados species during field test without familiarization (Appendix 1 – Figure 1). Tb: Tiaris bicolor (black-faced grassquit), Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove). ρ (Rho) = Spearman’s rank correlation.. 91
Figure 6. Relationship between rank latency to arrive from two experiments. The rank latency of arrival of Barbados species at feeding task in the field (data from Webster and Lefebvre 2001) plotted against rank latency of arrival of the Barbados species during field test without familiarization (Appendix 1 – Figure 1). Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove). ρ (Rho) = Spearman’s rank correlation ……………………………....… 92
Figure 7. Relationship between rank to contact task and rank latency to arrive. The rank number of Barbados species that first contacted a task in the field (data from Webster and Lefebvre 2001) plotted against rank latency of arrival of the Barbados species during field test without familiarization (Appendix 1 – Figure 1). Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove). ρ (Rho) = Spearman’s rank correlation .…………... 93
Figure 8. Relationship between rank number that solve task and rank latency to arrive. The rank number of Barbados species that solved a task in the field and in captivity (data from Webster and Lefebvre 2001) plotted against rank latency of arrival of the Barbados species during field test without familiarization (Appendix 1 – Figure 1). Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb:
11 Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove). ρ (Rho) = Spearman’s rank correlation.. 94
12 THESIS FORMAT
This M.Sc. thesis was prepared according to McGill University’s Faculty of Graduate and Postdoctoral Studies Office’s “Thesis Submission Guidelines” and completed under the supervision of Dr. Louis Lefebvre. Funding was provided by the Natural Sciences and Engineering Research Council of Canada through a graduate scholarship to L. Kayello through the Biology Department of McGill University.
CONTRIBUTIONS OF CO-AUTHORS
Throughout my M.Sc. candidacy, my supervisor, Dr. Louis Lefebvre, offered his guidance from the initiation until the completion of my thesis. I am the primary author of the studies included in this thesis. With the supervision of Dr. Lefebvre, I formulated the hypotheses, planned the studies, and carried out all of the experiments and analyses. Furthermore, he provided substantial support on all aspects of the thesis writing process, from formulation of the ideas to editing and revising final drafts of the work, which makes him a co-author of all chapters of this thesis. Members of the Lefebvre lab, Jean- Nicolas Audet and Simon Ducatez, assisted in the fieldwork, as well as data collection and analysis.
13 GENERAL INTRODUCTION
Animals differ in the way they search for food and the way they process information as they forage. One foraging strategy that is used by many species is opportunistic generalism, which can entail the consumption of a new food type or the use of a new searching and handling technique. In the literature on cognitive information processing, new foods and new techniques are subsumed under the term 'innovations'. Comparative studies have shown that innovation rate varies among avian and primate taxa, and is associated with variation in brain size, learning and problem-solving.
Despite the obvious logical link between an opportunistic foraging strategy and a high level of innovativeness and problem solving, no study has empirically tested the co- variation between these traits. In chapter 1 of this thesis, I review the concept of opportunistic feeding, first in the context of the many ecological correlates of cognition, and second, in relation to its parent strategy, generalism. I end the chapter with a critique of the different ways in which the term 'opportunism' is used in the biological literature and point out the difficulties associated with its operationalization.
In chapter 2, I report an empirical study on two sister species that previous anecdotal evidence suggests differ sharply in opportunism: the Barbados bullfinch Loxigilla barbadensis and the black-faced grassquit Tiaris bicolor. I document in the field the extreme differences in opportunism, boldness and neophobia that characterize these species. I also show that the sister species show no major differences in other field traits like social foraging and territoriality. Finally, I demonstrate that the extreme differences in opportunism and boldness in the field are associated with extreme differences in problem-solving of an obstacle removal task yielding food by captive wild- caught birds.
14
CHAPTER 1
Opportunism and its relation to generalism and other ecological determinants of cognition
15 Abstract
Animals vary in the way they respond to the distribution of food. Opportunistic foraging is thought to be linked to higher cognition, such as innovativeness and problem-solving, yet it does not stand alone as an operational measure. Given this, the purpose of this review is to isolate opportunism and derive an operational definition for future comparative studies. The first section provides a review of the ecology of cognition, focusing on cognitive traits that vary with environmental variables. The second section examines the concept of opportunism and suggests ways in which the circularity of its relationship with other measures, such as innovation and generalism, can be mitigated. We follow by carrying out a critical review of ‘opportunistic feeding’ definitions derived from zoological literature. We then contrast the many ways in which generalism has been quantified with the very rare attempts to quantify opportunism. Although we find most definitions and measures are weak or vague, we are able to derive a suitable definition and operational measure for opportunism in the context of cognitive ecology. With opportunism operationalized, we can assess the relationship between ecological flexibility and cognition; yet its applicability is limited to small-scale comparative analyses.
16 1. Ecological correlates of cognition
Opportunism is one of the many ecological variables that have been implicated in the evolution of cognition. These ecological variables range from features of the physical environment like climate variability and harshness (MacDonald 2002; Pravosudov and Clayton 2002; Roth et al. 2010; 2012a; 2012b; Schuck-Paim et al. 2008), as well as the distribution of food in space and time (Goldberg et al. 2001; Sol et al. 2005a), to traits that are assumed to adapt animals to such environmental variation, including diet or habitat breadth (Daly et al. 1982; Overington et al. 2011), territoriality (Carlier and Lefebvre 1996; Seferta et al. 2001), group size (Barton 1996; Dunbar 1992; Dunbar and Shultz 2007), invasiveness (Amiel et al. 2011; Martin and Fitzgerald 2005; Sol et al. 2002; 2005c; 2008) and migration (Sol et al. 2005b). Comparative studies, either on pairs or small numbers of sister taxa or large numbers of clades from an entire order or class, have looked at cognitive variables that range from the speed of individual, social or reversal learning, to innovation rate and problem-solving, to the size of the neural substrate for cognition, such as the brain or the cortex. They also occasionally feature two correlates of learning and problem-solving, low neophobia and exploration. In the first part of this chapter, we present a short review of the ecology of cognition. a. Environmental variables
Climatically varying environments pose many challenges, mainly in the form of uncertainty and unpredictability of resources. Though many studies suggest that animals with larger-brains are better prepared to cope with environmental challenges, only a handful directly address the association between cognition and climatic variability. Schuck-Paim and colleagues (2008) showed that, in neotropical parrots, there is an association between relative brain size and climatic variability, both on a temporal and spatial scale. Similarly, MacDonald (2002) found a positive association between climatic variability and innovation rate in African primates. However, Reader and MacDonald (2003) found no association between climatic variability and either brain size or innovation rate. Thus, the link between cognition and environmental variability remains questionable.
17 Climate harshness is another variable that has been recently addressed through studies addressing inter-population differences in caching, memory and the hippocampus in black-capped chickadees (Pravosudov and Clayton 2002; Roth et al. 2010; 2012a; 2012b). Roth and colleagues (Roth et al. 2010; 2012a; 2012b) have shown that chickadees from zones that differ in climate harshness, i.e. Alaska and Kansas, differ in spatial memory, neophobia and problem-solving, as well as in brain areas associated with these abilities, the hippocampus, the amygdala and the telencephalon respectively. The differences appear to be hard-wired, as the individuals tested were F1 descendants of Alaskan and Kansas parents and had been raised in the same environment at the University of Nevada (Roth et al. 2010). Strong seasonality in temperate or northerly zones leads many birds to migrate. However, some species, such as the black-capped chickadees, remain during the harsh season and adapt by food storing, while other residents survive through innovative behaviours. A comparative study of Western Palaearctic birds showed that resident species have larger brains relative to their body size and are more innovative than migratory species (Sol et al. 2005b). The resident passerines tend to rely on innovative feeding behaviours especially during stressful winter periods. However, there exists a strong negative correlation between innovation rate and degree of food storing in corvids and parids (Lefebvre and Bolhuis 2003), suggesting a possible trade-off between two cognitively demanding systems (Sherry and Schacter1987). The distribution of food in space and time can drive inter- and intra-specific differences in resource use, which can further influence cognition. Studies on Barbados Zenaida doves show that differences in the amount and distribution of food are associated with morphological differences that determine whether the doves aggressively hold territories (at sites with predictable, low density food) or feed unaggressively in groups (at sites with unpredictable, large amounts of food; Goldberg et al. 2001; Sol et al. 2005a). Learning, in turn, is determined by these social foraging differences, individual learning being slightly slower in territorial doves than in group feeding ones (Carlier and Lefebvre 1996; Seferta et al. 2001) and social learning being strongly biased towards different species of tutors (Carlier and Lefebvre 1996; Dolman 1996).
18 b. Animal traits that vary with environmental variables
In the previous examples, environmental effects (seasonal harshness, resource distribution) determine behavioural responses (respectively migrate or store food, defend a feeding area) that then determine cognition (respectively smaller brains and less innovation or better spatial memory, different attention to social tutors). In other cases, variation in feeding strategies is associated with cognition despite the fact that environmental drivers are only assumed, but not demonstrated. This is the case for group living. Many studies predict that the computational demands of living in large, complex societies select for large brains. In primates, for instance, neocortex size is associated with the size of both social groups (Dunbar 1992; Barton 1996) and grooming cliques (Kudo and Dunbar 2001). Similar relationship between sociality and relative brain size is also evident in ungulates (Perez-Barberia and Gordon 2005; Shultz and Dunbar 2006). However, recent analyses comparing birds and mammals (not including primates) show that the large relative brain size is associated specifically with pairbonded monogamy (Dunbar and Shultz 2007). This suggests that it is the cognitive demands of sociality, especially pairbonding, that triggered the evolution of large brains across higher vertebrates (Dunbar and Shultz 2007). Many papers on the relationship between group size, brain size and cognition assume that there is a social form of intelligence (also called 'machiavellian intelligence') that is distinct from 'ecological intelligence': one deals with social relationships and the other with non-social aspects of the environments. It should be pointed out that models based on the distribution of resources in space and time suggests that this might not be the case. Overington et al. (2008) have shown that when resources are predictable in space and time, both specialization and aggressive defense against others are more efficient than generalism and unaggressive group feeding; the opposite applies when resources are unpredictable. Cognition driven by feeding, and cognition driven by social relationships should therefore co-evolve as a result of the same environmental variables. Reader et al.'s (2011) comparative analysis empirically confirms this idea by showing that social (e.g. tactical deception, social learning) and non-social (e.g. tool use) forms of cognition fall on the same 'general intelligence' factor, while social (group size) and non- social (diet breadth) lifestyle categories also fall together on a second, orthogonal factor.
19 Brood parasitism is a reproductive strategy that seems to be associated with a smaller brain and an enlarged hippocampus. The strategy has evolved at least four times independently in birds: in cuckoos, honeyguides, cowbirds and whydaws. Boerner and Krueger (2008) have shown that brain size in brood parasitic Cuculiformes is 21% smaller than it is in cuckoos that do their own parental care. Cowbird from the genus Molothrus have small brains compared to those of sister genera like Quiscalus and Agelaius (Overington 2011), as do whydaws compared to other estrildine finches (Iwaniuk 2004). Honeyguides have both a smaller telencephalon and a larger hippocampus than their closest sister taxon, woodpeckers (Corfield et al. 2013). In Molothrus cowbirds, the enlargement of the hippocampus is associated with variation in the sex that does the spatial and temporal scouting of suitable nests in which to dump the eggs (Sherry et al. 1993; Reboreda et al. 1996). Invasiveness is another trait that is thought to be associated with cognition. Martin and Fitzgerald (2005) have shown that house sparrows at the edge of an invasive population expansion (Panama) are less neophobic than sparrows from long established invasive populations (USA). In introduced birds (Sol et al. 2002; 2005c), mammals (Sol et al. 2008), amphibians and reptiles (Amiel et al. 2011), but not fish (Drake 2007), colonization success is associated with brain size, and for birds, innovation rate in the zone of origin (Sol et al. 2005c). Diet is probably the ecological adaptation that has attracted the most attention in studies of cognitive evolution. Early studies on the ecology of brains showed that frugivorous primates had larger brains than folivorous ones (Clutton-Brock and Harvey 1980), a result that was later quantitatively extended to percent fruit in the diet (Barton 1996; Fish and Lockwood 2003). Later studies have further supported the role of diet in rodents and lagomorphs (Mace et al. 1980), where omnivores, insectivores, frugivores and granivores have larger brains than folivores. In bats, clades with a higher diet flexibililty have a larger telencephalon (Ratcliffe et al. 2006). A comparison of food aversion learning between two species of kangaroo rats (Dipodomys) show that the generalist forager learned better and more rapidly than the specialist (Daly et al. 1982). Similar findings were seen between the generalist song sparrow and the specialist swamp sparrow through field and wild-caught captive experiments (Greenberg 1989; 1990).
20 However, once reared under identical conditions in captivity the results were the opposite (Greenberg 1992), which suggest that experiential factors might be involved in the underlying mechanism that set an individual’s neophobia threshold. A more recent comparative study involving 13 species of Darwin’s finches illustrates that exploration and neophilia, or affinity to novelty, increased with diet diversity, suggesting that generalist species would more likely benefit from such traits than would specialists (Tebbich et al. 2009). Tebbich and colleagues (2010; 2011) further suggested that the difference in learning abilities between two closely related sympatric Darwin’s finch species, the small tree finch (Camarhynchus parvulus) and the woodpecker finch (Cactospiza pallida), can be attributed to their different feeding ecologies. The small tree finch mainly eats vegetable matter (e.g. nectar, fruits, leaves and seeds) that change in proportion across dry-wet seasons. The woodpecker finch, on the other hand, is specialized to feed under bark, mainly on arthropods, by using a diversity of feeding techniques throughout the seasons (Tebbich et al. 2004). This should normally make the woodpecker finch a better learner than the small tree finch. However, the results showed that while the woodpecker finch outperformed the tree finch at novel problem solving tasks, the small tree finch was better at reversal learning (Tebbich et al. 2010). Tebbich and colleagues relate this result to the persistent foraging style of the woodpecker finch associated with extractive foraging, which makes it engage in long bouts of energetic pecking without immediate food acquisition (Tebbich et al. 2004). Finally, Overington et al. (2011) compared 193 species of North America birds to see whether diet breadth, habitat breadth or predator diversity correlated positively with innovation rate and brain size. The only significant relationship they found was the one between innovation rate and habitat breadth.
2. Opportunism and generalism a. Are they the same thing?
As shown above, dietary generalism is often seen as a key ecological correlate of cognition. Generalist feeders are often also depicted as opportunists (MacCraken and Hansen 1987; Brown 1991; Graeve et al. 1994; Toft 1995; Hansen and Quinn 1998;
21 Waldenstrom et al. 2002; Klemetsen et al. 2003; Eeva et al. 2005; Rosalino et al. 2005; Gherardi 2006). Generalists have a wide diet breadth, consuming a variety of plants, animals, insects, and, in some cases, even carrion. This foraging strategy allows them to thrive in different habitats, especially those that experience drastic changes in environmental conditions and prey availability. Therefore it is not surprising that ‘opportunistic’ generalists respond adaptively by demonstrating a level of flexibility with regards to their foraging behaviour, diet composition, and habitat use (Bustnes and Systad 2001; Montevecchi et al. 2009; Lanszki et al. 2010; Zhou et al. 2010). Changes in the diet of many taxa, including insects, fish, birds and mammals, are often described as opportunistic. For instance, in an estuarine fish, the black drum (Pogonias cromis), variation in trophic niche breadth and feeding strategy are observed in response to seasonal changes in prey abundance (Blasina et al. 2010). In the case of birds, the black-headed gull (Larus ridibundus), characterized by its high dietary plasticity and flexible feeding strategy, responds to poor prey availability by switching foraging habitats (Schwemmer and Garthe 2008). Furthermore, these gulls demonstrate both short- term and long-term switches depending on tidal cycles or seasonal/breeding stages, respectively. Similarly, Northern gannets use a mixed foraging strategy, where they showed fidelity to inshore foraging sites but then adjusted to decreased prey abundance by foraging further offshore (Montevecchi et al. 2009). In mammals, a recent cross-genus study on Martes, an opportunistic and flexible feeder, showed that biogeographical variants, such as latitude, local climate (temperature) and food variety and attainability influenced their feeding habits (Zhou et al. 2010). On a broad geographical scale, martens demonstrated facultative feeding tactics in response to changes in food availability, foraging on foods that were abundant. Even if the terms 'generalist' and 'opportunist' are often used together, they do not describe identical traits. For example, Snail kites (Rothramus sociabilis) are specialized on a single genus of Pomacea snails that they catch with their feet, but they can opportunistically switch to crabs and turtles during periods of low snail availability (Beissinger 1990), steal otherwise unattainable snails from limpkins (Miller and Tilson 1985), or use disturbance created by waders to catch displaced snails (Bennetts and Dreitz 1997).
22 In and of itself, separate from generalism, opportunism is a key potential ecological correlate of cognition. Because opportunism is often associated with flexible feeding, it provides the element of change that is thought to be one of the main drivers of learning (Johnston 1982). Opportunism is in fact part of the definition of some cognitive measures and is mentioned several times in the Lefebvre et al. (1997) article where they also used ‘opportunistic’ as a key term during their survey of innovative foraging behaviours within ornithological journals. Lefebvre et al. (1997, page 550) go as far as saying that ‘the frequency of opportunistic innovations is, for a given taxonomic group, a useful indicator of its behavioural plasticity and its tendency to use novel means to solve environmental problems’. One problem posed by this definition is that it leads to circularity: one cannot predict that opportunism should be an ecological variable that correlates with innovativeness if opportunism is part of the definition of innovativeness. In the following section, we examine the concept of opportunism and suggest ways in which the circularity of its relationship with innovation can be mitigated. We review the most frequently cited papers in the Web of Science that deal with opportunism feeding and sort them into categories that correspond to the different meanings given to opportunism in the zoological literature. We then discuss each of these meanings and suggest that some of them should not refer to opportunism, in particular the use of the term to describe random feeding. Finally, we contrast the many ways in which generalism has been quantified with the very rare attempts to quantify opportunism. This lack of quantification often leads to a vague use of the term and precludes its inclusion in the large-scale comparative analyses that have been so prominent in the study of cognition. b. The many uses of the term 'opportunism': a review
By using the search terms ‘opportunistic foraging’ and ‘opportunistic feeding’, we surveyed the top 60 most cited articles published in peer-reviewed journals through the Web of Science. Each article that cited opportunism in the context of foraging was reviewed and its associated definition, whether explicitly stated or implicit in its use, was entered in one of the categories of the survey (Table 1).
23 From this review, we classified the papers in four categories (1) those that use opportunism to describe feeding on prey relative to its abundance; (2) those that equate it with generalism; (3) those that describe quick responses to increased concentrations of a resource under either natural or anthropogenic influences; or (4) those that use opportunism to describe flexible foraging strategies. Category 1 was the most abundant (36 of 60 articles), followed by category 2 (10 articles), category 3 (9 articles), and category 4 (3 articles). Some definitions of opportunism (4 incidences) did not perfectly fit with one assigned category; these articles were placed in a maximum of two categories. Seven articles were placed in a category for ‘other definitions’ or ‘undefined terms’. Some of these articles had definitions for opportunism that did not fit any category we have assigned, while others had no definition. Of the most frequently cited examples of category 1, feeding on prey relative to its abundance, include the studies of Wiens and Rotenberry (1979) and Pakhomov et al. (1996). Pakhomov et al. (1996) analyzed myctophid gut contents, expressed as a percentage of each food item to the total number of food items counted, to reveal that Myctophid species are opportunistic mesozooplankton feeders consuming primarily the most abundant species. Wiens and Rotenberry (1979) also used gut contents to derive the taxonomic composition of birds’ diet. Their analysis also addressed diet diversity via Levin’s index (formula discussed further in the upcoming section). Birds that were considered opportunistic were those that fed on prey relative to its abundance (i.e ‘eating by and large whatever they encounter’ (Wiens and Rotenberry 1979, page 255). For category 2, generalism, Klemetsen et al. (2003, page 26) mentioned in their review of the life history of brown trout (Salmo trutta) that the ‘trout is an opportunistic carnivore, although individuals appear to specialize at least temporarily on particular food items. The food eaten depends on availability’. Graeve et al. (1994) compared the trophic positioning of three species of Antarctic copepods through their lipid compositions. They used the fatty acid/alcohol composition to categorize the copepods feeding modes. One of the copepod species ‘showed an intermediate pattern, which implies a tendency towards an opportunistic feeding mode, positioned somewhere between the other two species [demonstrating a herbivorous and omnivorous pattern, respectively]’ (Graeve et al. 1994, page 915).
24 Category 3 includes articles that place opportunism in context of quick behavioural responses to feeding opportunities. We noticed that in this category resources encountered shared common features, they were unpredictable, abundant, and temporary. For instance, many marine animals are known to opportunistically scavenge on human- engendered carrion, a result of trawling, dredging and netting (Britton and Moron 1994; Kaiser and Spencer 1994). Bats also take advantage of sudden changes in resource availability. Fenton and Morris (1976) found that insectivorous bats quickly locate and exploit concentrated patches of insects made available by artificial light. They further stressed that the bats’ feeding remained selective towards larger insects, even though smaller ones were more abundant. As an example of flexible feeding strategy, category 4, Derocher et al. (2000) found that polar bears (Ursus maritimus), obligate predators that specialize on two seal species, opportunistically feed or scavenge on novel prey items, such as ungulates. The literature review suggests that the term 'opportunism' is used to describe different phenomena and needs to be standardized. From the point of view of cognitive evolution, the different uses of the term seem to lead to different predictions. Categories 3 and 4 imply sudden switches in foraging choices, as well as behavioural flexibility. These situations would benefit from rapid information processing, increased attention to potential opportunities, a large repertoire of searching and handling techniques, and an ability to quickly inhibit an initial search image and foraging tactic to profit from a new food source. The categories would therefore clearly select for increased cognitive abilities. In contrast, category 1, random selection of prey, would not. The definition of opportunism used in these cases implies that animals are not choosing, but taking whatever is available. Compared to categories 3 and 4, it is difficult to imagine that this situation would select for increased cognitive abilities as strongly as rapid switching and flexible foraging. The cognitive implications alone therefore suggest that we dissociate the uses of the term 'opportunism' for these categories. It is paradoxical that the vast majority of the highly cited papers use opportunism in the context of abundance related feeding. Feeding relative to abundance should instead be defined and categorized solely
25 as random feeding. We suggest that opportunistic feeding should relate to more active, or changes in, behaviours in response to environmental cues. We have also encountered the interchangeable use of generalism and opportunism in several articles (category 2). This creates an obvious problem: if opportunism is equivalent to generalism, then we do not need a redundant term to describe an animal's behaviour. Equating the two terms can also be problematic, as opportunistic feeding can occur in extreme specialists, as the snail kite example mentioned earlier suggests. Finally, several quantitative operational definitions of generalism are available, but few attempts have been made to operationalize opportunism. The following section elaborates on this idea. c. Quantifying opportunism and generalism
In light of ecological and comparative studies it is important to note that generalist and specialist strategies represent a continuum rather than definite contrasts (Newbold and MacMahon 2009). With that in mind, a need to better define feeding specializations has led some ecologists to further categorize the degree of specialization by proposing a general “specialization key” (i.e. adding modifiers such as ‘facultative’ and ‘obligatory’) based on the width of the subject’s facultative and realized niches (Shipley et al. 2009). Furthermore, species can tend toward either extremes of the continuum, such that they can be a feeding specialist and a habitat generalist at the same time, while others might be referred to as a selective opportunist or an opportunistic specialist. One way of operationalizing habitat or diet breadth is based on categorical variables. In the case of dietary generalism, many studies use an ordinal measure of the number of food types eaten per family (1 = uses one food type only, 2 = uses two food types and 3 = uses three or more food types; Owens et al. 1999, Bennett and Owens 2002). Similarly, the extent of habitat generalization can also be scaled based on the number of habitat types used during an allotted time frame (i.e. breeding season). Cassey et al. (2004), Overington et al. (2011) and Reader et al. (2011) provide more examples of diet breadth based on food type categories (e.g. fruit, invertebrate prey, vertebrate prey, etc.). The advantage with this kind of quantification is that data on diet and habitat breadth can be included in large-scale comparative analyses.
26 Trophic ecology of Pogonias cromis 529
Recreational fishing is an important tourist activity in Mar examine changes in the diet graphically, allocated into groups Chiquita throughout the year. P. cromis and the flounder of five individuals each and calculating the mean number for Paralichthys orbignyanus are regarded as the most important each group. game species due to their size and the top quality of their flesh The feeding strategy of P. cromis, in terms of specialization (Lucifora, 2001). and generalization, and the importance of each prey category in the diet were identified by plotting the prey-specific abundance (Pi) of each prey category against %Fi (Amundsen Field sampling and laboratory procedures et al., 1996). Pi refers to the relative abundance among prey Monthly samples of P. cromis were collected between May species found in the stomachs, and was calculated as the 2005 and April 2007. Sampling was in the vicinity of the mouth number of prey category i divided by the total number of prey of the lagoon towards the sea using 25 m long and 2 m wide in the stomachs that contained the prey category i, expressed gill-nets with 120, 68 and 57 mm mesh sizes, covering different as a percentage. Prey pointsBiogeographical located on the variation upper right in of the the diet of Holarctic martens fish sizes. Recreational fishery samples were also taken in the diagram would be indicative of specialization of the predator same locality.assessed Total by lengththe analysis (TL) was of measured stomach to and/or the nearest faeces, andpopulation. contain In contrast,review all prey we points use a located two-way along MANOVA or bellow with food derivation type mm andsufficient the sex information of each specimen with was which recorded. to calculate Their the the diagonal relative from theand upper species left to as the fixed lower factors right would and food groups as response stomachs were removed and stored at )20°C for subsequent reflect a generalized feeding strategy of the predator popula- laboratoryfrequency analyses. of different food categories in relationtion. to the Furthermore, total variables the distribution to explore of pointsthis potential along the source of bias. Because some In thenumber laboratory, of all prey food items items; were (3) identified sample sizes under had a todiagonal exceed from 60 the lowerof the left to studies the upper used right here corner (see provides Appendix S1) combined samples stereomicroscopestomach and/or to the lowest faecal possible samples; taxon, (4) all weighed recognizable and a food measure items, of prey importance,from different with sourcesdominant to prey characterize at the dietary composition, counted. Bait was excluded from analysis in those individuals upperAnother and means rare of preyquantifying at the diet lower breadth end is through (Amundsen the use etof statistical al., 1996). collectedand from not the only recreational the dominant fishery. foods, Whenever had to possible, be documented;measures.Levins A commonlyÕ andmeasure used measure (B)derivation was is usedLevin’s for of index materialcalculating (B) (Levins was niche1968) assigned, breadthsometimes to ‘faeces’ versus ‘stomach carapace(5) width geographical (CW) of location brachyuran and crabs the and timing maximum andreferred durationusing to as thediet of diversity followingthe index equationand (DDI), faeces’. calculated (Krebs, using 1989): the following equation: length of valves of bivalve mollusks (VL) were measured. study had to be described adequately. Investigations from 59 While then relative frequency of occurrence (RFO) is not 2 localities across the Holarctic region met these criteria (Fig. 1 theB most1= comprehensivepi technique for assessing a carnivorous ¼ i 1 Data analysisand and see feeding Appendix ecology S1 in Supporting Information). Results diet (ReynoldsX¼ & Aebischer, 1991), RFO values are considered Prey importancefrom within was assessed the same using study the percentage site (i.e. Je of˛drzejewski numberwhere etpi wheregives al., the 1993; p ipercentageis the proportion frequencyto be of highly of occurrence each suitable prey of the category ith for food inter-population iitemin theand n diet is the dietary comparisons (%N ), percentage of wet weight (%W ), percentage frequency and n is the total number of prey categories in the P. cromis i Zalewski, 2007) were pooledi to avoid pseudo-replicationtotal number of food items in the(Clavero species’ diet.et Levin’s al., 2003; index is Lozanofurther standardizedet al., 2006; Moleo´n et al., 2009). of occurrence (%Oi) (Hyslop, 1980) and the Index of Relativeacrossdiet. food items The standardizedas such: LevinsÕ index (Best = (B ) 1) ⁄ (n ) 1)) Importance(Hurlbert, (IRI) (Pinkas 1984). et Unfortunately, al., 1971): IRI very= %O few of[%- thewas studies used to we express nicheHere, breadth seven basic on a scale food from types 0 (narrowwere distinguished: carrion (large i i · N + %W ]. To allow comparisons with other studies, IRI niche breadth) to 1 (broad niche breadth). The Bootstrap i includedi were sufficiently detailed to allow us to test Charnov’s mammalsB = (B - 1) too⁄ (n - 1) big to have been killed by a marten, mainly was expressed on a percentage basis (%IRI) (Corte´ s, 1997). To method (random samplingest with replacement, 100 replicates) determine(1976) sample optimal size su foragingfficiency, criteria, the order that of is: stomachs (1) the rankswas used of food to estimateungulates), the mean B other(Krebs, mammals, 1989). A Student birds, herpetofauna (amphibians to express diet breadth on a scale from 0 (narrow)est to 1 (broad). sampleditems was (ranked randomized by net 100 energy times, gain and to the the cumulative consumer, ort-test ranked was used in for testingand the reptiles), null hypothesis invertebrates, of no difference vegetable matter and others The Shannon diversity index (H’) (or Shannon-Wiener diversity index) is also numberssome of prey alternative items were way) plotted were as a not function generally of stomach given, andbetween (2) B theest means. (secondary prey not in the previous categories, namely fish used to indicate whether a species is a generalist or a specialist in its feeding habits, numberenvironmental (Ferry and Cailliet, abundances 1996). If of the the plot most reached highly an rankedWe evaluated food theand relationship refuse). between predator length – asymptote, the number of stomachs analysed was sufficient.whichprey is determined length by using their relative total feeding length specializations (TL) of P. (Colwell cromis and, carapace Futuyma items were often not detailed. In our analyses and discussion For all studies we calculated trophic diversity and niche Cumulative curves were calculated for each factor considered1971)width. The equations (CW) ofis as brachyuran follows: crab and maximum length of valves in the analyses of feeding variation. (VL) of bivalve mollusks. We fitted an increase in minimum, we therefore make a subjective assessment of relative optimal- breadth using, respectively, Shannon’s diversity index (H¢) Preyity items informed were assigned by what to four data taxonomic are available categories: frommedian the studies and maximumH¢ = size) of(P consumed)(logP ) and prey Levins’ items with index (B) B = 1/ P 2, where C. angulatus, B. rodriguezi, C. affinis, and other Brachyura increasing predator size by testing thei significancei of the slopes i sampled, and thereby construct a coherent interpretive frame- P gives the percentage frequency of occurrence of a given food consisting of C. granulatus and unidentified Brachyura, the of 5, 50, and 95% quantilei P regressions (Scharf et al., 1998), P latter preywork. items with %IRI lesser to 1. To analyze ontogenetic respectively.It provides the sum of theitem relative (after frequency Je˛drzejewski of each food itemet al.multiplied, 1993; by Zhouthe et al., 2008a). Where and seasonalIn shifts the selected in the diet, studies,P. cromis variationwere grouped in the intologarithm derivation of the relative of frequency.possible, The value the of H’ proportions is inversely related of to fruits feeding among vegetable matter and three size-classes: I (<300 mm TL), II (300–400 mm TL) andspecialization, hence the higher the H’ value the more of a generalist feeder the species analysed food material (stomach contents or faeces)Results was a the proportion of rodents among mammals were also calcu- III (>400 mm TL), and the seasons defined as: autumn (April,is. May andconfounding June) and spring factor (October, for inter-population November and Decem- comparisonsOf the (Witt, 109 individualslated. of ForP. cromis each location,examined wefor also dietary included latitude (to a half A study by Zhou and colleagues (2010), mentioned earlier, implemented both ber). Only1980; these Cavallini two seasons & Volpi, were used 1995). in the Putman analysis (1984) because suggestedanalysis, that 101 (92.7%)degree) were found and elevationwith stomachs (metres) containing taken from information given the sample size was above the minimum number of samplesmeasuresprey by itemsusing the in information different regarding stages martens’ of digestion. diet composition Males f (nrom = previous 46) requiredsome to describe food the groups diet of are the under-represented predators according toin the faecesassessmentsranged compared of stomach from 239and/or to faecesin 780 the to mmdemonstrate studies TL, or whilethat from martens females a are geographical facultative (n = 55) database. When samples methodwith used by stomach Ferry and contents Cailliet (1996). due to differential digestion,generalists.ranged Another which from study 163 used to wereNorth 563 mmAmerican collected TL. bird Size overdiet classes compositions a large I, II area,derived and representativefrom III mean latitudes A one-way non-parametric permutation multivariate anal- consisted of 23, 43 and 35 individuals with stomach contents, could also potentially confound the combinedanalyses use of of samplesstomach and esophagus(within then assessed a discrete via Levin’s range index also per showed study site of 1°) and elevations ysis of variance (PERMANOVA) using Bray-Curtis distances with respectively. Size ranges of specimens in autumn (n = 53) and ‘opportunistic’ shifts in dietary composition in several bird species, including horned 10 000 permutationsfrom different of matrix sources. data However, (Anderson, in 2001) a broad-scale on the in analysis spring for (n = 48)(within were 227–572 a discrete and 163–518 range per mm study TL, site of < 500 m) were numberEuropean and weight wildcats, of the main no prey significant items was differences used to test the inlarks the (respectively.Eromophila consump- alpestris All) and cumulativeinferred meadowlarks curves (Lozano (Sturnella of spp.et minimum al.; Wiens, 2006). and numbers Rotenberry null hypothesistion of food of no groups differences from in different the diet sources composition (faeces1979) orreached. In stomach)their study an of asymptote, exploration in indicating 13 species of that Darwin's the samplefinches, Tebbich sizes wereet al. between sex, ontogenetic stages and seasons. This test is sufficient to describe and compare the diets (Fig. 1). were found (Lozano et al., 2006). Amongst martens, Muraka- designed on the basis of a distance measure between each pair Five taxonomic levelsEnvironmental of prey were identified variables in the diet: 1 of observationmi (2003) units found to obtain that, a distance for sables matrix. (M. The zibellina permu-), thebivalve frequency and 4 brachyurans. The most important dietary 27 tation testratio is used of food to create categories a distribution detected of F by and stomach obtain a P-contentcomponents, analyses in %IRI,Environmental were the mytilid, variablesBrachidontes for each rodri- study site included in our value (Anderson,did not differ 2001). from The the discriminating ratio detected prey by for faecal each analyses.guezi followed In this by themeta-analysis crab Cyrtograpsus were angulatus selected(Table on the 1). basis of their potential to group were determined using the Mann–Whitney test (Krebs, The mytilid B. rodriguezi was the dominant prey by percentage 1989). Non-parametric multi-dimensional scaling (nMDS) on of number, but second by percentage of occurrence and Bray-Curtis similarity (Clarke, 1993) was performed to weight. The C. angulatus crab was the second most dominant (a) 150°W120°W 90°W (b) 0° 30°E (c) 150°E
60°N 60°N
30°N 30°N
120°W 90°W 60°W 0°30°E 120°E
M. americana M. martes M. foina M. zibellina M. melampus
Figure 1 The 59 localities across the Holarctic region from which data were used in the analyses (for data sources see Appendices S1 & S2). (a) The American marten (Martes americana) in North America; (b) the pine marten (M. martes) and stone marten (M. foina) in Europe; (c) the sable (M. zibellina) and Japanese marten (M. melampus) in Asia.
Journal of Biogeography 38, 137–147 139 ª 2010 Blackwell Publishing Ltd (2009) implemented the Shannon diversity index to find that diet diversity and percent fruit in diet correlated positively with exploration. Analyses of stomach contents or faecal samples are indirect methods of obtaining a species’ diet diversity. Such methods provide only a snapshot of the individual’s last meal and may be biased (Iverson et al. 2004). So in an attempt to provide a better overview of predator diets, Iverson and colleagues proposed the use of quantitative fatty acid signature analysis (QFASA), which is an advanced statistical model that uses fatty acid signatures to provide quantitative estimates of the proportions of prey species in the diets of individual predators. The method can be applied to both marine and terrestrial animals, and it is done by assessing the uniquely structured fatty acids derived from the food items (e.g. fish) eaten by the predator, which end up undegraded and stored in the blubber or adipose tissue. The pattern left behind by the accumulation of these signature fatty acids is used to provide quantitative estimates of predators’ diets based on an ecological timescale. By combining both methods, a study used QFASA for diet composition as well as H’ for diet breadth to show that differences in diet composition and breadth between adult male and female grey seals (Halichoerus grypus) reflect seasonal changes in foraging behaviour and reproductive expenditure (Beck et al. 2007). Quantitative assessment of generalism includes, but is not limited to, the indices and analyses discussed. However, the use and applicability of these measures depend on the experimental question and resource accessibility with respect to the species studied. In contrast to generalism, there are no studies that quantify opportunism by an ordinal measure (e.g. species X with an opportunism measure of 2 and species Y with a 4) or an equivalent to Shannon's or Levin's index. When opportunism is quantitatively defined, it is always as random feeding. For example, Jaksić (1989, page 430) defined an opportunistic predator as one with a ‘diet that correlates with the profile of prey abundances as weighted by their respective body sizes’, and then assessed partial correlations between prey selection, prey abundance, and prey size. Kaspari and Joern (1993) went one step further and stressed the importance of integrating both prey availability and prey selection when assessing opportunism. They then compared feeding habits of three species of insectivorous grassland birds using dietary opportunism as the
28 null model, where an opportunist consumes prey in proportion to the preys’ relative abundance. The model was tested using Jacob’s (1974) index of selectivity (S):
4: is exclusive Assumption Handling from searching. r-p All threebird species often close theireyes, shakingand mandibulatingprey after capture (Kaspari 1990, pers. r+p-2rp obs.). It seems unlikelythat birds obtain further informa- tion aboutprey distributionduring where handling.r is the proportion of food item/prey in the diet and p is its proportion in the Assumption 5: Foragers in a sample the same wherer is the of a in the diet and is environment.perceive Depending on the number of prey consumedproportion relative prey to itstype abundance, the p prey abundance.Bird diets wereestimated from gut sam- its proportionin the environment.S starts at -1 (prey ples. Eachof seven estimateswasvalue collected of S can rangeover nobetween more - 1 (preynever never consumed consumed despite despite presence availability) in andhabitat) 1 (prey and ap- than three consecutivemornings, consumedfrom more the same often habitatthan predicted proaches by availability).1 (preyconsumed The null modelfar more of opportunism thanthat predicted on and aroundArapaho Prairie. So all birdson a sample by availability).S allows us to examinehow preferences date likely encounteredthe sameassumes prey. r = p and predicts constantfor S ’sprey approaching types change 0. S was with calculated the abundance for each preyof that and Assumption 6: Handling timesitem thereforeare constant providing within a means a otherof assessingprey. changing preferences for prey types Birds time with To test Prediction1 we calculateE/T's over a size species. may adaptivelyrelativevary handlingto abundance of that and other prey. Although this study is quantitative, solving changesin prey encounterrate and gut fullness (Kaspari range of acridids,the chief arthropodprey of this as- 1990). However,grasshopper thesparrows 'just so' useshow of opportunismno signif- insemblage. a large partThese of the dataliterature,are summarized it is not usefulin in a theseries of prof- icantinter-bird variation in handlingcontexttimes of cognition,(Kaspari because1990, it usesitability the 'randomcurves choice' that describe definitionthe of the relationship concept andbetween a this study, see also Pulliam 1985). preytype's size andit's E/T (Werer 1974,Davies 1977a, uses it as a null hypothesis to optimal diet choice and its predictions of selectivity. Assumption 7: Prey types are homogenous in energy Pulliam 1985). Even if S's are distributedbimodally content.Many studies treatbroad groups Corbinof and insect Kirika taxa (2002) (centeredproposed anotheraround statistical-1 and 1definition as per the of opportunism,All or None Rule), order or as We con- diets over a of (e.g., family), singleby predicting prey types. that the survival functionssampling of waiting times beforerange prey prey capture availabilities, in brown- yield- structedprey types in a two partprocess. First, prey were ing differentcombinations of -l's and l's, should pro- separatedbased on gross similarityhoodedin kingfisher shapeand/or (Halcyontaxo- albiventris vide a) indistribution Tanzania, shouldof mean differ S's from to prey the distribution size that mirrors nomic group (e.g., acridid,coleopteran, of waiting timeslepidoptera before movinglar- tothe a new shape perch of inthe unsuccessful profitability predationcurves. bouts. They also vae). Second, these taxa were split into size categories To test Prediction2 we examinethe distributionof S's predict that perch height, search time, horizontal attack distance and handling times uniformacross taxa. The resultingprey types (e.g., acri- for each availableprey type. If the All or None Rule is dids 5-15 mm, coleopteralarvae should<5 mm)differ aredepending morelikely on the kingfisher’ssupported, foragingthese S-distributionsstrategy. The kingfishersshould bewould bimodal be and to be more in content. clusteredaround -1 and 1. homogenous energyconsidered opportunistic if they were to preying on items as soon as they are detected. As Predictions of the Classical Model: The classical To test Prediction3, we correlatediet breadth,the total model makes four predictions:predicted, the prey capture distributionnumber indicatesof prey antypes opportun sampledistic strategy,in a bird withspecies shorterdiet, with waiting times than those of unsuccessfulthe abundance waits. Furthermore,of preferred thereprey werein the no significant habitatat the time 1) Prey are rankedby theirprofitabilities (energy/hand- of the sample. The Classical Model again predicts a relationships between search time and perch height, horizontal attack distance and ling time, or E/T) andadded to the diet in rankorder; negative correlation.We also relate the S's of highly 2) Preyare always either consumed handlingwhen times.encountered This is an interestingor preferred approach,prey but (mean it is difficultS >0.5) to to assume those opportunistic with intermediate no within a are S's - see The classicalmodel ignored, partialpreferences prey choice on whateversample comes first by(-0.75 comparing 0.5, successful below). and unsuccessful predationpredicts found (e.g., the All or None Rule); a negativecorrelation. 3) Diet breadthincreases with waits. decreasing abundance of To test prediction4, we relatethe S's of preywith their preferredprey (i.e., a prey's probabilityof selection own abundance.The ClassicalModel predicts no correla- shouldbe correlatedwith the abundanceof tion. negatively higherquality prey). 4) A prey'sprobability of selection should be independ- ent of its own abundance. The Central Place Foraging Model The classical model has been tested in a varietyof sys- Oriansand Pearson(1979) modifiedthe Classical29model tems (see Stephensand Krebs 1986). Prediction3 has to describe a foragerreturning prey to a centralplace been supportedwith two species of insectivorousbirds (e.g., a bird provisioningits brood in the nest). The (Davies 1977a, b). Prediction1 has been supportedfor questionconfronted by such a forageris which prey to two species of insectivorousbirds (Davies 1977a, Zach consumeon the spot versuswhich prey to carryback to and Falls 1978). the nest (addingto the prey the energy and time cost of Testing the Classical Model. The classical model and the roundtrip from the nest). The CentralPlace model the othersbelow predictwhich prey shouldbe selected predicts that energy maximizersshould select smaller and which ignored given a distributionof prey types, prey for immediateconsumption and carry largerprey handlingtimes, and profitabilities.Since our data are in back to the nest. the form of gut samples and not direct observationsof Numerousstudies of insectivorousbreeding birds have foraging,we need an index that describeshow prefer- confirmedthe otherpredictions of the CentralPlace Fo- ences changewith the abundanceof prey.We use Jacob's ragingModel (Stephensand Krebs 1986). For example, (1974) index of selectivity: as grasshoppersparrows on ArapahoPrairie forage far- ther from the nest, they returnwith more prey (Kaspari 1991a).Tests of prey size in adultsversus nestlingsare
416 OIKOS68:3 (1993) d. The operational definition used in this thesis
For papers of category 3, opportunism is defined as readiness of an individual to respond to new and/or different resources or alternatives, such as their ability to quickly take advantage of new feeding opportunities whether they are naturally or anthropogenically driven. For instance, turtles, sea birds, fish and marine mammals are reported to feed opportunistically on patches of discarded by-catch left behind by fishing trawls (Kaiser and Spencer 1994; Ramsay et al. 1997; Tomas et al. 2001; Bozzano and Sarda 2002). Both land and marine scavengers are notoriously known to feed on carrion, an infrequent or even scarce resource (Britton and Moron 1994; DeVault et al. 2003). As we pointed out earlier, these resources have some characteristics in common; they tend to be temporally and spatially unpredictable, unlike seasonal changes in prey abundance, and the switch exhibited by an opportunistic animal is usually quick. Seen in this way, opportunism implies a tendency for an individual to modify its behaviour in response to the presence of a new and/or alternative resource. It might thus be possible to quantify how opportunistic an individual or a species (averaged over individuals) by measuring the latency to switch to a suddenly abundant, yet spatially and temporally unpredictable, food source. Compared to the random feeding model of opportunism, this operational definition by the means of behavioural switching is simple and can be done in the field under controlled conditions. For example, applying this test along side neophobia tests between two different species with different foraging strategies (generalist and specialists) can provide a better understanding of how opportunism relates to foraging strategies and neophobic tendencies. Rather than simply associating generalism with opportunism, one can place a quantitative measure through the use of behavioural switching so that comparative correlational analyses can be made. In chapter 2 of this thesis, we use a test of this type to compare opportunism in the field for two sister species of Thraupidae in Barbados. We then assess on wild-caught individuals the relationship between opportunism in the field and problem-solving in captivity. However, because chapter 2 deals with two species only and because the results of both the opportunism field test and the captive problem-solving experiment turn out to be all-or-none, we present in appendix 1.A. the data on the 6 avian species that attended the opportunism trials described in chapter 2. The differences between the 6 species are
30 more graded than those between the two species on which chapter 2 focuses and thus allow a more nuanced assessment of the value of our operational definition of opportunism. appendix 1.B. also assesses the relationship between the latency to switch measure and different measures of cognition taken from the literature and from a preceding study by Webtster and Lefebvre (2001).
Acknowledgements I am grateful to Dr. Louis Lefebvre for assisting in the development and thorough revision of several drafts of this thesis chapter. This research was funded by Natural Sciences and Engineering Research Council (NSERC Canada) graduate scholarship to LK and an NSERC Discovery Grant to LL.
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43 Tables
Table 1. ‘Opportunism’ in the literature. Listed are the top 60 most cited articles published in peer-reviewed journals through the Web of Science, placed in five assigned categories. The associated definition in context of the article is provided. (*Indicates articles placed in more than one assigned category)
44
Source Toft&1995* James&1991 Richter&2000 Bjorndal&1991 Gherardi&2006*
Lowe&et&al.&1996 Catard&et&al.&2000 Sinclair&et&al.&1994 Cromar&et&al.&1999 Wishner&et&al.&1995 Pakhomov&et&al.&1996 May&and&Norton&1996 Motta&and&Wilga&2001 Link&and&Garrison&2002 Hansen&and&Quinn&1998* Wiens&and&Rotenberry&1979
),&an&opportunistic&omnivore,&shifts&its&diet&as&it&grows&relative&to&
)&is&an&opportunistic&feeder&in&terms&of&the&marine&environment&
Trachemys&scripta&scripta
Procellaria&aequinoctialis
203) encounter&(page&255,&281) nonNselective&and&eating&prey&in&relation&to&its&abundance&or&availability&in&the&environment.&(page&560) (page&1) availability&and&abundance&of&prey.&(page&388) abundance&of&resources amphibians.&Gut&content&analyses&showed&that&P.&clarkii&feeds&on&the&diverse&items&present&in&a&given&invaded&habitat&in& proportion&to&their&availability&and&that&its&diet&can&change&with&habitats&[...].&(page&175N181)& on&the&most&abundant&resources.& Example Birds&[demonstrate]&an&opportunistic&utilization&of&relatively&abundant&prey.&[...]&eating&by&and&large&whatever&they& Myctophid&species&are&opportunistic&mesozooplankton&feeders&[...]&consuming&primarily&the&most&abundant&species&[…]& Tiger&sharks&(Galeocerdo&cuvier)&may&be&opportunistic&feeders&that&prey&heavily&on&abundant,&easy&to&capture&prey.&(page& Planktonic&detritivores&implied&opportunistic&ingestion&of&bacterial&aggregates&that&were&most&abundant&in&their& [Carabid&species]&display&opportunisitc&feeding&behaviour&and&feed&on&various&plant&and&animal&material&that&is&readily& Atlantic&salmon&feed&on&a&wide&range&of&large&crustaceans,&pelagic&fish,&and&squid&in&the&marine&environment,&supporting& Selection&by&northern&fur&seals&of&a&wide&variety&of&numerically&dominant&prey&species&throughout&their&migratory&range& [Red&swamp&crayfish]&displays&generalist&and&opportunistic&feeding&habits,&consuming¯ophytes&and&preying&on& Sharks&are&generally&asynchronous&opportunistic&feeders&on&the&most&abundant&prey&item,&which&are&primarily&other&fishes.&(page&131) WhiteMchinned&petrels&( The&yellowMbellied&slider&turtle&( Most&of&the&major&prey&species&were&eaten&in&periods&when&they&[…]&were&abundant,&indicating&opportunistic&feeding&by&cod.&(page&109)& [for&opportunistic&wasps...]&The°rees&of&host&specificity&and&constancy&were&influenced&by&changes&in&prey&abundance& The&change&in&dietary&diversity&and&overlap&of&Ctenotus&may&be&explained&by&opportunistic&foraging,&that&is,&being&relatively& The&cat&is&generally&considered&to&be&an&opportunistic&predator,&with&the&level&of&predation&being&partly&dependent&on&the& […]&species&eating&prey&in&the&same&proportionsas&occurred&in&the&leaf&litter:&i.e.,&generalists&[or&opportunists].&(page&204) exploited,&alternating&between&the&use&of&water&close&to&the&colonies&and&Antarctic&water,&where&most&of&them&would&feed& environment available.&(page&188) has&led&to&the&general&conclusion&that&they&are&nonNspecific,&opportunistic&feeders.&(page&153) and&distribution&[…]&(page&125) the&hypothesis&that&Atlantic&salmon&are&opportunistic&feeders.&[...]&Atlantic&salmon&are&opportunistic&feeders&but&there&is&no& information&available&to&compare&the&diet&of&salmon&with&the&distribution&of&available&food&organisms.&(page&104N107)
Opportunism+Category (1)+Feeding+on+resources+relative+ to+abundance+or+encounter+rates 45
Fasola'1994 Churchill'1994 Selva'et'al.'2005 Todd'et'al.'1998 Mesa'et'al.'2004 Euliss'et'al.'1991 Jaksiç'et'al.'1989 Cherel'et'al.'1996 Burger'et'al.'1999 Weckel'et'al.'2006 Menard'et'al.'2007
Andersen'et'al.'2004 Leal'and'Oliveira'2000 Hodgson'and'Kitchell'1987 Terraube'and'Arroyo'2011 Di'Fiore'and'Rodman''2001 MacCraken'and'Hansen'1987*
)'foraging'strategy'is'an'opportunistic'response'to'changes'in'resource'
)'are'selective'forager,'rather'than'nonWselective'opportunistic'foragers;'
)'feed'opportunistically,'based'on'the'relative'abundance'of'fish'and'squid,'when'
)'demonstrates'an'opportunistic'foraging'strategy;'change'their'diet'in'response'to'
Polioptila,californica Circus,pygargus
Lagothrix,lagotricha,poeppigii
Aptenodytes,patagonicus
behavioral,and,morphological,attributes.,(page,582) consuming'arthropod'prey'of'relatively'large'size (page,115) scavenger,forages.,(page,1591), availability predator,hunts.,(page,429) changes'in'availability'of'different'prey'types' [Opportunistic,diets],where,prey,should,apprear,in,the,diet,of,the,predator,in,proportion,to,the,rates,of,encounter.,(page, King'pinguins'( An,opportunistic,scavenger,would,use,all,carcasses,proportionally,to,their,abundance,in,those,patches,where,the, Attine'ants'forage'on'items'in'accordance'to'resource'availability Most,benthic,nototheniids,are,opportunistic,and,feed,on,seasonally,or,locally,abundant,zooplanktonic,prey.,(page,321) Woolly'monkeys'( [Herons]…,tend,opportunistically,to,use,similar,habitat,and,prey,types,,presumably,the,most,profitable,and,locally, Coyotes,are,considered,opportunistic,,generalist,predators,consuming,prey,in,relation,to,its,availability.,(page,278), [Waterfowl]...,were,opportunistic,foragers,,shifting,their,diets,seasonally,to,the,most,abundant,foods,given,their, Tunas'and'billfishes'consume'whatever'they'encounter'based'on'abundance ,[Opportunistic]…,Harbour,seals,are,thought,to,consume,prey,species,largely,[…],according,to,their,abundance.,(page,1236) [...],insectivorous,bats,are,primarily,opportunistic,,feeding,on,the,most,readily,available,food,items,regardless,of,prey,type., Jaguars,(Panthera,onca),[...],classified,as,opportunistic,predators,because,they,consume,prey,relative,to,its,availability., "Opportunist",is,a,predator,that,takes,all,prey,in,the,same,relative,abundances,as,present,in,those,patches,where,the, California'gnatcatchers'( Foraging'opportunistically;'consuming'prey'in'proportion'to'their'abundance. Montagu’s'harrier'( (page,25) 324) abundant.,(page,113) food'is'scarce'during'the'winter'season.
46
Toft&1995
Brown&1991 Gherardi&2006* Eeva&et&al.&2005 Kaiser&et&al.&1994 Siepel&et&al.&1993 Moens&et&al.&1997 Graeve&et&al.&1994 Rosalino&et&al.&2005 Brack&and&LaVal&2006 Klemetsen&et&al.&2003 Corbin&and&Kirika&2002 Waldenstrom&et&al.&2002 Hansen&and&Quinn&1998* Britton&and&Morton&1994 MacCraken&and&Hansen&1987* Clusella3Trullas&and&Botes&2008
)&tend&towards&an&opportunistic&feeding&mode&positioned&between&herbivory&and&
)&are&generalist,&or&opportunistic,&foragers&that&are&affected&by&patterns&of&food&availability
%(Rhincalanus%gigas
Meles%meles
resource (page%211) amphibians.%Gut%content%analyses%showed%that%P.%clarkii%feeds%on%the%diverse%items%present%in%a%given%invaded%habitat%in% items.%The%food%eaten%depends%on%availability.%(page%26) proportion%to%their%availability%and%that%its%diet%can%change%with%habitats%[...].%(page%175F181)% Gray%myotis%exhibited%some%characteristics%of%an%opportunistic%forager,%feeding%on%readily%available%prey…%(page%7) [...]%relative%importance%of%each%prey%type%in%the%diet%was%significantly%explained%by%its%local%abundance%and%habitat,% %[...]%kingFfishers%are%opportunists%essentially%taking%prey%items%immediately%upon%detection.%(page%48) Brown%trout%is%an%opportunistic%carnivore,%although%individuals%appear%to%specialise%at%least%temporarily%on%particular%food% Antarctic&copepod Opportunistic&birds&are&those&with&non3specialized&feeding&habits Atlantic%salmon%feed%on%a%wide%range%of%large%crustaceans,%pelagic%fish,%and%squid%in%the%marine%environment,%supporting% [Red%swamp%crayfish]%displays%generalist%and%opportunistic%feeding%habits,%consuming%macrophytes%and%preying%on% […]%species%eating%prey%in%the%same%proportions%as%occurred%in%the%leaf%litter:%i.e.,%generalists%[or%opportunists].%(page%204) Badgers&( Coyotes%are%considered%opportunistic,%generalist%predators%consuming%prey%in%relation%to%its%availability.%(page%278)% [...]%a%more%opportunistic%forager,%F.%hypoleuca,%is%less%vulnerable%to%a%changing%invertebrate%composition%caused%by%human% Species&are&opportunistic&and&widely&foraging&generalists,&also&referred&to&as&non3selective&consumers. Aquatic%nematodes%are%[...]%opportunistic%feeders,%which%may%change%feeding%strategies%in%response%to%available%food.% Scavengers&are&facultative&feeder&that&feed&opportunistically&on&carrion,&a&spatially&and&temporally&infrequent&food& [...]%additional%resources,%such%as%those%made%available%by%trawling,%may%favour%certain%species%that%exhibit%opportunistic% Opportunistic&herbo3fungivores&take&advantage&of&period&increase&in&fungal&growth& confirming%the%opportunistic%foraging%strategy%of%[Montagu's%harrier].%(page%2111) environmental%impacts%than%a%caterpillar%specialist,%P.%major.%(page%629) omnivory& the%hypothesis%that%Atlantic%salmon%are%opportunistic%feeders.%[...]%Atlantic%salmon%are%opportunistic%feeders%but%there%is%no% information%available%to%compare%the%diet%of%salmon%with%the%distribution%of%available%food%organisms.%(page%104F107) feeding%behaviour%[...].%(page%48)
(2)$A$generalist$feeding$strategy (3)$Quick$response$to$new$ feeding$opportunities$ 47
Arlettaz&1996 Fernando&1994 Derocher&2000 Andersen&1991 Bon&et&al.&1996 Tomas&et&al.&2001 DeJean&et&al.&1994 Vickery&et&al.&1991 Bargagli&et&al.&1998 Petranka&et&al.&1994 Lefebvre&et&al.&1997 Thompson&et&al.&1991 Fenton&and&Morris&1976
Nicolson&and&Fleming&2003
)&demonstrate&behavioural&plasticity&in&response&to&a&novel&prey&item
)&opportunistically&feed&on&fish&from&discarded&patches&of&byGcatch&material
demonstrate&opportunistic&foraging
Ursus%maritimus
Caretta%caretta
(Halichoerus%grypus)%
resources.%(page%696) lower%level,%microphagous%filterEfeeders%to%upperElevel,%macrophagous%predators%depending%on%the%availability%of%food% novel%means%to%solve%environmental%problems.%(page%550) Bats%[...]%were%opportunistic%feeders,%quick%to%locate%and%exploit%local%concentrations%of%insects,%from%which%they%took%the% Tadpoles%of%many%species%are%perhaps%better%viewed%as%opportunistic%omnivores%that%can%quickly%shift%from%functioning%as% Tilapias&take&advantage&of&an&abundance&of&phytoplankton&and&detritus&when&available The%bats%selected%alternative,%more%abundant%and/or%more%profitable%prey%at%certain%times%of%the%year,%mostly%by%switching% Loggerhead&turtles&( [...]%frequency%of%opportunistic%innovations%is%[…]%a%useful%indicator%of%its%behavioural%plasticity%and%its%tendency%to%use% opportunistic&polar&bears&( [Ponerine%ants]...%is%opportunistic,%with%great%flexibility%of%nesting,%foraging,%and%diet%according%to%the%nature%of%the% Opportunist%uses%a%search%mode%that%permits%the%simultaneous%search%for%both%producing%and%scrounging%opportunities% Opportunists,%which%are%unspecialized%and%poorly%competitive%species%that%are%often%abundant%in%disturbed%habitats.%(page% Grey&seals& When%food%is%available%ad%libitum,%male%would%be%as%opportunist%as%females%in%their%feeding%choices.%(page%135) Opportunistic&benthic&invertebrates&(ex.&predators&and&scavengers) Opportunistic&or&occasional&nectarGfeeders,&as&opposed&to&specialist&or&nectarivorous&birds 578) from%their%traditional%feeding%habitats%to%secondary%(usually%temporary)%foraging%grounds.%(page%1) largest%individuals.%(page%529) environmental%constraints.%(page%191) and%exploit%them%as%detected.%(page%849)
undefined$terms (4)$Flexible$feeding$strategy (5)$Other$definitions$and$ 48
Connecting Statement
In Chapter 1, I reviewed the different definitions of opportunism in the biological literature. As an outcome of this critical review, I refined the definition of opportunism and proposed a means of its operationalization. Once isolated from generalism and innovation, opportunistic foraging might serve as an indicator of ecological flexibility. I operationalize opportunism, based on the concept of behavioural switching, as the latency to switch to an abundant, yet spatially and temporally unpredictable, food source. As a quantifiable trait, opportunistic foraging can thus be integrated into small-scale comparative analyses.
In Chapter 2, I implement this operationalized definition of opportunism alongside neophobia and problem-solving through a comparative study of sister species of Thraupidae in Barbados.
49
CHAPTER 2
Opportunism, Neophobia and Problem-solving in Sister Taxa from the Family Thraupidae, the Barbados Bullfinch Loxigilla barbadensis and the Black-faced Grassquit Tiaris bicolor
50 Abstract
Comparative research has identified foraging ecology as an important determinant of cognitive evolution. Although opportunistic feeding is evident across many species, no one has tested its link to cognition. We know that some species adapt to novelty or changing environments by discovering a new resource or solving problems to gain access to it, for instance by removing an obstacle. Given this, our purpose is to determine if an opportunistic species will perform better at problem-solving, and have lower neophobic tendencies, than a less opportunistic species. Our study compares two sister species of birds with different foraging strategies: the Barbados bullfinch (Loxigilla barbadensis), an opportunistic forager, and the black-faced grassquit (Tiaris bicolor), a conservative forager. In the field, we used focal observations to assess their foraging and territorial behaviors. We also carried out opportunism and neophobia experiments to measure their opportunistic tendencies and fear of novelty, respectively. In captivity, wild-caught individuals were run through a set of behavioural and cognitive tests, which included a neophobia test and a problem-solving obstacle removal task. Results show that although both species share overlapping foraging modes, territorial habits and neophobic tendencies, the Barbados bullfinch is much more opportunistic, bolder and better at problem-solving than the black-faced grassquit.
51 Introduction
Animals differ in their cognitive abilities and comparative research has identified ecology as an important determinant of cognitive evolution. In recent studies, Roth and colleagues have shown that chickadees from zones that differ in harshness of seasonal differences, i.e. Alaska and Kansas, differ in spatial memory, neophobia and problem-solving, as well as in brain areas associated with these abilities, the hippocampus, the amygdala and the telencephalon, respectively (Pravosudov and Clayton 2002; Roth et al. 2010; 2012a; 2012b). The differences appear to be hard-wired, as the individuals tested were F1 descendants of Alaskan and Kansas parents and had been raised in the same environment at the University of Nevada (Roth et al. 2010). Other cognitive measures have been associated with the distribution of resources in space and time. Food predictability and density affects the way animals will aggregate and defend resources, as well as the degree to which they specialize or eat a broad diet (Overington et al. 2008; Goldberg et al. 2001). As a consequence, dietary and habitat generalism have been found to correlate with avian neophobia (Greenberg 1983; 1984; 1989; 1990; but see Greenberg 1992), exploration (Tebbich et al. 2009) and innovation rate (Overington et al. 2011), while group living is associated with primate brain size (Dunbar 1998). Opportunism is one of the ecological measures mentioned in the literature on cognition. It is in fact part of the definition of one key measure of cognition, innovation rate. Lefebvre and colleagues (1997) repeatedly use the term 'opportunistic feeding' in introducing the concept of innovation rate, the frequency, corrected for confounding variables, with which different taxa use novel solutions to a feeding problem (Wyles et al. 1983; Kummer and Goodall 1985; Reader and Laland 2003). Opportunism is often used with 'generalism', but the two terms describe different aspects of feeding. An opportunist is an animal that is able to rapidly use an alternative food type if it presents itself, a strategy that can be used whether the animal is a generalist or a specialist. For example, snail kites are specialized in preying on the mollusc family Pomacea by swooping down on them with their talons, but are known to opportunistically feed on other foods (Beissinger 1990). While innovation rate deals with opportunistic behaviours in the field, problem- solving, or the ability to solve novel problems presented experimentally, is assumed to be
52 equivalent to innovation when comparing across species (Webster and Lefebvre 2001). Problem-solving has recently been used in several studies of avian cognition, notably with keas, New Caledonian crows (Auersperg et al. 2011), ravens (Schloegl et al. 2009), and caracaras (Biondi et al. 2010). In this paper, we examine the relationship between opportunism and problem-solving in a two-species comparative study. Ideally, candidate species for comparative studies should show the largest possible difference in the variable being tested, while showing as little differences as possible on other relevant traits. The species we compare here are sister species of the family Thraupidae that inhabit the island of Barbados: the Barbados bullfinch (Loxigilla barbadensis) and the black-faced grassquit (Tiaris bicolor). Even though their environment and ecologies overlap extensively, they have responded with completely different foraging strategies (Buckley and Buckley 2004; Buckley et al. 2009): the Barbados bullfinch is tame and opportunistic while the black-faced grassquit (Tiaris bicolor) is a more conservative forager and avoids humans. The island of Barbados is the most easterly Caribbean island of the Lesser Antillean archipelago. The Barbados bullfinch, endemic to the island, is closely related to the more widespread Lesser-Antillean bullfinch (Loxigilla noctis; Buckley et al. 2009). The black-faced grassquit is a Caribbean endemic from a genus that is the closest current descendant of the common ancestor with the Galapagos finch clade (Sato et al. 2001; Burns et al. 2003; Buckley et al. 2009). Black-faced grassquits (from here on referred to as grassquits) are usually observed in grassy areas and their diet is predominantly grass seeds (Evans 1990). The Barbados bullfinches (from here on referred to as bullfinches) are more generalist feeders with a wider habitat range, which includes open-country and woodlands (Buckley and Buckley 2004). They have been observed feeding on seeds, fruits, and artificial nectar, along side other passerine and columbid species (Carlier and Lefebvre 1996, Dolman et al. 1996; Webster and Lefebvre 2000). Given that they are ground feeders, they are often seen feeding near grassquits. Anecdotal and quantitative evidence has demonstrated that bullfinches are innovative and tame. A specific subpopulation of bullfinches in Barbados has been observed opening sugar packets, regarded as a novel locale-specific feeding behaviour (Reader et al. 2002; Ducatez et al. 2013). In a comparative study, the bullfinch has
53 demonstrated its opportunistic and neophilic nature when compared to a more specialized forager, the bananaquit (Webster and Lefebvre 2000). Furthermore, in a five species comparison of Barbados Passeriformes and Columbiformes, bullfinches were the least neophobic as well as good problem-solvers in the field, ranking second on this measure behind Carib grackles (Quiscalus lugubris), members of the most innovative Passeriforme genus in North America after Corvus (Webster and Lefebvre 2001). Previous work by Lefebvre and his team suggests that both species are similarly territorial (Lefebvre, pers. comm.). Yet, despite these experimental and anecdotal reports, there are no quantitative field data on the foraging ecologies and limited information on the cognitive propensities of these two species in Barbados. The purpose of this study is to determine if opportunistic foragers will have lower neophobic tendencies and perform better at problem-solving compared to less opportunistic foragers. Through this two-species comparison, we assess opportunism and neophobia in the field and complement it with neophobia and cognitive (problem- solving) experiments in captivity. We predict that the bullfinch will be more opportunistic and less neophobic than grassquits when foraging, and will outperform grassquits in problem-solving tasks in captivity. Via field observations, we further show that the differences are not confounded by variables such as social foraging.
Field Study
Methods
Field observations and all but one of the field experiments (neophobia, see below) were conducted between March and June 2012 in the parishes of St. James and St. Peter, Barbados. The areas sampled were within 500 m of the Caribbean coast and spanned 10.7 km between Speightstown (St. Peter) and Mahogany Bay (St. James). The coastal stretch included public beaches and parks, hotels and restaurant properties, as well as residential areas and vacant lots. Vegetation in these areas includes tropical dry forests, sparse hardwood forest, gullies, grasslands/pastures and cultivated croplands (mostly sugarcane), as well as a few small mangroves. The bullfinch and grassquit are abundant
54 throughout the island (Buckley et al. 2009), and can be found together by the coast and inland. Two types of data were collected: (a) latencies on field tests of provisioned food, as well as a field test of neophobia, and (b) focal observations of foraging and social interactions with hetero- and conspecifics. All statistical analyses were completed with the aid of SPSS (version 16.0 and 17.0) and graphics provided with the aid of Microsoft office: MAC 2011.
Food provisioning and neophobia experiments
Non-systematic observations over the past 25 years suggest that the grassquit does not approach patches of seeds offered by humans, but that the bullfinch does (Lefebvre, pers. observ.). To confirm and quantify these observations, two types of provisioning experiments took place, one that included familiarization to food before experimentation (6 trials) and one without familiarization (6 trials). Trials were carried out between April- June 2012 between 06h00 and 12h00 at locations that were spaced 100 – 600 m apart in and around Holetown, St. James. Sites were chosen after ad libitum observations had confirmed that both species routinely foraged there. On a given day, a trial was only started in this phase of the study if individuals of the two species were seen within 10 m of a potential site. Food provisioning without familiarization involved placing a plate, 40 cm in diameter, filled with 500 g of finch seed mix and 500 g pieces of bread and recording the arrival and feeding latencies and identities of the species that came to feed. Trials lasted 60 min, and a latency of 3601 seconds was assigned to species that never arrived to the feeding station. Familiarization involved presenting the same food plate for 7 days without recording. In the 8th day, a set of trials was conducted and recordings took place. Each trial day included seven bouts that lasted 20 min; an interruption by the experimenter followed each bout for the purpose of adding more food. A latency of 8401 seconds was assigned to species that never arrived at the feeding station. Latencies of the first individual of each species were log transformed for the analyses. Grackles, cowbirds, zenaida doves and common ground also fed alongside our study species at both non-
55 familiarized and familiarized provisioned sites, appendix 1.A. (Figures 1-4) provides the latencies to arrive and feed at the sites for all six species. The neophobia experiment was conducted in the field in July 2011. The trials were run in the mornings (07h00 to 10h00) and afternoons (13h00 to 16h00). Sampled locations were separated by 100 m to 600 m (with the exception of Farley Hill National Park, St. Peter, at ~ 9 km from Bellairs Research Institute), to avoid repeated testing of the same individuals. Locations included those within and around the Bellairs Research Institute, Folkestone Park and St. James Church in the parish of St. James, as well as the Sunset Crest housing area in St. James. We provided 20 g of finch seed mix in a 15 cm plastic dish at sites where individuals of the two species were frequently seen during walking transects. The observer stood at a distance of about 10 to 15 m from the food, and within a 20-minute limit, the latency to approach the dish was recorded. The subject was left to feed for 10 seconds before the experimenter slowly approached the feeding station. When the bird fled the food source, a marker was left as an indicator for the initial flight distance. The neophobia test that followed compared the latency to feed in trials randomly featuring either a novel object or no novel object placed close to the food (Greenberg 1984). In 'no object' trials, 10 g of finch seed mix was added and the food dish rotated, while 'novel object' trials, included the control procedures plus a novel object (two tennis balls attached to one-another with straws protruding from their tops) placed 6 cm from the food dish. After the observer moved away, the latency of the bird's return to the dish was noted. A second interruption of feeding followed, with a marker again indicating the bird's flight distance and the condition that was not offered on the preceding trial was now presented. The focal bird remained in sight of the observer at all times throughout the experiment. Upon loosing track of the bird visually or through visual aid, the experimental trials were canceled and the site was abandoned. The latency to initially arrive at the food patch measures opportunism as well probability of the bird detecting the food. The latency to return to a food only trial after interruption of initial feeding by the experimenter measures shyness, which is influenced by fear of the interrupting human. Neophobia per se is defined as the time between the latency to return with the novel object minus the latency to return with food only. It is thus specific to the novel object and is controlled for opportunism and shyness. All trials
56 were recorded with a digital video camera, Panasonic DMC-G3 and a Cannon HD HF R 2000. Field observations
Focal sampling of foraging and social behaviours in the two species took place during March-June 2012. Focal observation sessions were divided equally between mornings (07h00 to 10h00) and afternoons (15h00 to 18h00). To avoid repeated observations on the same individuals, 100 m to 600 m separated sites where individuals were observed. Observations were based on continuous recording of foraging and social behaviours. Each focal subject’s behaviour was noted by the same observer from an average distance of 15 m with the aid of a check sheet during periods lasting a maximum of 10 min. Length and number of foraging bouts were also measured with a stopwatch during the sampling period. A total of 7 hrs (3.5 hrs morning and 3.5 hrs afternoon) of recordings were made for each species on a total of 170 focal individuals (91 bullfinches and 79 grassquits). Observation periods were further divided by sex for the sexually dimorphic grassquits, but not for the monomorphic bullfinches. Behavioural categories for foraging included the substrate upon which the focal individual foraged (i.e. on the ground or in the trees (arboreal)), or the specific foraging site, such as an anthropogenic or provisioned site (i.e. cars, tables, abandoned food containers, and restaurant or residential terraces). The type of food eaten (i.e. grass seed, fruit, nectar, or anthropogenic or provisioned foods like bread, rice or sugar) was also noted. When recording time spent foraging, the foraging bouts where defined as periods of continuous feeding or searching for food not interrupted by more than 5 sec of other activities (e.g. locomotion, vocalizing). Behavioural categories for social interactions included the number of heterospecifics or conspecifics foraging non-aggressively within 5 m of the focal individual, their estimated distance from the focal individual, as well as their sex in the case of the grassquits. Aggressive interactions included displays (a hunched posture with semi- or fully-spread wings, accompanied by a series of shrill vocalizations); encounters (mutual displays by two birds facing each other); attacks (a sudden, fast and shallow flight by focal individual directed at the targeted bird); and chases (following an aggressive attack, the focal bird chases the target individual by flying after it, usually accompanied by a loud short call).
57 Due to the sparse data on aggressive interactions, we summed all 4 aggression categories (intraspecific and interspecific chases, aggression, displays and encounters) into one value per focal individual. A non-parametric Mann-Whitney test was used to assess between species differences. A 2x2 Pearson’s chi-squared test compared species differences in social interactions. We tested for differences between trends typical of territoriality (whether the focal bird was alone or paired with a conspecific) versus trends for gregariousness (whether the focal bird was within 5 m of more than one with conspecific, whether or not heterospecifics were also within the 5 m grouping criterion). For this analysis, we used the social state at the start of each focal session to avoid biasing the results with repeated data from the same focal session. A 2x2 Pearson’s chi- squared test also compared species differences in the number of focal sessions spent foraging on the different substrates.
Results
Response to food provisioning and novel objects in the field
Bullfinches and grassquits showed consistent, all or none differences in the three field experiments on provisioning and neophobia. The grassquits never came to either the non- familiarized and familiarized provisioning sites (Figure 1A and 1B, respectively), nor did they come to the feeding sites used for the neophobia experiment (Figure 2), despite their visible presence on the ground in the vicinity of the sampled sites in St. James and St. Peter. Therefore, no statistical comparison between species is possible given the lack of variation due to the absence of grassquits. Bullfinches arrived and fed alongside heterospecifics (grackles, cowbirds, zenaida doves, and ground doves) at all non-familiarized sites and at 5 out 6 of the familiarized sites. Their mean arrival latencies were 1,482.5 sec ± 593.63 (SEM) and 2,559.8 sec± 1,408.7, respectively. As for the field neophobia experiment, the bullfinches’ mean latency to arrive during control trials was 48.8 sec ± 12.09 (SEM; N = 8; Figure 2), significantly less that the mean latency to arrive in the presence of a novel object (382.6 sec ± 130.98 (SEM; Paired sample t-test: t(7) = -2.919, P = 0.022; latencies log- transformed for normalization).
58 Field Observations on social foraging
During the focal observations, both species showed the type of social foraging typical of territoriality: feeding most often alone or in pairs and using occasional chases, threat displays and chases against conspecifics. The rate of territorial acts averaged 0.101/min for the bullfinch and 0.107/min for the grassquit. There was no significant difference in the frequency of aggressive behaviours between species (Mann-Whitney test; U(170) = 3526.5, Z = -0.312 , P = 0.755). There was no significant difference between species in their foraging associations (Chi-square test; X2 = 0.214, P = 0.644, d.f.= 1). The number of focal scans where grassquits and bullfinches were either alone or in pairs (with or without heterospecifics) was similar, respectively 68 (86%) in grassquits and 76 (84%) in bullfinches. Focal scans where either of the two species were in groups of 3 or more conspecifics within 5 m were also similar, 11 (14%) in grassquits and 15 (16%) in bullfinches. Bullfinches foraged on a wider diversity of substrates, while grassquits were more often ground feeders (Figure 3). Incidences where grassquits were observed foraging on the ground or on trees and other substrates differed significantly from bullfinches (Chi- square test: X2 = 11.275, P = 0.001, d.f.= 1). Sixty-two focal grassquits were observed feeding on the ground, compared to 39 focal bullfinches. However, the bullfinch was seen more often feeding in the trees or on other substrates, with a total of 19 focal incidences, compared to 6 incidences observed with the grassquit (Figure 3). Of the total 170 focal individuals sampled for the two species, foraging was observed in 129 of these focal observations, 61 bullfinches and 68 grassquits. Three focal bullfinches were removed from analysis because they fed from two or more substrates during an observation.
Experiments in captivity
Subjects and Maintenance
For the captive study, 30 bullfinches and 15 grassquits were caught with mist nets over an area 0.04 km2 in St. James that extended from the Bellairs Research Institute to St. James cemetery, which includes farmland (0.02 km2). Previous work on bullfinches and other
59 Barbados birds used walk-in traps, but grassquits never entered these over the 25 years of work on the island (Lefebvre, pers. comm.). The use of mist nets was thus required for the two species, and it ensured the random sampling of wild target species, as the walk-in trap could bias capture towards bolder (in this case, L. barbadensis) or hungrier individuals. We used 4-shelved 15 x 15 mm nylon-mesh nets assigned for small ‘A’ passerines. Nets ranged from 2.5 - 3.5 m in height and 9 – 12 m in length, and were supported by removable poles that were temporarily secured into the ground. Mist netting was done between 06h00 – 18h00. Birds caught were extracted and placed in special cotton bags (W: 25 cm, L: 30 cm). Within 30 min after capture, they were transported to the aviary at Bellairs Research Institute for processing and housing. Each individual was banded using alphanumeric and color-coded leg rings (d: 2.5 mm, h: 7 mm; d: 2.5 mm, h: 4 mm, respectively; Interrex, Poland). Birds were placed in separate wood-framed wire mesh cages (L: 81 cm x H: 92 cm x W: 73.5 cm) visually but not acoustically isolated from each other in an indoor aviary. Each cage had three wooden perches, food (seed mix, rice and assortment of fruits) and water ad libitum, and easily removable bedding. For each experimental cycle, a maximum of 8 wild-caught individuals from either species were kept in captivity and a 2-day habituation period (excluding day of capture) preceded the experimental phase. Test subjects remained in captivity until the full battery of tests was completed, which required between 6 and 15 days; at the end of this period, birds were released at their site of capture. All experiments were conducted according to Animal Use Protocol # 2012-7140 approved by the McGill University Animal Care Committee and permit # 8434/56/1 from the Natural Heritage Department of the Barbados Ministry of Environment, Water Resources Management and Drainage.
Test Procedures
Starting on the third day after capture, neophobia and problem-solving tasks (obstacle removal) were given to each subject. Tests occurred between 06h30 and 13h00 for grassquits and 09h00 and 15h00 for bullfinches, following a 12h and 14.5h overnight food deprivation, respectively. Each subject’s trials were separated by the time required
60 for the birds in the cohort (maximum 4 birds per experimenter) to complete their assigned trials, approximately 5 – 15 min. All food rewards during trials were mixed finch seed. Each bird was allowed to feed for 10 seconds to ensure its motivation, after which the food was removed. At all times the experimenter was present and data was recorded in real time. Experimenters stood in a hide 3 m from the front of the cages. All trials were video-recorded using a Panasonic DMC-G3 HD and Cannon HD Vixia HF R 2000.
Neophobia in captivity
After overnight food deprivation, a control trial provided the subjects with their usual food and the latency to feed from the dish was recorded. The controls used in the neophobia field trials (initial presentation of food, interruption by the experimenter, return of the animal to either food only or food next to novel object) were not required in cages, as the animal cannot help but detect the food. In the second trial, an experimenter placed a novel object (a yellow tent peg and a black electric tape ring glued to an inverted petri dish) beside the food dish and recorded the latency for the bird to land, approach the dish and feed. Another control trial with no novel object followed and the latency to feed was also recorded. Each trial lasted 20 min and a maximum score of 1201 sec was given for birds who never fed during the neophobia trials.
Problem-solving: Obstacle removal task
Following the neophobia test, each subject was presented with a novel foraging apparatus where it had to remove an obstacle to obtain a food reward. The apparatus was a transparent cylinder (H 3.3 cm x W 3 cm) with a removable lid (Figure 4). All subjects were first primed with one trial in which the lid was removed from the cylinder and seed could be eaten directly. Latency to feed within a maximum period of 5 min was recorded. Following successful feeding on the open apparatus, the testing phase followed. The apparatus was presented with a closed, loose-fitting lid and the time it took for the bird to land, approach, contact, open and feed from the apparatus was recorded, along with the total time spent pecking at the apparatus. A maximum of 15 5 min trials were presented to each subject.
61 If a subject completed 15 trials without success, it was led through a systematic shaping procedure (Boogert et al. 2006). Here the subject was presented with progressively more difficult levels of the task: level 0, where the cylinder was open and the lid was placed on the side (Figure 5A); level 1, half of the opening of the cylinder was covered by the lid placed bottom-up (Figure 5B); level 2, three-quarters of the opening was covered, lid bottom-up (Figure 5C); level 3, the opening was fully covered, lid bottom-up (Figure 5D); level 4, opening fully covered, lid bottom-down, as in problem- solving trials. Two consecutive successes at each level led to the presentation of the next level. Upon first failure of the harder level, the easier level was re-presented. As a measure of individual learning performance, the trial number, difficulty level and latency to feed were recorded. Subjects that did not partake in the task were given a ‘non- participant’ (NP) and the trial was not regarded as a failure or success. Each trial lasted 5 min and totaled a maximum of 60 participating trials distributed over the course of 1 to 3 days. A non-parametric Mann-Whitney test was used to assess between species differences. All statistical analyses were completed with the aid of SPSS (version 16.0 and 17.0).
Results
Neophobia
Neophobia tests yielded measures of shyness (mean log latency to feed following human disturbance in food only trials) as well as neophobia per se (log latency to feed in the presence of a novel object minus latency to feed during food only trials). The mean shyness of bullfinches was significantly lower than that of the grassquits (NBF = 30, NGQ = 15; Mann-Whitney U = 48.00, P < 0.001; Figure 6). However, no significant difference in neophobia between species is evident (U = 205.0, P = 0.6387) (Figure 6).
Problem-solving: Obstacle removal task
Of the 30 bullfinches tested, 24 completed the obstacle removal task in an average of 5 trials (Figure 7). However, none of the 15 grassquits tested solved the task. All
62 unsuccessful grassquits and 3 out of the 6 unsuccessful bullfinches underwent shaping trials. All bullfinches and 5 grassquits reached level 4. Lower levels, 2 and 3, were completed by 4 and 6 grassquits respectively (Figure 8).
Discussion
Taken together, the results of our field and captive experiments comparing sister species suggest a strong link between opportunism, neophobia and problem-solving. The difference between the species was all-or-none on three of the five tests: grassquits did not come to either the food provisioning or noephobia experiments in the field (Figures 1 and 2), even though they were visibly close by, and did not succeed in the problem- solving experiment in captivity (Figure 7). Only the neophobia test in captivity and the shaping post-test showed that grassquits were capable of participating in our experiments, but with a lower level of performance compared to bullfinches (Figure 6). Coming from such closely related species, the differences are notable, but also larger than those usually reported in the comparative literature. Comparative studies usually show graded rather than all-or-none differences. For example, Roth and colleagues (2010) found differences in neophobia and problem- solving between chickadee populations belonging to environments with differing levels of seasonal harshness. The magnitude of the differences in task-completion by either chickadee groups ranged between 600 to 1200 sec, performing well below the trial limits (3600 sec) in their experiment. Our results, on the other hand, demonstrate that one of our two experimental species, the grassquits, failed to visit any field experiment (max 3600 and 8400 sec; Figures 1A and B, respectively) and to complete the problem-solving task (max 15 trials; Figure 7) in captivity. This raises the possibility that our experiments were inadequate to address the cognitive and ecological abilities of this species. This is a recurrent problem in comparative work, where observed differences between species are sometimes seen as artifacts of perceptual or motivational confounding variables (e.g. Macphail 1982 for arguments of this type) or potential type 2 errors resulting from inappropriately designed tasks (e.g. Shettleworth and colleagues (Shettleworth and Krebs 1986; Krebs et al. 1990) arguments for the window-shopping test for spatial memory in non-caching species). In our case, four results argue against the
63 possibility of a type 2 error due to inadequate procedures. First, both grassquits and bullfinches readily ate the seed presented in the priming pre-trial that preceded the problem-solving task with the closed lid; grassquits also readily ate the seed during ad libitum feeding outside experimental runs. Secondly, all grassquits reached level 2 of the shaping task, 11 out of 15 level 3, and 5 out of 15 level 4 (Figure 8). This suggests that all grassquits were motivated to feed from a cylinder whose opening was partially covered. It also suggests that removing the lid when it was in the closed, bottom down position was not beyond the motor or motivational abilities of the grassquits. Although we can exclude the possibility that grassquits were morphologically unable to do the problem- solving task, this does not mean that the size and shape of the bullfinches' beak did not favor its better performance. Morphological structures are advantageous when exploiting stable and predictable yet hard-to-reach resources (Ellis et al. 1976; Sherry 1990), but they also may constrain behavioural flexibility and diversity (Carrascal et al. 1995; Robinson and Wilson 1998). It may be that grassquits have more limited beak strength and maneuverability compared to bullfinches, rendering them less likely to remove obstacles in order to reach a food sources. Bullfinches on the other hand, are larger, have more robust beaks and are considered to have a more generalist foraging strategy, which could in consequence select for beaks with a wider set of possibilities when extracting food. However, while beak limitations in maneuverability might have affected the differences in motor-related problem-solving between our two species, it provides weak evidence when explaining the species’ differences in opportunism, as species with beaks that are very different from that of Loxigilla (i.e. Q. lugubris, Z. aurita and C. passerina) readily joined in our field experiments. Third, grassquits showed during the captive neophobia experiment the same differences with bullfinches that they showed in the field, except that in this case the differences were not all-or-none (compare Figures 2 and 6). In food only trials, the grassquit latency to feed was approximately five times higher than that of bullfinches (Figure 6). Adding a novel object next to the food added an extra 200 sec to the latency of both species, leading to a significant difference in shyness, but not in neophobia per se. Fourth, a parallel experiment on discrimination learning in bullfinches and grassquits (Audet, Kayello and Lefebvre, in prep.) shows that in some cognitive tasks conducted in
64 captivity, grassquits can actually perform better than bullfinches. In this task, subjects had to discriminate between seeds offered against either a yellow or a green background, one of which signaled that the seed could not be picked up because they were glued to the bottom of their dish. In this task, grassquits performed at the same level as bullfinches in terms of errors and were actually better than the bullfinches when the colors used during the discrimination phase were reversed. As in all other experiments, bullfinches responded more quickly than did grassquits in both the discrimination and reversal phases, but made more errors overall. What these results and those from the priming pre- trial and stages 2 and 3 of the shaping experiment mean is that grassquits are shier and slower than bullfinches in all tasks, but they respond well when there is no obstacle to remove to gain access to food. Anecdotal evidence suggests that grassquits are mainly seedeaters and bullfinches are more generalist foragers, feeding on grass seeds, fruits, nectar and other anthropogenic items (Buckley et al. 2009; Evans 1990). The results from our focal sampling reflect this difference in foraging ecology and show there are indeed species differences in time spent foraging on the ground, trees or different substrates (Figure 3). Nevertheless, the two species show a strong overlap in their foraging habits, often feeding together in grassy fields (Buckley et al. 2009; Buckley & Buckley 2004). Furthermore, grassquits were not limited to grass seeds during our focal observations. They also ate fruits, nectar, and insects, even hawking slow flying insects after a heavy rainstorm (Kayello, personal obsv.). Differences in habitat and diet breadth between our two species thus do not appear to be extreme enough to account for the all-or-none differences observed in shyness, opportunism and problem-solving. Even if dietary differences were larger, the evidence linking food generalism with cognition is weak. Greenberg (1983; 1984; 1989; 1990) found lower neophobia in the more generalist versus more specialized species in two sister taxon comparisons, but Overington et al. (2011) found in a comparative analysis of 193 species that habitat, but not diet breadth, correlated with innovation rate. In primates, Reader et al. (2011) found that diet breadth, although correlated with some measures of brain size, did not correlated with the general intelligence component where five measures of cognition (innovation, tool use, social learning, extractive foraging and tactical deception) all loaded.
65 Group living is thought to favor enhanced cognitive abilities because information about group members should normally require a 'larger neural computer' (Dunbar 1998), because resource unpredictability favors both group-feeding and opportunistic generalism (Goldberg et al. 2001; Overington et al. 2008) and because the scramble competition used by group-feeders should fuel a mental arms race instead of the physical race fuelled by aggressive territorial competition (Lefebvre and Palameta 1988). If the bullfinch were more of a group feeder than the grassquit, this might be one the factors behind its opportunism and problem-solving, but our field observations suggest that this is not case. Intraspecific aggression rates and instances where focal individuals were observed alone or paired with a conspecific were not significantly different between the two species. Focal observations where three or more conspecifics were close together, a state indicative of sociality, occurred in both species in 14 and 16% of the cases. Social foraging thus offers no evidence that might otherwise account for the extreme difference in opportunism and problem-solving performances. From an evolutionary standpoint, the grassquit and bullfinch might be showing traits that preceded their colonization of Barbados. Unlike its neighboring volcanic islands of the main Lesser Antillean arc, Barbados is a geologically young coral island (600,000 – 700,000 yrs old) (Buckley et al. 2009). Barbados also lacks the widespread tropical rainforest found on other Caribbean islands, a feature that has become more evident with the influence of urbanization (Buckley et al. 2009). The island is now home to a large number of agricultural fields, patches of woodlands, and a handful of mangrove wetlands. While the Barbados bullfinch (Loxigilla barbadensis) is endemic to Barbados, its recent ancestor, the Loxigilla noctis, along with black-faced grassquits (Tiaris bicolor) are also residents of neighboring islands. The occurrence of noctis in Barbados is extremely rare (one observation in Holetown, St-James; F. Cézilly, pers. comm.). Based on molecular analysis, both grassquits and bullfinches residing in Barbados most likely came from St. Lucia (Lovette et al. 1999). Buckley and Buckley (2004) stress that, in addition to being sexually monochromatic, the Barbados bullfinch evolved significant changes to its diet and foraging behaviour compared with its ancestor in St. Lucia. Despite this, there is evidence of similar, independent, feeding innovations (opening of
66 sugar packets) by L. noctis in St-Lucia and L. barbadensis on the south and west coasts of Barbados (Ducatez et al. 2013). This begs the question of how similar the Barbados bullfinches and grassquits are to those on St. Lucia. The 'flexible stem hypothesis', proposed by Tebbich et al. (2010) in an attempt to connect individual adaptability to species richness in Galapagos finches, would predict that flexibility in St. Lucian L. noctis might preadapt L. barbadensis to be opportunistic and innovative in Barbados. Interestingly, our study species, in particular Tiaris, are close relatives to the Galapagos finches (Burns et al. 2002). In their study, Tebbich et al. found that finch behavioural flexibility is primitive, serving as a predominant ancestral feature that becomes phenotypically present or absent depending on the adaptive response of the species to the changing environment. It is therefore interesting to address the drastic difference in cognitive flexibility between grassquits and bullfinches from the perspective of them sharing a common ‘primitive’ stem of flexibility. In this view, the conservative foraging strategy of T. bicolor would be a derived trait, enhanced perhaps in Barbados as a result of competition from Loxigilla. Initially, predictions for this study involved opportunism and cognition, with neophobia seen as a confounding variable that needed to be controlled. Given that fear of the experimenter or the apparatus can affect latency to solve a task in captivity, the usual approach is to assess these variables and remove them from cognitive measures (see Bouchard et al. 2007 for an example). In our study, however, shyness, not neophobia per se seemed to be a major factor for grassquits: they were slower than bullfinches in all the tests conducted in captivity and never came to the field tests. This suggests that non- cognitive factors might be important in the difference between the two species studied here. Shyness is one the best studied traits in the literature on behavioural syndromes (Sih et al. 2004). Although this literature focuses on individual differences, it is also relevant to interspecific comparisons (Réale et al. 2007). Sih and Del Giudice (2012) suggest that the shy-bold continuum may co-vary with similar continua of cognitive styles. One example they provide is a speed-accuracy continuum, where bold animals respond quickly to problems, but suffer an accuracy trade-off as a result of their speed. This idea is consistent with several features of our grassquit-bullfinch comparison. Bullfinches were faster and bolder than grassquits in all test situations, whether in the
67 field or in captivity. In the parallel study to this one (Audet, Kayello and Lefebvre, in prep), they were also faster to respond in the color discrimination and reversal experiments, but made more errors than did grassquits in the reversal phase. This is exactly the kind of result that would be predicted by Sih and Del Giudice (2012). If a key behavioural difference between grassquits and bullfinches lies in boldness, this may have important consequences for neural correlates of opportunism and problem-solving. For the moment, most of the literature in neuroecology deals with the size and neuron numbers of brain areas thought to be involved in different cognitive processes. Roth and colleagues (2010; 2012a; 2012b) have found differences between descendants of Alaska and Kansas chickadees in the hippocampus, whole telencephalon and arcopallium, areas respectively involved in spatial memory, problem-solving and neophobia. An obvious next step in our study would be to examine the telencephalon and arcopallium of L. barbadensis and T. bicolor. Correlational studies suggest that residual size of the largest areas of the avian telencephalon, mesopallium and nidopallium are associated with two key components of cognition, innovation (Timmermans et al. 2000) and tool use rate (Lefebvre et al. 2002). The nidopallium is the avian equivalent of the mammalian prefrontal cortex (Guntürkun 2012) and the mesopallium is enlarged in the New Caledonian crow (Melhorn et al. 2010), the species that shows the most sophisticated forms of intelligence in the whole class Aves. Neurotransmitter and receptor activity (in particular dopamine, implicated in Perez de la Mora et al. 2010) should also be measured in the mesopallium and nidopallium, as well as in the areas most likely to reflect species differences in shyness, the hypothalamus, amygdala, arcopallium and lateral striatum (Roth et al. 2012b; Perez de la Mora et al. 2012).
Acknowledgements
I would like to thank Dr. Louis Lefebvre for revising several versions of this manuscript. I am grateful to the members of the Lefebvre lab, Jean-Nicolas Audet and Simon Ducatez for their contributions in the field and the laboratory, as well as their aid in data collection and analysis. I also thank Frank Cézilly, Blandine Doligez, Laure Cauchard, and Melanie Couture for their support in field captures, and the staff of the Bellairs Research Institute for their help throughout this study. This research was funded by Natural Sciences and
68 Engineering Research Council (NSERC Canada) graduate scholarship to LK and an NSERC Discovery Grant to LL.
References
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72 Schloegl, C., A. Dierks, G. K. Gajdon, L. Huber, K. Kotrschal, and T. Bugnyar. 2009. What you see is what you get? Exclusion performances in ravens and keas. PloS one 4:e6368. Sherry, T. W. 1990. When are birds dietarily specialized? Distinguishing ecological from evolutionary approaches. Studies in Avian Biology 13:337– 352. Shettleworth, S. J., and J. R. Krebs. 1986. Stored and encountered seeds: a comparison of two spatial memory tasks in marsh tits and chickadees. Journal of Experimental Psychology Animal Behavior Processes 12:248–257. Sih, A., A. M. Bell, and J. Johnson. 2004. Behavioral syndromes: an integrative overview. Quarterly Review of Biology 79:241–277. Sih, A., and M. Del Giudice. 2012. Linking behavioural syndromes and cognition: a behavioural ecology perspective. Philosophical Transactions of the Royal Society of London. Series B, Biological sciences 367:2762–2772. Tebbich, S., B. Fessl, and D. Blomqvist. 2009. Exploration and ecology in Darwin’s finches. Evolutionary Ecology 23:591–605. Tebbich, S., K. Sterelny, and I. Teschke. 2010. The tale of the finch: adaptive radiation and behavioural flexibility. Philosophical Transactions of the Royal Society of London. Series B, Biological sciences 365:1099–1109. Timmermans, S., L. Lefebvre, D. Boire, and P. Basu. 2000. Relative size of the hyperstriatum ventrale is the best predictor of feeding innovation rate in birds. Brain, Behavior and Evolution 56:196–203. Webster, S. J., and L. Lefebvre. 2000. Neophobia by the Lesser-Antillean Bullfinch, a Foraging Generalist, and the Bananaquit, a Nectar Specialist. The Wilson Bulletin 112:6. Webster, S. J., and L. Lefebvre. 2001. Problem solving and neophobia in a columbiform– passeriform assemblage in Barbados. Animal Behaviour 62:23–32. Wyles, J. S., J. G. Kunkel, and A. C. Wilson. 1983. Birds, behavior, and anatomical evolution. Proceedings of the National Academy of Sciences of the United States of America 80:4394–4397.
73 Figures:
A
B
Figure 1. Response to food provisioning in the field. Mean ± SEM time to arrive
(seconds) during (A) trials without familiarization (Ntrials= 6) and (B) trials with familiarization (Ntrials= 6).
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Figure 2. Response to field neophobia experiment. Mean ± SEM of time to arrive
(seconds) of the first of each species. Bf: Bullfinch, Gq: grassquit. (NBF=8, NGQ=8).
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Figure 3. Number of focal bullfinches and grassquits foraging on different substrates. Categories for foraging include the substrate upon which the focal individual foraged; on the ground, in the trees (arboreal), or at anthropogenic or provisioned sites.
(NBF=61, NGQ=68).
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Figure 4. Problem-solving task. Lid-flipping task; subject must remove the lid to gain access to the seeds.
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Figure 5. Levels for shaping to learn lid-removal. Subjects that failed the problem- solving task were presented with progressively more difficult levels of the task: (A) level 0, apparatus open and the lid placed on the side; (B) level 1, half of the opening of the apparatus covered by the lid placed bottom-up; (C) level 2, three-quarters of the apparatus covered, lid bottom-up; (D) level 3, the apparatus fully covered, lid bottom-up; level 4, apparatus fully covered, lid bottom-down (see Figure 1).
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Figure 6. Results of captive neophobia experiment. Mean ± SEM latency (seconds) to feed without novel object (Shyness – light-gray bar) and with novel object (dark-grey bar) for bullfinches and grassquits. Neophobia (NEO dark-grey bar) calculated by removing the shyness in the latency to feed in the presence of a novel object. (NBF=30,
NGQ=15).
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Figure 7. Problem-solving in bullfinches and grassquits. Mean ± SEM number of trials to first completion of the obstacle removal task by the bullfinches (NBF=30). None of the grassquits (NGQ=15) completed the task. A maximum of 16 trials were assigned to non-solvers.
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Figure 8. Shaping for obstacle removal task. Difference between bullfinches (grey squares, NBF=3) and grassquits (black diamonds, NGQ=15) in proportion of birds that pass the learning criterion for 4 levels of the obstacle removal task. Error bars represent SEM.
81
GENERAL SUMMARY AND CONCLUSION
Opportunism is one of the many ecological variables that have been implicated in the evolution of cognition, but up to now only indirect associations have been demonstrated between them. The objective of my thesis was therefore to directly address the relationship between opportunism and cognition.
In chapter 1, I derived an operational definition for opportunism through a survey of highly cited peer-reviewed articles from the zoological literature with the objective of disentangling opportunism from associated ecological and cognitive measures such as generalism and innovation rate. I propose that opportunism be defined as the latency to modify foraging in response to a suddenly abundant, yet spatially and temporally unpredictable, food source.
In chapter 2, I provided empirical evidence of the relationship between opportunism, neophobia, shyness and problem solving. By means of a two-species comparison, I demonstrate that the opportunistic Barbados bullfinch (L. barbadensis), is bolder and better at problem-solving than its less opportunistic sister species, the black- faced grassquit (T. bicolor).
Field results for opportunism, for both provisioned sites with and without familiarization, showed an all-or-none difference, as only bullfinches arrived and fed at provisioned sites but grassquits did not. This is true for field neophobia and captive problem solving as well. All else being equal, the all-or-none difference in responses between such closely related species allowed me to demonstrate that the extreme differences in opportunism and boldness in the field can be associated with extreme differences in problem-solving of an obstacle removal task by captive wild-caught birds.
In the discussion of chapter 2, I provided arguments to suggest that the all-or-none differences are not due to a failure of this study to provide adequate tests of grassquit cognition. Firstly, if grassquits did not attend the field tests of opportunism and neophobia, or solve the obstacle removal problem in captivity, they did provide data for
82 the neophobia test and the shaping test in captivity. The data from these tests confirm the very large difference between grassquits and bullfinches in tests, where at least some data are provided by the latter species. Secondly, in a companion study to this one, grassquits were slower than bullfinches in responding to color discrimination learning and reversal tests, but made fewer errors.
With no evidence of a graded response, these all-or-none results fail to show the potential applicability of opportunism as a measure of ecological flexibility. However during our opportunism field tests, four other species either came to the patches offered or were clearly visible in the immediate vicinity. I recorded latencies for these species, and the distribution of results confirm, in a more graded fashion, the all-or-none results on L. barbadensis and T. bicolor. The results on all six species are presented in Appendix 1, Figures 1 to 4. Bullfinches were not the first species to arrive at the provisioned patches and grassquits were not the only granivorous species in the vicinity to fail to eat within the time limits of the experiment. Common ground doves (Columbina passerine) also failed to come to the provisioned patch despite the fact that they are known to consume the seed offered, while both Carib grackles (Quiscalus lugubris) and shiny cowbirds (Molothrus bonariensis) had a lower mean latency to arrive than did bullfinches. The Zenaida dove (Zenaida aurita) is intermediate between the Quiscalus- Molothrus-Loxigilla group of opportunists and the Tiaris-Columbina group of non- opportunists, both in the trials with prior familiarization at the provisioning sites (Appendix Figures 3 and 4) and those with no provisioning (Appendix Figures 1 and 2), whether the measure is time to arrive (Appendix Figures 1 and 3) or time to feed (Appendix Figures 2 and 4).
As the tests in chapter 2 were only conducted on two of the six species, one needs to look to other data to see if our operational measure of opportunism adequately predicts measures of cognition on a wider sample. Two measures that can be derived from the literature are innovativeness, taken from the database maintained by the Lefebvre lab (Overington et al. 2009, the latest published version of this database) and problem solving, taken from the five species study of Barbados birds by Webster and Lefebvre
83 (2001).
As can be clearly seen in Appendix Figures 5 and 8, there is a good rank relationship between our opportunism measure (taken from Appendix Figure 1) and the number of innovations per genus taken from Overington et al. 2009 (Appendix Figure 5), and the number of birds per species that solve the obstacle removal task in the field and in captivity in the Webster and Lefebvre (2001) experiments. These relationships are in fact closer than the ones between our data and the equivalent measures in Webster and Lefebvre (2001), the latency to arrive at (Appendix Figure 7) and contact (Appendix Figure 8) the food box presented in the field. Note that the current study provides a simple food patch, while the Webster and Lefebvre (2001) study offered the food inside a transparent Plexiglas box, adding a probable neophobia effect associated with the apparatus itself. Taken together, the results presented in the appendix and in chapter 2 offer good support for the idea that the operational measure of opportunism proposed in chapter 1 is a valid predictor of innovativeness and problem solving at least in six species of Barbados birds, and perhaps in a wider sample.
To further validate the relationship between opportunism and cognition, its future application, as per this thesis, in small- and large-scale comparative studies involving various mammalian, reptilian and avian species will be necessary. Future comparative studies integrating opportunism will further refine our understanding of the relationship between ecology and cognition.
References:
Overington, S. E., J. Morand-Ferron, N. J. Boogert, and L. Lefebvre. 2009. Technical innovations drive the relationship between innovativeness and residual brain size in birds. Animal Behaviour 78:1001–1010. Webster, S. J., and L. Lefebvre. 2001. Problem solving and neophobia in a columbiform–passeriform assemblage in Barbados. Animal Behaviour 62:23–32.
84
APPENDIX 1
A. Arrival and feeding latencies of Barbados birds at provisioned sites
85
Figure 1. Latency to arrive at provisioned site with no familiarization. Latency ±SEM (seconds) of the first of six species to arrive at the provisioned site. Tb: Tiaris bicolor (black-faced grassquit), Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove).
86
Figure 2. Latency to feed at provisioned site with no familiarization. Latency ±SEM (seconds) of the first of six species to feed at the provisioned site. Tb: Tiaris bicolor (black-faced grassquit), Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove).
87
Figure 3. Latency to arrive at provisioned site with familiarization. Latency ±SEM (seconds) of the first of six species to arrive at the provisioned site. Tb: Tiaris bicolor (black-faced grassquit), Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove).
88
Figure 4. Latency to feed at provisioned site with familiarization. Latency ±SEM (seconds) of the first of six species to feed at the provisioned site. Tb: Tiaris bicolor (black-faced grassquit), Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove).
89
APPENDIX 1
B. Opportunism’s relationship with data from literature
90
Figure 5. Relationship between rank innovation frequency and rank latency to arrive. Innovation frequencies (data from Overington et al. 2009 database) plotted against rank latency of arrival of the Barbados species during field test without familiarization (Appendix 1 – Figure 1). Tb: Tiaris bicolor (black-faced grassquit), Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove). ρ (Rho) = Spearman’s rank correlation.
91
Figure 6. Relationship between rank latency to arrive from two experiments. The rank latency of arrival of Barbados species at feeding task in the field (data from Webster and Lefebvre 2001) plotted against rank latency of arrival of the Barbados species during field test without familiarization (Appendix 1 – Figure 1). Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove). ρ (Rho) = Spearman’s rank correlation.
92
Figure 7. Relationship between rank to contact task and rank latency to arrive. The rank number of Barbados species that first contacted a task in the field (data from Webster and Lefebvre 2001) plotted against rank latency of arrival of the Barbados species during field test without familiarization (Appendix 1 – Figure 1). Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove). ρ (Rho) = Spearman’s rank correlation.
93
Figure 8. Relationship between rank number that solve task and rank latency to arrive. The rank number of Barbados species that solved a task in the field and in captivity (data from Webster and Lefebvre 2001) plotted against rank latency of arrival of the Barbados species during field test without familiarization (Appendix 1 – Figure 1). Lb: Loxigilla noctis (Barbados bullfinch), Ql: Quiscalis lugubris (Carib grackle), Mb: Molothrus bonariensis (shiny cowbird), Za: Zenaida aurita (zenaida dove), and Cp: Columbina passerine (common ground dove). ρ (Rho) = Spearman’s rank correlation.
94