Università Di Pisa Dipartimento Di Biologia Corso Di Laurea Specialistica in Biodiversità Ed Evoluzione

Home , Beza Mahafaly Reserve, Brexia, Common brown lemur, Ruffed lemur

Università di Pisa Dipartimento di Biologia Corso di Laurea Specialistica in Biodiversità ed Evoluzione

Tesi di Laurea Specialistica

Habitat disturbance and perceived predation risk in Eulemur collaris: a comparative study in littoral forest fragments of South-eastern Madagascar

Relatori: Dr. Giuseppe Donati Dr. Giulio Petroni Candidata: Marta Barresi

Anno Accademico 2013-2014 "Hazo tokana tsy mba ala".

One tree does not make a forest...

Un solo albero non fa una Foresta...

Alle persone che non hanno mai smesso di credere in me, anche nei periodi in cui io non sono stata abbastanza forte da credere in me stessa, quelle persone sulle quali so di poter sempre contare, in particolar modo Raul, Vale, Giulia, Marta e Giovanni ...e a quella parte di Madagascar che porterò sempre dentro di me. ABSTRACT

The littoral forest of South-eastern Madagascar is one of the most threatened ecosystems in the world, due to the high levels of deforestation and habitat fragmentation. The red-collared brown lemur, Eulemur collaris, is the largest frugivorous remaining in this habitat, where it plays a fundamental role in forest regeneration as seed disperser. Red-Collared Brown Lemurs show a high social and ecological flexibility, by adopting several behavioural and ecological strategies to cope with the unpredictability and degradation of their seasonal and fragmented environment. Despite this, due to the increasing loss of suitable habitats for this species, IUCN recently listed this lemur as Endangered. In fragmented habitats where predators are still present animals are expected to be more exposed to predation because of the modified habitat structure, the small group size or the overall vulnerable state due to nutritional stress. Thus, this aspect is a crucial one to understand whether these animals can cope with the new condition. In the present study I evaluated the simultaneous effect of habitat degradation, group size, habitat use, and physiological stress on perceived predation risk on two groups of Eulemur collaris living in the degraded forest of Mandena and two groups living in the less disturbed area of Sainte Luce, south-eastern Madagascar. I also evaluated whether animals of different sex or different rank show any difference in predation risk perception. The lemurs were observed for a one year using an Instantaneous Focal Sampling Method every 5 minutes and an All Occurrences Method for rare behaviours. Perceived predation risk was evaluated indirectly in terms of frequencies of anti-predator strategies (alarm calls and scanning) used by the lemurs during feeding and resting sessions. I used as predictors the exposure in tree crowns, the exposure within the forest canopy, the party size, the distance travelled, and physiological stress. Perceived predation risk, the response variables, and all the predictors were modelled using a General Linear Model. Furthermore, in order to elucidate the function of the unusual adult sex ratio in Eulemur collaris, which shows a multimale-multifemale social structure, the possible anti-predator role of the “extra-males” both for vigilance and as “sentinels” to better defend the offspring was tested by analysing the effect of sex, rank and presence of infants both on scanning frequencies and alarm rates, by using a Repeated Measures ANOVA model. A significant difference in terms of scanning rate was found between groups during feeding. The exposure on the crown and party size had a significant effect on alarm rates during feeding. No significant effect of the exposure in the canopy was found in terms of perceived predation risk. Daily path length had a significant effect during feeding both on alarm rates and scanning frequencies. Physiological stress had a significant effect on alarm rate during feeding. This findings seems to confirm the hypothesis that in fragmented habitats animals have to accurately evaluate costs and benefits of their survival strategies, in order to cope simultaneously with their perceived predation risk and with scarcity and patchily distribution of food resources, by making a choice accordingly to their constraints. This is further supported by the negative correlation found in the present study between time spent feeding and time spent for predator vigilance: indeed, in order to maximize their food intake, E. collaris seems to minimize the scanning frequencies during feeding, preferring to rather rely on some "sentinel" individuals that perform anti-predator alarm calls. No one of the social correlates considered in the analysis (sex, rank, presence of offspring) had a significant differences in terms of alarm rates or scanning frequencies. This finding does not support the possible anti-predator role of the extra-males for a better defence of infants against predators. Primate conservation strategies should take into account the role of predation in fragmented habitats. The present study is consistent with the most recent researches which underlined the necessity to evaluate the simultaneous effect of distribution and availability of resources and lemurs' landscape of fear in fragmented habitats. In fact, even when the animals are able to survive on available resources, potential extirpation due to predation events may have profound consequence for the ecosystem being recolonization less likely in forest fragments. TABLE OF CONTENTS

INTRODUCTION...... 1 – 32

1. GROUP LIVING AND PREDATION RISK IN PRIMATES...... 1 1.1 Costs and benefits of group living...... 1 – 4 1.2 Group size and predation risk...... 4 – 6

2. ANTI-PREDATOR STRATEGIES...... 6 2.1 Vigilance...... 6 – 7 2.2 Alarm calls...... 7 – 9

3. LEMURS: THE MAIN MADAGASCAN “FLAGSHIP” SPECIES...... 9 3.1 The peculiar adult sex ratio in gregarious lemurs...... 9 – 12 3.2 Lemurs: the most endangered mammals on Earth...... 12 – 17

4. HABITAT FRAGMENTATION OUTCOMES...... 17 4.1 Edge effect and its consequences...... 17 – 19

5. GENERAL CONTEXT OF THE PRESENT STUDY...... 20 5.1 Madagascar: a biodiversity hotspot...... 20 – 22 5.2 The south-eastern humid littoral forest in the Anosy region: the hottest spot in the hot spot...... 23 – 25 5.3 The role of QMM (QIT Madagascar Minerals)...... 25 – 26

6. THE AIM OF THIS STUDY...... 27 6.1 General goals...... 27 – 28 6.2 Hypothesis of investigation...... 28 – 32

MATERIALS AND METHODS...... 33 – 54

1. STUDY AREA...... 33 1.4 Study sites...... 33 – 36 2. STUDY SPECIES...... 36 2.1 Eulemur collaris (É. Geoffroy, 1817)...... 36 – 40

3. DATA COLLECTION...... 41 3.1 Study period and groups composition...... 41 – 43 3.2 Behavioural data...... 43 – 48 3.3 Ecological data and habitat use...... 49 – 51 3.4 Faecal samples and hormonal analyses...... 51 – 53

4. STATISTICAL ANALYSES...... 53 4.1 Ecological correlates to perceived predation risk...... 53 – 54 4.2 Social correlates to perceived predation risk...... 54

RESULTS...... 55 – 67

1. ECOLOGICAL CORRELATES TO PERCEIVED PREDATION RISK...... 55 1.1 Alarm rates during feeding and during resting at the two study sites...... 55 – 56 1.2 Scanning frequencies during feeding and during resting at the two study sites...... 56 – 57 1.3 Animals' exposure in the crown...... 57 – 58 1.4 Animals' exposure in the canopy...... 58 – 61 1.5 Party Size...... 62 1.6 Daily Path Length...... 63 1.7 Physiological Stress...... 64 1.8 Model outputs...... 65 – 67

2. SOCIAL CORRELATES TO PERCEIVED PREDATION RISK...... 67 2.1 Frequency of alarm calls performed by the two sexes and by high and low ranked individuals in presence or absence of offspring...... 67 – 68 2.2 Frequency of scanning performed by the two sexes and by high and low ranked individuals in presence or absence of offspring...... 69 – 70 2.3 Repeated Measures ANOVA: statistical outputs...... 70 – 72 DISCUSSION...... 73 – 91

1. ECOLOGICAL CORRELATES TO PERCEIVED PREDATION RISK IN Eulemur collaris...... 73 1.1 Evaluating the influence of ecological factors onlemurs' landscape of fear73 – 81

2. SOCIAL CORRELATES OF PERCEIVED PREDATION RISK IN Eulemur collaris...... 82 2.1 Evaluating a possible anti-predator function of lemurs' unusual adult sex ratio...... 82 – 85

3. LIMITATIONS OF THE STUDY, NEW RESEARCH FRONTIERS AND FURTHER PERSPECTIVES...... 85 3.1 Limitations and new research frontiers in the present study...... 85 – 86 3.2 Further perspectives...... 86 – 88

4. GENERAL CONSIDERATIONS...... 88 – 91

APPENDIX I – Ethogram of Eulemur collaris...... 92

APPENDIX II – Hormonal Extraction protocol...... 93

REFERENCES...... 94 – 123

ACKNOWLEDGEMENTS...... 124 – 126 INTRODUCTION

1. GROUP LIVING AND PREDATION RISK IN PRIMATES

1.1 Costs and benefits of group living

Among vertebrates, permanent group living is a taxonomically widespread social system [Krause and Ruxton, 2002; Majolo et al., 2008]. Despite the costs and benefits of group life may be generally similar in a number of taxa [Trivers, 1985; Mann et al., 2000], these have been more deeply investigated in primates. Three wide categories of group living benefits have been reported by many authors: predator avoidance, foraging advantages, and avoidance of conspecific threat [Chapman and Chapman, 2000]. Primate socio-ecological models consider group size to be an important factor influencing behaviour and individual fitness [Wrangham, 1980; van Schaik, 1983; van Schaik et al., 1983a Janson and Goldsmith, 1995; Sterck et al., 1997; Koenig, 2002]. Group size differences have been related to various benefits and costs for group members mainly considering two factors: food and predators. Other things being equal (e.g. habitat quality), larger groups should be more advantaged than smaller groups in reaching and monopolizing the best food sources, that is, larger groups should undergo less between-group contest food competition [Wrangham, 1980; Janson and van Schaik, 1988; Majolo et al., 2008]. Larger groups should also withstand a lower predation pressure as predator detection through vigilance and/or defence from predators (e.g. mobbing) are expected to be more efficient than in smaller groups [van Schaik, 1983; Sterck et al., 1997]. Overall, detection of predators, defence against predators, increased hunting efficiency in predators, increased detection of patchy resources, and defence of resource patches from other groups have been reported in literature as potential benefits of group living [Loehle, 1995]. Whereas, as potential costs, decreased per capita food availability or reproduction rates, and increased time spent in agonistic interactions have been proposed for larger groups [Loehle, 1995]. However, the principal expected cost for larger groups, is an increase in the

1 level of within-group food competition with increasing group size [Janson and van Schaik, 1988; Isbell, 1991]. Moreover, larger groups could suffer an increase in infant mortality due to disease or a higher probability of adults to get sick, because of the increased contamination of the environment by the group, for example [Freeland, 1976]. Typically, it is assumed that disease and parasites are most likely spread in larger host groups, thus they have been interpreted as a cost of group-living [Freeland, 1976; Møller et al., 1993; Loehle, 1995] even though some recent studies have underlined that group size is not sufficient to infer the risk of infectious disease related to social living in the complex societies of many primates [Griffin and Nunn, 2012]. What is evident is that the behaviour and fitness of group members depend on the balance between the various benefits and costs associated with group size differences [van Noordwijk and van Schaik, 1987; van Schaik, 1989; Isbell, 1991; Janson and Goldsmith, 1995]. According to socio-ecological models aiming at estimating the effect of environmental factors on species’ ecology and social behaviour, larger groups should face more within-group food competition than smaller groups but benefit from a decrease in predation pressure and/or between-group food competition. The balance between benefits and costs of living in larger groups may vary between populations and species, and it is often difficult to evaluate [Majolo et al., 2008]. For example, a high predation risk should constrain animals to forage and move close together: a strategy that should increase food depletion rate per unit area. This will have direct consequences for travel time and foraging effort and therefore also for time to be dedicated to other activities, such as resting. Several studies analysing the relationship between group size and predation have given opposite results, in fact some authors have found a positive relationship [van Schaik, 1983; Janson and Goldsmith, 1995] while others have not [Hill and Dunbar, 1998]. Data on predation pressure are rarely available and usually come from just one group per species. For this reason the importance of predation for primate socio-ecology may be considered still unclear. Most studies analysing the relationship between predation risk and group size have focused on predation-sensitive behaviour (e.g. vigilance) rather than on predation pressure per se because it is difficult to definitely measure it [Miller, 2002].

2 It may be hypothesized that group living provides to individuals the benefit of having more ears and eyes to better detect predators, more help in preventing predation attacks, and more group members to dilute the risk to any individual [Stanford, 2002]. The trade-off is that groups themselves may attract predators and other individual costs, such as feeding competition and mate competition, may increase in larger groups. Hence, understanding the evolutionary role of predation in shaping primate societies is a pivotal interest of primate field research [Stanford, 2002]. One of the most questioned issues is whether predation has been the primary selective force favouring the evolution of group living in primates. Nonetheless, the scarcity of direct evidence of predation makes difficult to solve this debate. Until now, however, some interesting patterns have emerged: 1) despite smaller primates may have greater predation rates than larger primates, even the largest primates are not invulnerable to predation; 2) primates can face higher predation rates when they use unfamiliar areas, which might be one pressure favouring philopatry, or site fidelity; 3) predation risk is higher for arboreal primates when they are more exposed (at forest edges and tops of canopies) than in more hidden locations; 4) predation by mammalian carnivores may often be episodic; 5) terrestrial primates may not experience greater predation than arboreal primates [Isbell, 1994]. The hypothesis that the risk of predation is greater for terrestrial primates than arboreal primates is undermined also by the finding that predation on arboreal primates can be severe. There are terrestrial animals that are capable of killing arboreal primates, at least in the Old World where fossas (Cryptoprocta ferox) [Goodman et al., 1993] and leopards are present. There are also avian predators that specialize in killing arboreal primates in Africa, the Neotropics, the Philippines, and Madagascar [Skorupa, 1989; Goodman et al., 1993; Goodman, 1994]. In two studies of crowned eagles (Stephanoaetus coronatus) in Kibale Forest, Uganda, monkeys accounted for 87% and 89% of prey items [Skorupa, 1989; Struhsaker and Leakey, 1990]. The grey mouse lemur (Microcebus murinus) represented 23% of the total biomass taken by barn owls during one year in Beza Mahafady, Madagascar [Goodman et al., 1993].

3 Studies on predation rates in Ranomafana National Park, in the south-eastern Madagascar, indicate that raptor predation is an important cause of mortality for lemur populations [Karpanty, 2006]. On the contrary, no avian predators are known to specialize in killing terrestrial primates [Isbell, 1994].

1.2 Group size and predation risk

Predator avoidance hypotheses propose that social living would favour: a) higher predator detection likelihoods [Boinski, 1987,1989; van Schaik and van Noordwijk, 1985, 1989; Cords, 1990]; b) getting confused the predator that focuses on an individual prey [Morse, 1977; Landeau and Terborgh; 1986]; c) a lower chance for each individual within the group to be preyed (dilution effect) [Hamilton, 1971]; d) an increased defence against predators [van Schaik and van Noordwijk, 1985; Boinski, 1987; Gautier-Hion and Tutin, 1988; van Schaik and van Noordwijk, 1989; van Schaik and Höstermann, 1994]. Supposing that group living is advantageous for primates, theoretical considerations suggest that the ability to detect the presence of a predator when there is still enough time to escape (early detection) should improve with group size. The hypothesis that the distance at which forest primates detect predators increases with the size of their party was also supported by observations [van Schaik et al., 1983b]. The negative correlation between party size and predation risk demonstrates that forest monkeys can modify their behaviour accordingly to variations in predation risk, and therefore supports the hypothesis that predation risk has been a relevant selective force responsible for the evolution of group living nonhuman primates [van Schaik et al., 1983a]. The role of predation as a selective pressure for the evolution of primate grouping patterns has been the subject of considerable debate [Alexander, 1974; Wrangham, 1980; van Schaik, 1983; Anderson, 1986; Cheney and Wrangham, 1987; Dunbar, 1988; Isbell, 1994]. While from some studies a positive correlation between predation rate and group size has been found [Anderson, 1986], yet others provided evidence for a positive relationship

4 between predation risk and group size, both within and across primate species [Dunbar, 1988; Hill and Dunbar, 1998]. Additionally, most studies seem to show some confusion and have actually failed to understand the importance of distinguishing clearly between predation risk and predation rate [Hill and Dunbar, 1998]. Predation rate is the annual mortality within a population directly attributable to predation; it represents the level of successful predator attacks that the animals are not able to control after they have put in place their anti-predation strategies. Predation risk, on the other hand, represents the animals' own perception of the likelihood of undergo an attack by a predator, independently on whether or not the attack is successful; it reflects the animals' collective past historical experience of actual attacks by predators and is the basis on which the animals carry out their anti-predator strategies. It can be operationalised as the likelihood of an animal (or a group) of encountering a predator. The animal's current behaviour is maintained by (and therefore driven by) predation risk and not predation rate because the animals will be just as responsive to unsuccessful attacks as to successful ones [Hill and Dunbar, 1998]. Predation risk as a selective force can be defined as the likelihood that an animal living on its own and performing no behavioural anti-predator strategies (e.g. vigilance) will succumb to a predator during any given time period [Hill and Dunbar, 1998]. Since this will be difficult to measure in practice, a suitable operational definition might be the frequency with which groups (or individuals) are subjected to predator attacks (regardless of whether or not these are successful). The frequency with which observers encounter predators may also be an acceptable approximation of predation risk [Hill and Dunbar, 1998]. Alternatively, predator encounter rates may be estimated theoretically by using the gas model [Lowen and Dunbar, 1994] to calculate the frequencies with which randomly moving prey will encounter randomly searching predators, given the observed densities of predators and prey in the habitat. Even among animals that are rarely preyed on, predation risk may have important effects on behaviour because a single successful predator attack can have profound consequences on individual fitness [Lima and Dill, 1990; Stanford, 2002; Campos and Fedigan, 2014].

5 Predation risk can be operationalized in different ways: intrinsic risk is the expected predation rate retaining anti-predator behaviour constant or at zero, and it is likely responsible for the evolution of anti-predator defence strategies [Janson, 1998; Campos and Fedigan, 2014]; whereas perceived risk is the animal’s own evaluation of the likelihood of an attack, and it is based on past experiences and imperfect knowledge [Bouskila and Blumstein, 1992; Hill and Dunbar, 1998]. Some studies have evidenced that perceived predation risk influences animals' short-term decisions and selection of habitats, duration of stay in a patch, and therefore also group size [Chapman and Chapman, 2000; Campos and Fedigan, 2014]. Indeed, an individuals' perceived predation risk has several different correlates, many of which are closely related to the local environment (e.g. density of predators, visibility within the habitat, distribution of refuges). Demographic factors are also an important correlate to an individual's risk of predation, first of all because of the selfish herd effect [Hamilton, 1971], which means that in larger groups the likelihood that an individual will be captured during a predator's attack is lower.

2. ANTI-PREDATOR STRATEGIES

2.1 Vigilance

Predation is a primary evolutionary force that has led up to a number of adaptations to avoid and deal with predators [Lima and Dill, 1990; Caro, 2005]. Anti-predator behaviour generally falls into one of several categories. First, animals try to avoid being targeted by a predator, either by avoiding places where predators forage or by being vigilant for them. Vigilance behaviour is often interpreted as part of an anti-predator strategy [Pulliam, 1973; Elgar, 1989; Lima, 1990; Quenette, 1990; Caro, 2005, Gaynor and Cords, 2012; Campos and Fedigan, 2014]. Studies of vigilance in a wide range of birds and mammals [Barnard, 1981 [sparrows]; Bertram, 1980 [ostriches]; Fitzgibbon, 1990 [Thomson’s gazelles]; Scheel, 1993 [African ungulates]; Sullivan, 1984 [woodpeckers]] have shown

6 that foraging animals spend less time scanning their surroundings when in larger foraging groups, which suggests a higher chance of safety when more eyes are present to look for danger [Stanford, 2002]. It was observed that large monkey groups were more efficient at detecting predators than small groups [van Schaik, 1983]. Moreover, monkeys in small groups were found to spend more time scanning than those in large groups [de Ruiter, 1986; Baldellou and Henzi, 1992; Treves, 1999], and thus it was concluded that predation risk is lower in larger groups [Stanford, 2002]. Studies have been also focussing on how sociality (or increasing group size) can decrease the costs of vigilance without exposing animals to higher predation risks. By sharing the job of being wakeful, individuals can spend less time for vigilance or stop their other activities less often without sacrificing safety [Pulliam, 1973; Parker and Hammerstein, 1985]. This extra or uninterrupted time then becomes available for other activities, such as feeding [Cords, 1990]. Vigilance rates vary with factors that influence predation risk, including exposure to predators, position in group, age and group size [Caro, 2005]. An additional approach to studying social vigilance when predation pressure is present is to use more specialized measures of social risk than group size or the presence of nearby conspecifics, based on known relationships between the subject and its neighbour [Gaynor and Cords, 2012]. Recent studies have analysed and provided evidence for both anti-predator and social monitoring functions of vigilance in social prey species [Hirsch, 2002; MacIntosh and Sicotte, 2009; Favreau et al., 2010; Campos and Fedigan, 2014]. Nonetheless, vigilance directed at conspecifics may not always be related to social threats; it may also help the function of predator detection, as conspecifics may alert group-mates to the presence of a predator [Dehn, 1990; Gaynor and Cords, 2012].

2.2 Alarm calls

Alarm calls are a widespread form of anti-predator behaviour, in which one or more group members act as sentinels for the rest of the group by signalling the presence of predators to conspecifics [Caro, 2005]. Possible functions can be

7 pursuit deterrence [Caro, 1995], signalling predator size and location [Evans and Marler, 1995; Blumstein and Armitage, 1997; Templeton et al., 2005] as well as identity to conspecifics [Seyfarth et al., 1980; Zuberbühler et al., 1997; Manser, 2001; Fichtel and Kappeler, 2002]. Since giving a loud alarm call presumably attracts the attention of the predator to oneself, alarm-calling has long been a paradoxical survival strategy from a Darwinian perspective. Warning one’s kin of danger while calling attention to oneself is interpreted as kin selected altruism from a Darwinian point of view [Sherman, 1977]. The same interpretation was attributed also to “stotting”, which can be observed in many African ungulates, supposing (among the numerous hypothesized functions of this peculiar behaviour) that individuals stott to warn conspecifics of the predator's presence [Caro, 1986]. Warning other group members that are less related may be explained as investment in a mate [Hogstad, 1995; Sherman, 1985], coordination of a flock escape response [Charnov and Krebs, 1975], or as a false signal to try to usurp a food item from a conspecific [Cheney and Seyfarth, 1990; Møller, 1988]. Functional reference was first suggested for vervet monkeys (Chlorocebus spp.), which produce acoustically distinct alarm calls for snakes, leopards, and eagles [Struhsaker, 1967; Seyfarth et al., 1980a, b; Willems and Russell, 2009]. Recipients react to each of these calls with a specific escape response. Such a referential system has also been found in three other primate species: ring-tailed lemurs (Lemur catta) [Macedonia, 1990; Pereira and Macedonia, 1991], Diana monkeys (Cercopithecus diana) [Zuberbühler, 1997, 2000, 2002], and Campbell's monkeys (C. campbelli) [Zuberbühler, 2001], suggesting that referential signals may be linked to some primate peculiarity [Fichtel and Kappeler, 2002]. Current knowledge on lemur alarm calls is scarce and largely anecdotal. Nocturnal lemurs, which are either solitary or pair living, are not known to have specific alarm calls for different predators [Petter and Charles-Dominique, 1979; Stanger, 1993; Macedonia and Stanger, 1994; Stanger, 1995; Zimmermann, 1995]. Lemurs of the genera Hapalemur and Eulemur are pair or group living and cathemeral, that is active both day and night [Tattersall, 1987]. They were observed to emit one kind of call ("grunt") during moderate disturbances and another one ("croak"or "shriek") during situations characterized by high levels of

8 arousal, including the presence of terrestrial predators [Petter and Charles- Dominique, 1979; Wilson et al., 1989; Bayart and Anthouard 1992; Colquhoun, 1993; Macedonia and Stanger, 1994; Curtis, 1997]. Only Eulemur coronatus and E. macaco give the latter type of call also in response to diurnal raptors [Wilson et al., 1989; Colquhoun, 1993]. In diurnal pair-living Indri indri and group-living Propithecus ssp., different alarm calls for aerial and terrestrial predators have been described [Jolly, 1966; Pollock, 1975; Petter and Charles- Dominique, 1979; Pollock, 1986; Pereira et al., 1988; Thalmann et al., 1993; Macedonia and Stanger, 1994; Oda and Masataka, 1996; Powzyk, 1997; Wright, 1998], but all of these studies are based on observations which did not elucidate whether these alarm calls refer to the respective class of predator or the subjectively perceived risk of the given threat [Fichtel and Kappeler, 2002].

3. LEMURS: THE MAIN MADAGASCAN “FLAGSHIP” SPECIES

3.1 The peculiar adult sex ratio in gregarious lemurs

The distribution and association patterns of adults of both sexes represents the most basic feature of any social system. While adult females distribute themselves in accordance to the distribution of risks and resources in their habitat, adult males essentially respond to the distribution of fertile females in space and time [Emlen and Oring, 1977; Ostner and Kappeler, 2004]. Among gregarious species, much of the variation in social organization between species and populations can be referred to the differences in the number of adult males within groups [Kappeler, 2000a]. This variation, which has broad effects on male and female reproductive strategies, has been related to the temporal distribution of receptive females [Ridley, 1986], female group size [Andelman, 1986; Altmann, 1990; Mitani et al., 1996], the interaction of both factors [Nunn, 1999] and associated benefits for males and females [Kappeler, 1999]. In group-living species, theoretical considerations indicate the existence of a basic conflict of interest between the sexes over the adult sex ratio. Females may obtain ecological as well as social advantages from a high number of co- resident males. For example, males in some species are better at detecting and

9 repelling predators [van Schaik and van Noordwijk, 1989] and may thus lower the overall risk of predation [van Schaik and Hörstermann, 1994] in addition to lowering per capita predation risk [Hamilton, 1971]. To accomplish these purposes, females may form large groups, synchronize their fertile periods [Ims, 1990] or transfer into a group with the optimal number of males [Sterck, 1997; Steenbeek et al., 2000; Ostner and Kappeler, 2004]. Males, on the other hand, should prefer to live in single-male groups, where they can monopolize reproduction, rather than in a multi-male group, where they are very likely to share paternity with other resident males [Kappeler, 1999]. In some cases, however, a male may also gain some benefits from the presence of additional males in his group [Kappeler, 1999]. Such possible advantages include a lower predation risk for themselves and their offspring [van Schaik and Hörstermann, 1994], the promotion of the reproductive success of related males [Goldizen, 1990; Pope, 1990], and availability of support of male coalition partners against extra-group males [Wrangham, 1979], the latter being especially effective if the coalitions consist of co-resident kin [Goldberg and Wrangham, 1997; Ostner and Kappeler, 2004]. The gregarious lemurs of Madagascar (Lemuriformes) live in relatively small groups with only a few adult females [Kappeler and Heymann, 1996] and highly variable adult sex ratios [Kappeler, 2000b]. Although they show a lack of sexual dimorphism in body and canine size [Kappeler, 1990, 1996a], which is generally related to a low direct male-male competition [Harcourt et al., 1981], lemur males within a group are typically organised along a dominance hierarchy [Pereira and Kappeler, 1997; Kraus et al., 1999; Ostner and Kappeler, 1999; but see Richard, 1992]. Males disperse from their natal group, whereas females are generally philopatric [Sussman, 1992; Richard et al., 1993; Wimmer and Kappeler, 2002], even if aggressive displacement of single females has been observed in some species [Vick and Pereira, 1989]. In anthropoids these aspects would inevitably result in single-male group organization [Andelman, 1986; Pope, 2000]. In fact, harems (i.e. single-male multi-female groups) are never the modal grouping pattern in gregarious lemurs; whereas, groups generally have an even or male-biased adult sex ratio [Kappeler, 2000b]. Because of the unusual pattern seen in lemurs, it was proposed that some additional males could provide some benefits for females and offspring, such as

10 vigilance and predator detection, and thermoregulation [Ostner and Kappeler, 2004; Donati et al., 2011]. Hence, males should be more responsible for scanning and detecting predators than females. There is an intense debate as to the past and present intensity of predation on Malagasy lemurs [Csermely, 1996]. In Mitoho Cave in the south-western Madagascar, near Beza Mahafaly Reserve, some bird bones attributable to a large eagle (Aquila), hitherto unrecorded on Madagascar, were recovered together with bone remains attributable to the extant lemur species Lemur catta and Propithecus verreauxi and the large extinct one Megaladapis edwardsi [Goodman, 1994]. As a consequence of this recovering, it was hypothesized that a strong selective pressure from extinct large eagles that may have eaten monkey size mammals might have been responsible for the anti-predator strategies that larger lemur species evolved [Goodman, 1994]. This would imply that predatory pressure on extant species of lemurs is now relaxed. Some authors, however, do not agree with this explanation [Csermely, 1996; Boinski et al., 2000], and recent field studies showing significant predation on lemurs by extant Madagascan raptors [Karpanty and Goodman, 1999; Karpanty and Grella, 2001; Karpanty, 2006] further weakened it. Birds of prey may constitute a significant risk for arboreal lemurs [e.g., Sauther, 1989; Langrand, 1990; Goodman et al., 1993; Karpanty and Grella, 2001; Karpanty, 2006], as indicated by their strong response towards raptors, which is hard to explain without reinforcement [Csermely, 1996, G. Donati et al., 1999]. Unlike anthropoids, lemurs are monomorphic [Glander et al., 1991] so that there is no particular size advantage for a female by having a male as a partner. Moreover, a male is not under the same energetic constraints as a female, especially when she is reproducing. Thus he may be a more safe choice as a ‘‘protector’’ than another female. The hypothesis of an anti-predator function provided by males has been supported in some anthropoids: adult males are more vigilant or attack predators more often than females [van Schaik and van Noordwijk, 1989; Cowlishaw, 1994]. In ring-tailed lemurs (Lemur catta), anyway, no sex difference in vigilance has been observed [Gould, 1996b] and preliminary results from redfronted lemurs (Eulemur rufifrons) show that females may be mostly responsible for monitoring [Overdorff, 1998b]. However, lemur females could also obtain a

11 benefit from an extra male, as up to a certain group size (about 10 individuals) individual safety increases because of higher detection and dilution effects [Dehn, 1990].

Fig. 1 The gregarious lemurs of Madagascar live in relatively small groups with only a few adult females and highly variable adult sex ratios. A group of Eulemur collaris during resting in the littoral forest fragment S9, Sainte Luce, South-East Madagascar. Photo by Marta Barresi, 2011

3.2 Lemurs: the most endangered mammals on Earth

A basic understanding of the taxonomy, diversity, and distributions of primates is essential for their conservation [Mittermeier et al., 2008]. A typical debate in Primate evolution concerns the time of crown primate origins: while the earliest primate fossils are dated ∼ 56 million years old [Steiper and Seiffert, 2012], whereas molecular estimates for the Haplorrhini-Strepsirrhini divergence are often ∼ 85-90 MYA [Perelman et al., 2011]. Recent studies have reconciled the molecular and fossil estimates of primate evolution, setting the Primate last common ancestor around 71-63 MYA, and the divergences within both Strepsirrhine and Haplorrhine during the latest Cretaceous (55-53 MYA, and 64-58 MYA, respectively) [Steiper and Seiffert, 2012; Springer et al., 2012]. According to Russell Mittermeier (2008, 2010), the president of Conservation International (CI), taxonomist Colin Groves, and others, there are nearly 101 recognized species or subspecies of extant (or living) lemur (suborder

12 Strepsirrhini, infraorder Lemuriformes), divided into 5 families (Cheirogaleidae, Lemuridae, Lepilemuridae, Indriidae, Daubentoniidae) and 15 genera. Madagascar's five endemic lemur families represent more than 20% of the world's primate species and 30% of family-level diversity [Schwitzer et al., 2014]. All species are listed by CITES (Convention on International Trade in Endangered Species of Wild Fauna and Flora) on Appendix I, which forbids trade of specimens or parts, except for scientific purposes. As of 2005, the International Union for Conservation of Nature (IUCN) classified 16% of all lemur species as Critically Endangered, 23% as Endangered, 25% as Vulnerable, 28% as "Data Deficient", and only 8% as Least Concern. Over the next five years, at least 28 species were newly described, none of which have had their conservation status assigned. Many are likely to be considered threatened since the new lemur species that have been identified recently generally live in small areas. Given the rate of current habitat destruction, undiscovered species could go extinct before being identified. Since the arrival of humans on the island about 2000 years ago, all endemic Malagasy vertebrates over 10 kg have disappeared [Burney, 2003], including 17 species, 8 genera, and 3 families of lemurs [Godfrey and Jungers, 2003]. The IUCN Species Survival Commission (IUCN/SSC), the International Primatological Society (IPS), the Conservation International (CI), and the Bristol Conservation and Science Foundation (BCSF) have included as many as five lemurs in their biennial "Top 25 Most Endangered Primates". The 2012-2014 list includes the blue-eyed black lemur (Eulemur flavifrons), the northern sportive lemur (Lepilemur septentrionalis), the silky sifaka (Propithecus candidus), the Madame Berthe's mouse lemur (Microcebus berthae), the red ruffed lemur (Varecia rubra), and the indri (Indri indri). The aim of the list, according to Russell Mittermeier, is "to highlight those primate species that are most at risk, to attract the attention of the public, to stimulate national governments to do more, and especially to find the resources to implement desperately needed conservation measures." Species are included in the list based on two main reasons: extremely small population sizes and very rapid declines in numbers. These reasons are heavily influenced by habitat loss and hunting, the two greatest threats primates have to cope with.

13 More in detail, threats listed in the report include deforestation due to slash-and- burn agriculture, clearing for pasture or farmland, charcoal production, firewood production, illegal logging, selective logging, mining, land development, and cash crop production; forest fragmentation; small population sizes; live capture for the exotic pet trade; and hunting for bushmeat and traditional medicine. In 2012, an assessment by the Primate Specialist Group of the IUCN stated that 94% of the then described species of lemur should be classified as Threatened on the IUCN Red Lists (more in detail, 21 species are listed as Vulnerable, 49 species as Endangered, and 25 species as Critically Endangered), making lemurs the most endangered group of mammals on Earth [Schwitzer et al., 2014].

Research on lemurs is thus important for several reasons:

1. Above all, not so much time could remain to increase our knowledge about lemurs in their natural habitats. Most of them live in very limited areas and their habitat is under a heavy anthropogenic pressure [Mittermeier et al., 1992]. Nonetheless, research on life history, physiology, genetics, infectious disease, and behaviour can help conservation of small populations of lemurs with the aim to successfully preserve them [Pereira et al., 1999]. 2. Since lemurs and other prosimians represent a basal branch in the primates phylogeny, sharing basic anatomical characters with their last common ancestor, they provide some unique perspectives on features that may basically distinguish primates among mammals. Moreover, the lemurs include a diverse, monophyletic radiation of primates [Yoder et al., 1996] separate from others since the Eocene [Martin, 1990] and only lemurs among prosimians naturally constitute cohesive social groups. Therefore, lemurs represent an invaluable model to study and test the hypotheses concerning mechanisms and constraints related to primate development and evolution [Kappeler, 1996b; Kappeler and Heymann, 1996]. Many primatologists consider crucial the hypotheses to be tested on lemurs in order to understand the evolution of primate social behaviour [van Schaik and Kappeler, 1996].

14 3. Lemurs have important ecological roles and are essential to preserve Madagascar's unique forests [Schwitzer et al., 2014] These forest habitats are severely threatened by anthropogenic exploitation. Remaining intact forest habitat was estimated to cover 92200 km2 in 2010, only 10 to 20% of Madagascar's original forest cover and down from 106600 km2 in 1990 [Schwitzer et al., 2014]. Habitat fragmentation has often deep consequences on large frugivores [Bollen and Donati, 2006]. Frugivorous animals have been shown to be important for seed dispersal and forest regeneration in Madagascar, where zoochorous tree species represent more than 75% of tropical plants [Bollen, 2003; Bollen and Donati, 2006]. Loss of fruit-frugivore interactions can therefore have serious consequences [Bollen and Donati, 2006]. 4. Lemurs are being used as indicator species for ecological monitoring [Durbin, 1999]. 5. Lemurs are the best known Malagasy wildlife, drawing the international interest on Madagascar's unique biodiversity and on the ecological changes that threaten their existence. Lemurs have been an important input for the creation of some of Madagascar's protected areas, whose goal is to preserve whole forest ecosystems. The presence of rare lemurs has brought researchers, funding, and conservation actions to some areas. Lemurs are also the main attraction for tourists, thus making a great economic contribution to a growing ecotourism industry and, potentially, to the future maintenance of national parks which especially helps local communities who receive half of the park entrance fees [Durbin, 1999]. For all the reasons listed above, CI has proclaimed lemurs as the "Madagascar's flagship mammal species", the most famous of which is the ring- tailed lemur (Lemur catta), which is considered an icon of the island. A flagship species, often a charismatic large vertebrate, is one that can be used to promote a conservation action since it attracts public interest. Lemurs, even if mostly smaller and more cryptic than many flagship species, are appealing, furry animals. Primates, in general, raise a particular attraction as our closest relatives in the animal kingdom. Beyond the educational and political support for conservation that such species can provide, a focused, single-species strategy

15 can also be a means of protecting many other plant and animal species and their whole habitats [Durrell and Mallinson, 1987, in Durbin, 1999]. Indeed, starting in 1927, the Malagasy government has declared all lemurs as "protected" by establishing protected areas that are now classified under three categories: National Parks (Parcs Nationaux), Strict Nature Reserves (Réserves Naturelles Intégrales), and Special Reserves (Réserves Spéciales). There are currently 18 national parks, 5 strict nature reserves, and 22 special reserves, as well as several other small private reserves, such as Berenty Reserve and Sainte Luce Private Reserve, both near Fort Dauphin. All protected areas, excluding the private reserves, comprise approximately 3% of the land surface of Madagascar and are managed by Madagascar National Parks, formerly known as l'Association Nationale pour la Gestion des Aires Protégées (ANGAP), as well as other non-governmental organizations (NGOs), including Conservation International (CI), the Wildlife Conservation Society (WCS), and the World Wide Fund for Nature (WWF). Most lemur species are covered by this network of protected areas, and a few species can be found in multiple parks or reserves. Conservation is also promoted by the Madagascar Fauna Group (MFG), an association of nearly 40 zoos and related organizations, including the Duke Lemur Center, the Durrell Wildlife Conservation Trust, and the Saint Louis Zoological Park. In June 2007, the World Heritage Committee included a great area of Madagascar's eastern rainforests as a new UNESCO World Heritage Site.

16 Fig. 2 Frugivorous animals have been shown to be important for seed dispersal and forest regeneration in Madagascar. Apollo, radio- collared sub-adult male of Eulemur collaris, feeding fruits of Voakarepoky (Brexia madagascariensis) in the littoral forest fragment of Mandena, south-east Madagascar. Photo by Marta Barresi, 2011

4. HABITAT FRAGMENTATION OUTCOMES

4.1 Edge effect and its consequences

Forest edges are dynamic zones characterized by the penetration (to varying depths and intensities) of conditions from the surrounding environment (matrix) into the forest interior [Malcolm, 1997; Lehman et al., 2006]. Variations in population dynamics as a result of edge effects can be defined as indirect biological effects [Murcia,1995]. Indirect biological effects are one of the least studied aspects of primate ecology and conservation biology. Despite edge effects have been described as a significantly determinant of primate distributions in most studies [Mbora and Meikle, 2004; Tweheyo et al., 2004], those studies relied only on subjective estimates of edge penetration distances. Thus, the data can not have extended far enough into forest interiors to be not influenced by abiotic and biotic edge effects [Murcia, 1995; Lehman et al., 2006]. Primate responses to edge effects may be of special concern for lemurs. Although the remaining forest is highly fragmented and may be prone to huge

17 edge effects, few data are available concerning how edge effects affect lemurs [Lehman et al., 2006]. For animals living in isolated fragments, natural or invasive predators can be an important cause of decline and extinction [Crooks and Soulé; 1999]. In terms of conservation, it is important to understand whether the impact of predation pressure may be higher in forest fragments [Irwin et al., 2009]. Habitat loss and fragmentation can generate serious environmental problems for forest species, and may eventually lead to local population extinction. One mechanism that might play a role in this process is the physiological stress response of individuals to habitat fragmentation outcomes such as patchily distribution of food resources or increased predation risk, because animals that experience chronic stress might show reduced rates of reproduction and survival. “Stress” has become an increasingly popular and widely used term in everyday language [Palme et al., 2005]. The definition of stress is difficult and controversial because the word is often used to refer to a whole range of symptoms and levels of suffering [Lane, 2006]. Even among biologists, the term “stress” has many meanings, thus it is usually preferred to avoid the word stress using instead the more explicit terms “stressors” to indicate the condition causing a response, and “stress response” to refer to changes in internal state provoked by the external condition [Creel, 2001]. The term “chronic stress” is used to refer to long-term overstimulation of coping response [Romero, 2004]. The survival and persistence of primates in forest fragments often depend on their ability to use the surrounding vegetation matrix, together with their home range size, their behavioural and dietary flexibility and the nature and level of fragmentation [Marsh, 2003; Martínez-Mota et al., 2007]. However, fragmentation effects on primate physiology have rarely been studied, although in recent years habitat degradation has been often proposed to act as a stressor for wild animals [Romero, 2004; Wikelski and Cooke, 2006], potentially having long-term negative outcomes onto individuals and therefore onto populations. There are several potential stressor stimuli for wild animals: they can be both natural, such as climatic factors, high predation pressure, low food availability, social aggression or competition, and anthropogenic, such as noise and habitat

18 modification [Cavigelli, 1999; Pride, 2005a; Ostner et al., 2008]. As a result, the stress response can be used to monitor potential threatened animal populations [Homan et al., 2003; Romero, 2004]. Glucocorticoids, steroid hormones secreted in parallel with the “fight-or-flight” stress response, are usually measured indicators of stress in vertebrates [Wingfield and Romero, 2001]. Elevated glucocorticoids levels have been found in animals facing both natural challenges [Alberts et al., 1992; Foley et al., 2001; Goymann et al., 2012] and anthropogenic environmental disturbances [Wasser et al., 1997; Wingfield and Romero, 2001]. Ecological stressors such as unfavourable climatic factors, decreased food accessibility, or high predation pressure have all been related with increased levels of glucocorticoids in primates [Cavigelli, 1999; Muller and Wrangham, 2004; Weingrill et al., 2004; Pride, 2005b] and vertebrates in general [Romero and Wikelski, 2001; Pereira et al., 2006; Ylönen et al., 2006; Angelier et al., 2007]. Hence, increased glucocorticoids secretion may be interpreted as an adaptive stress response to challenging situations [Sapolsky, 2002]. Since they can be measured in faeces, glucocorticoids provide a powerful non-invasive tool for evolutionary ecologists and wildlife managers [Pride, 2005a]. Moreover, high faecal glucocorticoids levels predict mortality in lemurs, for example [Pride, 2005a]. Causes of mortality that would correlate best with glucocorticoids levels include those that directly provoke a stress response, such as predator attack or conspecific agonism [Goymann et al., 2001]. Cortisol (the main glucocorticoid hormone in primates) has been used to evaluate primate physiological responses to a number of different stressors, including psychological stress [Norcross and Newman, 1999], social stress [Muller and Wrangham, 2004] and physical stress [Muller and Wrangham, 2004]. However, few attempts have been made to use cortisol to study environmental stress resulting from habitat fragmentation [Chapman et al., 2006].

19 5. GENERAL CONTEXT OF THE PRESENT STUDY

5.1 Madagascar: a biodiversity hotspot

Madagascar, officially the Republic of Madagascar (Malagasy: Repoblikan'i Madagasikara) and formerly known as the Malagasy Republic, is an island country in the Indian Ocean, off the coast of South-East Africa [Fig. 3]. The nation includes the island of Madagascar (the fourth-largest island in the world), as well as numerous smaller peripheral islands. Following the prehistoric breakup of the super-continent Gondwana, Madagascar split from India around 84-96 million years ago, allowing native plants and animals to evolve in relative isolation [Goodman and Benstead, 2003, Vences et al., 2009, Samonds et al., 2013].

Fig. 3 Madagascar location

As a result of the island's long isolation from neighbouring continents, Madagascar harbours a great variety of plants and animals found nowhere else on Earth [Tattersall, 2006; CI, 2011]. Roughly the 90% of all plant and animal species found in Madagascar are endemic, including the lemurs, the carnivorous fossa and many birds [Hobbes and Dolan, 2008]. More than 80% of Madagascar's 14883 plant species are found nowhere else in the world, including five plant families [Callmander et al., 2011]. Like its flora, Madagascar's fauna is diverse and shows a high rate of endemism: 100% of

20 amphibians and 92% of reptiles are endemic to the island [Goodman and Bestead, 2003]. Because of the high endemicity of its fauna and flora and due to the severe threats to the island's environment, Madagascar is considered an important global conservation priority [Mittermeier et al., 1998; Dumetz, 1999]. Since the arrival of humans around 2350 years ago, Madagascar has lost more than 90% of its original forest [Dupuy and Moat, 1998; Schwitzer et al., 2014]. According to a conservative estimate, about 40% of the island's original forest cover was lost from the 1950s to 2000 [Fig. 4], with a thinning of remaining forest areas by 80% [Harper et al., 2007]. As human population density increased on the island, deforestation accelerated beginning around 1400 years ago [Campbell, 1993]. At current deforestation rates it is estimated that in 2025 forest will only remain on the steepest slopes and in remote areas and nature reserves [Green and Sussman, 1990].

Fig. 4 Maps of distribution of rain forest in eastern Madagascar through time. Before human colonization, forest is thought to have covered much of eastern Madagascar includiing most of the eastern coast. [Green and Sussman, 1990].

This forest loss is mostly caused by tavy ("fat") [Fig. 5], a traditional slash-and- burn agricultural practice imported to Madagascar by the earliest settlers [Gade, 1996]. Beyond the traditional agricultural practice, wildlife conservation is endangered by the illegal cutting of protected forests, as well as the state-

21 sanctioned cutting of precious woods within national parks. Habitat destruction and hunting have threatened many of Madagascar's endemic species or led them to extinction.

Fig. 5 Tavy: a slash-and-burn area in the littoral forest of Sainte Luce. Photo by Marta Barresi, 2011

Madagascar is one of the first countries where the principles of the Biodiversity Convention and the IUCN-ICMM guidelines apply, indeed it is one of the countries with the highest biodiversity in the world [Ganzhorn, 2001]. The megadiverse countries are a group of countries that harbour the majority of the Earth's species and are therefore considered extremely biodiverse. CI identified 17 megadiverse countries, including Madagascar, in 1998: all are located in, or partially in, tropical or subtropical regions. On the biodiversity side, Madagascar has been also identified as one of the world's most important biodiversity hotspots [Myers et al., 2000; Mittermeier et al., 2004]. Conservation International defines a biodiversity hotspot as following: a biodiversity hotspot is a biogeographic region with a significant reservoir of biodiversity that is under threat from humans. To qualify as a biodiversity hotspot, a region must meet two strict criteria: it must contain at least 0.5% or 1500 species of vascular plants as endemics, and it has to have lost at least 70% of its primary vegetation [Myers, 2000].

22 5.2 The south-eastern humid littoral forest in the Anosy region: the hottest spot in the hot spot

The Anosy region [Fig. 6] is one of the ecologically most diverse regions of Madagascar [Barthlott et al., 1996; Goodman et al., 1997; Ramanamanjato et al., 2002], but also one of the poorest and most isolated of this island nation. The littoral forest ecosystem, which is limited to unconsolidated sand in a tight coastal band extending along Madagascar's east coast from north of Vohimarina to just south-west of Tolagnaro [Consiglio et al., 2006], has long been subjected to both natural disturbances, such as cyclones, and anthropogenic pressures such as fires, deforestation, conversion for agriculture, and urban expansion [Rabenantoandro et al., 2007:3.1]. Among the threatened ecosystems of Madagascar, the south-eastern humid littoral forests have been Fig. 6 The Anosy region (in red) and the Fort- assigned high conservation priority [Ganzhorn et al., Dauphin area. 1997; Dumetz, 1999; Ganzhorn et al., 2001; Ratsirarson and Goodman, 2005; Bollen and Donati, 2006]. The littoral forest on sandy soils in the Fort Dauphin region is one of the most endangered Malagasy ecosystems, with less than 2835 ha remaining [QMM, 2001]. Tolagnaro regional forest area was in constant decline between 1972 and 2002. In total, 26536 ha (40%) were cleared during those 30 years, equivalent to an average annual surface of 885 ha. The data indicate a high increase of deforestation between 1992 and 2002. In ten years, roughly 14000 ha of forest have been removed, and lowland formations have been severely damaged. Slash-and-burn culture is the main cause of this deforestation [Rabenantoandro et al., 2007]. The surface of littoral forest declined by 4022 ha (56%) between 1950 and 2005, which corresponds to an average annual loss of 73 ha. In 2005, just 3128 ha of littoral forest remained in the Tolagnaro area, allocated in three distinct areas, Sainte Luce, Mandena, and Petriky [Fig. 7]. The littoral forests at Petriky,

23 Mandena, and Sainte Luce have been severely degraded due to human exploitation especially during the last decade. The remaining forest is composed by approximately 250 individual fragments at different levels of degradation, from mostly intact to highly impacted, and ranging in size from 0.07 ha to 252 ha [Bollen and Donati, 2006; Rabenantoandro et al., 2007]. Levels of degradation are higher in the Mandena and Petriky areas, than that of Sainte Luce. These differences are related to significant pressure applied by the local population for slash-and-burn agriculture and charcoal production. Between 1995 and 1998, there was an increasing of charcoal production at Mandena. This rapid exploitation drove to the creation of a 230 ha conservation zone at Mandena in 1999, within a program for an efficient, community-based management of about 2000 ha of the Mandena forests. These conservation actions drew to an important reduction in deforestation between 1998 and 2005.

Fig. 7 Maps of the Sainte Luce, Mandena and Petriky areas in south-eastern Madagascar, indicating the location of major littoral forest parcels (light green), including those that comprise the established conservation zones at the two sites (dashed red and yellow lines) [Lowry et al., 2008].

In 2005, the littoral forest of the Tolagnaro region constituted about 6.5% of the country's remnant littoral forests, which represents less than 1% of all the remaining surface area of Malagasy forests [Consiglio et al., 2006].

24 By 2005, only 36% of the regional littoral forests remained in good state and 64% were degraded. These high rates of degradation are due to charcoal production in the Mandena and Petriky zones and selective tree cutting in Sainte Luce area. This deforestation caused a significant loss of habitat and the fragmentation of the littoral forests [Vincelette et al., 2007c]. Theoretically, forests can tolerate a certain level of selective cutting if it is practised in accordance with a precise management plan that applies a realistic rotation related to forest growth patterns [Armitage, 1998]. However, this type of sustainable management is not currently carried out on Madagascar because of the socio-economic situation, thus the forest degrades accordingly [Vincelette et al., 2007c].

5.3 The role of QMM (QIT Madagascar Minerals)

Some reforestation actions have been carried out by Rio Tinto, a mining company. This effort includes the creation of 2 tree nurseries near Fort Dauphin. The nurseries plant some 600 tree species native to Madagascar [Vincelette et al., 2007b]. However, in 2003, Rio Tinto also declared plans to mine ilmenite (used to make toothpaste and paint) in southern Madagascar. QIT Madagascar Minerals (QMM) is an organization jointly owned by Rio Tinto plc, UK and the Malagasy State represented by the Office des Mines Nationales et des Industries Stratégiques de Madagascar (OMNIS). Beginning in 1986, QMM performed an extensive exploration program along the eastern coast of Madagascar for heavy mineral sands, which are a source of titanium dioxide, mainly in the form of ilmenite and rutile. The major sediments are located underneath some of the last remaining littoral forest in south-eastern Madagascar, at Mandena, Sainte Luce, and Petriky [Vincelette et al., 2003, 2006]. The project was developed over 20 years and went through several steps into the recognition of the importance of the region's biodiversity [Vincelette et al., 2007a]. In late 2003, Rio Tinto gave additional support to biodiversity issues with the declaration of its biodiversity strategy and relate position statement, biodiversity principles and technical guidance documents [Rio Tinto, 2004]. The Rio Tinto

25 Biodiversity Strategy and Guidelines was officially launched in November 2004 during the IUCN World Conservation Congress in Bangkok [IUCN, 2004]. Since 1989, QMM has provided important economic and administrative support to researches that aimed at describing the flora and fauna of the Anosy Region, at identifying local and regional endemic species, habitats, ecosystem diversity, and their biogeographic relationships. Moreover, other studies concerning socio-economic aspects and the interface between human necessities and conservation issues have also been carried out. In collaboration with several institutional partners the main goals of these research programs can be summarized in: 1. Conservation of the regional biodiversity; 2. Rehabilitation of land after mining; 3. Partial restoration of natural ecosystems after mining; 4. Sustainable utilization and management of local natural resources. Biodiversity programs include biodiversity monitoring on the level of communities, populations, and population genetics, endemic species conservation plans, endangered lemur translocation program, and long-term seed conservation. The QMM environmental program also deals with education issues, a fundamental starting point to improve conservation, by initiatives such as the development of a littoral forest flora field guide. Nonetheless, international and national student programs and field schools have visited and worked on the site in the last fifteen years [Vincelette et al., 2007a]. All of these actions have been or are currently being carried out at Mandena as trials. Large-scale offsite tree plantations have been sowed at Mandena and Conservation Zones have been realised at Mandena and Sainte Luce before mining. All these measures have been implemented in close partnership with the local populations and authorities [Vincelette et al., 2007a]. The principle of active and reciprocal partnership, mutual respect, and long-term commitment has been stated in the Mandena Co-Management Agreement [Rarivoson, 2007]. In Madagascar, that is among the poorest nations in the world and is characterized by limited State intervention, the decentralized management of renewable natural resources has been suggested as an important means for inverting degradation and poverty trends [Polfor and Miray, 1998]. 26 6. THE AIM OF THIS STUDY

6.1 General goals

As Malagasy forests are being fragmented the remaining patches are being increasingly isolated and inaccessible to arboreal lemur species [Ganzhorn et al., 2001]. Large frugivores are often the most vulnerable to habitat fragmentation [Kannan and James, 1999] and this is the case for Eulemur collaris in the littoral forest of South-eastern Madagascar [Fig. 8]. Previous studies in degraded and/or fragmented areas have underlined the influence of habitat modification on primate ecology and behaviour [Lehman et al., 2006; Ganzhorn et al., 2007]. The most significant changes concern time budget, feeding choices, social interactions, groups' size and structure, animal distribution [Donati, 2002; Bollen and Donati, 2005; Lehman et al., 2006; Ganzhorn et al., 2007; Donati et al., 2007a; Donati et al., 2011a; Campera et al., 2014]. As part of a long-term study on Eulemur collaris in littoral forest fragments conducted in 2011, four MSc students from Pisa University supervised by Dr. Giuseppe Donati have collected eco-ethological data such as habitat use, activity patterns, feeding ecology, behavioural thermoregulation, social structure and anti-predator behaviours at two littoral forest sites, Mandena and Sainte Luce. Moreover, faecal samples have been collected at both study sites in order to evaluate glucocorticoids content as a measure of physiological stress in the animals. Floristic and structural features of the Mandena forest show a fragmented and seriously compromised habitat as compared to Sainte Luce [Vincelette et al., 2007c; Donati et al., 2007b]. Thus, the degradation of the forest of Mandena provides a model to study and possibly understand ecological and behavioural mechanisms used by medium-sized lemurs to cope with such a degraded habitat, by comparing it with a well preserved similar floristic composition, i.e. Ste Luce area (one of the most intact littoral forests remaining in Madagascar [Dumetz, 1999]). The collected data allowed to integrate previous knowledge on Eulemur collaris,

27 especially for what concerns their ecological and social response to fragmentation. Since this was a one-year work carried out by four different students as a team, some of the studied aspects (habitat use, activity patterns, feeding ecology, behavioural thermoregulation, and sociality) have been analysed and discussed in the two previous theses by Valentina Serra and Marco Campera, while the physiological stress has been evaluated in a third thesis by Michela Balestri.

The comparison of the data obtained from groups living in well preserved and in degraded habitats have shown ecological and social strategies/behaviours used by E. collaris to survive in a secondary forest. It was revealed that the animals living in the degraded forest are indeed more stressed from a physiological point of view compared with the conspecifics living in the more preserved area [Balestri et al., 2014].

6.2 Hypothesis of investigation

In this thesis I will focus on another important aspect related to habitat degradation and fragmentation, that is, the landscape of fear surrounding the lemurs. Indeed we expect a higher perceived predation risk among the groups living in the degraded area compared with lemurs living in the more preserved one.

More in detail, I will test the following research hypotheses:

ECOLOGICAL CORRELATES TO PERCEIVED PREDATION RISK IN LEMURS:

1. Are there any differences between the degraded forest (Mandena) and the more intact one (Ste Luce) in terms of animals' perceived predation risk?

As a consequence of habitat degradation and the related canopy reduction, and

28 according to a higher edge effect in the more fragmented forest, I would expect that lemurs living in Mandena should be more exposed, thus they should perceive a higher predation risk, measured in terms of frequency of anti- predatory behaviours.

2. Are there any differences between the lemur groups studied in terms of perceived predation risk, due for example to their different home ranges and group size?

According to the theory of dilution effect, and to the possibility of sharing vigilance tasks, I would expect a lower perceived predation risk in larger groups rather than in small groups.

3. Does the animals' use of the tree crown influence their perceived predation risk?

Since the main predators of Eulemur collaris in the two study areas are aerial predators [Donati, pers. comm.], I would expect that the animals perceive a higher predation risk when they are at the extremities of the crown.

4. Does the animals' use of the canopy influence their perceived predation risk?

Assuming that aerial predator attacks are most likely to happen in the upper part of the canopy, where the lemurs are more exposed, I would expect a higher perceived predation risk when they are in the upper forest layer.

5. Does the presence of other individuals sharing the same feeding or resting patch (party size) influence the frequency of anti-predator behaviours?

I would expect that the distance at which the animals are able to detect predators to increase with the size of their party, as it has been observed in other studies.

29 6. Are there any differences in terms of perceived predation risk caused by seasonal variations (as a consequence of food resource fluctuation) in the lemurs' daily distance travelled?

Assuming that the animals moving further tend to be more conspicuous (because of the higher patch depletion rate), I would expect them to be more vigilant and thus to spend more time scanning the environment than those moving less.

7. Since habitat differences have been related to difference in physiological stress in these lemurs [Balestri et al., 2014], is there any correlation between animals' landscape of fear and their physiological stress?

I would assume that more stressed animals should perform less frequent anti- predator behaviours being in a state of either potential nutritional deficit (the more likely cause of stress in these forests) or reproductive effort and thus less able to cope with other survival behaviours.

Since it was proposed that animals' spatial range use is mainly influenced by the distribution of resources and the presence of predators [Willems and Hill, 2009], all the above hypotheses will be tested both during feeding and during resting. Whereas the effect of resource distribution is essentially a direct effect of local availability, the influence of predators is mainly indirect: this means that, while the distribution and availability of resources are informative predictors of a species’ spatial ecology, predator distribution and density per se are not. Nevertheless, it was suggested that animals adjust their habitat use to their perceived predation risk [Lima and Dill, 1990; Willems and Hill, 2009]. In light of these considerations, I predict a difference in terms of resource priority and lemurs' perceived predation risk between the time spent feeding and the time spent resting. More in detail, I expect that each ecological correlate to perceived predation risk in the animals may influence anti-predator behaviours in a different way depending on whether lemurs are feeding or they

30 are resting. In fact, whereas the lemurs can actively choose the areas where to rest, the spots chosen for feeding are instead an obligate choice due to the scattered distribution and the highly variable availability of food resources. Thus, I expect the animals to be more vigilant and to perform more alarms while they are feeding.

SOCIAL CORRELATES TO PERCEIVED PREDATION RISK IN LEMURS:

1. In order to elucidate the possible advantage of the multimale-multifemale social structure in terms of vigilance efficiency, I will test if there are any differences in terms of frequency of anti-predator behaviours between sexes, and/or between low-ranked and high-ranked individuals.

Since it was proposed a possible anti-predator role of subordinate individuals, especially in the case of the extra-males which are observed in this brown lemur species, I would therefore expect a higher frequency of anti-predator behaviours and vigilance by males rather than by females, and/or by low-ranked individuals rather than by high-ranked ones.

2. Finally, I will test if there are any differences in terms of frequency of anti- predator behaviours between the season in which infants are present and that one in which they are not.

I predict a higher frequency of alarms and vigilance in the presence of offspring, that should be most vulnerable to predator attacks.

Answering all these questions may give a further insight into the eco-ethological responses and adaptations put in place by a medium-sized and flexible lemur species in order to cope with habitat fragmentation and degradation. This aims at providing additional conservation guidelines to preserve a species that is crucial to the littoral forest restoration, due to its fundamental ecological role for seed dispersal. Being the largest lemur species in the area, this animal represents a so-called “umbrella” species, that means that by protecting Eulemur collaris the entire littoral forest ecosystem can be preserved.

31 Hence, understanding the relationship between perceived predation risk and forest fragmentation is important in terms of ecology and conservation management.

Fig. 8 The humid littoral forest of South-East Madagascar. Mandena, Fort Dauphin. Photo by Marta Barresi, May 2011

32 MATERIALS AND METHODS

1. STUDY AREA

1.4 Study sites

This comparative study was conducted in the littoral forest fragments of Mandena (MAN) and Sainte Luce (STL) near Fort Dauphin in south-eastern Madagascar [Fig. 9].

Fig. 9 Forest conservation status at the two study sites. Map of the littoral forest areas remaining in 2000 at Ste Luce and Mandena. Conservation status of the forest fragments is indicated by colours: intact (dark green), well preserved (light green), fairly degraded (yellow), heavily degraded (orange), extremely degraded (red). Conservation Zones are indicated by dashed lines. Map provided by QMM This region is characterized by a tropical wet climate, with average monthly temperatures of 23°C (range: 18.2–25.9; n= 30), annual rainfall ranging from 1600–2480 mm, and no clear dry season [Bollen and Donati, 2005]. The Conservation Zone of Mandena (24°57' S, 47°0' E), 11 km North-West of Fort Dauphin, is located on sandy soils at an altitude 0–20 m above sea level. This study was conducted in M15 and M16 fragments (about 148 ha of “fairly degraded” littoral forest), included in the Conservation Zone (fragment numbering system proceeds from East to West). Approximately 82 ha of interspersed marsh and swamp connect the two fragments. Because collared lemurs used the swamp for travelling, feeding and resting, but also for drinking during the hottest periods, the two fragments (M15 and M16) and the swamp have been considered as a single area of about 240 ha, included in the Conservation Zone. M15/M16 are the only two forest fragments where collared lemurs are still present at this site [Donati et al., 2007a]. The average canopy height in M15 and M16 is 8.9 ± 4.4 m and the understorey is dense [Rabenantoandro et al., 2007]. In addition, some groups of Eulemur collaris use to live in another smaller fragment not included in the Conservation Zone: M20, that is approximately 6 ha of “heavily degraded” forest, and is located North- East of the other two fragments [Ganzhorn et al., 2007]. Red-collared lemurs use especially the swamp that links M20 with the other fragments. This swamp (about 40 ha) is called by local people analamafotra (ala = forest) from the vernacular name of the tree (mafotra) that characterize this swamp (“the forest of mafotra”). This swamp is out of the Conservation Zone and local people use it to pick up fruits, gather dead woods, and cut trees. In addition to Eulemur collaris, four nocturnal lemur species (Microcebus murinus, Cheirogaleus medius, Cheirogaleus major, Avahi meridionalis), and one cathemeral lemur species (Hapalemur meridionalis) live in this area. The second study site, the littoral forest of Sainte Luce (24°46’S, 47°10’E), around 30 km North of Fort Dauphin, is among the most intact littoral ecosystems in Madagascar and possesses a very high vegetation diversity [Bollen and Donati, 2006]. The 377 ha forest block S9 is one of two fragments where collared lemurs still occur in the STL area [Donati et al., 2007a]. This study was carried out in the fragment S9, about 252 ha of “well preserved” littoral forest and swamp, 190 of which are included in the Conservation Zone. E. collaris still occur in S17, an “almost intact” fragment of 237 ha, all included in the Conservation Zone. We studied only groups in S9 because in S17 there are no trails and there is no biological station as in S9. Moreover, in the fragment S17 it is more difficult to detect and track the lemurs, because of the lack of habituation and the proximity to the Ocean, whose noise strongly disturbs the observations. The average canopy height in S9 is 14.7 ± 4.3 m [Rabenantoandro et al., 2007]. In addition to Eulemur collaris, four nocturnal lemur species (Microcebus murinus, Cheirogaleus medius, Cheirogaleus major, Avahi meridionalis) live in S9. Hapalemur meridionalis is not present in Sainte Luce. Floristically, MAN and STL littoral forests are very similar, suggesting that these two areas were once connected [Rabenantoandro et al., 2007]. However, structural differences indicate that at the time of study, the forests of MAN represent degraded forms of the vegetation type in STL. This deduction is also suggested by the disappearance of some tree families known to be logged in MAN but not in STL [Rabenantoandro et al., 2007]. Forest degradation was evaluated in the two areas by estimating the percentage of surface area occupied by the canopy. This analysis resulted in the two categories of ‘‘intact to slightly degraded’’ and ‘‘degraded to highly degraded’’ for S9 and M15/M16, respectively [Vincelette et al., 2007]. Phenological records from the region [Bollen and Donati, 2005] indicate that there is a distinct peak in fruit production during the hot-wet season (December- February), while fruit availability is particularly low during the cool-wet season (June-August). Individuals of red-collared brown lemurs currently living in the Mandena forest fragments have been translocated in M15 and M16 between 2000 and 2001 [Donati et al., 2007b] from other littoral forest fragments (M3 and M4), threatened by charcoal makers. M15 and M16 in the meanwhile became an effective protected area. Translocation is rare in lemurs, and it is a risky option, but in this case it was the only opportunity to prevent the extinction of the species at Mandena (now M3 and M4 do not exist any more). At the moment of translocation the animals were 28, resulting in a density of 12 individuals per km2 [Donati et al, 2007b]. Then, after a small reduction, they were 36 in 2003, suggesting a good response to translocation and a good adaptation to the new habitat [Donati et al., 2007b]. Unfortunately, in 2004 animals decreased to 25 because of predation by immigrated subjects of Cryptoprocta ferox, that, subsequently, have been captured and then transferred to the Antananarivo Botanical and Zoological Park of Tsimbazaza. During our study period the population of red-collared brown lemurs in Mandena was between 12-17 animals. The cause of this reduction of population density is still unknown. It may be due to predation, scarcity of food resources, or to animal migration towards other forest fragments out of the Conservation Zone. Thus, during our observation period, the density of E. collaris in Mandena was about 4.8-7 individuals per km2. This is well below the density of 38 ind/km2 found in Sainte Luce in 2002 [Donati, 2002], which probably increased further until 2011 due to ceasing of human hunting.

2. STUDY SPECIES

2.1 Eulemur collaris (É. Geoffroy, 1817)

The collared brown lemur (Eulemur collaris) [Fig. 10], also known as the red- collared brown lemur or red-collared lemur, is a medium-sized strepsirrhine primate and one of twelve species of brown lemur (genus Eulemur) in the Lemuridae family (infraorder Lemuriformes) [Mittermeier et al., 2010]. Formerly considered a subspecies of the common brown lemur Eulemur fulvus (É. Geoffroy, 1817), the collared brown lemur was promoted to full species status in 2001 by the biological anthropologist Colin Groves together with all former E. fulvus subspecies (E. albifrons, E. cinereiceps, E. fulvus, E. rufus, E. rufifrons and E. sanfordi) [Wilson and Reeder, 2005; Markolf and Kappeler, 2013]. Fig. 10 Adult female of Eulemur collaris of Group AB in Mandena forest, in curled resting posture. Photo by Marta Barresi, 2011

This lemur is found in tropical moist lowland and mountain forests of southeastern Madagascar from the southern limits of the Ambatotsirongorongo transitional forest south- west of Tolagnaro [IUCN, 2014] north to the Mananara River [Fig. 11].

Fig. 12 Red-collared brown lemur (Eulemur collaris). Adult male of Group AB, during resting, Mandena. Photo by Marta Barresi, 2011 Fig. 11 Distribution of Eulemur collaris (in red). The western limits of the range are the forests of the Kalambatritra region. The Mananara River serves as a boundary between Eulemur collaris and its sister species Eulemur cinereiceps, except for isolated populations at Midongy du Sud National Park [Irwin et al., 2005] and at Vohipaho, near Vangaindrano [IUCN, 2014]. There are also small populations of E. collaris in the littoral forest fragments of the Mandena Conservation Zone, Sainte Luce Conservation Zone and Sainte-Luce Private Reserve [Donati et al., 2011], as well as in the Andohahela National Park [Mittermeier, 2006]. The Red-Collared Brown Lemurs [Fig. 12] are found in wet forest habitats and they have been studied in the littoral forest fragments of Sainte Luce and Mandena [Donati et al., 2007, 2011; Donati and Borgognini, 2006; Campera et al., 2014, Balestri et al., 2014]. In littoral forest fragments densities of this species are high (74 to 139 individuals/km2) [Ganzhorn et al., 2007]. In Midongy du Sud, densities were recorded at 14 individuals/km2 [Irwin et al., 2005]. In Andoahela National Park and Tsitongambarika the densities recorded are 8 and 11 individuals/km2, respectively [Nguyen et al., 2013]. In littoral forest fragments ranging areas vary from 20 to 100 hectares depending on habitat type, and social groups tend to be multi-male/multi-female with average group size from 2 to 17 individuals depending on habitat degradation [Donati et al., 2011; Campera et al., 2014]. Groups can include as much as 22 individuals in rainforest areas [Donati, pers. comm.]. The red-collared brown lemur is largely frugivorous with minor proportions of flowers and young leaves in the diet during the year (120 plants species from 45 families [Donati et al., 2007]). The most important plant species included in the diet are Syzigium spp., Dypsis spp., and Uapaca spp.. Eulemur collaris is a medium-sized lemur, mean body mass is 2.15±0.25 kg and mean body length is 46.1±2.6 cm (n=11) [Donati et al., 2011]. Like most species of lemur, it is arboreal, moving quadrupedally and occasionally leaping from tree to tree. Females give birth in September/October after a gestation of about 120 days and twins are not rare [IUCN, 2014]. This species is sexually dichromatic: - in males the dorsal coat is brownish-grey, the tail is darker, and there is also a dark stripe along the spine. The ventral coat is a paler grey. The muzzle, face and crown are dark grey to black. The creamy to rufous-brown cheeks and beard are thick and bushy, while the creamy to grey-coloured eyebrow patches vary in their prominence [Fig.13]; - in females, the dorsal coat is browner or more rufous than that of the male. The ventral coat is a pale creamy-grey. The face and head are grey. The cheeks are rufous-brown, but less prominent than in males [Fig. 14]. Both sexes have orange-red eyes [Mittermeier et al., 2010].

Fig. 14 Adult female of Group AB in Fig. 13 Adult male of Group AB in Mandena Mandena forest. Photo by Marta Barresi, forest. Photo by Marta Barresi, 2011 2011

The red-collared brown lemur, and brown lemurs in general, have been described as highly flexible in their ecology, according to their broad geographic distribution which includes several different habitat types and elevation zones [Tattersall and Sussman, 1998; Goodman and Ganzhorn, 2004]. Although E. collaris is a mainly frugivorous species, it can feed on leaves or less nutritious food when fruits are not available [Donati et al., 2011]. In fact, Malagasy rainforests represent a challenging environment for arboreal frugivorous primates as compared to other tropical forests [Ganzhorn et al., 1999; Wright, 1999; Ganzhorn, 2002; Bollen and Donati, 2005; Wright et al., 2005]. The unpredictable phenology and seasonal lean periods make these forests a hard challenge also for this species, despite its social and ecological flexibility [Donati et al., 2011]. This species is the largest lemur of the humid littoral forests of South-East Madagascar [Donati et al., 2007a], where it plays a fundamental ecological role as the principal seed disperser for many species of plants [Ganzhorn et al., 1999; Birkinshaw, 1999, 2001; Holloway, 1999, 2003; Bollen and Donati, 2006]. Red-collared brown lemur groups are defined as multimale-multifemale and they consist of related females associated with a conspicuous number of unrelated males [Donati et al., 2007a]. It seems that in this species there is female phylopatry and male dispersion [Donati, pers. observ.]. Since in most primates females tend to outnumber males and there is a tendency to polygynous groups, it is not yet clear why the groups of Eulemur tolerate a sex- ratio in favour of males. In E.collaris therefore a possible role of the extra-males in thermoregulation or in anti-predator behaviours has been hypothesized [Overdorff, 1998]. Red-collared brown lemurs are cathemeral [Tattersall, 1987], this activity pattern provides temporal flexibility in foraging, optimizing the exploitation of food resources during times of greatest abundance and quality, and low predation risk [Curtis and Rasmussen, 2006]. Cathemeral activity in E. collaris is strongly influenced by nocturnal luminosity and photoperiodic variations and it seems to be higher during the dry season, while a mostly diurnal activity is observed in the wet season [Donati and Borgognini-Tarli, 2006]. Eulemur collaris is listed as Endangered in the IUCN Red Lists of Threatened Species as this species is suspected to have undergone a population decline of ≥50% over a period of 24 years (three generations), due primarily to continuing decline in area, extent and quality of habitat [Andriaholinirina et al., 2014]. Illegal hunting for food by using traps seems to be a major problem for this species in some areas [Bollen and Donati, 2006]. However, the principal threat to the survival of E. collaris is habitat destruction, due to charcoal production and slash-and-burn agriculture [Bollen and Donati, 2006]. Ilmenite mining is also threatening the remaining populations occurring in littoral forest fragments. 3. DATA COLLECTION

3.1 Study period and groups composition

The data were collected in the field from February, 2011 to January, 2012, as a one-year project carried out by a team of students (Valentina Serra and Marta Barresi from February to July 2011, with the support of Murielle Ravaolahy from February to April; Michela Balestri and Marco Campera from July 2011 to January 2012). The data collected in July included a set of observations performed in pairs (Valentina Serra and Marco Campera; Marta Barresi and Michela Balestri) in order to evaluate and minimize the inter-observer variability. Data were recorded on four groups of Eulemur collaris: two groups living in Mandena (group AB-MAN and group C-MAN), and two groups living in Sainte Luce (group A-STL and group B-STL) [Table 1].

STL MAN Group A Group B Group AB Group C Adult males 4 3-4 2-3 2-3 Adult females 3 3-4 1 1-2 Juveniles 1 2 0 1 Infants 5 3 1 1 Total 8-13 8-11 3-4 5-6 Table 1 Composition of the four study groups over the full study period (February 2011 – January 2012) at Sainte Luce (STL) and Mandena (MAN).

Unfortunately, in Mandena, due to the very high water level of the swamp where Group C-MAN lived for most of the time, it was impossible to follow this group before the month of June, when the marsh conditions eventually allowed to conduct the observations. Furthermore, the same adverse swamp conditions and the arrival of a cyclone made it impossible to observe the group AB-MAN in the month of February. To ensure systematic observations, four animals (one for each group) were captured to install radio-tag collars and track them by the use of a radio-tracking SIKA receiver (Biotrack). The adult individuals (one for each group) were captured by caging them, using banana slices as a bait [Fig. 15], and rapidly anaesthetized with Zoletil 100 (5 mg/kg of tiletamine hydrochloride) to prevent trauma. Morphometric measurements were taken [Fig. 16] and then thermo- sensitive collars TW-3 (Biotrack, medium mammal tag) were attached. All animals recovered from anaesthesia within 1.5 hours and were not moved from the capture area nor kept in a cage, but were observed until regaining full mobility and rejoining thier own group. There were no injuries as a consequence of the captures.

Fig. 15 First capture (Sainte Luce, Fig. 16 First capture (Sainte Luce, February 2011). Adult female of Group A- February 2011). Morphometric STL, captured by the use of cage and measurements: canine length. Photo by banana slices as a bait. Photo by Marta Marta Barresi, 2011 Barresi, 2011

At Sainte Luce every observed lemur received a Malagasy name at the beginning of the study (Group A-STL: Fana, Volana, Ala for females; Sotro, Rivotra, Masoandro, Chefo Be for males; Jaza and Kely for the two infants. Group B-STL: Lanitra, Kintana, Rano, Alina for females; Nify, Omby, Shielo, Fotsy for males; Biby and Mamy for the two infants). Whereas at Mandena the QMM Biodiversity Staff already named the lemurs (Group AB-MAN: Abelardo, Octavio, Eddy for males; Bàrbara for the only female. Group C-MAN: Apollo and Filippo for males; Mamiska and Tina for females; Lita for the only female infant). The identification of each individual during the observations in the field has been allowed by the presence of radio-collars (in the case of radio-collared animals) and in general by some distinctive features such as sexual dichromatism, and differences in individual body size, canine length, fur colour, tail aspect and other morphological traits.

Fig. 17 Behavioural data collection in the forest of Sainte Luce (S9 fragment). Resting session. Photo by Valentina Serra, 2011

3.2 Behavioural data

Habituated groups from each site were followed for a mean of four days per month. Overall, 962 diurnal observation hours at Mandena were compared with 1118 hours at Sainte Luce. The groups were followed from 6:00 to 18:00 during each observation day. A different focal animal per each observation day was chosen among the adult individuals, in order to spread evenly the time spent observing males and females. The focal animal was followed as long as possible, and substituted with the first visible animal of the same sex if it was lost. Behavioural data were collected using the Instantaneous Focal Sampling method, with records every five minutes, together with the Continuous (All Occurrences) method and the ad libitum method [Altmann, 1974]. Focal sampling is a sampling technique that focuses on a single individual for a particular time period recording all instances of its behaviour. The focal animal is chosen (randomly) prior to observations. By the use of instantaneous time recording the observer notes whether a behaviour is occurring at given intervals of time. This type of recording can be used to determine the proportion of times a behaviour occurred. It can also be used thus as a proxy to estimate the duration of the behaviour (depending on sampling interval relative to the duration of behaviour). While conducting focal samples, one is sometimes able to record some additional observations on an ad libitum basis. In the present study, this method was used to record some additional, potentially interesting information such as weather or any potential source of threat and/or disturbance for the animals (presence of birds of prey, snakes, any kind of anthropic disturbance). Continuous recording is a recording rule that notes all occurrences of behaviours over a determined length of time [Altmann, 1974]. This recording rule allows the researcher to measure the true durations of the behaviour patterns. Behavioural data concerned animal activity [Fig. 17]: resting, moving, feeding, social interactions and anti-predator strategies, all recorded by the use of a specific ethogram [Appendix I, adapted from Donati, 2002]. By the use of Instantaneous Focal Sampling, besides the main activities (feeding, resting, moving) of the focal animal, also huddling (remaining inactive in very close contact with one or more conspecifics, [Fig. 18]) was recorded, together with all resting/huddling postures, in order to study both behavioural and social thermoregulation in these populations of red-collared brown lemurs. Fig. 18 Huddling, social thermoregulatory behaviour. Radio-collared adult male of Group A in huddling with other conspecifics (Sainte Luce). Photo by Marta Barresi, 2011

Furthermore, food items and tree species, proximity of conspecifics, number of animals on the same crown (party size), height of the animal (estimated by the observer using 1 m as unit), and crown exposure (distance from the trunk) were recorded. In particular, three different positions in the crown were distinguished by dividing the crown in three concentric circles of similar radius as shown in Fig. 19: 1. lemurs resting or feeding near the trunk, that is the less exposed zone; 2. lemurs resting or feeding in the middle of the crown; 3. lemurs feeding or resting in the more external part of the crown, near the extremities of branches, that is the most exposed zone. By the parallel use of Continuous (All Occurrences) Method, quick behaviours (events) and ocial interactions were recorded each time they occurred. During the All Occurrences we also recorded the identity of the actor and of the recipient of the interaction. The behaviours recorded via the All Occurrences were divided in four different categories: associative (H, KC), affiliative (G, LK, MG), agonistic (BIT, CH, CU, DS) and olfactory (GO, HR, SG) behaviours. These data were analysed in order to evaluate dominance relationships among animals, and the results of this analysis were used to calculate individual ranks [Serra et al., in prep.]. By the same All Occurrences Method, behavioural data related to anti-predatory strategies, alarm calls and scanning (rapid head rotation, laterally and up, focusing the attention to monitoring the surrounding, especially the sky, [Fig. 20 and Fig. 21]), were recorded each time any individual within the group performed that kind of behaviour, always recording the identity of the animal which gave the alarm call or made the scanning. Visual scanning, or vigilance, is often interpreted as part of an anti-predator strategy [Pulliam, 1973; Elgar, 1989; Lima, 1990; Quenette, 1990; Caro, 2005]. Generally, it can be difficult to determine the target and thus to distinguish between anti-predator vigilance and social monitoring in free-ranging populations [but see Favreau et al., 2010], so an understanding of the functions of vigilance usually comes from evaluating the circumstances in which it occurs. However, vigilance seems to be more closely related to predation risk than to social risk in Primates and therefore likely has the principal function of predator detection [Gaynor and Cords, 2012].

Fig. 21 Scanning (or vigilance), anti- predatory behaviour, in Eulemur collaris. Adult radio-collared female of Group AB, Mandena. Photo by Marta Barresi, 2011

F ig. 20 Scanning (or vigilance), anti- predatory behaviour, in Eulemur collaris. Adult radio-collared female of Group AB, Mandena. Photo by Marta Barresi, 2011

Only the alarm calls for winged predator (labelled in the ethogram as “AC1”) were used in the present analysis of perceived predation risk. During this anti- predatory behaviour, the animals immediately climb down in the lower part of the trees and emit vocalizations. Red-fronted brown lemurs (Eulemur rufifrons) at Kirindy Forest react to Polyboroides radiatus, Buteo brachypterus and various Accipiter species flying overhead with alarm calls and by moving quickly to lower forest layers, where they remain motionless [Donati et al., 1999]. It was suggested that red-fronted brown lemurs and sifakas (Propithecus verreauxi verreauxi) may possess a "mixed alarm call system," characterized by predator-specific calls for raptors and unspecific alarm calls for terrestrial predators [Fichtel and Kappeler, 2002]. However, both species give specific alarm calls exclusively towards raptors, whereas terrestrial alarm calls are also given in other situations associated with high arousal, indicating that the acoustic structure of aerial alarm calls of both species may provide access to mental representations of raptors. Moreover, it seems that both species identified the presented stimuli as different categories of either terrestrial or aerial predators, or as aerial non-predators [Fichtel and Kappeler, 2002]. It was concluded that both lemur species have evolved a functionally referential alarm call system for aerial predators but not for terrestrial predators. Calls which were given in response to playbacks of terrestrial predators were also given in other contexts associated with affective states of arousal. They may therefore express the subjectively perceived urgency of a given threat [Fichtel, 2001]. This is exactly what was observed also in the present study on red-collared brown lemurs (Eulemur collaris), where the behaviour labelled in the ethogram as “AC2” (the animals climb up emitting vocalizations such as “croaks”, generally “staring” and performing “tail wagging”) often occurred not in the presence of a real terrestrial predatory risk but rather in situations of general disturbance [pers. obs.]. This is the reason why only AC1 and scanning (vigilance behaviour) were considered in the present analysis as a measure of perceived predatory risk in E. collaris. This choice seems to be supported by what it was observed in a species closely related to E. collaris, the red-fronted lemurs (E. rufifrons), which seems to give woofs not only towards simulated and real terrestrial predators, but also during disturbances, such as sudden approaches or movements of humans, aggressive interactions with conspecifics, or during mobbing of snakes [Fichtel, unpublished data]. Moreover, woofs are usually accompanied by "staring" and "tail wagging," behaviours associated with a state of high arousal [Pereira and Kappeler, 1997]. The continuum from huvvs to woofs may reflect different levels of arousal in these contexts, but this remains to be tested explicitly. In any event, these calls appear to indicate general disturbances, rather than only the presence of terrestrial predators. 3.3 Ecological data and habitat use

Feeding trees were marked during each instantaneous of feeding, and resting trees were marked after three consecutive instantaneous of resting with a flag signed by a specific code (group name-activity-progressive number) [Fig. 22], the height was evaluated by 1 m-intervals by the observer and the diameter at breast height (DBH) was measured. The field assistant provided the vernacular name of the species and a small branch sample for taxonomical identification: with these data a botanist of QMM was able to identify the scientific names of the plants.

Fig. 22 Resting tree marked by signed flag during the study period (Ste Luce). Photo by Marta Barresi, 2011

Every half hour the position of the animals was also recorded by GPS (Garmin eTrex Legend HCx). In total, 2310 GPS points were used to obtain home range estimates for the STL groups (1229 for group A, 1081 for group B), and 1731 GPS points were used to obtain home range estimates for the MAN groups (1090 for group AB, 641 for group C). Daily distance travelled (km) was also calculated for each day of data collection and then the monthly mean Daily Path Length (D.P.L.) for each study group was used as a covariate in the statistical model used in the present analysis on perceived predation risk. Structure and botanical diversity of the forest within the animals’ home ranges were studied by analysing five plots (20 m x 50 m) within the home range of each study group. Every tree with a DBH (Diameter at Breast Height) > 5 cm was considered, recording vernacular name, DBH and crown diameter. Also, the vertical forest structure was characterized in each plot via the Gautier method [Gautier et al., 1994]. This consists in holding a measuring pole vertically along a 50 m transect was across the middle of each plot. At 1 m intervals each point of contact of the pole with the vegetation is recorded. All data about activity pattern, habitat use, feeding ecology, behavioural thermoregulation and social structure were analysed and discussed by Valentina Serra and Marco Campera in their MSc dissertations. Vertical microhabitat selection was quantified as the daily proportion of records in the canopy. The median of the distribution of tree heights for each home range (considering all the five plots for each group) was chosen as the best representative proxy measure of the mean canopy height. This measure was divided by 2, in order to obtain the threshold which allowed to consider a lower part of the forest and an upper part, assuming the latter to be more exposed to potential aerial predators. In fact, the main predatory risk, especially for infants due to their size, in these forest fragments indeed seems to be represented by endemic birds of prey (Accipiter, Buteo, Polyboroides). The Henst’s goshawk (Accipiter henstii) is a forest raptor widely distributed throughout most of Madagascar but absent from the south-west [Langrand, 1990]. It is rare throughout its range [Langrand, 1990; Morris and Hawkins, 1998], but seems to live in almost all suitable large forest blocks that have been surveyed [Zicoma,1999]. Population size is estimated to about 670-2000 mature individuals, and distribution size (breeding/resident) to 503,000/km2. The Madagascar Buzzard (Buteo brachypterus) has a very large range, which covers all the Island. The population is stable, and its distribution size (breeding/resident) is estimated to 591,000/km2 [IUCN, 2014]. The Madagascar Harrier-hawk or Madagascar Gymnogene (Polyboroides radiatus) has an extremely large range, which does not include only the central highland region of the Island. The population is estimated to number 1000- 10000 individuals, approximately corresponding to 670-6700 mature individuals, and the distribution size (breeding/resident) is estimated to 414,000 km2 [IUCN, 2014]. Since 2004, when large viverrids Cryptoprocta ferox in the conservation zone of Mandena were captured and released in the humid forest of Tsitongambarika about 25 km north of Mandena [Donati et al., 2007], no terrestrial predators have been recorded any longer at both study sites.

3.4 Faecal samples and hormonal analyses

Faecal samples from each study group at the two study sites were collected over the whole study period. A total of 537 faecal samples were collected in parallel with behavioural observations [Fig. 23-24], in order to evaluate the Glucocorticoid Metabolites concentration as a measure of physiological stress in the animals. Many studies have used elevated blood glucocorticoid levels as an index of physiological stress in animals. However, this measure can be difficult to collect from free-ranging animals and can be compromised because capture and handling can lead to rapid and significant increases in circulating glucocorticoid levels [Sapolsky, 1982; Astheimer et al. 1994; Wingfield et al., 1994]. Traces of glucocorticoid hormones (GCMs) are detectable in faeces and can be used as a non-invasive measure of stress levels in free-ranging populations [e.g. Graham and Brown, 1996; Hofer and East, 1998].

Fig. 23-24 Faecal samples collection on the field. Photos by Valentina Serra, 2011 Due to the mainly frugivorous diet of Eulemur collaris, most of the collected faecal samples contained seeds. For the first set of faecal samples (from February 2011 to July 2011), we did not consider the fact that the faecal weights were affected by the presence of different amounts of seeds. In fact, hormone concentrations are related to the dry faecal weight. If the latter is influenced by variable amounts (and thus weights) of seeds, this will affect the faecal hormone concentration per faecal weight in an unpredictable way and, if seed weight is high, also to a great extent. The margin of error mainly depends on the relative proportion that seed weight has on the total faecal weight and this may obscure real hormone levels and may cause wrong interpretations of the hormonal data. For this reason we decided not to consider the first set of sample, even if we had the possibility to analyse 30 samples of the first set (in this case it was possible to remove seeds by tweezers when faeces were completely dry and then to determine the real faeces weight; the same process was followed on all the samples of the second set, from August 2011 to January 2012). A total of 279 faecal samples (from 2 to 25 per animal; Rano, a female of group B, was excluded as we did not have her faecal samples), were used for the statistical analysis as we had the real faeces weight. The faecal samples were collected immediately after defecation: site, group, date, time, and identity of the donor were recorded. Faecal samples were preserved in 10 ml tubes with 96% ethanol, until hormonal analysis. Ethanol was added at the end of each diurnal observation. Faecal samples were stored at room temperature for one year until processing, therefore a storage effect test was performed: the test showed that storing faecal samples in ethanol for a period of 12 months did not substantially affect GCMs levels. Therefore, since all faecal samples were extracted after the same period of storage (one year), it can be argued that differences in GCMs concentrations found in the analysis are reliable. All faecal samples were processed and hormonal metabolites extracted using the protocol [Appendix II] described by Heistermann et al. (1995). Briefly, each faecal sample was extracted with 3 ml of 80% ethanol by vortexing for 15 minutes. Following centrifugation of the faecal suspension, the supernatant was recovered and stored at -20°C until a hormone analysis was performed. Faecal extracts were then sent to the “Department of Reproductive Biology” of the “German Primate Centre” (Göttingen, Germany) where Dr. Michael Heistermann and his staff performed the second part of the procedure to obtain GCMs concentrations. All data about hormonal analyses and physiological stress in the four study groups were analysed and discussed by Michela Balestri in her MSc dissertation.

4. STATISTICAL ANALYSES

4.1 Ecological correlates to perceived predation risk

In order to measure perceived predation risk in the four study groups and to evaluate the hypotheses, I compared the monthly means of the daily frequency of anti-predatory behaviours performed by each group respectively during feeding and during resting time. Thus, the possible influence of the two sites (Mandena and Ste Luce), the group (A, B, AB, C), the height in the canopy, the crown exposure, the party size, the daily path length travelled by each group, and the physiological stress on the frequency of alarm calls and scanning were analysed using STATISTICA (version 8.0). The months were the unit of the analysis thus all the continuous predictor variables represented monthly proportions or monthly means. The comparisons were performed using two analyses of covariance (ANCOVA, GLM), one which included the variables recorded during feeding and one with the same variables recorded while the animals were resting. Frequencies of alarm calls and scanning were used as response variables, Site and Group as Between-Subjects Nested Fixed Factors (categorical variables), while height in the canopy, crown exposure, party size, daily path length, and physiological stress as fixed covariates (continuous predictors). In order to meet the assumptions of the model, the normality of the analysis residuals (errors of the model) was checked by Kolmogorov-Smirnov test. According to K-S test, all model residuals (errors) show a normal distribution (p=0.200 for alarm rate and p=0.972 for scanning frequencies during feeding; p=0.874 for alarm rate and p=0.605 for scanning frequencies during resting). The potential multicollinearity of the continuous predictor variables was tested by Spearman's rho correlation coefficients between pairs of variables, choosing only one of them when rho>0.7. Test for Multicollinearity has given a Spearman's rho<0.7 for all the predictors. In addition to the GLM (which included all the predictors) and to identify the bivariate differences between the four groups for all the response variables and continuous predictors used in the above model, the effect of the groups on each continuous variable used in the GLM was tested via a one-way ANOVA.

4.2 Social correlates to perceived predation risk

Furthermore, in order to test possible differences in the frequency of anti- predatory behaviours between the two sexes and the high-ranked/low-ranked animals related to the presence or absence of offspring, the study period was divided into a “pre-lactation” (PRE-LAC, from February to September) and a “post-lactation” (POST-LAC, from October to January) season. Then, the frequencies of alarm calls and scanning performed by each individual respectively during PRE-LAC and POST-LAC period were compared using STATISTICA (version 8.0). The comparisons were conducted using a Repeated Measures ANOVA model with Season as Within-Subjects Factor and Sex and Rank as Between-Subjects Factors. The unit of analysis was the individual subject. The normality of the model residuals was analysed by Kolmogorov-Smirnov test. According to K-S test, all residuals show a normal distribution (p=0.865 for alarm calls and p=0.883 for scanning). RESULTS

1. ECOLOGICAL CORRELATES TO PERCEIVED PREDATION RISK

1.1 Alarm rates during feeding and during resting at the two study sites

5. Are there any differences between the degraded forest (MAN) and the more intact one (STL) in terms of animals' alarm rate?

6. Are there any differences between groups in terms of lemurs' alarm rate?

The mean daily number of alarm calls performed by the four groups at the two study sites was 0.7 ± 1.1 for Group A-STL, 1.3 ± 1.6 for Group B-STL, 0.5 ± 1.0 for Group AB-MAN, 1.0 ± 1.4 for Group C-MAN during feeding, while we recorded 0.6 ± 0.9 for Group A-STL, 0.6 ± 1.2 for Group B-STL, 0.8 ± 1.1 for Group AB-MAN, 1.1 ± 1.5 for Group C-MAN during resting [Fig. 25]. No significant differences in terms of alarm rate were found between the two study sites neither during feeding [Table 2] nor during resting [Table 3]. No significant differences in terms of alarm rate were found between the four study groups neither during feeding [Table 2] nor during resting [Table 3].

Fig. 25 Mean daily number of alarm calls performed by the four study groups during feeding (red columns) and during resting (green columns) over the study period. Error bars represent standard deviations.

1.2 Scanning frequencies during feeding and during resting at the two study sites

8. Are there any differences between the degraded forest (MAN) and the more intact one (STL) in terms of scanning rate?

9. Are there any differences between groups in terms of lemurs' scanning rate rate?

The mean daily number of scanning performed by the four groups at the two study sites was 2.0 ± 2.6 for Group A-STL, 4.2 ± 3.8 for Group B-STL, 2.5 ± 2.6 for Group AB-MAN, 1.2 ± 1.7 for Group C-MAN during feeding, 6.0 ± 5.8 for Group A-STL, 4.7 ± 3.9 for Group B-STL, 9.1 ± 6.1 for Group AB-MAN, 4.3 ± 3.6 for Group C-MAN during resting [Fig. 26]. No significant differences in terms of scanning rate were found between sites neither during feeding [Table 4] nor during resting [Table 5]. A significant difference in terms of scanning rate was found between groups during feeding [Table 4], while a tendency towards a difference was recorded during resting [Table 5].

55 Fig. 26 Mean daily number of scanning performed by the four study groups during feeding (red columns) and during resting (green columns) over the study period. Error bars represent standard deviations.

1.3 Animals' exposure in the crown

3. Does the animals' exposure in the crown influence their perceived predation risk?

The percentage of time spent in the most exposed zone of the crown (position 3) by the four groups at the two study sites was 74% ± 16% for Group A-STL, 67% ± 20% for Group B-STL, 52% ± 27% for Group AB-MAN, 54% ± 21% for Group C-MAN during feeding, showing significant differences between the groups (one-way ANOVA: F3,42=3.193, p=0.034). During resting the values recorded have been 9% ± 13% for Group A-STL, 7% ± 9% for Group B-STL, 1% ± 4% for Group AB-MAN, 2% ± 6% for Group C-MAN showing significant differences between the groups (one-way ANOVA: F3,39=5.554, p=0.003). [Fig. 27]. The exposure on the crown had a significant effect on alarm rates during feeding [Table 2] but not during resting [Table 3]. No significant effect was found on scanning rate neither during feeding [Table 4]

56 nor during resting [Table 5].

Fig.27 Percentage of time spent in the most exposed zone of the crown by the four study groups during feeding (red columns) and during resting (green columns) over the study period. Percentages were obtained by daily proportion of instantaneous recorded in position 3 on the total of feeding instantaneous and resting instantaneous, respectively. Error bars represent standard deviations.

1.4 Animals' exposure in the canopy

4. Does the animals' exposure in the canopy influence their perceived predation risk?

Five plots for each study group were analysed by Gautier method to characterize the vertical structure of the forest within each home range: the distributions of tree heights in each home range are shown in Fig. 28 (AB- MAN), Fig. 29 (C-MAN), Fig. 30 (A-STL), Fig. 31 (B-STL).

57 58 59 For each distribution, the median value (AB-MAN: 7 m; C-MAN: 8 m; A-STL: 10 m; B-STL: 10 m) was chosen as the best representative proxy measure of the mean canopy height. Thus, lemurs were considered in the upper canopy layer when they were at H≤3.5 m for Group AB-MAN, at H≤4 m for Group C-MAN, at H≤5 m for Group A-STL, at H≤5 m for Group B-STL, respectively. The percentage of time spent upper in the canopy by the four groups at the two study sites was 83% ± 19% for Group A-STL, 80% ± 17% for Group B-STL, 81% ± 21% for Group AB-MAN, 65% ± 26% for Group C-MAN during feeding, resulting in non significant differences between the groups (one-way ANOVA: F3,42=1.406, p=0.255). During resting the values recorded have been 85% ± 16% for Group A-STL, 88% ± 11% for Group B-STL, 83% ± 23% for Group AB- MAN, 79% ± 26% for Group C-MAN with non significant differences between the groups (one-way ANOVA: F3,39=1.991, p=0.133) [Fig. 32]. No significant effect of the height in the canopy on alarm rates was found neither during feeding [Table 2] nor during resting [Table 3]. No significant effect of the exposure in the canopy on scanning rate was found, neither during feeding [Table 4] nor during resting [Table 5].

Fig. 32 Percentage of time spent in the upper part of the canopy by the four study groups during feeding (red columns) and during resting (green columns) over the study period. Percentages were obtained by daily proportion of instantaneous recorded at a height ≥median(H)/2 for each group home range on the total of feeding instantaneous and resting instantaneous, respectively. Error bars represent standard deviations.

60 1.5 Party Size

5. Does the presence of nearby conspecifics ( party size ) influence the frequency of anti-predator behaviours?

The mean daily number of animals on the crown at the two study sites was 2.9 ± 0.9 for Group A-STL, 3.0 ± 1.1 for Group B-STL, 2.1 ± 0.6 for Group AB-MAN, 0.6 ± 1.1 for Group C-MAN during feeding, resulting in significant differences between the groups (one-way ANOVA: F3,42=4.682, p=0.07). During resting the values recorded have been 3.0 ± 0.9 for Group A-STL, 3.2 ± 1.2 for Group B-STL, 2.2 ± 0.5 for Group AB-MAN, 2.8 ± 1.1 for Group C-MAN with significant differences between the groups (one-way ANOVA: F3,39=3.686, p=0.021) [Fig. 29]. Party size had a significant effect on alarm rates during feeding [Table 2] but not during resting [Table 3]. No significant effect of party size on scanning rates was found neither during feeding [Table 4] nor during resting [Table 5].

Fig. 33 Mean daily number of animals on the crown during feeding (red columns) and during resting (green columns) over the study period. Means were obtained by the proportion of the total daily number of animals on the crown on the total number of feeding instantaneous and resting instantaneous, respectively. Error bars represent standard deviations.

61 1.6 Daily Path Length

6. Are there any differences in terms of perceived predation risk related with lemurs' daily distance travelled?

The total mean of D. P. L. over the study period was 956.86 ± 256.80 km for Group A-STL, 1104.08 ± 263.42 km for Group B-STL, 832.85 ± 162.60 km for Group AB-MAN, 779.33 ± 127.97 km for Group C-MAN, resulting in significant differences between the groups (one-way ANOVA: F3,42=4.575, p=0.008) [Fig. 34]. D.P.L. had a significant effect on alarm rates during feeding [Table 2] but not during resting [Table 3]. D.P.L. had a significant effect on scanning frequencies during feeding [Table 4] but not during resting [Table 5].

Fig. 34 Mean Daily Path Lenght of the four study groups over the study period. Error bars represent standard deviations.

62 1.7 Physiological Stress

7. Is there any correlation between lemurs' landscape of fear and their physiological stress?

The total mean faecal GCMs concentration over the study period was 1479.89 ± 1056.53 ng/g for Group A-STL, 1224.48 ± 890.75 ng/g for Group B-STL, 1707.61 ± 1754.40 ng/g for Group AB-MAN, 1212.5 ± 597.89 km for Group C- MAN, resulting in no significant differences between the groups (one-way ANOVA: F3,42=0.318, p=0.813) [Fig. 35]. Physiological stress had a significant effect on alarm rate during feeding [Table 2], while this was not apparent during resting [Table 3]. No significant effect of physiological stress on scanning rate was found during feeding [Table 4], while a significant effect was found during resting [Table 5].

Fig. 35 Mean GCMs concentration levels in the four study groups over the study period. Means were obtained from the GCMs concentrations of each collected sample from individuals of each group. Error bars represent standard deviations.

63 1.8 Model outputs

On the whole, the GLMs have shown a significant effect of the animals' exposure in the crown, their party size, daily path length and physiological stress on monthly means of daily frequencies of alarm calls during feeding

2 sessions [Overall model: F8,27 = 3.508, p = 0.006, adjR = 0.364; Table 2]. On the contrary, during resting time no significant correlation between the independent variables and the alarm calls frequencies was found [Overall model: F8,27 = 0.768, p = 0.634, adjR2= 0.056; Table 3]. In terms of vigilance, during feeding sessions a significant effect of groups was found as well as a significant correlation between scanning frequencies and

2 D.P.L. [Overall model: F8,27 = 3.523, p = 0.006, adjR = 0.366; Table 4]. Differences between groups in terms of scanning rate show a tendency even during resting time and there is also a significant correlation between scanning frequency and the animals' physiological stress [Overall model: F8,27 = 2.391, p = 0.043, adjR2= 0.241; Table 5].

Type III Tests of Fixed Effectsa Source Numerator of Denominator of F p-value Degrees of Degrees of Freedom Freedom Site 1 27 1.306 0.263 Group(site) 2 27 1.342 0.278 Exposure in the Crown 1 27 13.342 0.001 Height in the Canopy 1 27 0.479 0.495 Party Size 1 27 9.479 0.005 D.P.L 1 27 5.490 0.027 Physiological Stress 1 27 4.226 0.049 a. Dependent Variable: ALARM CALLS. Table 2 Results of the GLM for the analysis with alarm rates during feeding as Dependent Variable. In the model, Site and Group are the Between-Subjects Nested Fixed Factors (categorical predictors), while Exposure in the Crown, Height in the Canopy, Party Size, D.P.L. and Physiological Stress are the covariates (continuous predictors). The effect of each independent variable was considered significant at p-values≤0.05. Significant results are shown in red.

64 Type III Tests of Fixed Effectsa Source Numerator of Denominator of F p-value Degrees of Degrees of Freedom Freedom

Site 1 25 0.837 0.368

Group(site) 2 25 0.001 0.998 Exposure in the Crown 1 25 1.776 0.194 Height in the Canopy 1 25 0.143 0.709 Party Size 1 25 0.081 0.777 1 25 D.P.L. 0.420 0.522 Physiological Stress 1 25 0.510 0.481 a. Dependent Variable: ALARM CALLS. Table 3 Results of the GLM for the analysis with alarm rates during resting as Dependent Variable. In the model, Site and Group are the Between-Subjects Nested Fixed Factors (categorical predictors), while Exposure in the Crown, Height in the Canopy, Party Size, D.P.L. and Physiological Stress are the covariates (continuous predictors). The effect of each independent variable was considered significant at p-values≤0.05. The model shows no significant results.

Type III Tests of Fixed Effectsa Source Numerator of Denominator of F p-value Degrees of Degrees of Freedom Freedom Site 1 27 0.080 0.779 Group(site) 2 27 4.100 0.028 Exposure in the Crown 1 27 0.100 0.754 Height in the Canopy 1 27 1.743 0.198 Party Size 1 27 2.365 0.136 D.P.L 1 27 8.259 0.008 Physiological Stress 1 27 0.472 0.498 a. Dependent Variable: SCANNING. Table 4 Results of the GLM for the analysis with scanning frequencies during feeding as Dependent Variable. In the model, Site and Group are the Between-Subjects Nested Fixed Factors (categorical predictors), while Exposure in the Crown, Height in the Canopy, Party Size, D.P.L. and Physiological Stress are the covariates (continuous predictors). The effect of each independent variable was considered significant at p-values≤0.05. Significant results are shown in red.

65 Type III Tests of Fixed Effectsa Source Numerator of Denominator of F p-value Degrees of Degrees of Freedom Freedom Site 1 25 1.973 0.171 Group(site) 2 25 3.051 0.064 Exposure in the Crown (R) 1 25 0.125 0.727 Height in the Canopy (R) 1 25 1.130 0.297 Party Size (R) 1 25 0.000 0.991 D.P.L. 1 25 1.155 0.292 Physiological Stress 1 25 4.446 0.044 a. Dependent Variable: SCANNING. Table 5 Results of the GLM for the analysis with scanning frequencies during resting as Dependent Variable. In the model, Site and Group are the Between-Subjects Nested Fixed Factors (categorical predictors), while Exposure in the Crown, Height in the Canopy, Party Size, D.P.L. and Physiological Stress are the covariates (continuous predictors). The effect of each independent variable was considered significant at p-values≤0.05. The model shows only a tendency towards significativity for the Group(site) Factor (in orange) and a significant effect for Physiological Stress (in red).

2. SOCIAL CORRELATES TO PERCEIVED PREDATION RISK

2.1 Frequency of alarm calls performed by the two sexes and by high and low ranked individuals in presence or absence of offspring

The total mean daily number of alarm calls performed was 0.53 ± 0.69 during pre-lactation season and 0.72 ± 0.35 during post-lactation season [Fig. 36 and Fig. 37]. The mean daily number of alarm calls performed by females was 0.45 ± 0.41 during pre-lactation season and 0.70 ± 0.29 during post-lactation season. The mean daily number of alarm calls performed by males was 0.59 ± 0.85 during pre-lactation season and 0.74 ± 0.34 during post-lactation season [Fig. 36]. The mean daily number of alarm calls performed by high ranked individuals was 0.41 ± 0.33 during pre-lactation season and 0.82 ± 0.33 during post-lactation

66 season. The mean daily number of alarm calls performed by low ranked individuals was 0.65 ± 0.94 during pre-lactation season and 0.60 ± 0.35 during post-lactation season [Fig. 37].

67 2.2 Frequency of scanning performed by the two sexes and by high and low ranked individuals in presence or absence of offspring

The total mean daily number of scanning performed was 1.63 ± 1.52 during pre- lactation season and 1.57 ± 1.52 during post-lactation season [Fig. 38 and Fig. 39]. The mean daily number of scanning performed by females was 1.89 ± 1.83 during pre-lactation season and 1.49 ± 1.68 during post-lactation season. The mean daily number of scanning performed by males was 1.43 ± 1.23 during pre-lactation season and 1.63 ± 1.48 during post-lactation season [Fig. 38]. The mean daily number of scanning performed by high ranked individuals was 2.01 ± 1.79 during pre-lactation season and 1.94 ± 1.66 during post-lactation season. The mean daily number of scanning performed by low ranked individuals was 1.23 ± 1.02 during pre-lactation season and 1.12 ± 1.27 during post-lactation season [Fig. 39].

Fig. 38 Mean daily number of scanning performed by females, by males and by all individuals during pre-lactation season (February-September) and during post-lactation season (October-January). Error bars represent standard deviations.

68 Fig. 39 Mean daily number of scanning performed by high ranked, low ranked and by all individuals during pre-lactation season (February-September) and during post-lactation season (October- January). Error bars represent standard deviations.

2.3 Repeated Measures ANOVA: statistical outputs

In order to verify a possible role of the extra-males in vigilance and predator detection, two hypotheses were tested:

6. Are there any differences in terms of anti-predator behaviours (a. alarm calls and b. scanning ) frequencies between males and females and/or between low-ranked and high-ranked individuals? a) No significant effect on alarm rate was found neither for the variable sex nor for the ranks [Table 6]. Moreover, no significant interaction effect (Sex*Rank) was found on alarm rate [Table 6]. b) No significant difference in terms of scanning rate was found neither between sexes nor between ranks [Table 7], nor interaction effects (Sex*Rank) were revealed by the analysis [Table 7].

69 Tests of Between-Subjects Effects Measure: ALARM CALLS Transformed Variable: Average Source df F p-value Intercept 1 25.017 0.000 rank 1 0.059 0.811 sex 1 0.456 0.509 rank * sex 1 0.577 0.459 Error 16 Table 6 Results of the Repeated Measures ANOVA Test of Between-Subjects Effects for the analysis with ALARM RATES as Dependent Variable. The effect of each independent variable was considered significant at p-values≤0.05. The model shows no significant results.

Tests of Between-Subjects Effects Measure: SCANNING Transformed Variable: Average Source df F p-value Intercept 1 24.867 0.000 rank 1 1.898 0.187 sex 1 0.012 0.915 rank * sex 1 0.060 0.809 Error 16 Table 7 Results of the Repeated Measures ANOVA Test of Between-Subjects Effects for the analysis with SCANNING RATE as Dependent Variable. The effect of each independent variable was considered significant at p-values≤0.05. The model shows no significant results.

7. Are there any differences in terms of frequencies of alarm calls (a) and scanning (b) between PRE-LAC season (absence of offspring) and POST-LAC season (presence of infants)? a) No significant difference in terms of alarm rate was found overall between the two seasons [Table 8]. Moreover, there was no significant interaction effect on alarm rates (Season*Rank or Season*Sex) [Table 8]. b) No significant difference in terms of scanning rate was found between the two seasons [Table 9]. Moreover, no interaction effect on scanning rates (Season*Rank or Season*Sex) was found in the analysis [Table 9].

70 Tests of Within-Subjects Contrasts Measure: ALARM CALLS Source season df F p-value season Linear 1 2.444 0.138 season * rank Linear 1 2.697 0.120 season * sex Linear 1 0.389 0.542 season * rank * sex Linear 1 0.496 0.492 Error(season) Linear 16 Table 9 Results of the Repeated Measures ANOVA Test of Within-Subjects Contrasts for the analysis with ALARM RATES as Dependent Variable. The effect of each independent variable was considered significant at p-values≤0.05. The model shows no significant results.

Tests of Within-Subjects Contrasts Measure: SCANNING Source season df F p-value season Linear 1 0.656 0.430 season * rank Linear 1 0.010 0.923 season * sex Linear 1 1.236 0.283 season * rank * sex Linear 1 0.308 0.586 Error(season) Linear 16 Table 10 Results of the Repeated Measures ANOVA Test of Within-Subjects Contrasts for the analysis with SCANNING RATE as Dependent Variable. The effect of each independent variable was considered significant at p-values≤0.05. The model shows no significant results.

71 DISCUSSION

1. ECOLOGICAL CORRELATES TO PERCEIVED PREDATION RISK IN Eulemur collaris

1.1 Evaluating the influence of ecological factors on lemurs' landscape of fear

In the present study, the frequency of alarm calls and scanning (vigilance behaviour) of the endangered red-collared brown lemurs (Eulemur collaris) have been used as indirect evidence of perceived predation risk in two groups living in the degraded littoral forest of Mandena (MAN) and two groups living in the well preserved littoral forest fragment of Sainte Luce (STL).

More in detail:

1. Are there any differences between the degraded forest (MAN) and the more intact one (STL) in terms of perceived predation risk in Eulemur collaris ?

In our model situation, no significant differences between MAN and STL were found neither during feeding nor during resting both in terms of alarm rate and in terms of scanning frequencies. In degraded habitats the observed increase in infant mortality may be a consequence of the reduction of group size. Due to the size effect, small groups might be exposed to higher predation pressure than larger groups. Generally, indeed, living in larger groups has been shown to decrease individual predation risk [van Schaik, 1983a; van Schaik and van Hooff, 1983; Wrangham, 1980]. Predation pressure is difficult to quantify, but the frequency of attacks and predation by Polyboroides radiatus and other predators in the Mandena forest suggest that predation is significant in this area [Donati et al., 2007b]. In the more degraded forest of MAN the first lemurs' response to habitat degradation has been shown to be a reduction in group size [Campera et al., 2014; Serra et al., in prep.]. However, in the present study no significant

72 differences between MAN and STL were found neither in terms of lemurs' alarm rate nor in terms of scanning rate. This might be related to the small sample size (two groups per site may be not sufficient to evaluate variations between sites) and also to the high variability between groups within the same area, that show very different ranging patterns [Campera et al., 2014].

2. Are there any differences between groups in terms of lemurs' anti-predator behaviours frequency?

No significant differences in terms of alarm rate were found between the four study groups neither during feeding nor during resting. A significant difference in terms of scanning rate was found between groups during feeding, while a tendency towards a difference was recorded during resting. More in detail, Group B-STL has shown the highest scanning rate among the study groups during feeding, while Group AB-MAN seems to be the most vigilant during resting. The home range of Group B-STL was the smallest one among the four study groups [Campera et al., 2014] and this group showed high territoriality. This group has in fact a strong tendency to defend its home range from other groups of conspecifics and high frequency of aggressive interaction towards other groups of lemurs (almost always initiated by Lanitra, the dominant female, pers. obs.) over the whole study period. Considering these two aspects, the highest frequency of vigilance behaviour found in Group B-STL might be interpreted as prevalently social vigilance, since what in this group it was observed, a strong tendency to “monopolize” food resources within the home range. Group B- STL was also the most conspicuous in terms of number of adult individuals among the four study groups. In a study on a population of brown capuchin monkeys (Cebus apella) it was shown that the prevalent function of vigilance in this population is social monitoring, and the positive correlation between the number of nearby neighbours and vigilance rates supported this finding [Hirsch, 2002]. Concerning the tendency toward higher scanning rate found in Group AB-MAN

73 during resting, it might be explained by the fact that this group is the less numerous of the four study groups. Thus, within Group AB-MAN there might be a very low dilution effect and scarce possibility to share vigilance task among individuals. On the other hand, since Mandena groups live in a fragmented and degraded habitat, they may need to minimize the time spent vigilant in order to optimize their food intake. Such findings are of interest because vigilance is potentially costly, forcing a trade-off with feeding behaviour, that is, animals often show lower vigilance frequency when feeding than when resting [van Schaik and van Noordwijk, 1989; Treves et al., 2001; Kutsukake, 2006; Stojan-Dolar and Heymann, 2010]. This is the same trend found in the present study on E. collaris. Animals have multitasking strategies to reduce the cost of vigilance [Gaynor and Cords, 2012], but vigilance entails a decreased feeding efficiency and, if performed, is likely to have an important function. A negative relationship between time spent feeding and vigilance was also observed in blue monkeys (Cercopithecus mitis), probably related to the amount of visual attention that it is required for harvesting, processing and consuming food, which prevents vigilance [Gaynor and Cords, 2012]. Vigilance is in fact often inversely related to time spent feeding [Isbell, 1994]. For individuals in smaller groups, greater need of time for vigilance could reduce their food intake and, therefore, their reproductive success compared with that of individuals in larger groups [Janson, 1992]. In general, decreased food availability may increase the time individuals spend feeding and decrease their vigilance, potentially driving to a higher predation risk on them [Isbell, 1994]. This may be the case of Group C-MAN which in the present study showed the lowest scanning rate among the four study groups. Group C had also the lowest mean DBH and density of priority feeding trees, suggesting that these animals had the lowest food availability among the four study groups [Campera et al., 2014]. In fact, DBH is considered a good estimation of the fruit production and leaf availability of a tree, because of its correlation with the crown diameter [Chapman et al., 1994; Ganzhorn, 1995]. Because of the low food availability in its home range, Group C-MAN may be forced to reduce the time spent for vigilance in order to optimize its food intake. If this association holds true, this would mean that in a degraded habitat such

74 as Mandena, the availability and distribution of resources are the primary causes which drive lemurs' behavioural choices. This in contrast, for example, with what was observed in vervet monkeys (Chlorocebus pygerythrus), in which the effect of perceived predation risk may exceed that of resource distribution in determining the animals' behavioural patterns [Willems and Hill, 2009].

3. Does the animals' exposure in the crown influence their perceived predation risk?

Significant differences between the four E. collaris groups have been found in the current analysis in terms of percentage of time spent in the most exposed zone of the tree crown (position 3), both during feeding and during resting. Moreover, a significant effect of animals exposure in the crown was recorded in terms of alarm rate during feeding but not during resting. No significant effect was found in terms of vigilance frequency neither during feeding nor during resting. This is also in accordance with the inversely relationship between time spent feeding and time spent monitoring. The influence of animals' exposure in the crown on alarm rate during feeding but not during resting, as expected, suggests that lemurs perceive a higher predation risk when they are in the most exposed zone of the crown. While they can actively choose safer refuges for resting, such as position 2 or position 1 in the crown, indeed they are obliged to use the most exposed and risky zones during feeding due to the availability and distribution of food resources [pers. obs.]. Some studies showed that arboreal primates are more vulnerable to predation when they are at forest edges, in open forest, or on top of the canopy, where the vegetation is sparse and thus animals are more visible and exposed than when they are in dense forest [Isbell, 1994]. Primates that usually exploit such zones, for example black and white colobus (Colobus guereza), may therefore be particualrly vulnerable [Skorupa, 1989; Struhsaker and Leakey, 1990]. For instance, the increased vigilance at the edge of the forest that was observed in blue monkeys (Cercopithecus mitis), is principally related to the main threats of dogs and humans that are more common and easily visible at the forest edge [Gaynor and Cords, 2012].

75 The effect of animals' exposure in the crown on alarm rate during feeding and the absence of differences in terms of scanning frequencies might suggest another situation in which the lemurs in order to optimize the time spent feeding reduce the cost of vigilance. In these situations other anti-predator strategies may be preferred, such as alarm calls performed by some “sentinel” individuals [pers.observ.].

4. Does the animals' exposure in the canopy influence their perceived predation risk?

It was found that also height (vegetation density) can influence detection distance [van Schaik et al., 1983b]. No significant differences between the four study groups of E. collaris were found in terms of vertical use of forest layers. For those primates whose main predators are terrestrial carnivores, it was observed that the large groups spend more time low in the canopy where, presumably, they are at greater risk than they would be in the upper forest layer [Isbell, 1994]. In the present analysis, animals were considered at greater risk when they are in the upper part of the canopy, that is, when they are supposed to be more exposed to aerial predators, since birds of prey are the main predatory risk for these lemurs at the two study sites. However, no significant effect of height in the canopy was found neither in terms of alarm rate nor in terms of vigilance frequency. This finding suggests that aerial predators may represent a perceived predatory risk independently on the layer of the canopy, probably because the diurnal raptors remaining in these forests (Buteo brachypterus, Polyboroides radiatus, Accipiter henstii) are not very large birds and sometimes they can manoeuvre and prey also in the lower canopy [Csermely, 1996]. Henst’s goshawk (Accipiter henstii), for example, weighs only 1.2 kg but it successfully prey on medium-sized, diurnal species as well as on small-sized, nocturnal primates [Karpanty, 2003, 2006]. Solitary and secretive, this bird usually occurs in the sub-canopy [Morris and Hawkins, 1998]. The Madagascar harrier-hawk (Polyboroides radiatus) feeds mainly on insects,

76 insect larvae, and small vertebrates, but also on flying foxes and small lemurs [Morris and Hawkins, 1998; Karpanty, 2003, 2006]. This bird often searches for food by walking on the ground, and it extracts prey items from crevices and tree holes with its long legs [Morris and Hawkins, 1998]. In the Tolagnaro area, these birds were seen foraging in open areas on the ground, particularly around stones, cow dung, termite mounds, and rotten tree stumps [Langrand and Meyburg, 1984]. Also the Madagascar Buzzard (Buteo brachypterus) seems to have some terrestrial animals among its preys, such as tenrec (Tenrec eucaudatus) [Rand, 1936] and some reptiles [Goodman et al., 1997]. An opposite trend compared with that one found in the present analysis was recently observed in white-faced capuchins (Cebus capucinus), which seem to perceive a lower predation risk in the high and middle forest layers and they modify their vigilance behaviour accordingly to their spatial ecology [Campos and Fedigan, 2014]. This is likely to be related to the very different set of predators in the Neotropics, including large semi-terrestrial carnivores, as compared to Madagascar.

5. Does the presence of conspecifics sharing the same tree crown ( party size ) influence the frequency of lemurs' anti-predator behaviours?

The present study on red-collared brown lemurs has shown significant differences between the four groups in terms of party size, and this is in accordance with the smaller size of groups living in MAN compared with the more conspicuous groups living in STL. Moreover, party size had a significant effect on alarm rate during feeding. No significant effect of party size was found in terms of scanning rate, neither during feeding nor during resting. This is in accordance with what was observed in blue monkeys (Cercopithecus mitis), that is no effect of the absolute number of neighbours on vigilance [Gaynor and Cords, 2012]. Several studies showed that larger groups provide an advantage in avoiding or minimizing predation risk [Isbell, 1994]. Among wedge-capped capuchins (Cebus olivaceus) and vervets (Chlorocebus spp.), for example, large groups show higher levels of vigilance than do small group [de Ruiter, 1986; Isbell and

77 Young, 1993]. Among long-tailed macaques (Macaca fascicularis), large groups detect human potential predators earlier than do small ones [van Schaik et al., 1983b]. According to Pulliam (1973), larger parties are safer because they can detect predators at a higher distance in time to escape, and other studies confirmed that the distance at which forest primates detect predators increases with the size of their party (e.g. Presbytis thomasi, Macaca fascicularis, Macaca nemestrina, Hylobates lar, Hylobates syndactylus, Pongo pygmaeus [van Schaik et al., 1983b]). The finding that party size influences alarm rate but not scanning rate in Eulemur collaris during feeding seems to be in accordance to previous observations. In fact, the observations might indicate that, while the animals are busy in foraging activity and have less time to properly monitor the environment, it is easier for some individuals to act as sentinels in case of large party size by alerting the whole group when the predator is still far.

6. Are there any differences in terms of perceived predation risk related with lemurs' daily distance travelled?

In the current analysis on red-collared brown lemurs significant differences between the four study groups have been found in terms of daily path length. More in detail, Group A-STL and Group B-STL, that are the largest among the four study groups, travelled longer daily distances. This is in accordance with Chapman and Chapman (2000), that is individuals must travel more if they are in a large group than if they forage in a smaller group, because of the faster patch depletion, especially when food resources are patchily distributed. Furthermore, when depleting patches are rare, individuals minimize travel costs by reducing group size [Chapman and Chapman, 2000], and this is trend observed in MAN, where lemur groups are smaller and travel less. A study on a desert baboon population (Papio ursinus) [Cowlishaw, 1997] indicated that these primates choose their habitat on the basis of its predation risk, related to visibility through vegetation and predator attacks distance and velocities, thus paying a potential cost in terms of food availability. In fact, they spent less time foraging in high-risk/food-rich habitat and more time feeding in

78 low-risk/food-poor habitat. This suggests that baboons are conscious of the relative predation risk of each section of their habitat and strategically modify their behaviour accordingly [Hill and Dunbar, 1998; Chapman and Chapman, 2000]. Evaluating the potential costs of anti-predator behaviour in such cases it is very difficult because the habitat and microhabitat variables that are correlated with predation risk are numerous. We might expect that prey species avoid areas in which predators are known or are likely to occur [Stanford, 2002]. It has long been hypothesized that animals perceive a greater predation risk when they are in unfamiliar areas [Metzgar, 1967; Amborse, 1972 in Isbell, 1994]. Some support for this idea has been found in vervets (Chlorocebus spp.) [Isbell, 1994]. Whereas no evidence that red colobus (Procolobus spp.) groups avoided habitats in which they had been hunted in the recent past was recorded [Stanford, 1998]. Concerning the effect of D.P.L. on perceived predation risk in E. collaris, lemurs' daily path lengths were found to significantly affect both alarm rate and scanning frequency during feeding but not during resting. This seems to be in accordance with both the fact that travel distances are related to searching for food, which sometimes may force the animals to pass through unfamiliar area, and the observation that groups that travel more are in general more conspicuous. Thus, groups moving more frequently and over large areas may perceive a higher predation risk and consequently increase the frequency of their anti-predator strategies.

7. Is there any correlation between lemurs' landscape of fear and their physiological stress?

Faecal GCMs concentration levels actually showed that E. collaris living in degraded forest fragment of MAN are physiologically more stressed than conspecifics living in the well preserved forest of STL [Balestri et al., 2014]. No significant differences between groups have been found in terms of lemurs' physiological stress in the present analysis. However, physiological stress had a significant effect on alarm rate during feeding, while this was not apparent during resting. On the contrary, no significant effect of physiological stress on scanning rate

79 was found during feeding, while a significant effect was found during resting. This might suggest that stressed animals may be generally more vulnerable thus they have to accurately evaluate the costs of each survival behaviour, in order to minimize them as much as possible. All these findings seem to confirm that both physiological stress and animals exposure influence lemurs' perceived predation risk mainly in relation with availability and distribution of food resources, as it was observed also in vervet monkeys (C. aethiops) [Willems and Hill, 2009].

Overall, we can conclude that the threat of predation is rarely the only force determining primate grouping patterns. Animals must often spend time exposed to predation in order to forage for needed or highly desired foods or for water. The actual trade-offs between predation, feeding necessities, and other competing needs may vary from one species to another, between populations of the same species, and among different sexual age/classes within a group [Stanford, 2002]. The present finding that most of ecological correlates considered in the analysis significantly influenced lemur groups during feeding but not during resting seems to confirm that in fragmented forests primates have to make an accurate selection of the strategies to use, always trying to balance their costs and benefits in terms of fitness and survival. In Madagascan littoral forest ecosystem, the availability and distribution of food resources seem to constrain also the frequency of anti-predator strategies performed by Eulemur collaris and thus lemurs' perceived predation risk.

80 2. SOCIAL CORRELATES OF PERCEIVED PREDATION RISK IN Eulemur collaris

2.1 Evaluating a possible anti-predator function of lemurs' unusual adult sex ratio

1. Are there any differences in terms of anti-predator behaviours frequencies between males and females and/or between low-ranked and high-ranked individuals in Eulemur collaris ?

2. Are there any differences in terms of frequencies of alarm calls and scanning between PRE-LAC season (absence of offspring) and POST-LAC season (presence of infants)?

Social dynamics among individuals may play a role in primate predation risk. It was found, for example, that high-ranking male vervets (Chlorocebus spp.) were more likely than lower-ranking males to be eaten at waterhole [Cheney et al., 1993]. No significant differences were found in the present analysis in terms of anti- predator behaviours neither between sexes nor between ranks, or between PRE-LAC and POST-LAC seasons. Variation in the number of adult males is one of the most interesting aspects of primate group composition with broad effects on many features of male and female behaviour [Hamilton and Bulger, 1992; Preuschoft and Paul, 2000; van Hooff, 2000; Kappeler et al., 2009]. The most basic dichotomy is that between single and multi-male groups. At the beginning of the primate socio-ecology theory, researchers indicated ecological causes for this dichotomy, such as habitat type or predation risk [Kappeler, 2000a]. At present, this dichotomy is no longer explained as an invariant species-specific feature, but instead as a flexible response to variation among groups in ecological and demographic variables [Robbins, 1995; Steenbeek et al., 2000; Strier, 2000; Struhsaker, 2000; Watts, 2000].

81 Three recent comparative studies on arboreal folivores re-examining the proposed key determinants of the number of males in groups showed that the presence of monkey-eating eagles tends to increase the number of males in howlers and colobus on average from one to two, whereas ecologically similar langurs (and some colobus), which are not exposed to such predators, tend to live in single-male groups [van Schaik and Hörstermann, 1994; Kappeler and van Schaik, 2002]. Red-fronted lemurs (Eulemur rufifrons), a brown lemur species closely related to E. collaris, live in groups with a male-biased adult sex ratio. It was proposed that strong affiliative relationships between male and female ring-tailed lemurs, Lemur catta, may benefit males by providing increased safety from predators because they are able to remain within the social core of a group [Gould, 1996a]. The same advantage may apply to red-fronted lemur males as well. Vigilance behaviour by red-fronted lemurs has not been measured as precisely as in other lemur species such as L. catta [Gould, 1996b], but scanning the environment was recorded systematically during the 1988–89 field season and this may be an indication of vigilance behaviour [Overdorff, 1998b]. This activity was not recorded often (189 scan samples during the entire study period) and females were mainly responsible for monitoring the environment (89%), not males. Females also were responsible for making the initial alarm call on six occasions when large birds were detected near the social group [Overdorff, 1998]. Males that formed dyads (special relationships) with females, however, were also members of the social core and may benefit higher predator protection over peripheral males, especially if females are more rapid to detect predators. Moreover, although males do not actively monitor their environment, they may play a role as low-cost sentinels, because they are not exposed to the same biological and metabolic constraints of females [Sauther, 1993; Overdorff, 1998]. An alternative explanation for the lemurs peculiar sex ratio is that lemurs may increase thermoregulation through huddling behaviour, although the sex of the social partner is not a crucial aspect to this hypothesis [Overdorff, 1998]. Huddling behaviour among lemurs may be one way of conserving energy during cold weather, since prosimians are not as efficient as other primates at

82 thermoregulating [Morland, 1993]. According to Ostner and Kappeler (2004), some life history aspects may explain red-fronted lemur social organization, and both males and females might obtain some advantages from this unusual sex ratio. Increased thermoregulation and reduced predation risk have been proposed as possible benefits [Donati et al., 2011b]. Despite thermoregulation seems not to be related with the presence of extra-males in this species [Ostner, 2002], results of a study on vigilance behaviour on the same population indicated that males are more vigilant than females [Hilgartner, 2001]. Since neither sex nor rank of individuals, or any possible interaction effect of these two factors, seem to affect red-collared lemurs' alarm rate or vigilance behaviour, the multimale-multifemale social organization of E. collaris therefore might not be explained with an anti-predatory function of the extra-males. Thus, the conspicuous number of subordinate males within a group cannot be explained by a sentinel or vigilance function. In other lemur species it was observed that subordinate males provide no benefits in terms of anti-predator efficiency [Propithecus verreauxi (Kappeler et al., 2009)]. Our finding that social rank has a weak effect on vigilance is consistent with other studies on blue monkeys (Cercopothecus mitis) which largely showed that rank predicts little about their behaviour [Gaynor and Cords, 2012]. Therefore, what emerges from the present analysis is that the hypothesis of thermoregulation by huddling behaviour seems to be more reliable in the case of Eulemur collaris, and this is in accordance with previous published research on this species [Donati et al., 2011b] and the results of the analyses discussed by Valentina Serra and Marco Campera in their MSc dissertations. In fact they found that red-collared brown lemurs spent roughly half of their resting time in huddling posture, and no significant differences were found between Mandena and Sainte Luce in terms of huddling proportions [Campera et al., unpub. data]. Moreover, huddling frequency significantly increased during cooler season at both study sites, and a negative correlation between the frequency of huddling and corresponding temperatures was recorded [Donati et al., 2011b; Campera et al., unpub. data]. The finding of no correlation between sexes (and/or ranks) and frequency of anti-predator behaviours further supports these results on a possible social

83 thermoregulatory function for the peculiar multimale-multifemale social organization of Eulemur collaris. Furthermore, the finding that the presence of offspring does not affect the frequency of anti-predator behaviours in red-collared brown lemurs seems to further reject the hypothesis that the extra-males have a role of sentinels to better defend the offspring from predators.

3. LIMITATIONS OF THE STUDY, NEW RESEARCH FRONTIERS AND FURTHER PERSPECTIVES

3.1 Limitations and new research frontiers in the present study

The fact that predation risk has a strong effect on primate behaviour is undisputed [Stanford, 2002]. In previous studies in which specific hypotheses about the effects of predation on primate social systems were tested, predation rates were used to operationalize this independent variable [Anderson, 1986; Boinski and Chapman, 1995; Cheney and Wrangham, 1987]. However, now researchers agree that predation rate is not appropriate for such analyses because it disregards the effects of various countermeasures already in place to reduce the risk [Hill and Dunbar, 1998; Hill and Lee, 1998; Janson, 1998]. Realistic estimates of the underlying predation risk are difficult to obtain and quantify [Janson, 1998; Kappeler and van Schaik, 2002]. Almost all anti- predator behaviours are indirect evidence that predation is or it has been an important selective force that influences primate behaviour. It is indirect because predation is rarely observed but still it is considered crucial, since the animals carry out strategies that minimize the risk to be killed [Stanford, 2002]. An understanding of the role of predation as a selective force on primates will only be gained by studying the factors that are relevant in determining a primate's perceived risk of predation [Hill and Dunbar, 1998]. Many further perspectives in the study of anti-predator behaviours and lemurs' perceived predation risk can be envisaged. One possibility could be future researches directly focused on this topic, during which data collection could also concern

84 the abundance of predators in the study sites and infant mortality rate within lemur groups, as an estimate of a realistic predation pressure measure. The importance of studying also the behaviour of predators by using some predator-prey models was evidenced [Hirsch and Morrell, 2011], especially in fragmented habitats, where it was shown that, when fragmentation does not affect raptors predation rates, their impact on lemurs may drive them to local extinctions [Crooks, 2002; Mikkelson, 1993]. For example, it seems that Polyboroides may increase in fragmented habitats and that Accipiter henstii can use both primary and fragmented forests [Karpanty, 2003, 2006]. Thus, the lack of inclusion of predators' behavioural observations and predation rates may be seen as a limitation of the present analysis, such as in most previous studies. In fact, prey-focused observations could underestimate the predator ecology [Ganzhorn and Goodman, 2007; Irwin et al., 2009], but on the other hand long-term studies on predators are logistically problematic and often based on indirect methods [Irwin et al., 2009]. Primate conservation strategies should take into account the role of predation in fragmented habitats. In fact, even when the animals are able to survive on available resources, potential extirpation due to predation events may have profound consequence for the ecosystem being recolonization less likely in forest fragments [Irwin et al., 2009]. Furthermore, the present study considering ecological correlates to perceived predation risk and evaluating the synergistic influence both of distribution and availability of resources and lemurs' landscape of fear is consistent with the most recent researches which underlined the necessity to evaluate the simultaneous effect of these two important environmental variable on animal space use and habitat selection [Willems and Hill, 2009; Campos and Fedigan, 2014].

3.2 Further perspectives

Despite their large variation relatively little is known on the ecological determinants of social systems in New World primates and prosimians. These primates show interesting affinities in social organization to one another, and

85 peculiarities in social structure and mating systems that differ from the more familiar pattern of the better-known Old World primates [Kappeler and van Schaik, 2002]. Therefore, increasing study of platyrrhine and prosimian species and integrating the resulting patterns into existing models, which are now mostly focussed on cercopithecines, is an important goal for the future generation of primatologists [Kappeler and van Schaik, 2002]. Concerning the anti-predator strategies carried out by Eulemur collaris, another interesting aspect to be considered is that this lemur is a cathemeral species. Evidence for the hypothesis that cathemerality may represent an efficient anti- predator strategy is provided by studies of several cathemeral primates [Donati et al., 1999]. For example, E. rubriventer was seen to visit the exposed branches of Eucalyptus trees only during nocturnal activity [Overdorff, 1988]. Eulemur mongoz increased its nocturnal activity when least cover was provided by vegetation [Curtis, 1997; Rasmussen, 1998a]. On the contrary, a previous study on E. collaris [Donati et al., 2007a], although indicated that cathemerality may be linked to avoid diurnal raptors, showed that the evidence for an anti- predatory strategy as a determinant of the activity pattern variations is still not clear. Identifying causalities is complicated by the fact that activity and predation risk are related to body size. For raptors, in particular, prey size clearly limits their prey spectrum. It has been suggested that these medium-sized lemurs retained some nocturnal activity as a response to the presence of diurnal raptors, which must have imposed an even great risk for them a few millennia ago [Goodman et al., 1993; Goodman, 1994; van Schaik and Kappeler, 1996b]. Cathemeral lemurs often feed and travel more in the upper layer of the canopy at night than during the day and this has been interpreted as a strategy for predation risk minimization, as feeding in exposed parts of the canopy is safest at night when raptors are inactive [Overdorff, 1988; Andrews and Birkinshaw, 1998; Curtis et al., 1999; Donati et al., 1999; Rasmussen, 2005]. Other studies yet have reported no connection between cathemerality and predation, such as in E. f. mayottensis that is still cathemeral despite it has few predators [Tarnaud,

86 2004]. Therefore, this could be a further interesting aspect to be investigated, by considering the percentage of time spent by E. collaris feeding in the most exposed zones during its diurnal activity and during nocturnal bouts. This type of study has been already done on two groups in Sainte Luce [Donati et al., 2007a], but it would be interesting to test if there are any differences in terms of cathemerality and its correlates between a degraded forest and a more intact one, by comparing different groups at both sites of MAN and STL. Moreover, since in the present analysis of perceived predation risk no significant differences have been found between the more degraded area of MAN and the more pristine forest of STL, another intriguing aspect that could be investigated is the general level of animal disturbance, both natural and anthropogenic, at the two study sites. This could be studied, for example, by taking into account the frequency of AC2 (alarm calls for potential terrestrial predators/dangers: animals vocalize, looking down and swinging their tails as pendulums) and of other kinds of vocalizations such as croaks and woofs emitted by E. collaris and on which little is still known, possibly each time recording the specific context and sources of arousal. These efforts could further elucidate the level of anthropic disturbance and its effect on lemurs' physiological stress, for example, especially in a degraded and impacted area such as Mandena.

4. GENERAL CONSIDERATIONS

The island of Madagascar has been described as a harsh and unpredictable environment [Wright, 1999] due to poor soils, low plant productivity and a variable and severe climate [Ganzhorn et al., 1999]. It is thought that these features implies unpredictable and highly seasonal variations in food availability and low dietary diversity compared with other rainforests with similar sympatric primate abundance [Ganzhorn, 1995; Gould et al., 1999; Wright, 1999]. It is suggested that the lemur's characters have evolved to face with the unpredictable and climatically severe island of Madagascar [Wright, 1999]. Many of these features are adaptations to either conserve energy or maximize

87 the use of scarce resources [Gould et al., 1999; Vasey, 2005]. The littoral forests of south-eastern Madagascar are among the most threatened habitats in the world. Populations of the different lemur species responded variously in terms of population dynamics to the habitat fragmentation and degradation: the larger species such as E. collaris show strong, negative population responses (population decline, reduced group size) in degraded habitats, and eventually disappear from smaller fragments [Ganzhorn et al., 2007]. Short-term lemur inventories as indicators of habitat conservation status can be problematic since lemurs are long-lived animals able to persist in habitats that do not allow positive population growth. Thus, long-term studies are necessary to investigate the population dynamics and deduce general conclusions about the population over time [Ganzhorn et al., 2007]. Frugivores such as E. collaris play a fundamental role as seed disperser in the preserving of biodiversity in tropical forests, where zoochorous species represent the vast majority of tropical plant species [Bollen and Donati, 2006]. Loss of fruit-frugivore interactions can thus have important consequences [Bollen and Donati, 2006]. Lemurs are flexible, but this flexibility has its limits. The consequence of rapid climate change on the ecology and long-term survival of lemurs may be broad, and further amplified by human disturbance [Wright, 2006]. Indeed, climate change and weather-related natural disasters also threaten lemur survival. There are indications that deforestation and forest fragmentation are accelerating the gradual desiccation which is occurring in the western and highland regions [Wright, 2006]. The consequences of desiccation are important even in the rainforests. As annual rainfall decreases, the larger trees that constitute the high canopy are subjected to higher mortality, failure to fruit and lower production of young leaves, which are preferred food item for folivorous lemurs. Also cyclones can have profound consequences on canopy trees, even leaving lemur populations without fruit or leaves until the following spring, forcing them to shift on crisis food, such as epiphytes [Ratsimbazafy, 2006]. Challenges to in situ lemur conservation are huge. Despite of the scarcity of published data compared to other lemur-related topics, lemur poaching for bushmeat has severely increased since the onset of the political crisis in 2009

88 [Schwitzer et al., 2014]. Illegal logging of rosewood and ebony, mining, and slash-and-burn agriculture are all provoking lemur population declines, by habitat loss, fragmentation, and degradation. Effective management of Madagascar's protected areas, as well as creation of more reserves, will be crucial to future conservation of lemurs [Schwitzer et al., 2014]. The socio-economic issues have complicated conservation efforts, even though the island of Madagascar has been recognized by IUCN/SSC as a critical primate region for over 20 years [Schwitzer et al., 2014]. The IUCN has recently suggested a 3-year conservation plan aimed at helping local communities: this plan recommends conservation actions for 30 priority sites harbouring endangered lemurs, for a total budget of U.S. $ 7.6 million [Schwitzer et al., 2014]. Promoting and expanding ecotourism is one further aspect of the action plan proposed by IUCN. Lemurs represent Madagascar’s most distinctive flagship species. They attract tourists, even despite political problems, and provide livelihoods for rural communities in the surrounding [Durbin, 1999; Schwitzer et al., 2014]. Ecotourism indeed is a powerful means to help the national and local economy, and already rivals major exports such as coffee and prawns as the primary foreign currency earner, even at the current relatively low level [EIU, 1998]. An important issue is the development of local tourist guide associations. Another key aspect is the creation of protected areas managed at the community level [Schwitzer et al., 2014]. Another aim is to support and expand long-term research presence in critical lemur sites. Field stations with local and international field workers can help to trains Malagasy scientists and discourage illegal hunting and logging. Scientists are working with local communities, providing economic benefits and knowledge exchange for conservation at local levels [Schwitzer et al., 2014]. Two pivotal goals related to conservation efforts in Madagascar are education and local communities involvement. Personally, I can say without any doubt that one of the most significant aspects of my six months experience in the southeast of Madagascar was the realization, together with my friend and colleague Valentina Serra, of two presentations. Both were performed in Malagasy language at the schools of Ambandrika, Ampasy and Mangaiky, [Fig. 40] and at

89 the tree nursery of Mandena [Fig. 41]. During these presentations, we explained in Antanosy (the local language) to children and local employers the reasons of our research work and the importance of lemurs' survival for preserving the littoral forest ecosystem, on which those people strictly depend.

Fig. 40 Malagasy power point presentation for QMM employers at the pépinière of Mandena. Photo by Christophe Rambolamanana, June 2011

Fig. 41 Malagasy power point presentation for jazakely (children) at the school of Mangaiky. Photo by Christophe Rambolamanana, June 2011

90 91 Appendix II. Protocol for extraction of faecal samples stored in alcohol (Endocrinology Lab of the German Primate Center)

1. Number 30 ml or 50 ml conical polypropylene tubes (e.g. from Sarstedt; Art. No. 62.543 (30ml) or 62.559.001 (50 ml); type Art. No. into the search function to reach the information; see http://www.sarstedt.com/php/main.php?newlanguage=en) and determine their individual weight (without the cap) with an accuracy of 4 decimals. Whether you use a 30 ml or 50 ml tube depends on the volume of faeces and alcohol you have, probably 30 ml tubes are fine. 2. Homogenize faeces mechanically (e.g. using a metal stick or metal or wooden spatula) in its original alcoholic solvent. This is important if the faeces is not broken up already in small pieces but is present as a compact bolus. 3. Decant the suspension into the pre-weighed 30 ml or 50 ml tube(s). 4. Rinse the original tube with 2 ml 80% ethanol in water (shake the ethanol in the tube). Rinse also the stick or spatula (if it is re-used) with 1 ml of ethanol and add the rinse into the tube containing the faecal suspension. 5. Extract the hormones from the faecal sample by vortexing on a multitube vortex for 15 minutes. For an efficient and consistent extraction it is important that the faeces in the tube is swirling very well. 6. Following vortexing, centrifuge the sample at 3000 rpm for 10 min.

7. Decant the supernatant carefully into a 15 ml tube with gradation (0.5 ml steps or less; e.g. from Sarstedt; Art. No. 62554.001; see http://www.sarstedt.com/php/main.php?newlanguage=en) which is pre-numbered with sample ID (i.e. carries the same number as the original extraction tubes). 8. Determine the volume of the extract as accurate as possible using the check marks on the tube. 9. Fill about 1.5 ml of the extract into a 2 ml polypropylene tube (e.g. micro tube safe seal from Sarstedt; Art. No. 72.695; see http://www.sarstedt.com/php/main.php? newlanguage=en) which should be properly labeled with sample ID etc. (do not fill the tube fully to the top). For labeling preferably use a sticky freeze-resistant label (e.g. tough tag; see http://divbio.com/labels.aspx). 10. Put parafilm around the micro tube to reduce the risk of evaporation (critical!!) and store the tube with the extract at -20°C.

11. Dry the faecal pellet(s) to a constant weight by putting the tube(s) under the fume cabinet for 2 days (this helps to evaporating the ethanol in the faecal pellet) and subsequently placing the tube(s) in an oven (with or without vacuum) at 500C until the pellet is completely dried (tube weight remains constant). 12. Determine the dry faecal weight by weighing the tube (with dried faecal pellet, but without cap, see above) and substracting from this weight the net weight of the empty tube (see above). The dry weight is used for calculation of the faecal hormone concentration as it controls for variation in water content of the samples. 13. The rest of the extract can be discarded or a second aliquot of it can be stored frozen for safety reasons (e.g. in case samples are getting lost during shipment). 14. Prepare an excile file with all necessary information (e.g. sample ID, extract volume, dry faecal weight etc.)

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122 ACKNOWLEDGEMENTS

I sincerely want to thank all the people and organizations that made possible this research project and that had a special role in making my six months spent in Madagascar really meaningful and unforgivable.

The QMM Biodiversity Staff: Manon Vincelette and her husband John, Jean Baptiste Ramanamanjato, Johny Rabenantoandro, Christophe Rambolamanana, Laza Andriamandimbiarisoa, Faly Randriatafika, David Rabehevitra, Claude Soanary, and all the other QMM employers; the field assistants Kadofa, Josette, Givet, Philemon, Germain, Crescent; the field cooks Francoise (Rateta), Tina, Kristine. Because each of them constantly gave us fundamental logistic support.

The University of Antananarivo, in particular M.me Anta. The associations which gave us logistic and/or bureaucratic support: MICET, ANGAP, FIMPIA.

The local authorities of Ste Luce villages who received us as part of their family, especially the Chef de Fokontany Benaomby and Milson George.

The Rufford Foundation that trusted us by financing part of this project.

Dr. Michael Heistermann and his staff for the hormonal analyses.

I want to say also MISAOTRA BETSAKA from my “MAINTY FO” to all the people living in the villages of Ambandrika, Apanasatomboka, Manafiafy, Mangaiky, Anpasy, Mandromodromotra, Ebakika, and in Fort Dauphin (such as Ramanga, Tsiringaty, Lionesse, the very kind owners of Mahavoky Annex Hotel and Nepenthes and the restaurant Chez Perline, the taxi-drivers, the guides met in our trips to Natural Reserves, such as Olivier, and especially Julie and Ginette, Baldine, Soniata, Exas, Bartelitsy and Phideline and more in general all the JAZAKELY!). A special thanks is for Murielle Ravaolahy, the best friend we could meet and with whom we shared our wonderful forest, and also for Stephanie Bistritz, another important friend with whom we spent a very nice time and that was fundamental in helping us to translate in Antanosy our power point presentations for children. Last but not least, I want to thank the other friends we left on the “big red isle”: Christophe, Richard, Darie, Rado, Ny and Mbola. Thanks to all the people mentioned above, we never felt as simple “FOTSY VASÁ”.

Finally, I thank Dr. Giuseppe Donati for giving me the opportunity to go to Madagascar for

123 my thesis project, and for the patience in correcting this thesis by communicating by e-mail and in very short time windows.

…...E adesso, si passa all'italiano!!

Molto tempo è trascorso dalla raccolta dati sul campo alla stesura di questa tesi...molte cose sono successe nel frattempo e molte cose sono cambiate nella mia vita...Qui voglio primariamente ringraziare malalako Vale (la mia Quadratura del Cerchio!) per aver condiviso con me gioie e dolori sia dell'esperienza in Madagascar che della fatica di scrivere questa tesi dopo tanto tempo, come credo nessun altro avrebbe potuto fare: Vale, sei la migliore compagna di viaggio che si possa desiderare, sia che il viaggio sia un volo aereo con direzione Fort Dauphin o che si tratti invece del viaggio chiamato vita!

Le altre persone fondamentali nella mia vita che voglio ringraziare in questa sede sono: Raul, perché sei la persona con cui ho intrapreso un altro tipo di viaggio, trovando in te la mia casa e la mia famiglia, e adesso sono sicura che insieme a te e alla nostra Aina potrò affrontare qualsiasi cosa ci porterà la vita più serenamente; Giulia e Marta, perché siete i primi e più importanti “regali” che mi ha fatto la scelta di iscrivermi all'Università di Pisa: dieci anni di ricordi di momenti vissuti nel bene e nel male, tra angosce più o meno gravi e risate a crepapelle, sempre con una felice costante, LE MIE AMICHE; Giovanni, perché sei una delle persone che stimo di più in assoluto, oltre che un caro amico, e mi dispiace che in questa occasione saremo lontani fisicamente, ma sono molto fiera di te per ciò che stai realizzando.

Uno speciale ringraziamento va al Dr. Giulio Petroni, per avermi dato fiducia in un momento in cui io avevo perso la fiducia in me stessa, ed aiutandomi a reinserirmi nell'ambiente universitario è riuscito a spronarmi a portare a termine i miei studi.

Ringrazio anche i contro-relatori, Dr. Marchi e Dr. Giunchi, per avermi dato degli utilissimi consigli e suggerimenti che mi hanno aiutato davvero a perfezionare questa tesi.

Ringrazio, inoltre, la restante parte del “team” di ricerca che ha significativamente contribuito a questa tesi, ovvero Michela e Marco. E la mitica Piera, che durante tutta la nostra permanenza in Madagascar è sempre stata tanto affettuosa e premurosa con me e Valentina. E poi anche Matilde e Davide, per avere avuto tanta pazienza ed avermi dato supporto nel periodo in cui questa tesi si è sovrapposta con il nostro tirocinio extra-curriculare.

124 Ringrazio, poi, in modo speciale: Stefania e Stefano, ed anche Lori, per tutto l'aiuto di questi ultimi mesi, e soprattutto per avermi davvero accolto come una figlia, senza mai essere invadenti. Rosa, tu sei la persona che mi conosce meglio di chiunque altro: ti ringrazio per esserci sempre per me, e perché conosci perfettamente quale sia il mio stato d'animo persino quando non ci sentiamo.

Infine, ringrazio ovviamente tutte le persone che saranno presenti alla discussione, in particolar modo chi ha dovuto spostarsi di vari chilometri per raggiungermi, soprattutto Manu (la mia principessa!), Anto e Lucia, e mia cugina Maria, ed anche coloro che saranno presenti con il pensiero perché impossibilitati ad essere a Pisa.

Papà, non ti ho dimenticato: grazie per aver capito che io sono cresciuta e che se il nostro rapporto è in qualche modo cambiato questo non comporta volersi meno bene.

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