Individual and environmental drivers of resource use in an endangered vulture: Integrating movement, spatial and social ecology

Individual and environmental drivers of resource use in an endangered vulture: Integrating movement, spatial and social ecology Marina García Alfonso PhD Thesis Sevilla, 2020 Recommended citation: García-Alfonso, M. (2020). Individual and environmental drivers of resource use in an endangered vulture: Integrating movement, spatial and social ecology. PhD Thesis. Universidad de Sevilla, Seville, Spain. Cover photographs used on chapters were taken by Manuel de la Riva (chapter 1), Thijs van Overveld (chapter 2) and Marina García Alfonso (chapter 3 and 4). Any form of reproduction, distribution, public communication or transformation of the same without prior authorization of the author is forbidden. Estación Biológica de Doñana, EBD - CSIC Departamento de Biología de la conservación Universidad de Sevilla - Facultad de Biología Departamento de Zoología Doctorado en Biología Integrada TESIS DOCTORAL Individual and environmental drivers of resource use in an endangered vulture: Integrating movement, spatial and social ecology Memoria presentada por Marina García Alfonso para optar al título de Doctora por la Universidad de Sevilla Fdo. Marina García Alfonso Vº Bº de los Directores, Dr. José Antonio Donázar Sancho Estación Biológica de Doñana, Consejo Superior de Investigaciones Científicas Dr. David Serrano Larraz Estación Biológica de Doñana, Consejo Superior de Investigaciones Científicas Tutor del programa de doctorado Javier Balbontín Arenas Universidad de Sevilla CONTENTS Abstract Introduction Study system Chapter 1: Applying movement ecology to identify drivers of power line use by vultures. Chapter 2: Food predictability and social status drive individual resource specializations in a territorial vulture. Chapter 3: Individual- and farm-dependent drivers of vultures visits to livestock exploitations based on GPS data. Chapter 4: Probing into farmers’ perceptions of a globally endangered ecosystem service provider. General discussion References Conclusions 1............. 4............. 10........... 18........... ........... 86........... ......... 126......... ..... 170......... ...... 202......... 206......... 223......... Introduction 6 (Ogada et al., 2016, 2012a; Sekercioglu et al., 2016). Their decline began in the mid-19th century in Europe and North America (Mingozzi and Estève, 1997; Snyder, 1983) and it has been particularly fast and dramatic in Asia and Africa, where about 90% of vulture populations have disappeared in the last decades (Koenig, 2006; Ogada et al., 2012a; Proffitt and Bagla, 2004). The main causes of mortality according to Ogada et al., 2012a are: (1) Indirect or unintended poisoning; (2) Lead ingestion; (3) Human persecution; (4) Accidents with power lines; (5) Collisions with wind turbines blades; (6) Lack of food; and (7) Changes in habitats. For these reasons, vultures are common targets of conservation actions (Badia-Boher et al., 2019). Vultures are usually social species, having complex social dynamics and concentrating massively at specific places, such as roosting places or predictable feeding points. In areas with scarcity of trees, the use of power lines for perching and roosting is frequent with the subsequence risk of mortality by electrocution (Angelov et al., 2012; Benson, 1981; Donázar et al., 2002b; Lehman et al., 2007; Mainwaring, 2015; Phipps et al., 2013), which increases in more social species due to communal roosting habits (Arkumarev et al., 2014; Donázar et al., 2002b, 1996a). Additionally, they are highly dependent on the spatial distributions of feeding resources, so the concentration of carrion derived from human activity in certain places (farms, supplementary feeding stations) involves major effects at the individual level (García-Heras et al., 2013), on the spatial structure of populations (Carrete et al., 2007) and on within-guild relationships (Cortés-Avizanda et al., 2012). Vultures, as an ecological group with common adaptations and common roles in ecosystems, are of particular interest in the study of animal movement. These birds have evolved in a context of highly unpredictable resources, developing flight skills to cover vast areas expending relatively little energy. This has strong conservation implications since their foraging movements easily involve several administrative units (e.g. localities, regions, countries) that hinder management and conservation measures. From an ecological point of view, these movement patterns lead to a huge and complex amount of environmental interactions at large spatial scales, which makes difficult collecting information and unravelling the potential factors influencing their behaviour, ecology and conservation. Moreover, vultures have deferred-maturity which involves a long pre-adult stage. The life style regarding movement decisions and resource selection could be radically different after recruitment and presumably highly dependent on all the information collected during their pre-breeding period. Their long lifespan and delayed maturity involves the opportunity to establish complex interactions with the environment and conspecifics making it difficult to Introduction 7 disentangle the motivation and constraints of their movements. Additionally, these trade-off and interactions could depend on other individual traits, so a comprehensive understanding of movement should focus on individual attributes. Canarian Egyptian vultures as study model For assessing some key factors in conservation of vulture populations, we focus on the study of the movement ecology of the Canarian Egyptian vultures (Neophron percnopterus majorensis), an endangered subspecies endemic from the Canary Islands that still survives in Fuerteventura and Lanzarote. We assess internal and external factors influencing the use of resources, specifically electric pylons for roosting and perching, and feeding stations and farms as feeding sources. We also probe into stakeholders’ social perception and its drivers. Egyptian vulture has large wingspans, which makes it more sensible to electrocution on power lines as happens with other large birds (APLIC, 1996; Bevanger, 1998). Additionally, this species frequently live in open habitat where this mortality cause is especially pressing due to the scarcity of perches that provoked some birds to use electric infrastructures instead (Angelov et al., 2012; Benson, 1981; Donázar et al., 2002b; Lehman et al., 2007; Mainwaring, 2015; Phipps et al., 2013). Moreover, highly social species as Egyptian vultures conform large aggregation of birds in communal roosts being even most susceptible of electrocution when roost are located on electric pylons (Arkumarev et al., 2014; van Overveld et al., 2018). For all these reasons, we focus on electrocution which is the main cause of mortality for vultures on Canary Islands. Canarian Egyptian vultures depend heavily on livestock carcasses derived from animal husbandry. This is a general trend in Europe, where the replacement of most wild ungulates by domestic ones has changed the spatial and temporal distribution of carrion. Although human expansion may not have changed food availability, there is no doubt that it has become more predictable by concentrating animals in farms and creating muladares (outdoor dumps for dead livestock) (Grande et al., 2009). As a result, in Europe the majority of vultures’ diet comes from livestock carcasses, but current changes in livestock husbandry practices from extensive field grazing to intensive industrialised farming is diminishing carcass availability (Caballero, 2007; Donázar, 1993; Donázar et al., 2009a, 1997; López-López et al., 2014). Moreover, sanitary regulations imposed in 2001, after the outbreak of BSE, determined that livestock carcasses had to be destroyed, which resulted in a dramatic decline of carcass availability for vultures (Donázar et al., 2009b). To counteract this drop, there was a proliferation of supplementary feeding stations, despite some important negative effects of increasing carrion predictability Introduction 8 have been described (Cortés-Avizanda et al., 2016, 2012; García-Heras et al., 2013). In 2011, EU legislation changed to make possible again the abandonment of carcasses in the field (Arrondo et al., 2018; Margalida et al., 2012), but it has been implemented unevenly and not in all regions. Altogether, this new scenario is changing the predictability and amount of feeding resources for vultures, but scientific knowledge on its consequences is lacking except from general guidelines (Cortés-Avizanda et al., 2016, 2010; Moreno-Opo et al., 2015). Fuerteventura still holds a high number of goat farms under extensive regime, but it is changing to semi-intensive and intensive practices (García-Martínez et al., 2009). The abandonment of carcasses is still prohibited, but it occurs in some farms. Additionally, there are two supplementary feeding stations and a garbage dump. The European emerging scenario of different predictabilities is quite reflected in Fuerteventura, where the scavenger community is relatively simple, including only one vulture species and other 3 avian scavengers (see chapter 4 for details). Hence, the island constitutes an appropriate system to assess how vultures are reacting to such changes. In this thesis, we deep on vulture resource specializations and the factors affecting both those resource preferences and the specific use of livestock farms. Finally, Canarian Egyptian vultures have been historically related to human activities in Fuerteventura linked to traditional goat farming practices (Gangoso, 2006). However, the social perception is an aspect hardly ever considered in combination with ecological aspects such as resource use and animal movement. Social misperception may determine the emergence of wildlife-human conflicts (Everard et al., 2017) hindering conservation efforts against practices harmful for beneficial endangered species (Badia-Boher et al., 2019; Margalida et al., 2014b, 2013a; Ogada et al., 2012a), and even leading to the disappearance of those species (Allen, 1893). Scavengers provide crucial ecosystem services, so they have been always perceived as beneficial to humans (Moleón et al., 2014; Sekercioglu et al., 2016; Whelan et al., 2008). Nevertheless, as we mentioned above, avian scavenger declines are strongly related to unintended poisoning and human persecution besides other anthropogenic causes. Further, disconnection of ecosystems from human societies is a recent conservation concern (Bennett et al., 2016; Cowling et al., 2008; Martín-López and Montes, 2015; Olea and Mateo-Tomás, 2009). Thus, we probe into the perception of livestock farmers about avian scavengers on Fuerteventura Island and factors affecting awareness accuracy to enhance our understanding of the social dimension of vulture conservation. 9 Objectives The specifics objectives of this thesis are: 1. To determine drivers responsible for the intensity of use of power lines by Egyptian vultures using predictive models. Then, to contrast the resulting predictions with detected mortality due to power lines. In prep.: García-Alfonso, M., van Overveld, T., Gangoso, L., Serrano, D., Donázar, J.A. Applying movement ecology to identify drivers of power line use by vultures. 2. To assess individual plasticity and repeatability in movements and in the exploitation of food resources varying in predictability. Additionally, to determine the preferences for such resources and the underlying individual characteristics. Published: van Overveld, T., García-Alfonso, M., Dingemanse, N.J., Bouten, W., Gangoso, L., de la Riva, M., Serrano, D., Donázar, J.A., 2018. Food predictability and social status drive individual resource specializations in a territorial vulture. Scientific Reports 8, 15155. doi:10.1038/s41598-018-33564-y 3. To investigate how livestock farms determine the probability of use by vultures according to both farm and individual characteristics Under review: García-Alfonso, M., van Overveld, T., Gangoso, L., Bouten, W., Serrano, D., Donázar, J. A. Individual- and farm-dependent drivers of vultures visits to livestock exploitations based on GPS data. Movement Ecology 4. To evaluate if Canarian Egyptian vultures are acknowledged by local farmers as beneficial ecosystem service providers. In addition, to contrast presence and abundance of vultures at farms as derived from GPS data with farmers’ awareness of those patterns, while disentangling the factors influencing such adjustment. Published: García-Alfonso, M., Morales-Reyes, Z., Gangoso, L., Bouten, W., Sánchez- Zapata, J.A., Serrano, D., Donázar, J.A., 2018. Probing into farmers’ perceptions of a globally endangered ecosystem service provider. Ambio 48, 900–912. doi:10.1007/s13280- 018-1102-3 Study system 10 Study system Target species and study area The Egyptian vulture is a migratory, long-lived scavenger that is declining in virtually all parts of its range, apparently due to increasing mortality from non-natural causes, so it is classified as “endangered” according to IUCN (Birdlife International, 2017). It mainly lives in open landscapes of rugged and arid regions where it consumes carcasses of animals of medium or small size. It nests in cliff cavities of variable size, maintains breeding territories during the breeding season and normally lays two eggs (Cramp and Simmons, 1980; Donázar, 1993), of which one or two chicks fledge the nest. They have a delayed maturity with an age of about 7 years old for the first breeding attempt. Although they are territorial, during such a long preadult stage, individuals are highly social congregating in large numbers at feeding locations and communal roosts, a behaviour showed mainly by non-adult individuals (del Hoyo et al., 1994). The species has occupied historically some archipelagos even at great distances of the mainland: Canary Islands, Balearic Islands, Cape Verde and Socotra (Donázar et al., 2002a; Freitas et al., 2019; Porter and Suleiman, 2012). It maintained very dense populations in these insular systems but strong declines took place during the 20th century in the Atlantic regions. In the Canary Islands the Egyptian vulture probably was present in all the islands, but it approached the extinction at the end of the 20th century. Currently it survives only in the most-easterly islands, Fuerteventura and Lanzarote (Fig. 1), with the bulk of the population congregated in Fuerteventura (Agudo et al., 2010; Bannerman, 1963, 1912; Donázar et al., 2002b; Martín, 1987). The Canarian Egyptian vulture is an endemic subspecies locally known as “Guirre”. Their insular context adds further ecological components of great interest: it is the only vulture species in the Canary Islands and this relict population is sedentary with a virtually non-existent immigration, being highly disconnected from others population. The Canary Islands are situated in the Northeast Atlantic ocean, between 27º 37’ and 29º 25’ N, and 13º 20’ and 18º10’ W. Fuerteventura is the nearest island to the African continent (97 km). The island measures 100 km long x 25 km width (1660 km2 ICE, 2008). In contrast with the remaining islands of the archipelago, their mean altitude is low; 54% of the land is below 200 m a.s.l., and 87% below 400 m a.s.l. (Donázar et al., 2002b). Some mountain ridges have sheer hillsides and cliffs. The climate is very dry with a mean annual temperature of 21.1ºC and 98 mm of annual rainfall (AEMET 2015). In addition, aridness is increased by Study system 11 strong northerly winds, the so called “allisios” (with an average speed of 20 km/h) that are particularly strong during spring and summer (Johnson and Stevens, 2000). The landscape is dominated by grass and scrublands with an almost total absence of woodland (Rodríguez Delgado et al., 2000). On this island crops are extremely scarce, only 16.75% of the territory are potential arable lands (Molina, 2002) of which only 0.27% are being cultivated (Cabildo de Fuerteventura, 2007). Resident human population in 2019 was almost 123.000 people (INE 2019), mostly living in the town of Puerto del Rosario (32%). Furthermore, almost two million tourists visit the island every year (Frontur Canarias, 2015). Lanzarote (846 km2 ICE, 2008) is the closest island being 11 km northern of Fuerteventura and there is an islet named Isla de Lobos (4.58 km2 ICE, 2008) between them (Fig. 1). Lanzarote is the third island most populated on Canary Islands having about 151.000 people (INE 2019). Figure 1. Canarian archipelago and their location on the world. The most easterly islands are Fuerteventura (south) and Lanzarote (north) on dark grey. Study system 12 Population monitoring This Canarian population has been monitored since 1998 intensively by a team of the EBD-CSIC. Every year a 2 or 3-people team conducts field work during six months covering the whole breeding season (from late February to late June). During this time all occupied territories in both islands (Fuerteventura and Lanzarote) are localized and controlled. Each territorial individual’s ring is identified and number of fledglings at the end of the breeding season was determined when nests were accessible for ringing and/or fully visible with spotting scopes. The population changed from only 21 territories in 1998 to 77 in 2019, which represents an average annual growth rate of 6%. Population size in 2019 reached 361 individuals, 198 non-breeding and 163 breeding conforming 154 breeding pairs and 9 trios. 89% of the individuals carried out metal and/or plastic rings in 2019. Breeding success has been extremely low as compared to other studied populations during all the study period (Donázar et al., 2002b and own data) and shows an apparent long-term decrease throughout the study period (Fig. 2). Figure 2. Number of breeding territories occupied by Egyptian vultures during the studied period and productivity calculated as the number of fledglings per number of occupied nest using only nest with known breeding success. Study system 13 Between 1998 and 2017, 429 fledglings were captured in their nests (mean age 55 days old, from mid-May to early August). In addition, 26 juvenile (1-year old), 240 subadult (2- to 5-years old) and 101 adult (≥6-years old) birds were captured using cannon-nets baited with carcasses. Birds could be aged until their fifth year of age according to plumage patterns (Cramp and Simmons, 1980; Forsman, 2016), but later they acquire the adult plumage. All the birds were ringed with both plastic and metal rings engraved with an individual alphanumeric code, and blood samples, feathers, typical measures and pictures were taken (Fig. 3). Individual sex was determined by genotyping in the Laboratory of Molecular Ecology (EBD-CSIC). Figure 3. Images of field work during monitoring and trapping of Egyptian vultures on Fuerteventura (Canary Islands). Between 1998 and 2019 field monitoring has been done (in chronological order) by César J Palacios, Ana Trujillano, Carmen Díez, Marcos Mallo, Sandra Sierra, Juan Ramírez, Toni Mulet, Walo Moreno, Julio Roldán, and José Sarrión. Individual movement monitoring In order to assess movement behaviour of Canarian Egyptian vultures, 49 different individuals have been tagged with GPS devices between 2013 and 2017 (SM1 chapter 1). Two type of devices were used: 27 UvA-BiTS (Bouten et al., 2013) and 21 E-obs (GmbH, Munich, Germany) that were fixed respectively to 30 (including reusing) and 21 individuals. Both kinds of devices are solar-powered and have multiple on-board sensors providing the geographical coordinates, altitude and speed of each individual according to a defined time interval. The collected information is stored in the devices which have a limited memory. Study system 14 UvABiTS devices (Fig. 4) use a type of Bluetooth-network to download the collected data, requiring a base-station which consists of an antenna and a laptop. Data are downloaded to the laptop when birds are in the reception area that can be extended by using a relay. It is not possible to localize target individuals using radiotracking. These devices offer the possibility of defining two different time blocks, making possible the establishment of high frequencies of collecting data during day and low frequencies during night. Figure 4. Details of an UvABiTS device on the left and a Canarian Egyptian vulture equipped with an UvABiTS device on the right. E-obs devices (Fig. 5) use the GSM-GPRS signal, which is the same as mobile phones use. A base-station is not needed, though to ensure connections where there is not signal they include a high-speed radio-link for wireless on-site data download. Normally, data collected is daily downloaded and when a device does not connect for any reason, data are kept until a new connection. It is possible to localize target individuals using radiotracking, so recovering of dead individuals is easier than using UvABiTS. However, e-obs do not offer the possibility of defining two different times blocks. Figure 5. Details of an e-obs device on the left and a Canarian Egyptian vulture with e-obs device being equipped on the right. Study system 15 In both devices, all downloaded data are removed from the transmitter, recovering space in the memory. Settings for collecting data can be changed at any moment and devices will detect such changes in the next connection. Due to requirements of UvABiTS devices, 2 base-stations and 3 relays are currently installed (Fig. 6). Batteries of relays have to be replaced every 3 months and the whole system requires frequent watching for occasional maintenance. The battery of the devices has to be periodically controlled in order to redefine the settings when facing low voltages, so periods without collecting information are avoided. Figure 6. Details of the required system for the correct functioning of UvABiTS devices. (A) Laptop installed close to the main supplementary feeding station conforming the base station number 1. (B) Antenna connected to the laptop 1. (C) Relay used during the installation of a supporting relay for base station 1. (D) Laptop installed close to the garbage dump conforming the base station number 2. (E) Antenna connected to the laptop 2. (F) Relay installed inside the garbage dump supporting the base station 2. (G) Another relay installed inside the garbage dump supporting the base station 2. Food predictability and social status drive individual resource specializations in a territorial vulture 88 Abstract Despite increasing work detailing the presence of foraging specializations across a range of taxa, limited attention so far has been given to the role of spatiotemporal variation in food predictability in shaping individual resource selection. Here, we studied the exploitation of human-provided carrion resources differing in predictability by Canarian Egyptian vultures (Neophron percnopterus majorensis). We focussed specifically on the role of individual characteristics and spatial constraints in shaping patterns of resource use. Using highresolution GPS data obtained from 45 vultures tracked for 1 year, we show that individual vultures were repeatable in both their monthly use of predictable and semi-predicable resources (feeding station vs. farms) and monthly levels of mobility (home range size and flight activity). However, individual foraging activities were simultaneously characterized by a high degree of (temporal) plasticity in the use of the feeding station in specific months. Individual rank within dominance hierarchy revealed sex-dependent effects of social status on resource preference in breeding adults, illustrating the potential complex social mechanisms underpinning status-dependent resource use patterns. Our results show that predictable food at feeding stations may lead to broad-scale patterns of resource partitioning and affect both the foraging and social dynamics within local vulture populations. Keywords: GPS-tracking, food predictability, Neophron percnopterus, resource specialisation, social rank, vultures. Chapter 2 89 Food predictability and social status drive individual resource specializations in a territorial vulture 90 Introduction Foraging tactics are often highly plastic, allowing individuals to respond adaptively to spatial and temporal fluctuations in resource availability and environmental changes. Yet, despite plasticity in foraging, individuals of the same species typically tend to use only a subset of the resources available in the environment, often displaying distinct foraging specializations and/or dietary preferences (Bolnick et al., 2003). Such individual divergence in resource use may arise from phenotypic differences (e.g., morphology, behaviour, and physiology) and environmental constraints affecting foraging trade-offs (Bolnick et al., 2003). As such, foraging specialisations are generally thought of as different foraging optimization strategies (Pyke et al., 1977; Stephens and Krebs, 1986). However, the extent to which the interplay between ecological conditions and individual resource preferences affects (or determine) population spatial dynamics remain poorly understood (Araújo et al., 2011). A major determinant of individual foraging strategies is the spatial clumping and temporal predictability of resources, affecting decisions on patch choice, patch departure times and inter-patch movements (Stephens and Krebs, 1986). Although temporal predictable food patches (pulsed resources) characterize most natural systems (e.g., upwelling, insect outbreaks, carcasses Yang et al., 2010), the presence of anthropogenic food resource pulses (e.g., fishing discards, refuse dumps, feeding stations) are increasingly impacting the natural dynamics of food supply, creating new ecological conditions upon which many animals base their foraging decisions (Oro et al., 2013). Predictable food patches can greatly alter the costs and benefits of foraging, either by reducing the time and energy needed for food searching (Bartumeus et al., 2010) or by increasing levels of competition among individuals attracted to the same resource and hence, the costs associated with food acquisition (Goldberg, 2001; Grand and Grant, 1994). While high levels of competition and interference at predictable food may lead to the exclusion of subordinate individuals from these resources, the mechanisms underlying the usage of locally superabundant food are likely more complex. First, the ‘economic defendability’ of this resource is typically low (Brown, 1964). While dominant individuals may be able to monopolize a large share of the food, there will always be some food available to lower-ranked individuals. For example, predictable food patches are often visited by individuals for which the costs of food searching may be high, such as young, inexperienced individuals or immigrants from other populations with limited knowledge of their Chapter 2 91 environment (Sanz-Aguilar et al., 2015). Second, for territorial birds, central place foraging constraints during breeding may importantly affect the ability of making use of predictable food (García-Heras et al., 2013). Such constraints may in turn differ among individuals depending on social rank if, for instance, the location of predictable food influences local territory quality (Carrete et al., 2006b; Sergio et al., 2007). Although there is increasing evidence that predictable anthropogenic resources are used by only a subset of the population, including seabirds (Patrick et al., 2015; Tyson et al., 2015; Votier et al., 2010) and storks (Sanz-Aguilar et al., 2015), studies examining the potential trade-offs responsible for the asymmetric use of anthropogenic food are still scarce (but see Sanz-Aguilar et al., 2015). European vultures currently rely on feeding stations (where abundant food is supplied on a regular basis) (Cortés-Avizanda et al., 2016) and, to a lower extent, on the surroundings of cattle farms (more places, but where food is scarcer and less predictable) (Cortés-Avizanda et al., 2012). Despite concerns about the potential impact of such large feeding stations on the natural foraging habits and social structure of local vulture populations (Carrete et al., 2006a; Fluhr et al., 2017; Margalida et al., 2013b), a mechanistic understanding of how the use of surplus food varies within and among individuals is still lacking. The extent to which changes in the spatial distribution and predictability of resources may influence behavioural processes key to understand spatial population dynamics therefore still remain poorly understood. Here, we assessed individual plasticity and repeatability in the exploitation of food resources varying in predictability by a territorial, but highly social avian scavenger. We took advantage of a twenty-year research program on a closed island population of the endangered Canarian Egyptian vulture (Neophron percnopterus majorensis). Continuous monitoring has resulted in 90% of the birds (total population size c.a. 300 individuals) being ringed in 2016, 16% of them carrying GPS-transmitters (n = 45). Firstly, we described seasonal variation in the monthly use of food resources varying in their spatiotemporal predictability (i.e. highly predictable feeding stations and garbage dump, versus semi-predictable goat/sheep farms) and how vultures allocated their time into flight and non-flight behaviour. Next, we tested our main hypothesis that individual vultures differ in resource preferences as a result of traitspecific foraging optimization strategies. In a first step, we assessed whether individual vultures were repeatable in their preferences for food resources differing in predictability (farms vs. feeding stations) and levels of mobility (home range size and flight activity). Second, we specifically test whether birds preferring predictable food reduce their overall food searching activities (i.e., showing both smaller home ranges and reduced flight activity) Food predictability and social status drive individual resource specializations in a territorial vulture 92 by analysing both within- and among-individual correlations between resource use and mobility. Finally, we examine whether predictable food is of higher value to dominant birds, owing to their superior competitive skills, by analysing the effects of individual rank within a dominance hierarchy, as well as sex, age, and territorial status. In addition, in territorial birds, we examine the role of spatial constraints in shaping individual resource use and patterns of mobility, by analysing how territory location (i.e. distance to predictable feeding sites) may affect resource use and ranging behaviour, again, in relation to individual traits. Materials and Methods Study species and population The Canarian Egyptian vulture is a sedentary and endemic long-lived scavenger occupying the eastern part of the Canarian Archipelago (between 27.62º - 29.42º N, and 13.33º - 18.17º W). The species was once abundant throughout the archipelago (Bannerman, 1963), but is currently classified as ‘critically endangered’ owing to severe population declines since the 20th century. Fuerteventura Island (1662 km²) is the stronghold of the population, which is home to 60 breeding pairs and has an estimated population size of about 300 individuals in 2016 (authors unpublished). Extensive fieldwork (ringing of nestling and trapping of adults) has resulted in over 90% of the individuals being individually marked in 2016. Egyptian vultures are facultative scavengers that forage solitary (or sometimes in couples). The species leads a vagrant but very social lifestyle prior to recruitment, but afterwards adults are much more solitary and territorial. Throughout the year, they may form large aggregations at places with an abundance of food and roosting often occurs communally (Donázar et al., 1996b). On Fuerteventura, the species heavily relies on human-provided carcases available at goat and sheep farms throughout the island (Fig. 1, further details see below). At these farms, livestock carcasses appear irregularly in time. Slaughterhouse remains (pork heads and intestines, ± 200 kg per week) are provided once or twice a week at each of the two feeding stations, one being located in the centre of the island (created in 1998) and one in the north (created in 2008) (Fig. 1). Local farmers regularly add additional livestock carcasses to both feeding stations. The feeding stations are separated by approximately 40 km distance. Vultures sometimes also forage at the garbage dump near the capital city Puerto del Rosario. Apart from these human-provided food resources, vultures may consume randomly encountered carcasses, especially those of feral goats and small-sized vertebrates such as wild rabbits (Oryctolagus cuniculus) and feral pigeons (Columba livia ) (Gangoso et al., 2006). Chapter 2 93 GPS tracking Vultures were captured with cannon-nets about 3km away from the main feeding station in the centre of the island. GPS trackers (UvA-BITS, www.uva-bits.nl, University of Amsterdam, n = 26; e-obs, e-obs Digital Telemetry, Grünwald, Germany, n = 19) were attached to the bird using backpack harnesses. The total weight of the system varied between 31 g (UvABiTS) and 54 g (e-obs) (1.4-2.4% of the weight of the bird) which is assumed to be harmless to the individual (Sergio et al., 2015). In total, we used GPS-tracking data from 45 birds (24 females (14 territorial and 10 non-territorial) and 21 males (11 territorial and 10 nonterritorial) collected over a 12-month period (October 2015- September 2016). GPS loggers were programmed to record locations every 1 to 5 minutes, but data were re-sampled to an interval of 10 minutes (range 9-11 minutes, R-function developed by D.S. Viana) to allow direct comparisons between individuals. Because of low-battery levels and/or poor satellite reception, intervals exceeding15 minutes were removed from the dataset. We only used GPS- fixes between sunrise and sunset. We included all months with continuous recording of GPS- locations, independent of downloading error (which was small due to sunny weather conditions). However, we excluded months for which we had incomplete logging data (e.g. due to exceedance of data logging capacity and mortality (N = 2). We also excluded all movements made to the neighbouring Lanzarote island (e.g. one bird breeds on Lanzarote, but spent its time outside the breeding season on Fuerteventura). In total, we had data available for 486 individual-month (994.179 fixes), comprising 12 months for 35 individuals and between 3 to 11 months for 10 individuals. The median percentage of time explained per month by GPS fixes was 94.8% (range 16.13 – 100 %, further details below). Monthly activity budgets To construct monthly activity budgets we distinguished between time allocated to flight vs. non-flight behaviour (including resting and foraging) using a threshold ground speed 3 m/s for data obtained from both GPS devices (see Fig. S1). Non-flight behaviour was further subdivided into time allocated to foraging at two types of food resources: highly predictable places (the two feeding stations and the garbage dump) and semi-predictable places (goat-sheep farms). To classify GPS data into resource use, we used the number of GPS locations within a buffer zone of 75 m around the centre of the two feeding stations and a buffer zone of 250m around the centre of the garbage dump, covering respectively the total fenced area and the total surface of the garbage dump. Since farmers drop carcasses at variable distances from their farms, we used a buffer zone of 250m to determine the use of Food predictability and social status drive individual resource specializations in a territorial vulture 94 farms as source of food (i.e. based on 10 farms where we knew the exact distance (median 254 m, range 60– 610m, García Alfonso et al. under review). In total, we were able to retrieve the coordinates of 319 out of 437 farms (73%). Farms differed greatly in size (median 202 animals, range 10-4217, n = 292). Our data included all farms with more than 500 animals (N = 67). Annual mortality rate of sheep and goats (including lambs) at farms is estimated at about 10% (see Margalida and Colomer, 2012). We described monthly variation in average timebudgets of all individuals (flight vs. non-flight behaviour), specifically detailing the time spent at resources differing in predictability in the non-flight category (the two feeding stations, garbage dump and all farms pooled). See Fig. S2 for an overview of average monthly time-budgets. Ranging behaviour Monthly ranging behaviour per individual was quantified by calculating utilization distributions (UD) using the fixed kernel contour method on the adehabitHR package, R version 3.0.3 (Calenge, 2014). Since we were interested in food searching behaviour and/or explorative movements, ranging behaviour was defined using the 95% kernel density estimate (95KDE, in km²). We excluded all non-flight GPS fixes at the feeding stations, garbage dump and farms to improve the independence of our home range estimate. Since the use of a reference smoothing factor (href) led to unrealistic estimates of home ranges (see Fig. S3 for details), we checked manually home range sizes using different smoothing parameters (h) (Wand and Jones, 1993) and realistic estimates were found for h between 500-1000m (see Fig. S4 for examples and more details on selection of smoothing parameters). We therefore chose to set the width around each point location to 750 m, using a constant kernel width for each individual allowing comparing ranging behaviour between individuals. To check for effects of temporal/spatial autocorrelation of locations on home range estimates, we recalculated 95%KDE using Brownian Bridge Movement Models (BBMM), which method specifically integrates movement paths in estimates of home range sizes (Walter et al., 2011). However, both methods produced highly similar 95%KDE when using similar smoothing parameters, or estimates were highly correlated when using various custom made smoothing factors (details provided at Fig. S4-S5). Chapter 2 95 Dominance data Data on social dominance were collected in February 2016 (early breeding season) and August-September 2016 (post-breeding season). We noted all agonistic displacements between colour-ringed individuals around baits at the central feeding station (from a hide) between sunset and sunrise. In total, we observed 4593 displacements between 141 individuals that were involved in more than 20 displacements (average 65.1 ± 3.0 S.E., range 20-175 ), including 40 birds fitted with GPS loggers (19 males and 21 females: average 65.5 ± 6.4 S.E. displacements, range 20-175). Rank scores for each individual were determined using David’s score using the ‘compete’ package in R (Curley, 2016), corrected for chance of encounter and thus independent of group size or visiting rate, see Suppl. Mat. text S1 and Fig. S6 for details (Gammell et al., 2003). Scores obtained from the total dataset were used (details in Fig. S7). Rank was scaled between 0-1 with 1 being the most dominant bird. Statistical analyses We conducted all statistical analyses using SAS 9.4 software (SAS Institute Inc., Cary, NC). We used a three-step approach to analyse our data. First, to quantify individual differences in the use of predictable and semi-predictable resources and movement behaviour we tested for repeatable individual differences in resource use (time spent at the main feeding station and farms, both square-root transformed), resource preference (ratio time spent at feeding station: farms, arctangent-transformed) and mobility (ranging behaviour by 95KDE, log-transformed, and time spent flying by ‘flight activity’, square-root transformed). All transformed response variables were scaled by the standard deviation and mean-centred. Repeatability (R) was calculated based on a null model without main effects (i.e., nonadjusted), as the among-individual variance divided by the sum of the among-individual and the residual within-individual variance (Dingemanse and Dochtermann, 2013), using univariate mixed-effect models with bird ID as a random effect and a Gaussian error distribution. To interpret factors influencing individual repeatability in behaviours, non-adjusted repeatability indices were compared with adjusted repeatability in full models including individual traits and environmental factors (see below). To test the significance of repeatability, we compared models with and without the random effect of bird ID using a likelihood ratio test LRT (Pinheiro and Bates, 2000; Zuur et al., 2009). Food predictability and social status drive individual resource specializations in a territorial vulture 96 Second, links between individual preferences for resources differing in predictability and mobility patterns were tested by analysing within- and between-individual correlations in monthly resource use, ranging behaviour and flight activity (based on average daily measurements) using bivariate mixed-effects models (Dingemanse and Dochtermann, 2013). Significance of within-individual correlations was tested by comparing unconstrained models with models where the within-individual covariance was constrained to zero, again by applying an LRT test (to compare the χ2 against P(χ 2, df = 1). In the last part of our analyses, we tested the effects of individual attributes and territory location on resource preferences and mobility (dependent variables). First, we fitted LMMs with bird ID as random effect and included month, sex (male or female), dominance rank, age (in years) and territorial status (yes or no) as fixed effects. Since exploratory analyses showed that resource use and patterns of mobility varied strongly across the year in a non-linear manner (Fig. S2), we included month squared in all analyses. To test whether effects of dominance rank on resource use varied between the sexes and between territorial and non-territorial birds, we included two interactions: sex × rank and territorial status × rank in all models. We also included another two interactions (month squared × sex and month squared × dominance rank) to test for sex- or dominance-specific seasonal relationships. All covariates were mean and variance standardized. Finally, for territorial birds, we tested whether distance from the territory (nest location) to the central feeding station affected resource use and mobility, and whether territory location was explained by social rank (for males and females separately), using a LMM again with bird ID included as a random effect. Full models included all main fixed effects, random effects and interaction terms irrespective of their significance. Note that adjusted repeatability indices were calculated based on these full models. Results Temporal dynamics in resource use and movement pattern The overall monthly proportion of time spent at human-provided food resources (feeding stations, farms, garbage dump; all pooled, see Fig. 1 for an overview) was 14.7% ± 9.8 SD. Vultures spent most time at the central feeding station and to a lesser extent at farms (average monthly proportion of time 8.5% ± 9.0 SD and 3.9% ± 4.6 SD, respectively). The garbage dump and the feeding station located in the north, were rarely used (average 1.5% ± Chapter 2 97 2.4 SD and 0.9% ± 2.3 SD, respectively). Monthly time budgets varied strongly over the course of the season. As a general pattern, average monthly flight activity was generally low during the non-breeding season (July-December) and substantially increased during the breeding season (January-June). By contrast, average monthly time spent at the central feeding station, and to a lesser extent at farms, decreased during the breeding season and again increased during the non-breeding season (Fig. S2, details in text S2 and below). Individual repeatability and plasticity in resource use and mobility There was significant among-individual variance in the intercepts (i.e. non-adjusted individual repeatability) of the time spent at the central feeding station (variance ± SE = 0.43 ± 0.10, χ21 = 175.6, p < 0.001), farms (0.45 ± 0.11, χ21 = 203.4, p < 0.001) and the ratio feeding station: farms (‘resource preference’: 0.47 ± 0.11, χ21 = 209.1, p < 0.001). Both measures of mobility were also individually repeatable: logKDE95 (0.43 ± 0.10, χ21= 184.8, p < 0.001), and flight activity (0.18 ± 0.06, χ21= 39.8, p < .0001). There was no significant within-individual or among-individual covariance between the use of farms and feeding stations (Table 1), nor among-individual covariance between resource use and mobility parameters (Table 1, for territorial and non-territorial males and females, Fig. 2. a.1-d.1). Positive within-individual covariance was found between the use of the feeding station and LogKDE95 (χ = 34.4, p < .0001, Table 1), while negative withinindividual covariance was found between time spent at the central feeding station and flight activity (χ = 89.1, p < 0.001, Table 1), indicating that individual birds increased home-ranges and decreased flight activity in those months when they visited the feeding station more frequently. A similar relationship was found for resource preference (χ = 27.1 and 20.6, both p < 0.001, for covariance with flight activity and LogKDE95, respectively), but not the use of farms, indicating that the effects of resource preference on mobility were driven by the use of the feeding station (Table 1). Within-individual covariance between time spent at the central feeding station and mobility parameters (home-range size and flight activity) were both significant in territorial birds, with females: 0.23 ± 0.04, χ = 39.3, p < 0.001 (Fig. 2. a.2-a.3) and -0.37 ± 0.07, χ = 39.1, p < 0.001; and males: 0.25 ± 0.06, χ = 24.2, p < 0.001 and -0.26 ± 0.06, χ = 21.6, p < 0.001 (Fig. 2. b.2-b.3), while for non-territorial females and males, significant within-individual covariance was found only between time spent at the central feeding station and flight activity with p <0.001 for non-territorial females (Fig. 2. c.2-c.3) and males (Fig. 2. d.2-d.3). Food predictability and social status drive individual resource specializations in a territorial vulture 104 food may importantly affect both the foraging and social dynamics of local vulture populations. However, our results also evidence that other poorly known sex-specific mechanisms are at play, opening new research avenues. Overall, our study highlights the need to take into account social rank differences when studying patterns of individual resource specialization in highly social species. Acknowledgements We thank Ana Trujillano, Carmen Díez, Marcos Mallo, Walo Moreno, Juan Ramírez, and Julio Roldán for their invaluable work in monitoring the ‘’Guirre’’ population on the Canary Islands. We also thank David F. Westneat for help SAS codings. TVO received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No ”SocForVul 659008”. The long-term monitoring of the vulture population has been funded by the projects REN 2000–1556 GLO, CGL2004-00270/BOS, CGL2009-12753-C02-02, CGL2012-40013-C02-01, and CGL2015- 66966-C2-1-2-R (Spanish Ministry of Economy and Competitiveness and EU/FEDER). Further support was provided by, the Cabildo Insular de Fuerteventura and the Dirección General de Protección de la Naturaleza (Viceconsejería de Medio Ambiente, Canarian Government). Ethic statements Capture, banding and monitoring of Egyptian vultures were conducted under permits and following the protocols approved by the Cabildo Insular de Fuerteventura and the Dirección General de Protección de la Naturaleza (Viceconsejería de Medio Ambiente, Canarian Government) and following the protocols approved by the Ethic Committee of CSIC (CEBA-EBD-12-56), in accordance with the approved guidelines. Author Contributions T.V.O., N.J.D, M.G.A and J.A.D developed research questions. T.V.O. and L.G. conducted fieldwork and T.V.O. collected dominance data. T.V.O. carried out the statistical analyses with input from N.J.D., T.V.O wrote the manuscript with editorial input from coauthors (J.A.D., D.S., L.G., N.J.D., M.G.A, W.B., M.R.). All authors gave final approval for publication. Chapter 2 105 Figure 1. Overview of Fuerteventura showing the availability of semi-predictable resources (farms, black dots, n = 319), and predictable resources (two feeding stations at approximately 40 km distance (red stars) and garbage dump (red dot)). The grey dots represent the territories of GPS- logged territorial birds (11 females and 9 males) and the white dots all occupied territories in 2016 (n = 60). Food predictability and social status drive individual resource specializations in a territorial vulture 106 Figure 2. Within- and among-individual correlations between mobility parameters (home range size and flight activity) and time spent at the central feeding station (X-axis) in Egyptian vultures for (a) territorial females, (b) territorial males, (c) non-territorial females and, (d) non-territorial males, tracked between October 2015 and September 2016. (a.1-d.1) among-individual correlations (n = 45 individual means), (a.2-d.2 and a.3-d.3) within-individual correlation (n = 486 months). The plot of the among-individual correlation is visualized as the correlation between means of each individual trait; the within-individual correlation is visualized as the correlation between the deviations of each monthly observation from a focal individual’s mean for each trait. Chapter 2 107 Figure 3. Differences in a) dominance rank (high values indicating high ranks) and b) resource preference (ratio time spent at feeding stations:time spent at farms (scaled by the standard deviation and mean-centred) for 40 Egyptian vultures fitted with GPS loggers categorized according to sex and territorial status (TF: territorial females, NTF: non-territorial females, TM: territorial males, NTM: non-territorial males). Food predictability and social status drive individual resource specializations in a territorial vulture 108 Figure 4. Overview of monthly variation in a) time spent at the central feeding station, and b) farms (all pooled), c) home range size (95% Kernel Density Estimate, KDE), d) flight activity (number of hours flying), e) flight distance from the central feeding station, and f) the total number of farms visited. Data for territorial female Egyptian vultures tracked with GPS-loggers on Fuerteventura between October 2015 and September 2016. For illustrative purposes, individuals were categorized according to dominance status (dominant above and subdominant below the median), but included as a continuous variable in statistical models. Note that the breeding activities of vultures occur between January and July (with the peak in egg-laying occurring in March) Chapter 2 109 Figure 5. Overview of monthly variation in a) time spent at the central feeding station, and b) farms (all pooled), c) home range size (95% Kernel Density Estimate, KDE), d) flight activity (number of hours flying), e) flight distance from the central feeding station, and f) the total number of farms visited. Data for territorial male Egyptian vultures tracked with GPS-loggers on Fuerteventura between October 2015 and September 2016. For illustrative purposes, individuals were categorized according to dominance status (dominant above and subdominant below the median), but included as a continuous variable in statistical models. Note that the breeding activities of vultures occur between January and July (with the peak in egg-laying occurring in March) Food predictability and social status drive individual resource specializations in a territorial vulture 110 Figure 6. Overview of monthly variation in a) time spent at the central feeding station, and b) farms (all pooled), c) home range size (95% Kernel Density Estimate, KDE), d) flight activity (number of hours flying), e) flight distance from the central feeding station, and f) the total number of farms visited. Data for non-territorial Egyptian vultures tracked with GPS-loggers on Fuerteventura between October 2015 and September 2016. In non-territorial males and females no effects of dominance was present. Note that the breeding activities of vultures occur between January and July (with the peak in egg-laying occurring in March) Chapter 2 111 Figure 7. Relationship between dominance rank and distance from the breeding territory to the central feeding station (km) for male and female Egyptian vultures on Fuerteventura in 2016. Black dots represent birds fitted with GPS-loggers (13 females and 9 males) and crosses birds with known dominance rank (36 females and 25 males). The relationship in females is significant (Spearman rank correlation, r = -0.77, p = 0.002, and r = -0.59, p = 0.0001, respectively), while non-significant in males (p = 0. 55 and p = 0.18 respectively). Food predictability and social status drive individual resource specializations in a territorial vulture 112 Table 1. Estimated within- and among-individual covariances (Cov.) and correlations between mobility parameters (home range size (logKDE95), and flight activity (time spent flying)), resource use (time spent at farms and at the central feeding station, square-root transformed), and resource preference (ratio time spent at the feeding station:farms, arctangent transformed) of Egyptian vultures on Fuerteventura extracted from a bivariate mixed model with no covariates. Significant correlations (p < 0.05) are printed in bold. Activity Home range Farms Feeding station Cov. ± S.E. r Cov. ± S.E. r Cov. ± S.E. r Cov. ± S.E. r a) Within-individual correlation Home range 0.03 ± 0.03 0.10 Farms 0.05 ± 0.03 -0.10 0.04 ± 0.03 0.07 Feeding station -0.30 ± 0.04 -0.42 0.15 ± 0.03 0.27 0.01 ± 0.03 0.01 Resource preference -0.16 ± 0.03 -0.24 0.11 ± 0.03 0.21 -0.20 ± 0.03 -0.37 0.39 ± 0.10 0.77 b) Between-individual correlation Home range 0.03 ± 0.03 0.08 Farms -0.02 ± 0.05 -0.05 -0.04 ± 0.07 -0.05 Feeding station 0.01 ± 0.05 0.02 0.04 ± 0.07 0.09 -0.10 ± 0.07 -0.23 Resource preference 0.02 ± 0.05 0.05 0.06 ± 0.07 0.14 -0.27 ± 0.09 -0.60 0.42 ± 0.03 0.87 Chapter 2 113 Table 2. Results of GLMM on seasonal effects and individual attributes affecting monthly resource preference (ratio time spent at the feeding station:farms, arctangent transformed), home range size (logKDE95) and flight activity (time spent flying, square-root transformed) of 45 Egyptian vultures tracked with GPS-loggers on Fuerteventura (Spain). All transformed response variables were scaled and centred. Repeatability (R) was calculated as the among-individual variance divided by the sum of the among-individual and the residual (within-individual) variance, and its significance tested by comparing models with and without the random effect of bird ID using a likelihood ratio test. a) Resource preference a) Home range size c) Activity Fixed effects β (SE) FNUMdf, DENdf P β (SE) FNUMdf, DENdf P β (SE) FNUMdf, DENdf P Intercept -0.52 (0.23) 0.031 -0.73 (0.25) 0.005 1.31 (0.23) 0.000 Sex -0.28 (0.33) 2.65 1,58.2 0.110 0.25 (0.36) 0.95 1,55.7 0.330 -0.96 (0.33) 4.94 1,51.9 0.031 Age -0.27 (0.09) 9.33 1,32 0.045 0.05 (0.10) 0.27 1,32.8 0.610 0.10 (0.09) 1.17 1,31.5 0.290 Territorial status -0.80 (0.33) 0.02 1,51.4 0.880 2.21 (0.35) 46.67 1,49.6 0.000 -0.06 (0.33) 0.40 1,46.4 0.530 Dominance rank -0.68 (0.31) 0.19 1, 52.8 0.670 -0.03 (0.33) 0.04 1,50.8 0.840 0.47 (0.33) 4.22 1,47.5 0.046 Month 0.08 (0.03) 6.29 1, 393 0.013 -0.12 (0.03) 12.67 1,392 0.000 0.12 (0.03) 14.80 1, 391 0.000 Sex*dominance rank 1.53 (0.37) 17.48 1, 53.9 0.000 0.01 (0.34) 0.00 1, 51.8 0.950 -0.15 (0.37) 0.17 1, 48.4 0.680 Sex*territorial status 15.55 1, 53.9 0.000 7.08 1, 51.7 0.010 0.84 1, 48.4 0.360 Month² 0.17 (0.11) 15.34 1, 389 0.000 0.23 (0.11) 1.69 1, 389 0.190 -1.02 (0.10) 126.7 1, 388 0.000 Month²* sex*dominance rank 6.80 2, 387 0.001 4.15 2, 387 0.017 4.28 2, 386 0.015 Month²* sex*territorial status 8.38 3, 387 0.000 25.14 3, 387 0.000 3.19 3, 386 0.024 Random effects σ² (SE) Z P σ² (SE) Z P σ² (SE) Z P Individual 0.18 (0.06) 3.2 0.001 0.22 (0.07) 3.35 0.000 0.21 (0.06) 3.33 0.000 Residual 0.46 (0.03) 13.81 0.000 0.47 (0.03) 13.82 0.000 0.40 (0.03) 13.79 0.000 Adjusted repeatability R χ² P R χ² P R χ² P 0.28 64.7 0.000 0.32 82.3 0.000 0.34 85.8 0.000 Null-model σ² (SE) Z P σ² (SE) Z P σ² (SE) Z P Individual 0.47 (0.11) 4.23 0.000 0.43 (0.10) 4.18 0.000 0.18 (0.06) 3.2 0.001 Residual 0.53 (0.04) 14.86 0.000 0.56 (0.04) 14.87 0.000 0.83 (0.06) 14.85 0.000 Non-adjusted repeatability R χ² P R χ² P R χ² P 0.47 209.1 0.000 0.43 184.8 0.000 0.18 39.8 0.000 Food predictability and social status drive individual resource specializations in a territorial vulture 120 Figure S6. Relationship between the number of displacements scored for each individual (n = 141, > 20 displacements) and the dominance score (David’s score), corrected for chance. A weak, but significant, positive correlation exists between the number of interactions and dominance score (Pearson correlation: r = 0.32, p = 0.001), which is due to dominant birds visiting the feeding station more frequently (see results). Figure S7. Relationship between unstandardized David’s score calculated using either all interactions between 141 birds in the total datasets (4593 displacements) and scores calculated using interactions between GPS birds only (550 displacements) (Pearson correlation: r = 0.95, p <.0001) Chapter 2 121 Text S1. The structure of dominance relations To examine whether the dominance relationships were linear we calculated the ‘adjusted linearity index h’(de Vries, 1995), using the ‘Compete’ package in R (Curley, 2016). This index ranges from 0 (non-linear) to 1 (highly linear). To determine the statistical significance of h’, we tested whether this index differed significantly from the expected value for random dominance relations by running 10000 randomizations (corrected for unknown relationships by randomly filling in null dyads). Landau’s linearity indices h for both the total and GPS dataset were low (h = 0.07 and h = 0.14, respectively), although significant (p = 0.0001, p = 0.0017). The low h indexes are most likely due to the high number of null dyads in the datasets leading to a bias in these estimates (Shizuka and McDonald, 2013). We therefore also calculated the directional consistency index (DCI) (Van Hooff and Wensing, 1987), which provides a measure for assessing how frequent a type of behaviour occurred in its more frequent direction relative to the total number of times it occurred (using the equation DCI = (H - L)/(H + L), where H is the total number of times the behaviour occurred in the direction of the higher frequency and L is the number of times in the less frequent direction). DCI scores were high in both datasets (DCI = 0.957 and DCI = 0.945 respectively), indicating a relatively strong linearity in hierarchy. Food predictability and social status drive individual resource specializations in a territorial vulture 122 Text S2. Monthly variation in resource use Average monthly flight activity was generally low during the non-breeding season (July-December) and substantially increased during the breeding season (January-June) (18.2% ± 7.0 SD, n = 250 and 31.1% ± 10.3, n = 236 respectively). Average monthly time spent at the central feeding station was lower during the breeding season compared to the non-breeding season (18.25h ± 23:02 SD, n = 236 and 42:16h ± 35:25 SD, n = 250, respectively). This difference was due to a lower (absolute) number of visits (14.4 ± 16.9 SD, n = 236 vs. 26.3 ± 21.1 SD, n = 250), shorter visiting bouts (01:15h ± 00:46 SD, n = 185 vs. 01:38h ± 00:46 SD, n = 226) and fewer individuals visiting this feeding site (30.8 ± 3.0 SD, n = 6 vs. 37.7 ± 1.8 SD, n = 6) during breeding. Foraging activities were also more dispersed during the breeding season compared to the non-breeding season (i.e., average monthly flight distance from central feeding station: 16.1 km ± 10.0 SD, n = 236 vs. and 11.8 km ± 9.7 SD, n = 250, respectively). Average monthly time spent at farms was slightly lower during the breeding season compared to the non-breeding season (12:23h ± 14.29 SD, n = 236 and 15.54h ± 17:56 SD, n = 250, respectively). Visiting bouts at farms were shorter during the breeding season (00:59h ± 00:41 SD, n = 218 vs. 01:30h ± 01:14 SD, n = 242) while visiting rates were slightly higher (12.3 ± 11.8SE, n = 236 vs. 10.6 ± 10.1SD, n = 250, respectively). Farms visited during the breeding season were located further away from the central feeding station compared to the farms visited during the non-breeding season (average monthly distance: 16.7km ± 11.3 SD, n = 222 and 11.8km ± 9.8 SD, n = 246, respectively). The average monthly number of farms visited (per individual) did not differ between the breeding and non-breeding season (4.8 ± 4.0 SD, n = 236 and 4.6 ± 2.9 SD, n = 250 respectively). Chapter 2 123 Table S1. Results of GLMM on seasonal effects and individual attributes affecting monthly time spent at the central feeding station (square-root transformed), time spent at farms (square-root transformed), home range size (logKDE95), flight acivity (time spent flying, square-root transformed) and number of farms visited (square-root transformed) for territorial males (9 individuals, 101 months), territorial females (13 individuals, 142 months) and non-territorial birds (18 individuals (10 males and 8 females), 209 months). All transformed response variables were scaled by the standard deviation and mean-centred. “Distance” as “Dist” and “Dominance” as “Dom.”. Territorial females Territorial males Non-territorial birds Dependent Fixed effects β (SE) FNUMdf, DENdf P β (SE) FNUMdf, DENdf P β (SE) FNUMdf, DENdf P variable Time at central feeding station Sex n/a n/a n/a n/a n/a n/a 0.23 (0.37) 0.39 1,24.5 0.540 Dom. rank 0.82 (0.23) 12.49 1,16.8 0.003 -0.02 (0.46) 0.00 1,7.83 0.970 n/a n/a n/a Dist territory -0.60 (0.18) 11.10 1,18.1 0.004* -0.35 (0.16) 4.77 1,8.42 0.060 n/a n/a n/a Month -0.10 (0.05) 3.55 1,128 0.060 0.02 (0.06) 0.09 1,89 0.770 -0.02 (0.05) 0.11 1,191 0.740 Month² 0.93 (0.11) 75.95 1,127 0.000 0.25 (0.11) 5.22 1,88.1 0.025 0.27 (0.07) 17.66 1,189 0.000 Month²*Dom. rank -0.26 (0.09) 7.74 1,128 0.006 -0.60 (0.16) 13.14 1,88.1 0.001 n/a n/a n/a Month²*Dist territory 0.20 (0.07) 8.30 1,140 0.005* 0.22 (0.06) 14.07 1,88.1 0.000 n/a n/a n/a Month²*sex n/a n/a n/a n/a n/a n/a 0.06 (0.13) 0.19 1,189 0.660 * Significant when entered in the model without Dom. rank Time at farms Sex n/a n/a n/a n/a n/a n/a -0.32 (0.27) 1.35 1,33.8 0.250 Dom. rank -0.13 (0.20) 0.461,11.3 0.51 1.51 (0.53) 7.98 1,6.48 0.028 n/a n/a n/a Month -0.23 (0.05) 18.61 1,130 0.000 -0.19 (0.06) 10.16 1,90.7 0.002 -0.20 (0.05) 13.76 1,194 0.000 Month² 0.16 (0.07) 5.93 1,129 0.016 0.24 (0.07) 10.54 1,89.6 0.002 -0.04 (0.10) 2.90 1,192 0.090 Month²*Dom. rank 0.09 (0.10) 0.79 1,128 0.380 0.21 (0.18) 1.76 1,88.5 0.19 n/a n/a n/a Month²*sex n/a n/a n/a n/a n/a n/a -0.06 (0.29) 1.32 1,192 0.220 Food predictability and social status drive individual resource specializations in a territorial vulture 124 Territorial females Territorial males Non-territorial birds Dependent Fixed effects β (SE) FNUMdf, DENdf P β (SE) FNUMdf, DENdf P β (SE) FNUMdf, DENdf P variable Home range size Sex n/a n/a n/a n/a n/a n/a -0.74 (0.20) 14.21 1,18.5 0.001 Dom. rank 0.16 (0.26) 0.38 1,14.5 0.550 0.37 (0.54) 0.47 1,10.3 0.510 n/a n/a n/a Month -0.13 (0.04) 8.86 1,128 0.004 -0.31 (0.08) 14.51 1,90.9 0.000 -0.01 (0.05) 0.08 1,196 0.77 Month² 0.56 (0.10) 33.46 1,127 0.000 0.13 (0.15) 0.65 1,89.1 0.420 -0.50 (0.06) 68.4 1,193 0.000 Month²*Dom. rank -0.38 (0.08) 20.09 1,127 0.000 -0.47 (0.24) 3.88 1,89 0.052 n/a n/a n/a Month²*sex n/a n/a n/a n/a n/a n/a 0.19 (0.12) 2.45 1,192 0.120 Flight activity Sex n/a n/a n/a n/a n/a n/a -0.11 (0.22) 0.29 1,17.9 0.590 Dom. rank 0.46 (0.26) 3.18 1,16.4 0.090 0.45 (0.36) 1.61 1,13.2 0.230 n/a n/a n/a Month 0.10 (0.06) 2.67 1,127 0.100 0.23 (0.07) 13.01 1,91.8 0.001 0.01 (0.04) 5.59 1,193 0.019 Month² -0.58 (0.13) 18.75 1,126 0.000 -1.05 (0.12) 71.67 1,89.4 0.000 -0.78 (0.05) 252.25 1,191 0.000 Month²*Dom. rank -0.19 (0.11) 2.55 1,127 0.110 -0.32 (0.19) 2.86 1,89.3 0.090 n/a n/a n/a Month²*sex n/a n/a n/a n/a n/a n/a 4.64 1,190 0.033 Total number of farms Sex n/a n/a n/a n/a n/a n/a -0.67 (0.25) 7.00 1,39.6 0.012 Dom. rank -0.84 (0.32) 6.50 1,15.9 0.022 0.77 (0.49) 2.45 1,9.45 0.150 n/a n/a n/a Month -0.02 (0.07) 0.09 1,128 0.770 -0.20 (0.08) 6.91 1,90.4 0.010 -0.27 (0.06) 23.23 1,196 0.000 Month² -0.22 (0.14) 2.32 1,127 0.130 0.23 (0.14) 2.68 1,88.4 0.110 -0.21 (0.07) 8.75 1,193 0.004 Month²*Dom. rank 0.32 (0.12) 6.93 1,128 0.010 -0.07 (0.22) 0.10 1,88.3 0.750 n/a n/a n/a Month²*sex n/a n/a n/a n/a n/a n/a 0.11 1,193 0.740 125 Chapter 3 Individual- and farm-dependent drivers of vultures visits to livestock exploitations based on GPS data Marina García-Alfonso1,a, Thijs van Overveld¹, Laura Gangoso2, Willem Bouten2, David Serrano1 and José A. Donázar1, a 1 Department of Conservation Biology, Estación Biológica de Doñana (CSIC). C/Américo Vespucio 26, 41092 Sevilla, Spain. 2 Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands 169 Chapter 4 Probing into farmers' perceptions of a globally endangered ecosystem service provider Marina García-Alfonso1,a, Zebensui Morales-Reyes2, Laura Gangoso3, Willem Bouten3, José A. Sánchez-Zapata2, David Serrano1 and José A. Donázar1 1 Department of Conservation Biology, Estación Biológica de Doñana (CSIC). C/Américo Vespucio 26, 41092 Sevilla, Spain. 2Department of Applied Biology, Miguel Hernández University, Avda. de la Universidad, s/n, 03202 Elche, Spain 3 Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands Chapter 4 171 Individual- and farm-dependent drivers of vultures visits to livestock exploitations based on GPS data 178 Analyses included a total of 12,432,333 locations of 46 different vultures collected over 914 days between 1st July 2013 and 31st December 2015 (Figure S1). Mean (±SD) number of locations per individual was 270,268 (±351,651). Number of days with information per individual was 444 (±364) days (Table S1). We included GPS information from 18 months before to 18 months after the completion of the surveys, to better capture the general behavior of the vulture population. Use of farms by vultures Since carcasses resulting from the activity of the farms were not discharged at the farm buildings but rather in their vicinity, we first calculated the mean dumping distance from the buildings to the disposal sites. We tried to obtain such information through phone calls (n = 122, M. García-Alfonso unpublished data), but only 10 farmers were willing to reveal where they left the carcasses. We extrapolated this information (mean distance: 286 m, 95% confidence interval 180 - 393 m) to all farms surveyed (section 2.5). We used these lower and upper confidence limits to establish two buffer areas around the farm buildings and selected all GPS fixes within these distances. Accordingly, two sets of analyses were performed. To determine the presence of vultures foraging at farms, we selected stationary GPS fixes by establishing a maximum altitude of 25 m and a maximum instantaneous speed of 2 m/s (Klaassen et al., 2017; Schlaich et al., 2016). After filtering the data set, we retained 6,472,416 stationary locations. Local ecological knowledge We conducted 59 face-to-face surveys through questionnaires with farmers in July 2014 (Table S2). The sampling strategy was systematically divided into three main stages. First, we randomly selected an initial set of farmers of extensive livestock farming systems from the Spanish General Register of Livestock Farms. Second, we acquired the contact information of farmers from the local sanitary authorities. Third, we conducted the surveys with farmers on or near their farms. The sample size was representative of the total population of farmers in the study area (see Morales-Reyes et al., 2018a) for details and Figure 1). All farmers were informed that their participation was voluntary and anonymous. We used the questionnaire to collect information regarding two topics: (i) perception of the capacity of Canarian Egyptian vultures to provide ecosystem services relative to the other three scavenger species (buzzards, ravens and gulls), and (ii) farmers’ awareness of the presence and number of Canarian Egyptian vultures in his/her farm or its surroundings. Chapter 4 179 First, to evaluate the farmers’ perceptions about the capacity of Egyptian vultures and the other scavengers to provide ecosystem services, according to Morales-Reyes et al., 2018a, we used two variables: (1) Ecosystem service provider (ESP) index: average farmer's perception of each one of the four avian scavenger species habitually found at carcasses. We used a fivepoint scale from very harmful to very beneficial, asking the respondents to explain their answers (n = 59); (2) Scavenging services [%]: percentage of farmers that selected each species as a provider of scavenging services (i.e. carcass consumption) either in the first, second or third ranking of importance (n = 59). Secondly, to determine factors influencing the consistency between farmers' awareness of Egyptian vulture presence and GPS data, we used the following information from the surveys: (1) occurrence of vultures perceived by farmers on their farms (n = 55), (2) number of goats and sheep on the farms (n = 55), (3) number of vultures detected simultaneously by farmers on their farms (n = 22), and (4) period of the day (i.e. morning, midday and/or afternoon) when vultures were observed by farmers on their farms (n = 21). Farmers' answers were considered as a representation of their global experience on farms in the medium-term instead of specific observations in a specific period of time (see Table S3 for specific questions answered). Statistical analyses We used the Kruskal-Wallis test (α = 0.05) to identify differences in farmers' perceptions of the capacity of avian species to provide ecosystem services (ESP index), and Pearson's chi-squared test (α = 0.05) to determine differences in the perception of species as providers of scavenging services in particular (Scavenging services [%]). For determining factors influencing consistency between awareness of vulture occurrence and GPS data, we selected three response variables: (1) Presence of vultures (Presence). Awareness was considered consistent (value = 1) when the response of the farmers matched the GPS data (i.e. farmers answered that they detected vultures and there was at least one GPS location associated with their farms, or farmers did not detect vultures and no GPS locations were associated with their farms); and inconsistent for the other two possibilities (value = 0). (2) Period of the day with the presence of vultures (TimeSlots). Awareness was considered consistent (value = 1) when farmers answered that they detected the presence of vultures at a certain time of day (morning, midday and/or afternoon) and there was at least one GPS location associated with their farm during this time period, or they did not detect vultures and there were no GPS locations; and inconsistent for the other two Individual- and farm-dependent drivers of vultures visits to livestock exploitations based on GPS data 180 possibilities (value = 0). (3) The number of vultures perceived by the farmers at their farms (Number). We used the mean value when the farmer gave a range of numbers of vultures. The explanatory variables were divided into four groups (Table 1): (1) four variables representing vulture behavior (i.e. vulture visits); (2) three associated with farmers; (3) one associated with time; and (4) eight related to characteristics of the farms. Before modeling, collinearity between explanatory variables was tested (Graham, 2003). We never included in the same model pairs of variables with a correlation coefficient higher than |0.5| (Spearman) or a p-value higher than 0.05 (Mann-Whitney U). All the variables were included in the modeling procedures except for the explanatory variable Hour, which was only fitted to the response variable TimeSlots. We standardized all variables (except Gender and Hour) by subtracting the mean of each variable and dividing the resulting value by its standard deviation. Since explanatory variables had a non-normal distribution, data were analyzed in a Generalized Linear (Mixed) Model framework (Bolker et al., 2009). Presence was modeled by means of Generalized Linear Models (GLMs), with binomial error distribution and logit link function. For TimeSlots, we used Generalized Linear Mixed Models (GLMMs) with binomial error distribution and logit link function, where farmer was included as a random factor to avoid pseudoreplication since the response variable TimeSlots involved three values per farm (morning, midday and afternoon). Moreover, the four "vulture visits" variables were calculated for each period of the day. For each of the two first response variables (i.e. Presence and TimeSlots), we performed two sets of models corresponding to values of explanatory variables ("vulture visits") within the two buffers established by lower and upper limits of the confidence interval of the distances from carcass disposal sites to the farms (180 and 393 m, see above), thus implying a total of four sets of models. Models were fitted with a maximum of four variables simultaneously to avoid overparameterization. The number of candidate models per set differed because collinearity was different for each buffer (Tables S4 and S5). Model selection was made on the basis of the Akaike’s Information Criterion corrected for small samples size (AICc) (Sugiura, 1978). We discarded models including uninformative parameters, i.e. parameters whose 85% confidence interval overlapped with 0 (Arnold, 2010; Burnham and Anderson, 2002). In addition, when top-positioned models were redundant, i.e. two or more models included fixed effects with a similar biological interpretation, only one of them was retained, e. g. the four variables related to vulture visits or connectivity index variables with corresponding distance variables (Table 1). Models differing less than two AICc points from the top-ranked models (i.e. the one with the lowest AICc) were considered statistically Chapter 4 181 equivalent, and thus model averaging was applied to deal with model selection uncertainty (Burnham and Anderson, 2002). We tested for overdispersion and determined the explained deviance in the selected subsets of models. We used Spearman’s correlation to test the relationship between the number of vultures that farmers observed on their farms (Number) and the four "vulture visits" explanatory variables (Table 1). We used R statistical software (R Core Team, 2016) with the stats package for GLM and confidence intervals, lme4 (Bates et al., 2015) for the GLMM analysis, AICcmodavg (Mazerolle, 2016) for model ranking and MuMIn for model averaging and for calculating overdispersion and explained deviance in GLMMs (Barton, 2016). Results Farmers perceived Egyptian vultures as the most beneficial avian scavengers, followed by common buzzards, yellow-legged gulls and common ravens (Kruskal-Wallis test, χ² = 125.7, p < 0.001; Figure 2a). Reasons given by farmers for considering Egyptian vultures as beneficial (n = 56) were: vultures are scavengers (n = 48), vultures do not produce damage (n = 2), vultures are necessary (n = 1), vultures are predators (n = 1), and no reason (n = 5). Moreover, Egyptian vultures were significantly perceived as the main providers of scavenging services followed by common ravens (Pearson's chi-squared test, χ² = 117.6, p < 0.001; Figure 2b). Surveys (see section 2.5) revealed an average number of 119 (range 2 - 425) livestock casualties per farm and year, with larger farms showing a higher number of deaths (Spearman's rho = 0.49, p < 0.01, n = 50). Farmers indicated whether they abandoned the carcasses always (n = 4), sometimes (n = 29), or never (n = 25). Some farmers also revealed that large farms benefited more from the official carcass-collecting service, to the extent that some owners of small farms indicated that they do not receive this service at all. Overall, about 60% of farmers’ perceptions about the visits of vultures on their farms were consistent with GPS data (Table 2). In 40% of the surveys, there was consistency between the presence of GPS tagged-vultures on the farms and positive answers by farmers regarding the occurrence of vultures (Table 2). On the contrary, between 35 and 42% of them (depending on the radius considered) did not perceive the presence of the birds even though the GPS-tagged vultures certainly visited their farms. Absences of GPS data were always Individual- and farm-dependent drivers of vultures visits to livestock exploitations based on GPS data 182 consistent with the farmer's perception of absence (i.e. no farmers indicated that vultures were visiting their farm when no GPS-tagged vultures made visits). Concerning the consistency of the presence of vultures (Presence), we obtained similar evidence at both spatial scales (180 and 393 m): there were both an effect of gender of the farmer and the number of days with visits of vultures (Table S4). Thus, the probability of this consistency was higher for males and for those farms visited more frequently by GPS- tagged vultures (Table 3). Two additional variables were influential at the smallest radius (Table S4): farmers' awareness was more consistent with GPS data for those farms with a smaller number of livestock and located near communal roosts used by vultures at night (Table 3; Figure 3). The percentage of explained deviance was 20.3 and 11.2% for 180 m and 390 m radii, respectively. The consistency in awareness in relation to the period of the vulture visits (TimeSlots) decreased from morning to afternoon with the number of livestock at farms and with the distance to communal roosts (Table 4 and S5). Moreover, at 180 m radius, farmers' responses were more consistent with GPS data for those farms receiving visits of more vultures, while at the 393 m radius we found an additional positive relationship with the age of the farmer (Table 4 and S5). The percentage of explained deviance was 41.8% and 35.0% for 180 m and 390 m radii, respectively. Regarding the number of vultures detected by the farmers (Number), we did not find significant relationships with the four variables measuring "vulture visits" (Spearman’s rho between -0.04 and 0.15; p> 0.06 in all the cases). Discussion To our knowledge, this is the first study comparing stakeholder awareness of the presence and abundance of ecosystem service providers with highly accurate quantitative field data measuring the spatial distribution of these providers. Since our results revealed that farmers largely perceived the Egyptian vulture as beneficial due to their scavenging habits, this approach helps us understand how stakeholders directly perceive the potential benefit they obtain from the service suppliers. Our findings showed that farmers that did not receive vulture visits at their farms never detected their presence, but half of the farmers receiving visits of vultures did not notice them, which could lead to an underestimation of actual services. Some increase in misperceptions when vultures visited the farms was apparent when Chapter 4 183 the buffer of observations around the farm increased (Table 2), which is consistent with a less precise perception of those birds moving outside the activity zone and sight of the farmers. Since GPS-tagged vultures are only a fraction (15%) of total vultures inhabiting the island, it could be argued that we obtained only a partial view of the probability of the presence of vultures on the farms. Thus, some farms visited by Egyptian vultures would appear in our analyses as non-visited, leading to an increase of false absences. Nevertheless, all farmers detecting vultures at their farms received visits of GPS-tagged individuals, which indicates that we achieved a representative sample for the purposes of this study. Additionally, it should be taken into account that we used GPS data recorded in the same period of the surveys to accumulate medium-term data on the occurrence of vultures on the farms. Thus, temporal biases were minimized. The fact that the vast majority of farmers perceived vultures as highly beneficial and acknowledged their scavenging services is probably due to the persistence in the study area of traditional extensive livestock farming systems (see Morales-Reyes et al., 2018a). In fact, Fuerteventura, along with other oceanic islands, is one of the few places in the world where vultures and human activities are still deeply connected and where cultural ecosystem services associated with the charismatic Egyptian vultures still survive (Gangoso et al., 2013, 2006). However, misperceptions among farmers receiving vulture visits suggest that the actual benefits received at their holdings are somewhat undervalued. Thus, acquiring informed knowledge on the factors affecting awareness accuracy may be key to understanding the social dimension of vulture conservation. The highest consistency between GPS data and farmer awareness of vulture presence was found in older men, a finding that is likely related to historical and cultural factors. Although we only examined a very specific aspect of LEK, this result would agree with recent studies conducted in rural areas of Spain, that found that men have a higher traditional ecological knowledge than women, and that LEK increases with age (Gómez-Baggethun et al., 2010; Oteros-Rozas et al., 2013). Other studies, however, depicted different scenarios in which women and younger people perceived regulating services (e.g. those provided by vultures through the removal of carcasses) as more important, with provisioning services perceived as more important by men and older people (Briceño et al., 2016; Martín-López et al., 2012). In this sense, it has been shown that regulating services are perceived to a lesser degree than provisioning services, which are more directly detected since they are more readily observable (de Oliveira and Berkes, 2014; MA, 2005; Muhamad et al., 2014). The apparent contradiction between our results and previous research regarding older males perceiving a regulating service, such Individual- and farm-dependent drivers of vultures visits to livestock exploitations based on GPS data 184 as carcass removal, more accurately may result from the fact that vultures are easily observable, unlike most regulating services that are intangible (e.g. air purification or climate regulation), and thus they are as detectable by people as a provisioning service (Martín-López et al., 2012). Moreover, the effect of age could be related to the high abundance of Egyptian vultures in the past (Donázar et al., 2002b), and thus older people would be much more familiar with the species and its detection. In the same way, it is also possible that female farmers were less common in the past due to cultural reasons and that this has affected our results. Finally, it cannot be discarded that age and/or sex asymmetries in the time spent by owners on farms may have influenced our results, but unfortunately these data were not available. As would be expected, farmer awareness about the presence of vultures was more consistent with data from GPS-tracked birds when they frequently visited the farm. Thus, a major presence of vultures, either on the farm or in its surroundings, clearly increases the concordance between farmer perceptions and GPS data. Therefore, adjustment of perception of an ecosystem service to data obtained from GPS-tagged birds seems to depend on the frequency of the service as well as the number of providers. In the same way, locations of the farms regarding the distribution of vultures over the island influenced farmers' perceptions. Perception was more consistent with GPS data when farms were closer to roosting places, increasing the probability of observing vultures in the surroundings of the farms. Consequently, more contact with vultures, even outside the farms, could imply a greater knowledge and ease of recognition of the species (Roque De Pinho et al., 2014), motivating a major predisposition to recognizing vulture presence on farms. More attention should be paid to the negative relationship between farm size and the probability of consistent perception. This result may seem counterintuitive considering our initial prediction of increasing "consistency" because more livestock should imply more carcasses and, consequently, a higher frequency of visits of vultures (Mateo-Tomás and Olea, 2010). However, it can be argued that the sanitary regulations imposed by the European Union after the outbreak of bovine spongiform encephalopathy in 2001 may play a role in our results (Donázar et al., 2009b; Margalida et al., 2010; Moleón et al., 2014). Despite the fact that the abandonment of livestock carcasses is still banned in Fuerteventura, some owners of small farms indicated that they rarely or never received carcass collection services. Therefore, the availability of carcasses can certainly be lower on large farms where illegal dumping of large amounts of carrion can be problematic (M. García-Alfonso unpublished data). Nonetheless, this only partially explains our results because the GPS-tagged vultures still visited large farms without detection by the farmers. Owners of large farms often hire help from outside the family (Navarro-Ríos et al., 2011) and probably spend less time in outdoor activities Chapter 4 185 (including the disposal of carcasses and other livestock remains), which would be carried out by employees. Thus, although some carcasses and remains are probably still abandoned to vultures on large farms, their presence would not be known by the owners. In agreement with this, previous studies have reported that farmers with smaller livestock numbers had a more positive perception of the ecosystem services provided by scavengers (Morales-Reyes et al., 2018a). Finally, the finding that farmers had an awareness more consistent with GPS data during the morning than during the afternoon may be a reflection of their daily duties, i.e. milking and feeding activities, which are carried out in early hours, while vulture behavior was monitored throughout the day. This suggests that local people perceive the environment at different times compared to scientific studies performed collecting information throughout the day (see Knapp et al., 2013; Morales-Reyes et al., 2018b). Concluding remarks Because humans are part of ecosystems (Cowling et al., 2008; Olea and Mateo-Tomás, 2009), a dissociation between nature and human society may lead to the loss of ecosystem services. Here, we show that LEK of older farmers working on small farms was more consistent with GPS data in relation to the ecosystem services provided by vultures on their property. LEK is important to balance resource use with conservation and manage natural resources sustainably (Eshuis and Stuiver, 2005; Knapp et al., 2013). In the Mediterranean area, farmers’ LEK and a greater appreciation of ecosystem services is clearly derived from the maintenance of traditional livestock farming practices, such as transhumance (e.g. Morales-Reyes et al., 2018a; Oteros-Rozas et al., 2013), but these practices are disappearing in many regions of the world due to industrialization and globalization. They persist in rural areas but are likely to continue declining (Gómez-Baggethun et al., 2010). In agreement with previous studies in different contexts (Gómez-Baggethun et al., 2010; Kai et al., 2014; Turner and Turner, 2008) but contrary to a recent study on farmers’ LEK (Morales-Reyes et al., 2018b), our results indicate the deterioration or loss of LEK, apparently associated with increased farm size and mechanization resulting from the intensification of livestock practices, which is occurring across Europe (García-Martínez et al., 2009). Thus, even if the service providers continue to supply the service, the farmers no longer perceive it as such. Our results add a new dimension to previous studies claiming the importance of traditional livestock farming practices in the conservation of scavengers (Liberatori and Penteriani, 2001; Mateo-Tomás and Olea, 2010; Morales-Reyes et al., 2018a; Olea and Mateo-Tomás, 2009) and provide evidence of the importance of management of livestock and associated practices from both the farmer and policymaker perspective. Individual- and farm-dependent drivers of vultures visits to livestock exploitations based on GPS data 186 Our study also shows that the stakeholders' perception of the ecosystem services provided is dependent on the spatial distribution of the population of the providing species, as well as its abundance. A higher frequency of visits and greater proximity to dense population nuclei, such as the communal roosts where most of the island's population of vultures is concentrated (see Donázar et al., 2002), implied a greater probability of consistency between farmer awareness and data from GPS-tagged vultures. To assess the individual knowledge of stakeholders it is therefore necessary to incorporate accurate information about the distribution and abundance of the species as well as on the movement of individuals. This result not only presents interesting perspectives to explain why there are strong local asymmetries among stakeholders' perceptions receiving apparently similar ecosystem services (Morales-Reyes et al., 2018a), but could have other important implications. Despite perceiving vultures as beneficial due to their scavenging behavior, half of the farmers were not aware of receiving the service, and thus a decline in animal populations, along with a disconnection from nature presumably resulting from the loss of traditional practices, could change perceptions in the long-term towards a misperception of their benefits. In summary, our findings indicate that studies aimed at understanding how the local community perceives animals operating as ecosystem service providers should include multiple dimensions. While personal features of stakeholders, such as gender or age, are widely recognized as important aspects, other socio-cultural factors associated with changes in traditional practices and the resulting loss of LEK are less understood. Our study highlights the potential role of modern livestock husbandry in disconnecting people from the benefits provided by wild animals, and how all of these aspects act in concert with the distribution, abundance, and frequency of the ecosystem service provider itself, such that the service may be even more underappreciated for scarce or threatened organisms. Acknowledgements We thank Manuel de la Riva, Julio Roldan, Walo Moreno, Margarita Yécora, Isabel Baños, and Juan Ramírez for their help with fieldwork, and Mathijs van Overveld for helpful comments. Funding was provided by the Dirección general de Protección de la Naturaleza (Viceconsejería de Medio Ambiente, Gobierno de Canarias), the Spanish Ministry of Economy and Competitiveness and EU/FEDER (projects CGL2012-40013-C02-02 and CGL2015-66966-C2-1-R), the Severo Ochoa Excellence Award from the Ministerio de Economía y Competitividad (SEV-2012-0262) and ENDESA (Convenio EBD(CSIC)- ENDESA). Z.M.-R and M.G.-A were supported respectively by a pre-doctoral grant (FPU12/00823) and a contract from “Programa de FPU del Ministerio de Educación, Cultura y Deporte” (FPU13/05429) Chapter 4 187 Figure 1. Spatial information used for studying farmer's perception of vultures and awareness of their presence in Fuerteventura as contrasted with information provided by GPS-tagged birds. Surveyed farms: location of farms where the 59 face-to-face surveys were done. Other farms: location of non-surveyed farms with goats and/or sheep in Fuerteventura between 2013 and 2015. Predictable feeding sources: location of the three more predictable places in terms of food for vultures. Capture site: location of the cannon net used for capturing vultures and tagging them with GPS devices. Probing into farmers' perceptions of a globally endangered ecosystem service provider 194 Table S1. Information about GPS locations used for analyzing the probability of consistency between data of GPS-tagged vultures and farmers' awareness of vulture presence at their farms. PVC: individual identifier. Locations: number of GPS-fixes retained after removing non-stationary locations, i.e. locations with speed higher than 2 m/s and altitude higher than 25 meters. Days: number of days with information on stationary locations. Min date: date of the first location for each individual. Max date: date of the last location for each individual. Locations total: total number of locations, including stationary and non-stationary. Days total: total number of days, including stationary and non-stationary locations. PVC locations days min date max date locations total days total 225 326726 914 2013-07-01 2015-12-31 591679 914 226 325525 914 2013-07-01 2015-12-31 578904 914 228 588846 914 2013-07-01 2015-12-31 1234537 914 22C 375463 912 2013-07-01 2015-12-31 632599 912 22T 395452 914 2013-07-01 2015-12-31 680585 914 22W 67602 137 2013-07-01 2013-11-14 109045 137 22X 378273 914 2013-07-01 2015-12-31 720759 914 237 314246 912 2013-07-01 2015-12-31 553926 912 2X1 415875 914 2013-07-01 2015-12-31 795628 914 2X2 509825 912 2013-07-01 2015-12-31 1027161 912 2X3 273701 844 2013-07-01 2015-12-30 465455 914 2X4 219430 914 2013-07-01 2015-12-31 405831 914 2X5 621664 905 2013-07-01 2015-12-31 1177793 905 3FC 237965 914 2013-07-01 2015-12-31 468382 914 3FF 212434 893 2013-07-01 2015-12-31 364119 893 3NP 549832 791 2013-10-23 2015-12-31 942524 791 231 238637 797 2013-10-26 2015-12-31 483968 797 234 66407 583 2014-05-28 2015-12-31 141662 583 371 62930 583 2014-05-28 2015-12-31 119133 583 224 52736 580 2014-05-31 2015-12-31 98786 580 341 66970 580 2014-05-31 2015-12-31 116251 580 2XV 43590 578 2014-06-02 2015-12-31 65050 578 2XM 24863 221 2015-05-23 2015-12-31 45355 221 3PU 22837 222 2015-05-23 2015-12-31 43497 222 Chapter 4 195 PVC locations days min date max date locations total days total 3PX 20474 222 2015-05-23 2015-12-31 39677 222 2XC 26248 221 2015-05-25 2015-12-31 47636 221 3FA 19610 221 2015-05-25 2015-12-31 45052 221 221 1322 89 2015-09-16 2015-12-31 26645 107 222 1030 90 2015-09-16 2015-12-31 27837 107 255 719 81 2015-09-16 2015-12-29 31135 107 370 1074 94 2015-09-16 2015-12-31 28306 107 3AC 797 76 2015-09-16 2015-12-29 29090 107 3XV 804 100 2015-09-16 2015-12-31 18232 107 254 775 87 2015-09-17 2015-12-31 30217 107 40H 686 82 2015-09-19 2015-12-30 18245 105 22M 726 76 2015-09-20 2015-12-29 21723 104 22P 519 74 2015-09-20 2015-12-31 24562 104 2XX 1131 84 2015-09-20 2015-12-31 26344 104 40C 569 78 2015-09-20 2015-12-31 26482 105 40F 59 19 2015-09-20 2015-11-06 3065 56 20H 700 79 2015-09-22 2015-12-31 13815 102 2XJ 475 59 2015-09-22 2015-12-30 18467 102 2XL 966 78 2015-09-22 2015-12-31 23453 102 257 607 82 2015-09-23 2015-12-31 28610 101 3AU 705 74 2015-09-23 2015-12-31 28954 102 40J 591 80 2015-09-23 2015-12-31 12157 102 Individual- and farm-dependent drivers of vultures visits to livestock exploitations based on GPS data 196 Table S2. Demographic information of the surveyed farmers' on Fuerteventura. Surveys evaluated farmers' perception of Canarian Egyptian Vultures and awareness of their presence in their own farms. Position: charge of the farmer in the farm. Sex: sex of the surveyed farmer (Male or Female). N: total number of surveyed farmers. N (GPS analyses): number of surveyed farmers' answers included for comparison with vultures GPS data. Position Sex Range of age N N (GPS analyses) Manager M < 30 2 2 Manager M 30-40 2 2 Owner F > 60 1 1 Owner F 30-40 1 1 Owner F 40-50 4 4 Owner F 50-60 2 1 Owner M < 30 1 1 Owner M > 60 6 6 Owner M 30-40 9 8 Owner M 40-50 10 9 Owner M 50-60 19 18 Shepherd M 40-50 1 1 Shepherd M 50-60 1 1 Chapter 4 197 Table S3. Variables used to evaluate farmers' perception about Canarian Egyptian vultures on Fuerteventura and to analyze consistency between farmers' awareness of vulture presence and GPS data. Question in surveys column shows question asked to farmers during face-to-face surveys. Variable Question in surveys ESP index Among the species that you see, could you evaluate how much beneficial or harmful are they for you? Evaluate them between 1 (very harmful) and 5 (very beneficial). Why do you consider each one beneficial or harmful? Scavenging services [%] Among the species that you see eating carcasses at your farm, which of them do you think that participate more in removing such carcasses? Could you sort the species according to their importance in the disposal of carrion? Presence Do Egyptian vultures visit your farm? Yes No TimeSlots What time do Egyptian vultures usually visit your farm?: Morning Midday Afternoon Number How many Egyptian vultures do you usually see in your farm? Individual- and farm-dependent drivers of vultures visits to livestock exploitations based on GPS data 198 Table S4. Top-ranked candidate models for the probability of consistency between data of GPS-tagged vultures and farmers' awareness of vulture presence (Presence) at their farms. Models selected for model averaging are shown in bold. Models including uninformative parameters and correlated variables were removed. Delta AICc: difference in AICc between each model and the best model (lowest AICc). AICcWt: AICc weights. Cum.Wt: Cumulative weights. Radius: threshold distances around the farms. K: number of parameters. ModelLik: likelihood of each model. Model AICc Delta AICc AICcWt Cum.Wt Variable K ModelLik Radius 180 m 772 67.645 0 0.286 0.286 Goat Sheep + Dist Roost + Num days + Gender 5 1 38 68.613 0.968 0.176 0.462 Goat Sheep + Dist Roost 3 0.616 647 69.694 2.049 0.103 0.565 Goat Sheep + Dist Main AFS + Dist Roost + Num days 5 0.359 242 69.96 2.315 0.09 0.655 Goat Sheep + Num days + Gender 4 0.314 108 70.28 2.635 0.077 0.731 Num days + Gender 3 0.268 418 70.342 2.697 0.074 0.806 Dist Roost + Num days + Gender 4 0.26 2 71.799 4.154 0.036 0.841 Goat Sheep 2 0.125 40 71.898 4.253 0.034 0.876 Goat Sheep + Num days 3 0.119 105 72.438 4.793 0.026 0.902 Dist Roost + Gender 3 0.091 12 72.631 4.986 0.024 0.925 Dist Roost 2 0.083 892 72.897 5.252 0.021 0.946 Dist Main AFS + Dist Roost + Dist Terr + Num days 5 0.072 0 72.98 5.335 0.02 0.966 1 1 0.069 292 73.008 5.363 0.02 0.985 Dist Main AFS + Dist Roost + Dist Terr 4 0.068 293 73.598 5.953 0.015 1 Dist Main AFS + Dist Roost + Num days 4 0.051 Radius 393 m 97 72.603 0 0.700 0.700 Num days + Gender 3 1 14 75.14 2.537 0.197 0.897 Num days 2 0.281 0 76.842 4.239 0.084 0.981 1 1 0.12 248 79.792 7.189 0.019 1 Dist AFS + Dist Roost + Dist Terr 4 0.027 Chapter 4 199 Table S5. Top-ranked candidate models for the probability of consistency between data of GPS-tagged vultures and farmers' awareness of vulture presence in each time slot (TimeSlots). Models selected for model averaging are shown in bold. Models including uninformative parameters and correlated variables were removed. Delta AICc: difference in AICc between each model and the best model, (lowest AICc). AICcWt: AICc weights. Cum.Wt: Cumulative weights. Radius: threshold distances around the farms. K: number of parameters. ModelLik: likelihood of each model. Model AICc Delta AICc AICcWt Cum.Wt Variable K ModelLik Radius 180 m 95 86.51 0 0.363 0.363 Max indvs day + Hour + (1|Farm ID) 5 1 263 87.317 0.808 0.242 0.605 Goat Sheep + Dist Roost + Hour + (1|Farm ID) 6 0.668 16 87.821 1.311 0.188 0.793 Hour + (1|Farm ID) 4 0.519 48 89.194 2.684 0.095 0.888 Dist Main AFS + Max indvs day + (1|Farm ID) 4 0.261 40 89.909 3.399 0.066 0.954 Goat Sheep + Dist Roost + (1|Farm ID) 4 0.183 0 90.66 4.151 0.046 1 (1|Farm ID) 2 0.126 Radius 393 m 16 85.828 0 0.321 0.321 Hour + (1|Farm ID) 4 1 263 86.033 0.206 0.289 0.610 Goat Sheep + Dist Roost + Hour + (1|Farm ID) 6 0.902 525 86.231 0.404 0.262 0.872 Age + Goat Sheep + Dist Roost + Hour + (1|Farm ID) 7 0.817 40 89.814 3.986 0.044 0.916 Goat Sheep + Dist Roost + (1|Farm ID) 4 0.136 0 89.873 4.045 0.042 0.958 (1|Farm ID) 2 0.132 128 89.916 4.088 0.042 1 Age + Goat Sheep + Dist Roost + (1|Farm ID) 5 0.129 Probing into farmers' perceptions of a globally endangered ecosystem service provider 200 Figure S1. Movements of GPS-tagged Canarian Egyptian vultures (N = 46) over Fuerteventura used for analyzing the probability of consistency between GPS data and farmers' awareness of vulture presence at their farms. 201 202 General discussion The study of animal movement has a major role in knowing essential aspects for animal conservation, but has proved difficult so far particularly in very mobile organisms. This is the case of vultures, which have evolved to perform large-scale movements routinely, covering vast areas with relatively little energy expenditure. In addition, other features of vultures’ lifestyles add complexity to the study of how they move to cope with spatial and temporal variations in the distribution and abundance of resources. Vultures are highly social and long-lived vertebrates with delayed sexual maturity, so intricate social relationships and environmental knowledge is expected to develop over long lifespans in which they exhibit two clearly differentiated lifestyles, before and after recruitment as breeders. This is especially true for territorial breeders, such as Egyptian vultures, that pass from a communal pre-adult stage spanning several years to an adult stage in which they defend exclusive breeding territories. Moreover, as the most endangered avian functional guild (Ogada et al., 2016, 2012a; Sekercioglu et al., 2016), vulture populations and so their ecological functions and the ecosystem services they provide require conservation actions (Badia-Boher et al., 2019; Johnson and Hackett, 2016; Margalida et al., 2014a). All these particularities make vultures interesting study models both from basic and applied perspectives, and indeed they have been subject of a large body of research in recent decades (DeVault et al., 2016; Donázar et al., 2009a; Duriez et al., 2014; Margalida et al., 2014a; Moleón et al., 2014). Nonetheless, some aspects associated with vulture movement, which are essential to making informed management and conservation decisions, remain highly unknown. Understanding how vultures exploit the environment according to individual traits through their different life-history stages, the spatiotemporal structure of the population, and the distribution of resources, is a key part for the comprehension of their behaviour and an indispensable step to face conservation challenges effectively. In order to shed light on these issues, this thesis combine GPS technology, 20-years of population monitoring data, and detailed environmental information to investigate how Canarian Egyptian vultures interact with human facilities used for feeding, resting and roosting, and to assess human perception of their presence and importance as ecosystem service providers. Particularly, we increased our understanding about drivers of electrocution risk by reducing typical biases of previous studies. We expanded what is known about how the emerging scenario of changing predictability on feeding resources is affecting vultures foraging and social dynamics. Ultimately, we examined livestock farmers’ perception about vultures as ecosystem service providers, and disentangled the factors influencing the General discussion 203 consistency between the use that vultures make of farms detected with GPS and the farmers’ awareness of that use. Spatial and/or temporal concentration of otherwise naturally unpredictable food has strong ecological effects in populations, communities and ecosystems due to induced changes in animal behaviours and distribution (Cortés-Avizanda et al., 2016; Gilroy and Sutherland, 2007; González et al., 2006; López-Bao et al., 2010; Monsarrat et al., 2013; Mundy et al., 1992; Schoech et al., 2008; Selva et al., 2017; Zuberogoitia et al., 2013). Our findings indicate that an uneven predictability of feeding resources deeply influences the Canarian Egyptian vultures’ movement behaviour. In Fuerteventura there are three highly predictable feeding places, the garbage dump and two supplementary feeding stations. The older feeding station, located in the center of the island, not only provides abundant and predictable food, but also seems to act as an important social meeting point which modulates how vultures make use of other resources: in its surroundings, electric pylons were used more intensively and farms were more visited. This point resulted greatly attractive for less experienced, non-breeding individuals which benefited from food predictability. In the case of breeding birds, the more dominant females (the larger sex) preferred to feed on this predictable feeding source than in less predictable points such as farms, to the extent that they tend to settle in nearby territories. In addition, the territorial subdominant males, which apparently relied more on wild preys during the breeding season, used with greater intensity the feeding station during the non-breeding season, probably due to a lower availability of wild carcasses, a release from the spatial constraint imposed by reproductive tasks, and/or to improve their social rank in the population. All these findings indicate that the spatio-temporal distribution of food resources in this insular system determined that birds exploited the landscape in a complex manner. Important ecological and conservation consequences arise because the value of territories and hence their propensity to be occupied seem to be determined by their location regarding the supplementary feeding stations, as has been suggested for continental Egyptian vultures (Grande et al., 2009; Oppel et al., 2017) and other species (García and Margalida, 2009). Underlying mechanisms of settlement are however poorly known and other factors, such as previous knowledge of prospected areas (Chaine et al., 2013; Haughland and Larsen, 2004; see Serrano, 2018 for raptors) and conspecific attraction (Blanco and Tella, 1999; Carrete et al., 2007; Krause and Ruxton, 2002), could be playing a pivotal role. Livestock farms are predictable in space but not so in time (semi-predictable feeding resources) and are distributed all over the island, which imply lower levels of competition for food in comparison with the feeding station. Farms with larger herd and where livestock carcass disposal is higher were more attractive for vultures, as it could be expected due to References 210 Delgado, M. del M., Miranda, M., Alvarez, S.J., Gurarie, E., Fagan, W.F., Penteriani, V., di Virgilio, A., Morales, J.M., 2018. The importance of individual variation in the dynamics of animal collective movements. Philos. Trans. R. Soc. B Biol. 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