El proceso de urbanización y su efecto en la dispersión de las aves: el caso de la lechucita de las vizcacheras (Athene cunicularia)

El proceso de urbanización y su efecto en la dispersión de las aves: el caso de la lechucita de las vizcacheras (Athene cunicularia) Memoria presentada por el Licenciado en Biología Álvaro Luna Fernández para optar al título de Doctor por la Universidad de Sevilla Tesis Doctoral – Sevilla 2019 Doctoral programme Biología Integrada Tutor José Manuel Guerra García Supervisors/Directors Martina Carrete (Doñana Biological Station/ Pablo de Olavide University) José Luis Tella (Doñana Biological Station) Ana Sanz Aguilar (Mediterranean Institute for Advanced Studies [IMEDEA] /University of Balearic Islands) Recommended citation: Luna Á. El proceso de urbanización y su efecto en la dispersión: el caso de la lechucita de las vizcacheras (Athene cunicularia).2019. PhD Thesis. Universidad de Sevilla, Spain Cover image is an original creation of Paula Martin Art (@paulamartinart). Any form of reproduction, distribution, public communication or transformation of this property without prior authorization of the authors is forbidden. The work developed by Álvaro Luna in this thesis, including fieldwork and stays in other institutions, have been funded by Obra Social "la Caixa" International PhD Programme 2015. First drawing of a Burrowing Owl John James Audubon (1785-1851) Prologue 15 Chapter 2 Table 1. Modelling the effects of habitat (hab), productivity (product), and conspecific density (consp.density) on the probability to develop cooperative breeding in burrowing owls Athene cunicularia. Only models with an AICcweight >0 are shown (the complete series of model in SP1). df: degree of freedom, AICc: Akaike Information Criterion corrected for small sample sizes, ΔAICc: difference between the AICc of model i and that of the best model (i.e. the model with the lowest AICc), w: Akaike weights. Table 2. Relative importance of the breeding system (bi-parental vs. cooperative breeding) and habitat (rural vs. urban) on the body condition of chicks of burrowing owls Athene cunicularia. Estimates and 95% confidence intervals (2.5% and 97.5%) were assessed after model averaging. We considered that a given variable has no, weak or strong support when the 95% confidence interval strongly overlapped zero, barely overlapped zero, or did not overlap zero (in bold), respectively. Models shown are those with w>0. Df: degree of freedom, AICc: Akaike Information Criterion corrected for small sample sizes, ΔAICc: difference between the AICc of model i and that of the best model (i.e. the model with the lowest AICc), w: Akaike weights. hab=habitat; coop. breed.= cooperative breeding Table 3. Testing the effects of the breeding system developed (bi-parental vs cooperative breeding) and habitat on fecundity of burrowing owls. Df: degree of freedom, AICc: Akaike Information Criterion corrected for small sample sizes, ΔAICc: difference between the AICc of model i and that of the best model (i.e. the model with the lowest AICc), weight: Akaike weights. Null: null model. Table 4. Modelling the effects of breeding system (bs), age (juv: juvenile; ad: adult) habitat (hab:habitat; urb:urban; rur:rural), and time (t) on survival. All models considered the effect of field effort on recaptures (SP4). Df= degrees of freedom; w=weight. Prologue 16 Chapter 3 Table 1. Alternative models (∆BIC < 6) obtained to assess the relative importance of individual’s traits (age, sex and behaviour, measured as FID), previous breeding experience (breeding success, productivity and predation in the previous year t-1) and conspecific density on the dispersal pattern (site fidelity and dispersal distances) of rural and urban (habitat) burrowing owls Athene cunicularia. Models were run using information from individuals of known age (ringed as chicks). See Table S1 for alternative models obtained using the Akaike Information Criterion corrected for small sample sizes (AICc). Table 2. Relative importance of an individual’s traits (sex and behaviour, measured as FID), previous breeding experience (breeding success, productivity and predation in the previous year t-1) and conspecific density on the dispersal pattern (site fidelity and dispersal distances) of rural and urban (habitat) burrowing owls Athene cunicularia. Estimates and 95% confidence intervals (2.5% and 97.5%) were assessed after model averaging. We considered that a given variable has no, weak or strong support when the 95% confidence interval strongly overlapped zero, barely overlapped zero, or did not overlap zero (in bold), respectively. Models were run using all individuals of unknown age, as age has not received statistical support (see Table 1 and S1). Models shown are those used for model averaging (ΔBIC ≤ 6). See Table S2 for results obtained using the Akaike Information Criterion (ΔAICc < 6). Table 3. Relative importance of an individual’s traits (sex and behaviour, measured as FID), previous breeding experience (breeding success, productivity and predation in the previous year t-1) and conspecific density on the dispersal pattern (site fidelity and dispersal distances) of rural burrowing owls Athene cunicularia with FID within the range of urban ones (5- 87m). Estimates and 95% confidence intervals (2.5% and 97.5%) were assessed after model averaging. We considered that a given variable has no, weak or strong support when the 95% confidence interval strongly overlapped zero, barely overlapped zero, or did not overlap zero (in bold), respectively. Models Prologue 17 shown are those used for model averaging (ΔBIC ≤ 6). See Table S3 for results obtained using the Akaike Information Criterion (ΔAICc < 6). General discussion Table 1.Summary of the main biological questions and results obtained in this thesis. Resumen Prologue 19 Resumen La urbanización del territorio se ha convertido en una de las mayores transformaciones del paisaje a nivel global, afectando profundamente a la biodiversidad presente donde las ciudades se asientan. Sin embargo, algunas especies son capaces de colonizar las ciudades e incluso prosperar en ellas. En los últimos años, un creciente interés se está focalizando en comprender qué caracteriza a los organismos que habitan ciudades, y cómo su conducta y dinámica poblacional se ve afectada por las transformaciones humanas del paisaje. La dispersión, un proceso fundamental con influencia en la demografía y la estructura poblacional, se encuentra entre los principales procesos ecológicos que puede verse alterado por la urbanización del territorio. Sin embargo, la investigación centrada en estudiar estrategias de dispersión en entornos urbanos es escasa. Esta tesis se focaliza en la dispersión de la lechucita de las vizcacheras (Athene cunicularia) en la ciudad de Bahía Blanca (Argentina) y su entorno rural. Allí, un programa de monitoreo específico conducido entre 2006 y 2018 ha seguido aproximadamente 2500 territorios urbanos de esta especie y 3200 rurales, midiendo parámetros reproductores y anillando unos 2000 adultos y pollos. Este estudio a largo plazo se ha complementado con medidas de conducta. Específicamente, durante este tiempo se ha medido la variación individual respecto a la susceptibilidad a humanos. Este rasgo de personalidad se incluye en un conjunto de conductas donde se incluyen también la toma de riesgos, la agresividad, la exploración y la tendencia a dispersar, jugando un rol en la colonización de ciudades. La hipótesis principal de esta tesis es que los individuos dispersan acorde a sus fenotipos, aunque sus decisiones de dispersión pueden estar también influenciadas por las heterogéneas presiones selectivas presentes en el área de estudio. Además, la coexistencia de diferentes estrategias de dispersión puede jugar un papel positivo o negativo en términos de “fitness” individual, con efecto potencial en la dinámica poblacional. Así, el objetivo de este estudio es comprender la influencia de características individuales (conducta, sexo y edad) y factores ambientales (calidad de Prologue 20 territorio natal y reproductor, presión de predadores y tipo de hábitat) en las estrategias de dispersión de la lechucita de las vizcacheras que habitan dos hábitats adyacentes pero profundamente diferentes, la ciudad y su zona rural inmediata. Además, evaluamos si las decisiones referentes a la dispersión influencian la eficacia biológica de los individuos en ambos hábitats en términos de reproducción y supervivencia. En el primer capítulo nos hemos focalizado en la dispersión natal, los movimientos de los individuos juveniles entre su territorio de cría y aquel en el que se reproducirá por primera vez. Encontramos que las lechucitas urbanas dispersan menos que las rurales. Además, las hembras, los individuos atrevidos (“bold”) y aquellos que han nacido en territorios de peor calidad dispersan más. Las hembras e individuos rurales que se instalan en territorios de cría más alejados de los de su origen obtienen beneficio en su primera reproducción, y esto se extiende a los dos sexos y hábitats cuando consideramos la productividad a lo largo de toda la vida. Como contrapartida las hembras que dispersan lejos sobreviven peor. En el capítulo 2 exploramos la aparición de cría cooperativa, una estrategia poco habitual en esta especie de búho generalmente monógama. Mostramos que la cría cooperativa suele conformarse solo por tres adultos. El individuo adicional es generalmente un macho nacido la temporada previa en el mismo territorio que retrasa su dispersión y ayuda a sus padres. La colaboración de estos “ayudantes” puede incrementar el aprovisionamiento de comida, como lo evidencia el hecho de que los pollos nacidos en cría cooperativa tienen mejor condición física. La cría cooperativa aparece con mayor frecuencia en áreas más productivas en las que se agregan un mayor número de congéneres: la ciudad y zonas rurales de alta calidad. Además, territorios con ayudantes colaborando en tareas reproductoras obtienen mayor éxito reproductor. La descendencia criada en familias cooperativas tiene solo un ligero incremento en sus probabilidades de supervivencia al compararlo con juveniles nacidos en el sistema biparental habitual. En general, la supervivencia presenta variación temporal y el factor principal que influye en la supervivencia son la edad y el Prologue 21 hábitat: los adultos presentan mayor supervivencia que los jóvenes, que a su vez muestran mayor supervivencia en áreas urbanas que rurales. Finalmente, el tercer capítulo se centra en la dispersión reproductora, los movimientos de los adultos entre territorios de cría en períodos reproductores consecutivos. Observamos que una parte significativa de la población se mantiene en el mismo nido. En caso de dispersar, los desplazamientos son más cortos que en la dispersión natal. Las hembras dispersan más que los machos y sus movimientos son más largos. Como también pasaba para la dispersión natal, los ejemplares urbanos muestran mayor fidelidad al territorio y dispersan distancias más cortas. En las zonas rurales, los individuos que sufren eventos de predación o fallan en la reproducción son más dados a dispersar. Sin embargo, los individuos más atrevidos (“bold”) dispersan menos que los temerosos, probablemente porque son más capaces de hacer frente a potenciales perturbaciones sufridas durante el período de reproducción sin que ello les incite a dispersar. La influencia del comportamiento en la dispersión desaparece en el hábitat urbano, donde solo se observa que los individuos nacidos en territorios más ocupados por conspecíficos dispersan más. Summary Prologue 23 Summary Urbanization has become one of the greatest landscape transformations at global level, deeply affecting the biodiversity present where cities settle. However, some species are able to thrive and even prosper in urban ecosystems. In recent years, a growing interest is focusing in understand what characterizes the organisms inhabiting cities, and how their behavior and their population dynamics can cope with human transformed environments. Dispersal, a fundamental process with influence on the demography and the structure of populations, is among the main ecological processes that may be altered by the urbanization. However, research devoted to study the dispersal strategies of animals in urban environments is scarce. This thesis focuses on the dispersal of the burrowing owl (Athene cunicularia) in the city of Bahía Blanca (Argentina) and its rural surroundings. There, a specific monitoring program conducted annually from 2006 to 2018 have surveyed ca. 2500 urban and ca. 3200 rural nests of this species, recording reproductive parameters and marking ca. 2000 adults and chicks. This long-term study has been complemented with measurements of burrowing owls behavior. Specifically, we have recorded the individual variation in the susceptibility to humans. This personality trait is included within a range of behaviors that encompasses risk taking, aggressiveness, and exploration and dispersal propensity, also playing a role in the colonization of cities. The main hypothesis of this thesis is that individuals disperse according to their phenotypes, although their dispersal decisions may be also influenced by the heterogeneous selective pressures observed in the study area. Furthermore, the coexistence of different dispersal strategies may play a positive or negative role in term of individual fitness, with potential effect in the population dynamic. Thus, the aim of this study is to understand the influence of individual cues (behavior, sex and age) and environmental factors (quality of natal and breeding zones, predation pressure and habitat type) in dispersal strategies of burrowing owls in adjacent but deeply different habitats, the city and their immediate rural area. Moreover, we assess Prologue 24 whether dispersal decisions influence the biological effectiveness of individuals in both habitats in terms of reproductive parameters and survival. In the Chapter 1 we focus on natal dispersal, movement of juveniles between its birth site and the site where it first reproduces. We find that urban burrowing owl disperse less than rural ones. In addition, females, bold individuals and those born in poor quality territories disperse more. Females and rural individuals who settle far from their familiar territories improve their reproductive output in their first breeding attempt, and this extends to both sexes and habitats when we consider productivity throughout the entire life. On the contrary, females that disperse farther show lower local survival. In the Chapter 2 we explore the development of cooperative breeding, an uncommon strategy in this monogamous owl. We show that cooperative families are mainly composed by three adults. The extra individuals are generally males born the last breeding season in the same territory delaying their dispersal to help their parents. The collaboration of these helpers can increase food provisioning, as evidenced by the fact that chicks born in cooperative breeding have a better physical condition. Cooperative breeding appears more frequently in highly productive areas in which a greater number of conspecifics aggregate: the city and high quality rural areas. Furthermore, territories with helpers collaborating in reproductive tasks show higher breeding success. The offspring raised in cooperative families have only a slight increase in their survival probabilities compared with juveniles raised in common pairs. Survival show temporal variations and the main factors driving survival differences are age and habitat: adults show higher survival than juveniles, which show a higher survival in urban than in rural habitats. Finally, in the Chapter 3 focuses we study breeding dispersal, the movements of adults between breeding territories in subsequent breeding seasons. We observe that a significant part of the population remains faithful to the same territory. When disperse, the distances covered are shorter than those observed in the natal dispersal. In general, females disperse more frequently and they travel longer distances than males. Again, urban individuals are less prone to disperse, settling at shorter distances Prologue 31 Why to study movements in urban environments? In the last centuries the expansion of humans and the consequent loss of natural habitat has forced to most species to live in fragmented and isolated territories (Fahrig 2005; Tremblay and Clair 2011). This has been associated with a growing interest in studies related to animal’s movements in altered landscapes, which have been facilitated by the development of tracking devices and the growth of long term monitoring programs (Fisher and Davis 2011). Urbanization is included among the extreme forms of land-use alteration, and the landscape structure and resource availability for wildlife species change substantially along the natural–urban gradient (Faeth et al.2005; Shochat et al.2010). Indeed, urbanization represents an extreme process that may constraint or directly impedes the movements of species, especially of those with low movement capabilities (Prange et al. 2004; Markovchick-Nicholls et al. 2008; Roth and Vetter 2008). This situation can have demographic and genetic consequences, such as a rapid genetic differentiation, genetic drift and inbreeding, and bottleneck effects (Nöel and Lapointe 2010; Björklund et al. 2009; Munshi-South and Nagy 2014; Lourenço et al. 2017). However, in some occasions even wildlife with greater movement capability cope with the growing humanization of the environment by reducing their movements, due to the unavailability of suitable habitat, as confirmed in terrestrial mammals (Tucker et al. 2018), or by the high predictability of subsidized resources, that make unnecessary longer movements and the use of wide territories (Oro et al. 2013; Šálek et al. 2015). From the different aspects related with the movements that can be studied in urban animals, one of them is the dispersal, the movement of individuals from their birth territory to their first breeding territory (natal dispersal), and the movement from one breeding territory to another in subsequent breeding seasons (breeding dispersal) (Greenwood and Harvey 1982). This trait that can play an important role for individual fitness (Forero et al. 2002; Nevoux et al. 2013) but also can affect the gene flow, the genetic structure and the demographic dynamics of populations (Clobert et al. 2001; Bowler and Benton 2005). Studying dispersal is especially difficult because of its inherent difficulties, and despite of its importance, it has been studied to a lesser Prologue 32 extent than others aspects of the animal ecology (Baguette and Van Dyck 2007; Penteriani and Delgado 2010). Growing evidences confirm that dispersal is a highly plastic trait that responds to factors such as the fragmentation of the natural habitats, the resource availability and/or the population density (Coulon et al. 2010). Moreover, a recent hypothesis named “matching habitat choice” suggests that individuals would tend to occupy different habitats according to their phenotype (Benard and McCauley 2008; Edelaar and Bolnick 2012). Thus, different authors have highlighted that the heterogeneity among individuals and populations regarding their dispersal movements could help to explain colonization processes and the expansion of certain species in new habitats, including cities (Fraser et al 2001; Rehage and Sih 2004). Recent studies support this hypothesis, for example Hanski et al. (2004) and Duckworth and Badyaev (2007) have shown that the phenotypic composition of recently established colonizing populations differs from those of the original population in dispersal traits. Nonetheless, it is striking to note the few research efforts devoted to understand the dispersal strategies showed by species inhabiting cities (LaPoint et al. 2015; Marzluff 2016). As explained previously, the urbanization supposes a great transformation of the territory, and the species that colonize and thrive in metropolitan areas are subjected to strong selective pressures that can influence their dispersal decisions. Under these circumstances, individuals can disperse in two ways: 1) they may tend to disperse less distance o even remain in the same territory because the own structure of cities, together with the human activities, may limit the movements between suitable patches (Etter et al. 2002); or 2) individuals may show a greater tendency to disperse by intrinsic phenotypic traits or forced by the low availability of suitable patches, which would favor both the initial colonization and the subsequent expansion in such habitat (Møller 2009). In summary, a wide understanding of the factors that influence dispersal decisions and the distance covered in dispersal movements could help to gain a better understanding of the dynamics of urban and rural populations, as well as the colonization process itself. Prologue 33 The study model Birds seem to be a suitable study model to study dispersal in urbanized environments, because: this group is widely distributed in cities worldwide (Aronson et al. 2014); there is a reasonable knowledge about avian dispersal (Paradis et al. 1998); and a great number of studies have focused on birds and cities since long ago (Chace and Walsh 2006). Furthermore, dispersal strategies of birds in urban environments remain largely unknown to the date, offering a challenging field to explore in following years. The model species selected for this thesis is the burrowing owl (Athene cunicularia) (Fig 1A), a small raptor distributed from Canada to southern Chile and Argentina, with populations also in the Caribbean Islands (Del Hoyo et al. 1999; Poulin et al. 2011;Fig 2). The burrowing owl is an underground nesting bird (Fig 1B) that mainly inhabit shortgrass plains, arid zones, sand dunes, transformed lands dedicated to agriculture and livestock, and urbanized areas (Millsap 2000; Conway et al. 2006; Cavalli et al. 2016; Rebolo- Ifrán et al. 2017). Burrowing owls are active both in the day and the night, hunting a great variety of preys in the ground (Cavalli et al. 2014). The burrowing owl is a medium-short lived species, with a mean life expectancy of 1.3–2.9 years (Carrete and Tella 2013). They start to breed in its first breeding season in which they become adults. Their mean productivity is typically 1.5 – 2.5 fledglings per nest, but the more successful pairs are able to raise 6 chicks (Conway et al. 2006; Griebel et al. 2007; Rebolo- Ifrán et al. 2017). Adults are monogamous and territorials (Rodriguez- Martínez et al. 2014), remaining perched close to the entrance of their burrows most of the time. The unique existent study measuring adult movements indicate that territorial adults have small home-ranges and focus their activity in the surroundings of their territories (Mrykalo et al. 2007). Prologue 34 Figure 1. A) Adult burrowing owl perched close to the nest. B) Typical burrow of burrowing owl decorated with diverse materials. The study area comprises the city of Bahía Blanca and its surrounding rural areas. Bahía Blanca (38°43′S 62°16′W; Buenos Aires, Argentina; Fig 2) was founded in the first half of the 19th century, being a small settlement until a few decades ago, when the expansion of the city has led to a current population size of almost 300,000 inhabitants. The city is located in a flat landscape, the semi-arid Pampas, a large area dominated by natural grasslands mostly dedicated to low-intensive cereal crops and wide-ranging livestock, with interspersed patches of xerophytic forests and scrublands (Carrete and Tella 2011; Rodriguez-Martínez et al. 2014). In the city burrowing owls breed in residential areas where they excavate their burrows in spaces between buildings, in the golf course and the cemetery, as well as in roundabouts, avenues, private gardens and public parks, but always in direct contact with the neighbors and with the daily activity of the city (Rodriguez- Martínez et al. 2014). On the contrary, rural burrowing owls breed in natural grasslands and pastures with a few unpaved roads and scarce human presence, mainly devoted to human activities like livestock farming and cereal crops (Carrete and Tella 2010). In these habitats some individuals excavate their nests while others occupy the burrows excavated by the Argentine plains vizcacha (Lagostomus maximus) (Rebolo-Ifrán et al. 2017), hence the Spanish name of this small raptor: “lechucita de las vizcacheras”. Prologue 35 Figure 2. Distribution range of the Burrowing owl. The color red represents the breeding area for the migrants, and the blue area represents the winter areas. The violet color represents the areas inhabited for year-round residents. Bahía Blanca is the study area of this thesis. In order to study dispersal, is essential to collect data at individual and population level through long-term studies (Paradis et al. 1998; Camacho et al. 2019). The recent expansion of Bahía Blanca and the subsequent colonization of this city by the burrowing owl make this scenario suitable to develop research programs. Furthermore, this small raptor seems a suitable study model, given that they show diurnal activity, usually remain near to their territories, their nests are easily detectable, and by the high number of breeding territories located in the city and in their adjacent rural area (Rodriguez-Martínez et al 2014; Rebolo- Ifrán et al. 2017). Thus, a monitoring program of the burrowing owl population of Bahía Blanca started in 2006 and still remains active. This represents one of the few cases with such effort Bahía Blanca Prologue 36 devoted to monitoring a single species in urban environments from a multidisciplinary approach. During these years, different group members have conducted fieldwork each breeding season monitoring the active nests, ringing chicks and adults and assessing the reproductive success. This monitoring program has been complemented with parallel experiments focused in the behavior, genetic, diet and physiology of burrowing owls living in both the urban and the rural area. Results from this long-term study include relevant findings on how the individual susceptibility to human presence influences the distribution of burrowing owls between urban and rural habitats, in a way that urban colonizers are tame individuals while those rural have a major variety of responses to human presence, including both shy and bold individuals (Carrete and Tella 2010; Carrete and Tella 2011; Carrete and Tella 2013). Furthermore, more studies focused in demographic parameters show that individuals inhabiting the city obtain higher reproductive success and have few predatory pressure, hence the higher breeding densities observed in this habitat (Rebolo-Ifrán et al. 2015; Rebolo-Ifrán et al. 2017). Finally, now we know through genetic analysis that the burrowing owl maintains their monogamy breeding behavior (Rodriguez-Martínez et al. 2014). Thesis hypothesis and chapters My thesis focuses on the dispersal of the burrowing owl in landscapes with a different degree of anthropization: the city of Bahía Blanca and its rural surroundings. During the long-term monitoring conducted in this species and study area various dispersal strategies have been observed: philopatric adult burrowing owls that remain within their breeding territory over years; young individuals that remain in their natal territory (sometimes cooperating in reproductive tasks with other adults) and; individuals dispersing different distances from their natal or breeding territory. Gaining knowledge about the causes and consequences of these coexisting dispersal strategies could improve the general understanding of the processes governing its recent urban colonization. Furthermore, this research can provide novel information about how this small raptor thrives in the city, and also explain the factors influencing Prologue 37 their success in such humanized habitat. In addition to this, I can explore whether certain dispersal traits differ between individuals living in the city and the ones from original rural areas, and the potential influence of dispersal processes in the demographic dynamics in this spatially structured population. The main hypothesis of this thesis is that dispersal is not random, and birds inhabiting habitats with different ecological characteristics as urban and rural landscapes may present differences. Individuals may disperse according to their phenotypes, although their settlement decisions could be also influenced by heterogeneous selective pressures, leading even to the appearance of atypical breeding systems. Furthermore, different dispersal strategies could have different consequences in term of fitness, which could contribute to explain the species demographic and spatial dynamics. Consequently, the first aim of this thesis is to understand the influence of individual characteristics (behavior, sex and age) and environmental factors (quality of birth and breeding zones, predation pressure and habitat type) on dispersal decisions. Then, the second aim of this thesis is to evaluate whether dispersal decisions influence the main fitness components: the reproductive and survival parameters. In chapter 1 I study the factors and consequences of natal dispersal decisions in burrowing owls born in urban and rural territories. Given that the urban population is composed mainly by bolder individuals and the rural by individuals with different degree of fear of humans (Carrete and Tella 2017), I consider that if natal dispersal is related to personality traits and environmental cues the strategy adopted may differ between individuals and habitats. To explore this I determine how the type of habitat and social factors related to the environment where the individuals born, in addition to individual traits (sex and behavior) determine natal dispersal distances. Furthermore, I evaluate whether the natal dispersal decisions of burrowing owls have effects in the reproductive success of the individuals (both in the first breeding attempt but also during the lifetime) and in their future survival. Prologue 38 In chapter 2 I examine the existence of cooperative breeding strategies. First, the identity of the adults forming cooperative breeding system is assessed using genetic data and through continuous monitoring of marked individuals. Then, I study the influence of social factors linked to the habitat quality, such as the conspecific density and productivity in the area, together with the habitat type (urban vs. rural) on the probability to develop cooperative breeding systems. Finally, I evaluate the potential consequences of different breeding systems (biparental breeding vs. multiple cooperative breeding) in the antipredator behavior of the adults, the reproductive output (breeding success and productivity) and the survival of the offspring raised. In chapter 3, I explore the factors responsible of breeding dispersal decisions of burrowing owls living in urban and rural areas. In this case I first analyze the factors that influence site fidelity (individuals that remain in the same nest), and only for dispersers I evaluate the drivers that contribute to move longer or shorter distances. Having in mind the intrinsic differences of each type of habitat and the behavioral differences between rural and urban individuals, I consider that some individuals may be more prone to disperse, showing differences in their site fidelity and dispersal distances. Here I assess the importance of age, sex, and behaviour, conspecific density around breeding territories, as well as the previous experiences of breeders related with predation events and reproductive success on dispersal and fidelity decisions. Finally, I evaluate the possible influence of breeding dispersal decisions in survival. Prologue 39 References Ahern J. Urban landscape sustainability and resilience: The promise and challenges of integrating ecology with urban planning and design. Landsc Ecol. 2013; 28(6):1203–12. Alberti M, Correa C, Marzluff JM, Hendry AP, Palkovacs EP, Gotanda KM, Hunt VM, Apgar TM, Zhou Y. Global urban signatures of phenotypic change in animal and plant populations. Proc Natl Acad Sci. 2017; 201606034. Antrop M. Landscape change and the urbanization process in Europe. Landsc Urban Plan. 2004;67(1–4):9–26. Aronson MF, La Sorte FA, Nilon CH, Katti M, Goddard MA, Lepczyk CA, ... Dobbs CA. Global analysis of the impacts of urbanization on bird and plant diversity reveals key anthropogenic drivers. Proc R Soc Lond B Biol Sci. 2014; 281(1780): 20133330. https://doi.org/10.1098/rspb.2013.3330. Badyaev AV, Young RL, Oh KP, Addison C. Evolution on a local scale: developmental, functional, and genetic bases of divergence in bill form and associated changes in song structure between adjacent habitats. Evolution. 2008; 62(8), 1951-1964. Baguette M, Van Dyck H. Landscape connectivity and animal behavior: Functional grain as a key determinant for dispersal. Landsc Ecol. 2007; 22(8):1117–29. Benard MF, McCauley SJ. Integrating across life-history stages: consequences of natal habitat effects on dispersal. Am Nat. 2008; 171(5), 553-567. Bettencourt LM, Lobo J, Helbing D, Kühnert C, West GB. Growth, innovation, scaling, and the pace of life in cities. Proc Natl Acad Sci USA. 2007; 104(17), 7301-7306. Bichet C, Scheifler R, Cœurdassier M, Julliard R, Sorci G, Loiseau C. Urbanization, trace metal pollution, and malaria prevalence in the house sparrow. PLoS One. 2013; 8(1):1– 10. Bjorklund M, Ruiz I, Senar JC. Genetic differentiation in the urban habitat. Biol J Linn Soc. 2010; 99:9–19. Prologue 40 Bonier F, Martin PR, Wingfield JC. Urban birds have broader environmental tolerance. Biol Lett. 2007; 3(6):670–3. Bowler DE, Benton TG. Causes and consequences of animal dispersal strategies: relating individual behaviour to spatial dynamics. Biol Rev. 2005; 80(2), 205-225. Callaghan CT, Bino G, Major RE, Martin JM, Lyons MB, Kingsford RT. Heterogeneous urban green areas are bird diversity hotspots: insights using continental-scale citizen science data. Landsc Ecol. 2019; 34(6):1231–46 Callaghan CT, Bino G, Major RE, Martin JM, Lyons MB, Kingsford RT. Heterogeneous urban green areas are bird diversity hotspots: insights using continental-scale citizen science data. Landsc Ecol. 2019; 34(6):1231–46. Camacho, C, Martínez-Padilla J, Canal D, Potti J. Long-term dynamics of phenotypedependent dispersal within a wild bird population. Behav Ecol. 2019; 30(2), 548-556. Carrete M, Martínez-Padilla J, Rodríguez-Martínez S, Rebolo-Ifrán N, Palma A, Tella JL. Heritability of fear of humans in urban and rural populations of a bird species. Sci Rep. 2016; 6, 31060. Carrete M, Tella JL. Behavioral correlations associated with fear of humans differ between rural and urban burrowing owls. Front Ecol Evol. 2017; 5, 54. Carrete M, Tella JL. Individual consistency in flight initiation distances in burrowing owls: a new hypothesis on disturbance-induced habitat selection. Biol Lett. 2010; 6: 167–170.doi: 10.1098/rsbl.2009.0739. Carrete M, Tella JL. Inter-individual variability in fear of humans and relative brain size of the species are related to contemporary urban invasion in birds. PLoS One. 2011; 6(4). Carrete M, Tella, JL. High individual consistency in fear of humans throughout the adult lifespan of rural and urban burrowing owls. Sci Rep. 2013; 3, 3524. Prologue 47 Penteriani V, Delgado MM. Thoughts on natal dispersal. J Raptor Res. 2009; 43(2), 90- 99. Pickett STA, Cadenasso ML, Grove JM, Nilon CH, Pouyat R V, Zipperer WC, et al. Urban ecological systems : linking terrestrial ecological, physical, and socioeconomic components of metropolitan areas source. Annu Rev Ecol Syst. 2001; 32,127. Poulin RG, Todd LD, Haug EA, Millsap BA, Martell MS. (2011). Burrowing Owl (Athene cunicularia). The Birds of North America (AF Poole, Editor). 2011. Cornell Lab of Ornithology, Ithaca, NY, USA. Prange S, Gehrt SD, Wiggers EP. Influences of anthropogenic resources on raccoon (Procyon lotor) movements and spatial distribution. J Mammal. 2004; 85(3):483–90. Rebolo-Ifrán N, Tella JL, Carrete M. Urban conservation hotspots : predation release allows the grassland-specialist burrowing owl to perform better in the city. Sci Rep. 2017; 7(1), 3527. https://doi.org/10.1038/s41598-017-03853-z. Rehage JS, Sih A. Dispersal behavior, boldness, and the link to invasiveness: a comparison of four Gambusia species. Biol Invasions. 2004; 6(3), 379-39. Rodriguez-Martínez S, Carrete M, Roques S, Rebolo-Ifrán N, Tella JL. High urban breeding densities do not disrupt genetic monogamy in a bird species. PLoS One. 2014; 9(3). Roth TC, Vetter WE. The effect of feeder hotspots on the predictability and home range use of a small bird in winter. Ethology. 2008; 114(4):398–404. Rucandio MI, Petit-Domínguez MD, Fidalgo-Hijano C, García-Giménez R. Biomonitoring of chemical elements in an urban environment using arboreal and bush plant species. Environ Sci Pollut Res. 2011; 18(1):51–63. Šálek M, Drahníková L, Tkadlec E. Changes in home range sizes and population densities of carnivore species along the natural to urban habitat gradient. Mammal Rev. 2015; 45(1), 1-14. Prologue 48 Santini L, González-Suárez M, Russo D, Gonzalez-Voyer A, von Hardenberg A, Ancillotto L. One strategy does not fit all: determinants of urban adaptation in mammals. Ecol Lett. 2019; 22(2):365–76. Shannon G, McKenna MF, Angeloni LM, Crooks KR., Fristrup KM., Brown E, McFarland, S. A synthesis of two decades of research documenting the effects of noise on wildlife. Biol Rev. 2016; 91(4), 982-1005. Shochat E, Lerman SB, Anderies JM, Warren PS, Faeth SH, Nilon CH. Invasion, competition, and biodiversity loss in urban ecosystems. BioScience. 2010; 60(3), 199- 208. Slabbekoorn H, Peet M. Ecology: Birds sing at a higher pitch in urban noise. Nature. 2003; 424(6946), 267. Tratalos J, Fuller RA, Warren PH, Davies RG, Gaston KJ. Urban form, biodiversity potential and ecosystem services. Landsc Urban Plan. 2007; 83(4):308–17. Tremblay MA, St. Clair CC. Permeability of a heterogeneous urban landscape to the movements of forest songbirds. J Appl Ecol. 2011; 48(3):679–88. Tucker MA, Böhning-Gaese K, Fagan WF, Fryxell JM, Van Moorter B, Alberts SC…& Bartlam-Brooks H. Moving in the Anthropocene: Global reductions in terrestrial mammalian movements. Science. 2018; 359(6374), 466-469. Wu J. Urban ecology and sustainability: The state-of-the-science and future directions. Landsc Urban Plan 2014;125:209–21. Yeh PJ. Rapid evolution of a sexually selected trait following population establishment in a novel habitat. Evolution. 2004; 58(1), 166-174. II| Chapters Chapter 1 “Sex, personality and conspecific density influence natal dispersal with lifetime fitness consequences in urban and rural burrowing owls.” Content of this chapter has been submitted to PLOS ONE as: Sex, personality and conspecific density influence natal dispersal with lifetime fitness consequences in urban and rural burrowing owls. Álvaro Luna, Antonio Palma, Ana Sanz-Aguilar, José L Tella, Martina Carrete Chapter 1 54 Sex, personality and conspecific density influence natal dispersal with lifetime fitness consequences in urban and rural burrowing owls. Abstract There is a growing need to understand how species respond to habitat changes and the potential key role played by natal dispersal in population dynamics, structure and gene flow. However, few studies have explored differences in this process between conspecifics living in natural habitats and those inhabiting landscapes highly transformed by humans, such as cities. Here, we investigate how individual traits and social characteristics can influence the natal dispersal decisions of burrowing owls (Athene cunicularia) living in urban and rural areas, as well as the consequences in terms of reproductive success and apparent survival. We found limited dispersal movements among individuals, with differences between urban and rural birds (i.e., the former covering shorter distances than the latter), maybe because of the higher conspecific density of urban compared to rural areas. Moreover, we found that urban and rural females as well as bold individuals (i.e., individuals with shorter flight initiation distance) exhibited longer dispersal distances than their counterparts. These dispersal decisions have effects on individual fitness. Individuals traveling longer distances increased their reproductive prospects (productivity during the first breeding attempt, and lifetime productivity). However, the apparent survival of females decreased when they dispersed farther from their natal territory. Although further research is needed to properly understand the ecological and evolutionary consequences of dispersal patterns in transformed habitats, our results provide information about the drivers and the consequences of the restricted natal movements of this species, which may explain its population structuring through restricted gene flow between and within urban and rural areas. Natal dispersal in urban and rural owls 55 Introduction Natal dispersal, defined as the movement of individuals from their birthplace to their first breeding area (Greenwood and Harvey 1982) may influence the future survival, fecundity, and lifetime fitness of individuals (Forero et al. 2002; Doligez and Pärt 2008; Serrano and Tella 2012), playing an important role in the evolution, persistence and spread of populations and species (Skellam 1951; Kokko and López-Sepulcre 2006; Jongejans et al. 2008; Baguette et al. 2013; Kubisch et al.2014; Canestrelli et al. 2016; Bonte and Dairel 2017). Thus, a large number of studies have investigated the factors driving natal dispersal decisions, in particular the importance of social and environmental clues [e.g. conspecific density and habitat characteristics (Doligez et al. 2004; Garant et al. 2005), previous experience (Davis and Stamps 2004)] and phenotypic attributes, including personality (Fraser et al. 2001; Bize et al. 2017), structural size (Camacho et al. 2013; Camacho et al. 2015), body mass (Barbraud et al. 2003; Garant et al. 2005) and sex (Trochet et al. 2016), among others (reviewed by Clobert et al. 2009). All of these factors can interact in complex and subtle ways, varying across the spatial range of a species, such that natal dispersal decisions, as well as their conditioning, can differ among species but also among populations of the same species (Clobert et al. 2009). Therefore, studies comparing the dispersal patterns of conspecifics inhabiting areas with contrasting characteristics and subjected to different selection regimes are important to better understand the dynamic nature of dispersal as well as how drivers of global change affect the fate of animal populations. Urbanization is the most drastic and persistent alteration of a landscape, creating new habitats starkly different from the natural habitats it replaces (Grimm et al. 2008). Currently, urbanization is occurring globally at an unprecedented rate, with predictions that, by 2050, approximately 60% of the world’s human population will be living in urbanized landscapes (United Nations 2007). Although urbanization leads to an overall loss of biodiversity (the so-called ‘biotic homogenization process: McKinney and Chapter 1 62 Results During the study period, we marked 830 urban and 566 rural burrowing owls with PVC rings, and were able to record 321 natal dispersal events in 75 rural (48 males and 27 females) and 246 urban (129 males and 117 females) birds. However, as FID was not measured for all individuals, our dataset was reduced to 224 individuals, 85% of which were resighted during their first breeding. Although some individuals moved more than 10km, median dispersal distance was much shorter (322m), and most birds bred for the first time close to their natal areas (percentage of individuals remaining within 1 km of their natal sites: 75%; Figure 1A) and in the same habitat of birth (96% of dispersions were within the same habitat type). Movements between habitats were rare (10 individuals out of 224), and mainly from urban to rural areas (6 movements from urban to rural areas vs 3 movements from rural to urban ones). Natal dispersal in urban and rural owls 63 Dispersal distance (km) Dispersal distance (m) Percentage of individuals Rural owls FID (m) Dispersal distance ( km) Percentage of individuals Dispersal distance (m) Urban owls FID (m) Dispersal distances (log-transformed) A) B) 0 10 20 30 40 50 5 10 15 20 0 020 40 60 80 100 1 2 3 4 0 0 10 20 30 40 50 5 10 15 20 0 1 2 3 4 00 20 40 60 Percentage of individuals Figure 1. A) Natal dispersal distances of urban and rural burrowing owls Athene cunicularia (males: grey bars; females: black bars). The inserted figure shows a detailed distribution of dispersal distances lower than 1km.B) Relationship between natal dispersal distances (log-transformed) and individual personality (measured as FID, flight initiation distance). Lines show the tendency observed for males (grey line) and females (black line). Dashed lines represent the 95% confidence interval. Dots are raw data (males: grey dots, females: black dots). Chapter 1 64 Correlates of natal dispersal Sex, individual personality and habitat were the most important variables to explain interindividual differences in natal dispersal distances (Table 1). Urban birds dispersed over shorter distances than rural ones, with females moving farther than males in both habitat types. Moreover, individuals with shorter FID dispersed at greater distances than their counterparts, regardless of their sex or the habitat where they were born (Figure 1B). Although social variables were weakly related to dispersal distances, individuals born in areas with low conspecific density tended to cover greater distances than those born in high-density areas (Table 1). Importantly, when habitat was removed from the analysis, conspecific density received stronger support as a predictor of dispersal distances, with individuals born in high-density areas dispersing less than those born in more isolated sites (Table 1). This change in the result suggests that, besides the higher conspecific density recorded in the surroundings of urban compared to rural sites (estimate: 13.16, 95% CI: 10.99 - 15.33), there are other traits associated with urban sites that may be affecting natal dispersal decisions. Finally, we found no differences in conspecific density or productivity between natal and dispersal areas in both habitat types (conspecific density: estimate: 2.44, 95% confidence interval: -5.58 - 1.35; conspecific productivity: estimate: 0.65, 95% confidence interval: -0.29 - 1.59). However, individuals dispersing farther settled in areas more similar in terms of conspecific densities than those staying close to their natal areas (estimate: - 1.17, 95% CI: -2.20 - -0.15), a pattern not observed when considering changes in conspecific productivity (estimate: 0.27; 95% CI: -0.77 - 1.32). It is worth noting that similar results were obtained when restricting our dataset to individuals resighted during their first breeding attempt (Table S1). Natal dispersal in urban and rural owls 65 Table 1. Relative importance of individual’s traits (sex and personality, measured as FID), and social variables (conspecific density and productivity in the natal area) on the natal dispersal distances of rural and urban (habitat) burrowing owls Athene cunicularia. Estimates and 95% confidence intervals (2.5% and 97.5%) were assessed after model averaging. We considered that a given variable has no, weak or strong support when the 95% confidence interval strongly overlapped with zero, barely overlapped with zero (asterisk), or did not overlap with zero (in bold), respectively. Models shown are the first 10 models ranked using their AICc. Variable (*): model averaging performed using the subset of models that did not include habitat. w: Akaike weights. Model K AICc ∆AICc w Variable Estimate 2.50% 97.50% FID + habitat + sex 6 590.51 0.00 0.25 FID -0.18 -0.34 -0.03 conspecific density + FID + habitat + sex 7 590.86 0.35 0.21 habitat (urban) -0.49 -0.88 -0.09 conspecific productivity + FID + sex + habitat 7 592.53 2.03 0.09 sex (female) 0.63 0.40 0.87 conspecific density + FID + sex (*) 6 592.93 2.42 0.07 conspecific density -0.10 -0.25 0.05 conspecific productivity*habitat + FID*habitat + sex*habitat 10 593.07 2.56 0.07 conspecific density + sex (*) 5 593.16 2.65 0.07 Variable (*) Estimate 2.50% 97.50% habitat + sex 5 593.70 3.19 0.05 FID -0.10 -0.23 0.03* sex (*) 4 594.34 3.83 0.04 sex (female) 0.59 0.35 0.83 conspecific density + habitat + sex 6 594.61 4.10 0.03 conspecific density -0.14 -0.28 0.00 FID*habitat + sex*habitat 8 594.70 4.20 0.03 Chapter 1 66 Correlates of natal dispersal distances on productivity and survival Birds breeding for their first time in rural areas were less productive than those inhabiting urban ones (Table 2). However, when they dispersed farther from their natal areas, they raised more chicks during their first breeding attempt than those staying nearby, a relationship that was absent among urban individuals. Besides, females dispersing at larger distances of their natal areas also increased their productivity in the first breeding event. When considering the lifetime productivity of individuals (data available for 144 individuals), we found that all birds, urban and rural, tended to increase productivity with age and when disperse at greater natal distances (Table 2). Results remained consistent when we repeated models using only individuals resighted during their first breeding attempt (Table S2). Table 2. Relationship between natal dispersal distances and productivity during the first breeding attempt, and lifetime productivity of rural and urban (habitat) burrowing owls Athene cunicularia. Estimates and 95% confidence intervals (2.5% and 97.5%) were assessed after model averaging. We considered that a given variable has no, weak or strong support when the 95% confidence interval strongly overlapped with zero, barely overlapped with zero (asterisk), or did not overlap with zero (in bold), respectively. All models were run including year as a random term; models for lifetime productivity also included individual as a random term. Models shown are the first 10 models ranked using their AICc. w: Akaike weights Productivity during the first breeding attempt Model k AICc ∆AICc w Variables Estimate 2.50% 97.50% sex + dispersal distance*habitat 7 1372.93 0.00 0.42 dispersal distance -0.27 -0.82 0.28 dispersal distance*sex + habitat 7 1374.79 1.86 0.17 sex (females) 0.50 0.13 0.87 dispersal distance*sex 6 1374.90 1.96 0.16 habitat (rural) -0.36 -0.76 0.04 sex 4 1376.48 3.55 0.07 dispersal distance*sex (females) 0.62 0.05 1.19 sex + habitat 5 1376.54 3.61 0.07 dispersal distance*habitat (rural) 0.42 0.11 0.72 dispersal distance*habitat 6 1377.89 4.96 0.04 sex + dispersal distance + habitat 6 1377.99 5.06 0.03 sex + dispersal distance 5 1378.24 5.31 0.03 dispersal distance + habitat 5 1382.84 9.91 0.00 dispersal distance 4 1383.60 10.67 0.00 Lifetime productivity Model k AICc ∆AICc weight Variables Estimate 2.50% 97.50% sex + age 5 1239.58 0.00 0.20 sex (female) 0.27 0.10 0.45 sex + age 5 1239.58 0.00 0.20 age 0.08 0.03 0.14 sex + age + habitat 6 1240.69 1.11 0.11 habitat (urban) 0.11 -0.11 0.34 sex + age + habitat 6 1240.69 1.11 0.11 dispersal distance 0.02 -0.06 0.11 sex + age + dispersal distance 6 1241.34 1.76 0.08 sex + age + dispersal distance 6 1241.34 1.76 0.08 sex + age + dispersal distance + habitat 7 1242.15 2.57 0.05 sex + age + dispersal distance + habitat 7 1242.15 2.57 0.05 sex + age + dispersal distance*habitat 8 1242.48 2.90 0.05 sex + age + dispersal distance*habitat 8 1242.48 2.90 0.05 Chapter 1 68 We estimated the effect of dispersal distances on future apparent survival probabilities using encounter histories of 248 individuals (1411 resightings). The overall goodness- of-fit test of the model was not statistically significant (2 = 34.34, d.f. = 43, p=0.824). Model selection showed that resighting probabilities were lower for females (estimate: 0.82, 95% CI: 0.72 - 0.90) than for males (estimate: 0.93, 95% CI: 0.86 - 0.96; Table 3). Using this resighting structure, we tested the effect of natal dispersal distances on survival probabilities. The best model supported an interaction between dispersal distance and sex (Table 3), with females dispersing farther reducing their survival prospects compared to females staying closer (beta estimate: -1.21, 95% CI: -2.29 - - 0.14). For males, future survival was not correlated with dispersal distances, the estimate of the slope of this variable was not different to 0 (beta estimate: 1.60, 95% CI: -0.30 - 3.50; Figure 2). Habitat was not retained in models as a significant predictor of survival. Table 3. Model comparison to assess the effects of natal dispersal distances (distance) on immediate survival probabilities of urban and rural (habitat) burrowing owls Athene cunicularia. Smaller AICc values suggest a better fit of the model to data while also penalizing for complexity (k, number of parameters). Models whose AICc values differ from that of the top model by less than two (∆AICc < 2) are considered as alternative relative to the top model. Natal dispersal in urban and rural owls 69 Survival model Resighting model k deviance AICc ΔAICc distance*sex sex 6 735.58 747.73 0.00 constant sex 3 744.20 750.25 2.51 distance sex 4 743.24 751.24 3.51 sex sex 4 743.72 751.80 4.06 habitat sex 4 744.17 752.25 4.51 distance*habitat sex 6 740.19 752.35 4.62 distance+sex sex 5 743.03 753.14 5.41 distance+habitat sex 5 743.18 753.29 5.55 habitat+sex sex 5 743.66 753.77 6.03 time sex 12 729.65 754.24 6.50 time+sex sex 13 728.62 755.30 7.57 habitat*sex sex 6 743.57 755.73 7.99 time+habitat sex 13 729.65 756.33 8.60 time+habitat+sex sex 14 728.59 757.38 9.65 time*sex sex 20 722.68 764.29 16.55 time*habitat sex 21 722.75 766.51 18.78 time*habitat*sex sex 36 703.86 781.10 33.37 time*habitat*sex constant 35 707.06 782.01 34.28 time*habitat*sex habitat+sex 37 703.84 783.39 35.65 time*habitat*sex habitat 36 707.05 784.29 36.56 time*habitat*sex habitat*sex 38 703.56 785.42 37.68 time*habitat*sex time+sex 41 697.32 786.17 38.43 time*habitat*sex time 40 700.19 786.70 38.96 time*habitat*sex time+habitat+sex 42 697.31 788.51 40.78 time*habitat*sex time+habitat 41 700.17 789.02 41.29 time*habitat*sex time*sex 46 695.13 795.81 48.08 time*habitat*sex time*habitat 46 697.52 798.21 50.47 time*habitat*sex time*habitat*sex 57 682.28 809.86 62.13 Chapter 1 70 Figure 2. Relationship between survival probabilities of male (gray lines) and female (black lines) burrowing owls Athene cunicularia. Solid lines represent the general tendency; dashed lines: 95% confidence intervals. Natal dispersal in urban and rural owls 71 Discussion Our results show that variability in the natal dispersal distances observed among burrowing owls was mainly explained by the additive effects of sex, personality and habitat. As expected, females moved farther distances than males in both habitat types, while urban birds (both males and females) dispersed over shorter distances compared to rural ones, partly because of the higher conspecific density recorded in urban compared to rural areas. Moreover, bold individuals —those with shorter FID dispersed larger distances than their counterparts, regardless of their sex or the habitat and social environment in which they were born. Sexual differences in natal dispersal distances are common among vertebrates to prevent mating between close relatives (inbreeding avoidance: Pusey 1987; Szulkin and Sheldon 2008; Lebrige et al. 2010). However, the sex that disperses farther is not always the same and largely depends on the prevailing mating system of the species. In resource-defence mating systems, which is the prevailing system among birds, natal dispersal distances are generally shorter for males because they have to acquire and defend territories and, therefore, they may benefit from remaining near their natal area, where they are most familiar with resources and are probably best able to compete for them (Clarke et al. 1997; Pärt 1995; Piper et al. 2008). In our study species, males, but rarely females, actively defend an area larger than that immediately surrounding the nest burrow from conspecifics, with a more active response toward intruders at distances shorter than 100m (Moulton et al. 2004). This behavioral difference between sexes may underlie the sexual differences observed in the dispersal distances of individuals. Sex is not the only individual trait affecting dispersal distances among burrowing owls. Previous findings showed that bolder, more asocial, and more active individuals can move greater distances and are more suited to colonizing new areas than shyer, social and less active ones (Fraser et al. 2001; Fogarty et al. 2001; Cote et al. 2010). In Chapter 1 78 Clobert J, Le Galliard JF, Cote J, Meylan S, Massot M. Informed dispersal, heterogeneity in animal dispersal syndromes and the dynamics of spatially structured populations. Ecol Lett. 2009; 12(3):197–209. doi: 10.1111/j.1461-0248.2008.01267.x. Cote J, Clobert J, Brodin T, Fogarty S, Sih A. Personality-dependent dispersal: characterization, ontogeny and consequences for spatially structured populations. Philos Trans R Soc B Biol Sci. 2010; 365(1560):4065–76. doi: 10.1098/rstb.2010.0176. Cote J, Fogarty S, Weinersmith K, Brodin T, Sih A. Personality traits and dispersal tendency in the invasive mosquitofish (Gambusia affinis). Proc R Soc Lond B Biol Sci. 2010; 277(1687): 1571-1579. doi: 10.1098/rspb.2009.2128. Cox AS, Kesler DC. Reevaluating the cost of natal dispersal: post-fledging survival of red-bellied woodpeckers. The Condor. 2012; 114(2): 341-347. Dale S. Female‐biased dispersal, low female recruitment, unpaired males, and the extinction of small and isolated bird populations. Oikos. 2001; 92(2): 344-356. https://www.jstor.org/stable/3547240. Danchin E, Boulinier T, Massot M. Conspecific reproductive success and breeding habitat selection: implications for the study of coloniality. Ecology. 1998; 79(7): 2415- 2428. doi: 10.2307/176832. Danchin E, Giraldeau LA, Valone TJ, Wagner RH. Public information: from nosy neighbors to cultural evolution. Science. 2004; 305(5683): 487-491. doi: 10.1126/science.1098254. Davis, JM, Stamps, JA. The effect of natal experience on habitat preferences. Trends Ecol Evol. 2004; 19(8): 411-416. doi: 10.1016/j.tree.2004.04.006. Díaz M, Møller AP, Flensted-Jensen E, Grim T, Ibáñez-Álamo JD, Jokimäki J., ... Tryjanowski P. The geography of fear: a latitudinal gradient in anti-predator escape distances of birds across Europe. PloS one. 2013; 8(5), e64634. Natal dispersal in urban and rural owls 79 Dingemanse NJ, Both C, Van Noordwijk AJ, Rutten AL, Drent PJ. Natal dispersal and personalities in great tits (Parus major). Proc R Soc Lond B Biol Sci. 2003; 270(1516): 741-747. doi: 10.1098/rspb.2002.2300. Doligez B, Pärt T, Danchin E, Clobert J, Gustafsson L. Availability and use of public information and conspecific density for settlement decisions in the collared flycatcher. J Anim Ecol. 2004; 73(1): 75-87. https://doi.org/10.1111/j.1365-2656.2004.00782.x. Doligez B, Pärt T. Estimating fitness consequences of dispersal: A road to “knowwhere”? Non-random dispersal and the underestimation of dispersers’ fitness. J Anim Ecol. 2008; 77(6):1199–211. doi: 10.1111/j.1365-2656.2008.01446.x. Duckworth RA, Badyaev AV. Coupling of dispersal and aggression facilitates the rapid range expansion of a passerine bird. Proc Natl Acad Sci. 2007; 104(38): 15017-15022. doi: 10.1073/pnas.0706174104. Fogarty S, Cote J, Sih A. Social personality polymorphism and the spread of invasive species: a model. Am Nat. 2001; 177(3): 273-287. doi: 10.1086/658174. Forero MG, Donázar JA, Blas J, Hiraldo F. Causes and consequences of territory change and breeding dispersal distance in the Black Kite. Ecology. 1999; 80(4): 1298-1310. doi: 10.2307/3071887. Forero MG, Donázar JA, Hiraldo F. Causes and fitness consequences of natal dispersal in a population of black kites. Ecology. 2002; 83(3): 858-872. doi: 10.2307/3071887. Fraser DF, Gilliam JF, Daley MJ, Le AN, Skalski GT. Explaining leptokurtic movement distributions: intrapopulation variation in boldness and exploration. Am Nat. 2001; 158(2): 124-135. doi: 10.1086/321307. Garant D, Kruuk LE, Wilkin TA, McCleery, RH, Sheldon, BC. Evolution driven by differential dispersal within a wild bird population. Nature. 2005; 433(7021): 60. doi: 10.1038/nature03051. Chapter 1 80 Gavin TA, Bollinger EK. Reproductive correlates of breeding‐site fidelity in Bobolinks (Dolichonyx oryzivorus). Ecology. 1988; 69(1): 96-103. doi: 10.2307/1943164. Greenwood PJ, Harvey PH. The natal and breeding dispersal of birds. Annu Rev Ecol Syst. 1982; 13(1): 1-21. www.jstor.org/stable/2097060. Greig-Smith, PW. Dispersal between nest-sites by stonechats Saxicola torquata in relation to previous breeding success. Ornis Scandinavica;1982; 232-23. doi: 10.2307/3676304. Grimm NB, Faeth SH, Golubiewski NE, Redman CL, Wu J, Bai X, et al. Global change and the ecology of cities. Science. 2008; 319756–60. doi: 10.1126/science.1150195. Grueber CE, Nakagawa S, Laws RJ,Jamieson IG. Multimodel inference in ecology and evolution: challenges and solutions. J Evol Biol. 2011; 24(4): 699-711. doi: https://doi.org/10.1111/j.1420-9101.2010.02210.x. Hoelzel AR, Dover GA. Genetic differentiation between sympatric killer whale populations. Heredity. 1991; 66(2): 191. doi: 10.1038/hdy.1991.24. Jongejans E, Shea K, Skarpaas O, Kelly D, Sheppard AW, Woodburn TL. Dispersal and demography contributions to population spread of Carduus nutans in its native and invaded ranges. J Ecol. 2008; 96(4): 687-697. doi: 10.1111/j.1365-2745.2008.01367.x. Kokko H, López-Sepulcre A. From individual dispersal to species ranges: perspectives for a changing world. Science. 2006; 313(5788): 789-791. Kubisch A, Holt RD, Poethke HJ, Fronhofer EA. Where am I and why? Synthesizing range biology and the eco‐evolutionary dynamics of dispersal. Oikos. 2014; 123(1): 5- 22. https://doi.org/10.1111/j.1600-0706.2013.00706.x. Lebigre C, Alatalo RV, Siitari H. Female‐biased dispersal alone can reduce the occurrence of inbreeding in black grouse (Tetrao tetrix). Mol Ecol. 2010; 19(9): 1929- 1939. https://doi.org/10.1111/j.1365-294X.2010.04614.x. Natal dispersal in urban and rural owls 81 Lebreton JD, Burnham KP, Clobert J, Anderson DR. Modeling survival and testing biological hypotheses using marked animals: a unified approach with case studies. Ecol Monogr. 1992; 62(1): 67-118. https://doi.org/10.2307/2937171. Lemel JY, Belichon S, Clobert J, Hochberg ME. The evolution of dispersal in a two-patch system: some consequences of differences between migrants and residents. Evo Ecol. 1997; 11(5): 613-629. https://doi.org/10.1007/s10682-997-1516-z. Luna Á, Palma A, Sanz-Aguilar A, Tella JL, Carrete M. Personality-dependent breeding dispersal in rural but not urban burrowing owls. Sci Rep. 2019; 9(1), 2886. 10.1038/s41598-019-39251-w. Luna Á, Romero-Vidal P, Hiraldo F, Tella JL. Cities may save some threatened species but not their ecological functions. PeerJ. 2018; 6, e4908. Matthysen E. Density-dependent dispersal in birds and mammals. Ecography .2005; 28(3):403–16. https://doi.org/10.1111/j.0906-7590.2005.04073. McKinney ML, Lockwood JL. Biotic homogenization: a few winners replacing many losers in the next mass extinction. Trends Ecol Evol. 1999; 14(11): 450-453. https://doi.org/10.1016/S0169-5347(99)01679-1. McKinney ML. Urbanization as a major cause of biotic homogenization. Biol Conserv. 2006; 127(3): 247-260.doi: 10.1016/j.biocon.2005.09.005. Møller AP, Diaz M, Flensted-Jensen E, Grim T, Ibáñez-Álamo JD, Jokimäki J, ... Tryjanowski, P. High urban population density of birds reflects their timing of urbanization. Oecologia. 2012; 170(3): 867-875. doi: 10.1007/s00442-012-2355-3. Møller AP. Interspecific variation in fear responses predicts urbanization in birds. Behav Ecol. 2010; 21(2): 365-371. https://doi.org/10.1093/beheco/arp199. Montgomery M. United Nations Population Fund: State of world population 2007: Unleashing the potential of urban growth. Population and Development Review. 2007; 33(3): 639-641. Chapter 1 82 Moulton CE, Brady RS, Belthoff JR. Territory defense of nesting Burrowing Owls: responses to simulated conspecific intrusion. J. Field Ornithol. 2004; 75(3): 288-295. https://www.jstor.org/stable/4151311?origin=JSTOR-pdf. Mueller JC, Kuhl H, Boerno S, Tella JL, Carrete M, Kempenaers B. Evolution of genomic variation in the burrowing owl in response to recent colonization of urban areas. Proc R Soc Lond B Biol Sci. 2018; 285(1878): 20180206. doi: 10.1098/rspb.2018.0206. Nager RG, Johnson AR, Boy V, Rendon-Martos M, Calderon J, Cézilly F. Temporal and spatial variation in dispersal in the greater flamingo (Phoenicopterus ruber roseus). Oecologia. 1996; 107(2): 204-211. doi: 10.1007/BF00327904. Nakagawa S, Schielzeth H. A general and simple method for obtaining R2 from generalized linear mixed‐effects models. Methods Ecol Evol. 2013; 4(2): 133-142. https://doi.org/10.1111/j.2041-210x.2012.00261.x. Pärt T. The importance of local familiarity and search costs for age-and sex-biased philopatry in the collared flycatcher. Anim Behav. 1995; 49(4): 1029-1038. https://doi.org/10.1006/anbe.1995.0132. Payo-Payo A, Sanz-Aguilar A, Genovart M, Bertolero A, Piccardo J, Camps F, Ruiz-Olmo J, Oro D. Predator arrival elicits differential dispersal, change in age structure and reproductive performance in a prey population. Sci Rep. 2018; 8, 1971. doi: 10.1038/s41598-018-20333-0. Piper WH, Walcott C, Mager JN, Spilker FJ. Nestsite selection by male loons leads to sex‐biased site familiarity. J Anim Ecol. 2008; 77(2): 205-210. doi: 10.1111/j.1365- 2656.2007.01334.x. Pusey A, Wolf M. Inbreeding avoidance in animals. Trends Ecol Evol. 1996; 11(5): 201- 206. https://doi.org/10.1016/0169-5347(96)10028-8. Pusey AE. Sex-biased dispersal and inbreeding avoidance in birds and mammals. Trends Ecol Evol.1987; 2(10): 295-299. doi: 10.1016/0169-5347(87)90081-4. Natal dispersal in urban and rural owls 83 R Development Core Team R. A language and environment for statistical computing, http://www.R-project.org. 2008. Rebolo-Ifrán N, Carrete M, Sanz-aguilar A, Rodríguez-Martínez S. Links between fear of humans, stress and survival support a non-random distribution of birds among urban and rural habitats. Sci Rep. 2015; 5, 13723. doi: 10.1038/srep13723. Rebolo-Ifrán N, Tella JL, Carrete M. Urban conservation hotspots : predation release allows the grassland-specialist burrowing owl to perform better in the city. Sci Rep. 2017; 7(1), 3527. https://doi.org/10.1038/s41598-017-03853-z. Rodrigues, AM, Johnstone, RA. Evolution of positive and negative density-dependent dispersal. Proc R Soc Lond B Biol Sci. 2014; 281(1791): 20141226. doi: 10.1098/rspb.2014.1226. Rodriguez-Martínez S, Carrete M, Roques S, Rebolo-Ifrán N, Tella JL. High urban breeding densities do not disrupt genetic monogamy in a bird species. PLoS One. 2014; 9(3). https://doi.org/10.1371/journal.pone.0091314. Serrano D, Tella, JL. Lifetime fitness correlates of natal dispersal distance in a colonial bird. J. Anim. Ecol. 2012; 81(1): 97-107. doi: 10.1111/j.1365-2656.2011.01878.x. Skellam JG. Random dispersal in theoretical populations. Biometrika. 1951; 38(1/2): 196-218. https://doi.org/10.1093/biomet/38.1-2.196. Sol D, González‐Lagos C, Moreira D, Maspons J, Lapiedra O. Urbanisation tolerance and the loss of avian diversity. Ecol Lett. 2014; 17(8): 942-950. doi: 10.1111/ele.12297. Spear LB, Pyle P, Nur N. Natal dispersal in the western gull: proximal factors and fitness consequences. J Anim Ecol. 1998;67(2): 165-179. Sprau P, Dingemanse, NJ. An approach to distinguish between plasticity and nonrandom distributions of behavioral types along urban gradients in a wild passerine bird. Front Ecol Evol. 2017; 5, 92. https://doi.org/10.3389/fevo.2017.00092. Chapter 1 84 Stracey CM, Robinson SK. Are urban habitats ecological traps for a native songbird? Season‐long productivity, apparent survival, and site fidelity in urban and rural habitats. J Avian Biol. 2012; 43(1): 50-60.doi: 10.1111/j.1600-048X.2011.05520.x. Szulkin M, Sheldon BC. Dispersal as a means of inbreeding avoidance in a wild bird population. Proc R Soc Lond B Biol Sci. 2008; 275(1635): 703-711. doi: 10.1098/rspb.2007.0989. Tarwater, CE, Brawn, JD. Family living in a Neotropical bird: variation in timing of dispersal and higher survival for delayed dispersers. Anim Behav. 2010; 80(3): 535-542. https://doi.org/10.1016/j.anbehav.2010.06.017. Tella JL, Canale A, Carrete M, Petracci P, Zalba, SM. Anthropogenic nesting sites allow urban breeding in burrowing parrots Cyanoliseus patagonus. Ardeola. 2014; 61(2): 311-322. doi: 10.13157/arla.61.2.2014.311. Trochet A, Courtois EA, Stevens VM, Baguette M, Chaine A, Schmeller DS, ... Wiens JJ. Evolution of sex-biased dispersal. Q Rev Biol. 2016; 91(3): 297-320. Wiklund CG. Breeding lifespan and nest predation determine lifetime production of fledglings by male Merlins Falco columbarius. Proc R Soc Lond B Biol Sci. 1996; 263(1371): 723-728.doi: 10.1098/rspb.1996.0108. Chapter 2 “Kinship, ecological determinants and fitness benefits of cooperative breeding in a typically monogamous owl.” Cooperative breeding in urban and rural owls 93 Individuals were sexed based on plumage characteristics (Carrete et al. 2013) and, when needed, by molecular procedures (Rodríguez-Martínez et al. 2014). Delayed dispersal and kinship We genotyped individuals belonging to 5 complete cooperative families (all adults and chicks) using 17 polymorphic microsatellites previously tested for the species (see Rodriguez-Martínez et al. 2014 for details) to know the relatedness between the adults involved in cooperative breeding systems. DNA was extracted from blood samples using a modification of the silica-based protocol (Ivanova et al. (2006). Then, the loci were amplified by PCR in 2 independent multiplex reactions. For each PCR sample, 1.5 ml of the primers mix (5 ml of each in a final concentration of 2 mM), 3 ml of RNase free water (provided with the QIAGEN Multiplex PCR master mix), 4 ml of template DNA and 6.5 ml of QIAGEN Multiplex PCR master mix were used. The reaction consisted in a 5 min denaturation step at 95ºC, 32 cycles of 30 seconds at 95ºC, 90 seconds at 55ºC and 30 seconds at 72ºC, and ending with a final step of 30 minutes at 60ºC. PCR products were run on 1.5% agarose gels to check for amplification and yield, and then on an ABI3100 DNA analyzer to find DNA sizes. Genotypes were assigned in two ways, manually and automatically, using GeneMapper 3.7 (Applied Biosystems, Foster City, CA), and all electropherograms obtained were independently checked by two experts. All the microsatellites included in the study were at Hardy-Weinberg and linkage equilibrium (Rodriguez-Martínez et al. 2014). The kinship among the adults was assigned using the program Cervus 3.0.3 (Kalinowski et al. 2007), applying a likelihoodbased approach to assign parentage, combined with simulation of parentage analysis to determine the confidence of parentage assignments. We generated 100,000 simulated offspring, assuming 0.7 % sampled parents, 99 % loci typified, an inbreeding rate of 0.06%, and a genotyping error of 0.01 (Rodríguez-Martínez et al. 2014). Previous studies have confirmed genetic monogamy in the burrowing owl (Rodríguez- Martinez et al. 2014), so we complemented the information about the relatedness among adults of cooperative units using information obtained through year by year resights of birds marked as chicks of known parents. Chapter 2 94 Ecological correlates that drive cooperative breeding We used Generalized Linear Mixed Models (GLMM) to investigate factors affecting delayed dispersal using the probability of cooperative unit formation as the dependent variable (binomial error distribution, logistic link function). We considered cooperative breeding when more than two adults were observed during the complete breeding season involved in breeding tasks. Otherwise, we considered that the territory was occupied only by a pair. We included the effects of social variables (conspecific density and productivity in the natal area) and habitat (rural vs urban) as explanatory variables, as well as their interactions. “Year” was considered as a random term in models to control for potential interannual differences. Conspecific density was created by an annual aggregation index for every breeding territory, calculated as the relative position of a breeding territory within the spatial distribution of all breeding territories (Carrete et al. 2006). The index was obtained using the GPS location of all breeding territories as Si = Σ exp (−dij) (with i ≠ j), where dij was the linear distance between pairs i and j. Moreover, we used the conspecific productivity in the surroundings of each breeding territory, calculated as a modification of the same aggregation index, but the distance to each breeding territory was weighted by its reproductive output (number of fledglings raised in that season). Then, conspecific productivity was obtained as the residual of this last variable against the aggregation index calculated previously. Both variables were not correlated (Spearman correlation: rho=0.23, p< 2.2e-16).All covariates were centred before modelling to properly estimate their main effects (Grueber et al 2011). The analyses were done using package lme4 (Bates et al. 2015) in R environment (R Score Team, 2008). Cooperative breeding in urban and rural owls 95 Brood condition and current reproductive output We explored whether the body condition of chicks is influenced by the breeding system (bi-parental vs. cooperative breeding) and habitat (rural vs. urban) by Linear Mixed Models (LMM). To determine the individual body condition we measured morphometric parameters in captured chicks that were summarized into a body condition index, estimated as the residuals of a log-log regression of body mass on wing length (Schulte-Hostedde et al. 2005; Labocha and Hayes 2012). Considering that some chicks share their natal territory the models included the nest as a random effect to control for non-independence between breeding territories. We also evaluated potential differences in breeding success and productivity in nests occupied by breeding pairs and cooperative units. First, we tested by GLMM with a binomial error distribution and a logistic link function the effect of the breeding system (biparental vs cooperative breeding) and habitat in the breeding success, as the likelihood of raising at least one chick. Then, we tested the effect of breeding system and habitat on total productivity (number of fledglings raised by nest) by GLMM with a negative binomial error distribution and a logistic link function. All the models performed included the year as a random effect to control for non-independence between years. The analyses were also done with package lme4 (Bates et al. 2015) in R environment (R Score Team 2008). Future brood survival Finally, we tested if juvenile and/or adult survival of burrowing owls was related to the natal family structure (bi-parental vs. cooperative breeding) by means of capturerecapture models. To this end we created encounter histories (code 1= observed, code 0= not observed) for every marked chick for which data on natal nest family structure was known (N= 1407 individuals, N= 2060 resightings). Encounter histories were grouped by natal habitat (rural and urban) and family structure (bi-parental vs. cooperative breeding). Then, we evaluated the potential existence of heterogeneity in survival and or /recapture by assessing the goodness-of-fit tests of the Cormack-Jolly-Seber including Chapter 2 96 two age classes (ϕ2age*t pt) in program U-CARE (Choquet et al. 2009a). The overall GOF was not statistically significant, thereby indicating a good fit to the data (chi2=34.34, 43df, p=0.824). Our starting model considered the interaction among time, habitat and age on survival and the interaction between habitat and time on recapture. We started model selection by testing the effects of time, habitat and effort (differentiating years of low fieldwork effort “2007 and 2008” and years with intense fieldwork effort “2009 to 2017”) on recapture while maintaining survival as in the starting model. Once the best structure for recapture was selected, we modelled the effects of habitat and time on survival. Then, using the previous selected structure of survival and recapture parameters, we tested the effect of family structure on future juvenile and adult survival of the offspring. Models were implemented in program E-SURGE 2.1.4 (Choquet et al. 2009b). Model selection Model selection was performed using Akaike Information Criterion corrected for small sample sizes, AICc (Burnham and Anderson 2002). Within each set of models (which includes the null model), we calculated the ΔAICc (as the difference between the AICc of model i and that of the best model) and the Akaike weight (w) of each model. Models within 2 AICc units of the best one were considered as alternatives and used to perform model averaging (MuMIn package, Barton 2017). We considered that a given effect received no, weak or strong support when the 95% confidence interval (CI) strongly overlapped zero, barely overlapped zero, or did not overlap zero, respectively. Cooperative breeding in urban and rural owls 97 Results Delayed dispersal and kinship During our study period we monitored 5518 breeding events, of which 251 events (4.5% of total) corresponded to breeding units formed by more than 2 individuals (hereafter, cooperative units). Cooperative breeding events occurred all the breeding seasons but were a less common breeding strategy. Most cooperative units (almost the 97%) included only one additional male, while in 3% of the cases we recorded 2 additional birds (2 males, 1 male and 1 female, or 2 females). Ringing data show that these extra-individuals were close relatives (offspring) of the main breeders, both when the social identity of all individuals was known (the additional individuals and the main male and female, n = 12) as well as when only one of the breeder was of known identity (n = 22 cases). These individuals are grown offspring with delayed dispersal, postponing the settlement in their own breeding territories. Genetic parentage analysis performed in 5 families where all the 3 adults were ringed and bled corroborate that the additional members of the cooperative units were offspring of the main breeders. Ecological correlates that drive cooperative breeding Territories located in urbanized areas were more prone to host cooperative reproductive structures (5.2% of the monitored breeding events) than territories in rural areas (2.1% of the monitored breeding events). Productivity, conspecific density, habitat type and the interaction between conspecific density and habitat had influenced the probability of occurrence of cooperative breeding (Model 1, w=0.40; Table 1). Cooperative breeding is developed in most cases in the city, but we detected a significant and negative effect of the interaction between the habitat and the conspecific density, so that the probability to form alternative breeding structures was especially high in densely occupied rural areas (Figure 1). Finally, although two other alternative models including additional interactions were close to the best supported model in terms of AICc, the effects of these additional interactions were not significant (Models 2 and 3; SP2). Table 1. Modelling the effects of habitat (hab), productivity (product), and conspecific density (consp.density) on the probability to develop cooperative breeding in burrowing owls Athene cunicularia. Only models with an AICc weight >0 are shown (the complete series of model in SP1). df: degree of freedom, AICc: Akaike Information Criterion corrected for small sample sizes, ΔAICc: difference between the AICc of model i and that of the best model (i.e. the model with the lowest AICc), w: Akaike weights. Model Family structure (n=5518) Df AICc ΔAICc w Model 1 produc+hab+consp.density+ hab*consp.density 6 1941.62 0.00 0.40 Model 2 produc+hab+consp.density + hab*consp.density+hab*produc 7 1942.99 1.37 0.20 Model 3 produc+hab+consp.density + hab*consp.densityt+produc*consp.density 7 1943.47 1.85 0.16 Model 4 hab+consp.density+hab*consp.density 5 1944.62 3.00 0.09 Model 5 produc+hab+consp.density 5 1945.39 3.77 0.06 Model 6 produc+hab+consp.density+ hab*produc 6 1946.50 4.88 0.03 Model 7 produc+hab+consp.density+ produc*consp.density 6 1946.86 5.24 0.03 Model 8 produc+hab+consp.density+ hab*produc+produc*consp.density 7 1947.49 5.87 0.02 Figure 1. Cooperative breeding probabilities in urban and rural habitats according to the conspecific density and productivity in the area. Based in model averaged estimates. Coop breed= cooperative breeding; density= conspecific density; productivity= productivity in the area. Chapter 2 100 Brood condition, current fecundity and future brood survival Following a model selection procedure the best supported model (Model 1, w= 0.86) revealed significant effects of habitat, breeding system and the interaction between the two variables in the body condition of chicks (Table 2). The coefficients relating brood condition with breeding system were positive (15.69, CI: 7.57, 23.82), indicating that chicks raised in cooperative breeding systems have better body condition. We found no significant effects of the habitat nor the interaction between the habitat and the breeding system in the brood condition. Table 2. Relative importance of the breeding system (bi-parental vs. cooperative breeding) and habitat (rural vs. urban) on the body condition of chicks of burrowing owls Athene cunicularia. Estimates and 95% confidence intervals (2.5% and 97.5%) were assessed after model averaging. We considered that a given variable has no, weak or strong support when the 95% confidence interval strongly overlapped zero, barely overlapped zero, or did not overlap zero (in bold), respectively. Models shown are those with w>0. Df: degree of freedom, AICc: Akaike Information Criterion corrected for small sample sizes, ΔAICc: difference between the AICc of model i and that of the best model (i.e. the model with the lowest AICc), w: Akaike weights; coop. breed.= cooperative breeding. Models Body condition (n=1594) Df AICc ΔAICc w Variables Estimate 2.5% 97.5% Model 1 habitat+ breeding system+ habitat*breeding system 6 14125.74 0.00 0.86 habitat (urban) 2.20 -0.57 4.96 Model 2 habitat + breeding system 5 14129.87 4.12 0.11 breeding system (coop. breed.) 15.69 7.57 23.82 Model 3 breeding system 4 14132.24 6.50 0.03 habitat*breeding system -5.20 -14.88 4.49 Chapter 2 102 The breeding success (probability of raise at least one chick) of burrowing owls differed between breeding system and habitats (Model 1, w= 0.65, Table 3A). Specifically, urban territories and territories including helpers had higher probability to breed successfully (Figure 2). Similarly, mating system and habitat also affected breeding productivity (Model 1, w= 0.59, Table 3B). The number of fledglings per nest was higher in territories occupied by cooperative breeders and in urban territories (Figure 2). Models including interactions between variables were close in terms of AICc but the effect of interactions was not statistically significant (Model 2A, Model 2B; Table 3. To see details SP3). Cooperative breeding in urban and rural owls 109 development of cooperative breeding strategies. Previous research conducted on this species and study area indicates that the demographic trends and selective pressures vary between habitats and within them. Thus, higher breeding densities occur in high quality zones with low predation pressure, mainly in the city and certain rural patches (see details in Rebolo- Ifrán et al. 2017). In this sense, our results indicate that cooperative breeding is twice more common in the city; however, in high dense rural areas cooperative breeding also occur, and with high probabilities. The role of the ecological constraints as explanation for the development of cooperative breeding has been widely accepted in birds (Koenig et al. 1992; Emlen 1994). The high selective pressures observed in certain patches in our rural area may hinder or impede the successful settlement in marginal territories (Sergio and Newton 2003; Farrell et al. 2012). Certainly related to this, in areas with heterogeneous habitat quality the direct fitness benefits of independent breeding in poor quality patches may not outweigh the indirect inclusive fitness gains of remain in the natal territory (inheritance of natal or very close territories) (Stacey and Ligon 1991, Komdeur 1992; Pen and Weissing 2000). These ecological factors may explain why the delayed dispersal of some young males and the subsequent development of cooperative strategies emerge with major probability in high quality territories (Stacey and Ligon 1987; Komdeur 1992; Hatchwell and Komdeur 2000). Brood condition, current fecundity and future brood survival The additional adults involved in cooperative breeding can contribute in different reproductive related tasks, from egg incubation to territory defense (Boland 1998; Maklalov 2002). However, helper behavior may be specialized or mainly focused in one single labor, instead of divided in all the possible tasks (Arnold et al. 2005). Our results revealed that chicks raised with the help of extra adults have better body condition, suggesting that the role played by the helper could be related with food provisioning. Moreover, in a previous study conducted with this species in the same study area, Lois (2013) showed that helpers did not actively participate in or increase the effectiveness Chapter 2 110 of nest defense (indeed, individuals in cooperative units took longer to approach the predator and performed less aggressions toward it than breeding pairs), suggesting that the helping behavior conducted by the additional adult is focused to offspring food provisioning. The contribution of helpers in cooperative breeding units can affect the reproductive success of the nests in which this reproductive system occur, but the overall contribution of helpers in this sense is variable: they can have positive but also irrelevant effects on the reproductive output (Hatchwell 1999; Legge 2000; Eguchi et al. 2002; Hatchwell et al. 2004; Blackmore and Heinsohn 2007). In this sense, Magrath and Yezerinac (1997) showed that the presence of additional adults involved in reproductive tasks in the white-browed scrubwrens (Sericornis frontalis) does not lead to an increase in the reproductive success of this species. On the contrary, Woxvold and Magrath (2005) and Kingma et al. (2010) have demonstrated the reproductive benefits of cooperative breeding in the apostlebird (Struthidea cinerea) and the purple‐crowned fairy‐wren (Malurus coronatus) respectively. In our case, the presence of helpers clearly enhanced the fledgling production of burrowing owls, probably via the potentially higher body condition or quality of individuals raised by cooperative breeding. This suggests that the contribution of an extra adult can be of greater value. The assistance of non-breeder adults may also influence the survival of the offspring (Bennun, 1994; McGowan et al. 2003; Ridley 2007; Lloyd et al. 2009; Meade et al.2010). However, the effects of helper individuals in this component of fitness are much difficult to detect than immediate reproductive consequences (Emlen 1991; Arnold and Owens 1998). Here, using a long term monitoring on marked individuals, we show that survival rates slightly increase for individuals raised with the help of extra adults. The small advantage of birds raised by cooperative breeding systems may be due to the better body condition acquired as nestling when helpers collaborate in food provisioning. However, after independence, selection pressures not related with the body condition may affect similarly birds raised in bi-parental families or in Cooperative breeding in urban and rural owls 111 cooperative system, hence the scarce differences observed in terms of survival (Woxvold and Magrath 2005). Conclusion Here we show how social related factors and changes associated to human habitat transformation can promote delayed dispersal to develop cooperative breeding behavior in a typically bi-parental species. Genetic analyses and resights of marked individuals suggest a high kinship between the adults involved in cooperative breeding events. The existence of high quality areas, mainly located in the city and in certain patches of natural areas, may determine the formation of alternative breeding systems. The potential benefits of cooperative behavior emerge mostly the form of better reproductive results and body condition of chicks in such territories with helpers, but only a slight improvement of better survival probabilities of the offspring was detected. The fact that reproductive capable adults delay their dispersal reinforces the idea that this species show a low dispersal tendency. Further research is needed to evaluate the fitness benefits for the helper and for the breeders along their lifetime. Chapter 2 112 References Arnold KE, Owens IP. Cooperative breeding in birds: a comparative test of the life history hypothesis Proc R Soc Lond B Biol Sci. 1998; 265(1398), 739-745. Arnold KE, Owens IP, Goldizen AW Division of labour within cooperatively breeding groups. Behaviour. 2005; 142(11-12), 1577-1590. Baglione V, Marcos JM, Canestrari D, Ekman J.). Direct fitness benefits of group living in a complex cooperative society of carrion crows, Corvus corone corone. Anim Behav. 2002; 64(6), 887-893. Barton K. MuMIn: Multi-Model Inference. 2018. R package version 1.42.1 https://CRAN.R-project.org/package=MuMIn. Bates D, Maechler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 2015; 67(1): 1-48. doi:10.18637/jss.v067.i01. Bennun L. The contribution of helpers to feeding nestlings in Grey-capped Social Weavers, Pseudonigrita arnaudi. Anim Behav. 1994; 47(5), 1047-1056 Biard C, Brischoux F, Meillère A, Michaud B, Nivière M, Ruault S, et al. Growing in Cities: An Urban Penalty for Wild Birds? A Study of Phenotypic Differences between Urban and Rural Great Tit Chicks (Parus major). Front Ecol Evol. 2017;5, 1–14 Blackmore CJ, Heinsohn R. Reproductive success and helper effects in the cooperatively breeding grey‐crowned babbler. J Zool. 2007; 273(3), 326-332. Boland, C. R. (1998). Helpers improve nest defence in cooperatively breeding Whitewinged Choughs. Emu-Austral Ornithology, 98(4), 320-324. Bonte D, Dahirel M. Dispersal: a central and independent trait in life history. Oikos. 2017; 126(4): 472-479. Cooperative breeding in urban and rural owls 113 Brouwer L, Richardson DS, Komdeur J. Helpers at the nest improve late-life offspring performance: evidence from a long-term study and a cross-foster experiment. PloS one. 2012; 7(4), e33167. Browning LE, Patrick SC, Rollins LA, Griffith SC, Russell AF Kin selection, not group augmentation, predicts helping in an obligate cooperatively breeding bird. Proc R Soc Lond B Biol Sci. 2012; 279(1743), 3861-3869. Burnham KP, Anderson DR. Model selection and multimodel inference. A practical information-theoretic approach. New York: Springer-Verlag.2002. doi: 10.1007/978-1- 4757-2917-7_3. Caballero IC, Bates JM, Hennen M., Ashley MV. Sex in the city: breeding behavior of urban peregrine falcons in the midwestern US. PloS one. 2016; 11(7), e0159054 Carrete M, Sánchez-Zapata JA, Tella JL., Gil-Sánchez JM, Moleón M. Components of breeding performance in two competing species: habitat heterogeneity, individual quality and density-dependence. Oikos. 2006; 112: 680-690. Carrete M, Tella JL. Individual consistency in flight initiation distances in burrowing owls: a new hypothesis on disturbance-induced habitat selection. Biol Lett. 2010; 6: 167–170. Carrete M, Tella JL. Inter-individual variability in fear of humans and relative brain size of the species are related to contemporary urban invasion in birds. PLoS One. 2011; 6(4). Carrete M, Tella, JL. High individual consistency in fear of humans throughout the adult lifespan of rural and urban burrowing owls. Sci Rep. 2013; 3, 3524. doi: 10.1038/srep03524. Carrete, M., Martínez-Padilla, J., Rodríguez-Martínez, S., Rebolo-Ifrán, N., Palma, A., & Tella, J. L. (2016). Heritability of fear of humans in urban and rural populations of a bird species. Scientific reports, 6, 31060. Chapter 2 114 Carrete, M, Tella, JL. Behavioral correlations associated with fear of humans differ between rural and urban burrowing owls. Front Ecol Evol. 2017; 5, 54. https://doi.org/10.3389/fevo.2017.00054. Choquet R, Lebreton JD, Gimenez O, Reboulet AM, Pradel R. U‐CARE: Utilities for performing goodness of fit tests and manipulating CApture–REcapture data. Ecography. 2009; 32(6): 1071-1074. Choquet R, Rouan L, Pradel R. Program E-SURGE: a software application for fitting multievent models. In Modeling demographic processes in marked populations. pp. 845-865. Springer, Boston, MA, 2009. Cockburn A. Prevalence of different modes of parental care in birds. Proc R Soc Lond B Biol Sci.2006; 273(1592), 1375-1383. Cockburn A. Evolution of helping behavior in cooperatively breeding birds. Annu Rev Ecol Syst. 1998; 29(1), 141-177. Cockburn A, Sims RA, Osmond HL, Green DJ, Double MC, Mulder RA. Can we measure the benefits of help in cooperatively breeding birds: the case of superb fairy‐wrens Malurus cyaneus?. J Anim Ecol. 2008; 77(3), 430-438. Conrad KF, Clarke MF, Robertson RJ, Boag PT. Paternity and the relatedness of helpers in the cooperatively breeding bell miner. The Condor. 1998; 100(2), 343-349. Cornwallis CK. Cooperative breeding and the evolutionary coexistence of helper and nonhelper strategies. Proc Natl Acad Sci USA 2018; 115(8), 1684-1686. Clutton-Brock T. Breeding together : kin Selection and mutualism in cooperative vertebrates. Science. 2002; 296(5565), 69-72. Dickinson JL, Hatchwell BJ. Fitness consequences of helping. Ecology and evolution of cooperative breeding in birds, 2004. 48-66. Dickinson JL, Koenig WD, Pitelka, FA. Fitness consequences of helping behavior in the western bluebird. Behav Ecol. 1996; 7(2), 168-177. Cooperative breeding in urban and rural owls 115 Eguchi K, Yamagishi S, Asai S, Nagata H, Hino T. (Helping does not enhance reproductive success of cooperatively breeding rufous vanga in Madagascar. J Anim Ecol. 2002; 71(1), 123-130. Emlen ST, Reeve HK, Sherman PW, Wrege PH, Ratnieks FL, Shellman-Reeve J. Adaptive versus nonadaptive explanations of behavior: the case of alloparental helping. Amer Nat. 1991; 138(1), 259-270. Emlen ST. Benefits, constrainsts and the evolution of the family. Trends Ecol Evolut. 1994; 9(8), 282-285. Farrell SL, Morrison ML, Campomizzi AJ, Wilkins RN. Conspecific cues and breeding habitat selection in an endangered woodland warbler. J Anim Ecol. 2012; 81(5), 1056- 1064. Griffin AS, West SA. Kin discrimination and the benefit of helping in cooperatively breeding vertebrates. Science. 2003; 302(5645), 634-636. Grimm NB, Faeth SH, Golubiewski NE, Redman CL, Wu J, Bai X, et al. Global change and the ecology of cities. Science. 2008; 319756–60. Grueber CE, Nakagawa S, Laws RJ,Jamieson IG. Multimodel inference in ecology and evolution: challenges and solutions. J Evol Biol. 2011; 24(4): 699-711. Haig SM, Walters JR., Plissner JH. Genetic evidence for monogamy in the cooperatively breeding red-cockaded woodpecker. Behav Ecol Sociobiol. 1994; 34(4), 295-303. Hammers M, Kingma SA, Spurgin LG, Bebbington K, Dugdale HL, Burke T., ... Richardson DS. Breeders that receive help age more slowly in a cooperatively breeding bird. Nat Commun. 2019; 10(1), 1301. Hatchwell BJ, Komdeur J. Ecological constraints, life history traits and the evolution of cooperative breeding. Anim behav. 2000; 59(6), 1079-1086. Chapter 2 116 Hatchwell BJ, Russell AF Provisioning rules in cooperatively breeding long-tailed tits Aegithalos caudatus: an experimental study. Proc R Soc Lond B Biol Sci. 1996; 263(1366), 83-88. Hatchwell BJ, Russell AF, MacColl AD, Ross DJ, Fowlie MK, McGowan A. Helpers increase long-term but not short-term productivity in cooperatively breeding longtailed tits. Behav Ecol. 2004; 15(1), 1-10. Hatchwell BJ. The evolution of cooperative breeding in birds : kinship , dispersal and life history. Philos Trans Roya Soc. B. 2009; 3217–27. Heg D, van Treuren R. Female–female cooperation in polygynous oystercatchers. Nature. 1998; 391(6668), 687. Heinsohn RG. Parental care, load-lightening, and costs. Ecology and evolution of cooperative breeding in birds. 2004; 67-80. Ivanova NV, Dewaard JR, Hebert PDN An inexpensive, automation friendly protocol for recovering high-quality DNA. Mol Ecol Notes. 2006; 6: 998–1002. Jetz W, Rubenstein DR. Environmental uncertainty and the global biogeography of cooperative breeding in birds. Curr Biol. 2011;21(1):72–8. Kalinowski ST, Taper ML, Marshall TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol Ecol 16: 1099–1106. Kingma SA, Hall ML, Arriero E, Peters A. Multiple benefits of cooperative breeding in purple‐crowned fairy‐wrens: a consequence of fidelity?. J Anim Ecol. 2010; 79(4), 757- 768 Koenig WD, Pitelka FA, Carmen WJ, Mumme RL, Stanback MT. The evolution of delayed dispersal in cooperative breeders. Q Rev Biol. 1992; 67(2), 111-150. Kokko H, Lundberg P. Dispersal, migration, and offspring retention in saturated habitats. Amer Naturalist. 2001; 157(2), 188-202. Cooperative breeding in urban and rural owls 117 Kokko H, Ekman J. Delayed dispersal as a route to breeding: territorial inheritance, safe havens, and ecological constraints. Amer Naturalist. 2002; 160(4), 468-484. Komdeur J. Importance of habitat saturation and territory quality for evolution of cooperative breeding in the Seychelles warbler. Nature. 1992; 358(6386), 493. Komdeur J. The effect of kinship on helping in the cooperative breeding Seychelles warbler (Acrocephalus sechellensis). Proc R Soc Lond B Biol Sci. 1994; 256(1345), 47- 52. Labocha MK, Hayes JP. Morphometric indices of body condition in birds: a review. J Ornithol. 2012; 153(1), 1-22. Lloyd P, Taylor AW, Du Plessis MA, Martin TE. Females increase reproductive investment in response to helper‐mediated improvements in allo‐feeding, nest survival, nestling provisioning and post‐fledging survival in the Karoo scrub‐robin Cercotrichas coryphaeus. J Avian Biol. 2009; 40(4), 400-411. Luna Á, Palma A, Sanz-Aguilar A, Tella JL, Carrete M. Personality-dependent breeding dispersal in rural but not urban burrowing owls. Sci Rep. 2019; 9(1), 2886. 10.1038/s41598-019-39251-w. Luna Á, Romero-Vidal P, Hiraldo F, Tella JL. Cities may save some threatened species but not their ecological functions. PeerJ. 2018; 6, e4908. Machicote M, Branch LC, Villarreal D. Burrowing owls and burrowing mammals: are ecosystem engineers interchangeable as facilitators?. Oikos. 2004; 106(3), 527-535. Magrath RD, Yezerinac SM. Facultative helping does not influence reproductive success or survival in cooperatively breeding white-browed scrubwrens. J Anim Ecol. 1997; 658-670. Maklakov AA. Snake-directed mobbing in a cooperative breeder: anti-predator behaviour or self-advertisement for the formation of dispersal coalitions?. Behav. Ecol. Sociobiol. 2002; 52(5), 372-378. Chapter 2 118 McKinney ML. Urbanization as a major cause of biotic homogenization. Biol Conserv. 2006; 127(3): 247-260. McGowan A, Hatchwell BJ, Woodburn RJ. The effect of helping behaviour on the survival of juvenile and adult long‐tailed tits Aegithalos caudatus. J Anim Ecol. 2003; 72(3), 491-499. Meade J, Nam K, Beckerman AP, Hatchwell BJ. Consequences of ‘ load-lightening ’ for future indirect fitness gains by helpers in a cooperatively breeding bird. J Anim Ecol. 2010; 79(3), 529-537. Møller AP Successful city dwellers: a comparative study of the ecological characteristics of urban birds in the Western Palearctic. Oecologia. 2009; 159(4), 849- 858. Møller AP. Interspecific variation in fear responses predicts urbanization in birds. Behav Ecol. 2010; 21(2): 365-371. Mueller JC, Kuhl H, Boerno S, Tella JL, Carrete M, Kempenaers B. Evolution of genomic variation in the burrowing owl in response to recent colonization of urban areas. Proc R Soc Lond B Biol Sci. 2018; 285(1878): 20180206. doi: 10.1098/rspb.2018.0206. Nam KB, Simeoni M, Sharp SP, Hatchwell BJ. Kinship affects investment by helpers in a cooperatively breeding bird. Proc R Soc Lond B Biol Sci. 2010; 277(1698), 3299-3306. Nelson‐Flower MJ, Wiley EM, Flower TP, Ridley AR. Individual dispersal delays in a cooperative breeder: Ecological constraints, the benefits of philopatry and the social queue for dominance. J Anim Ecol. 2018; 87(5), 1227-1238. Oro D, Genovart M, Tavecchia G, Fowler MS, Martínez‐Abraín A. Ecological and evolutionary implications of food subsidies from humans. Ecology letters. 2013; 16(12), 1501-1514. Chapter 3 124 Personality-dependent breeding dispersal in rural but not urban burrowing owls Abstract Dispersal propensity has been correlated with personality traits, conspecific density and predation risk in a variety of species. Thus, changes in the relative frequency of behavioural phenotypes or in the ecological pressures faced by individuals in contrasting habitats can have unexpected effects on their dispersal strategies. Here, using the burrowing owl Athene cunicularia as a study model, we test whether changes in the behavioural profile of individuals and changes in conspecific density and predation pressure associated with urban life influence their breeding dispersal decisions compared to rural conspecifics. Our results show that breeding dispersal behaviour differs between rural and urban individuals. Site fidelity was lower among rural than among urban birds, and primarily related to an individual’s behaviours (fear of humans), which has been reported to reflect individual personality. In contrast, the main determinant of site fidelity among urban owls was conspecific density. After taking the decision of dispersing, urban owls moved shorter distances than rural ones, with females dispersing farther than males. Our results support a personalitydependent dispersal pattern that might vary with predation risk. However, as multiple individuals of two populations (one urban, one rural) were used for this research, differences can thus also be caused by other factors differing between the two populations. Further research is needed to properly understand the ecological and evolutionary consequences of changes in dispersal behaviours, especially in terms of population structuring and gene flow between urban and rural populations. Breeding dispersal in urban and rural owls 125 Introduction Dispersal has important consequences for an individual’s fitness, affecting population structure, species distributions, and range shifts (Greenwood and Harvey 1982; Pasinelli et al. 2007). Thus, understanding why and how organisms disperse is central to many questions in theoretical and applied ecology and evolution (Serrano et al. 2001; Bowler and Benton 2005). Breeding dispersal (i.e. the inter-annual movement of individuals between breeding sites) has received much attention in recent decades, especially for birds. Within this taxonomic group, breeding dispersal has been related to an individual’s characteristics such as age or sex, suggesting differences in gender roles in territory acquisition (Greenwood and Harvey 1982) as well as benefits derived from breeding-site familiarity (Newton and Marquiss 1982; Forero et al. 1999; Serrano et al. 2001). However, within a sex or age class, individual variation in dispersal movements can be important and linked to an individual’s experience such as breeding success, mate loss, or predation pressure in the previous year (Pasinelli et al. 2007; Ganey et al. 2014; Payo-Payo et al. 2018), which can be ultimately influenced by habitat quality (Payo-Payo et al. 2017) and modulated by conspecific density (Hammill et al. 2017). A recent theory has suggested that individual variation in dispersal may also be linked to individual differences in behavioural types or behavioural syndromes that can be stable over the ontogeny or across situations (defined as a given set of conditions at one point in time, involving different levels along an environmental gradient or different sets of conditions across time; Sih et al.2004), leading a personality-dependent dispersal (Clobert et al. 2009; Denoël et al. 2017). However, as behavioural differences between individuals usually influence their vulnerability to predation (Jones and Godin 2009; Harris et al. 2010) the pattern of personalitydependent dispersal can be modified when factors motivating dispersal, such as predation risk, change (Cote et al. 2013). Thus, studies contrasting dispersal patterns of conspecifics subjected to different selection regimes can help us better understand the dynamic nature of dispersal as well as its drivers. This is particularly important in the Chapter 3 126 context of global change, as dispersal is a crucial mechanism allowing species to respond to shifting environmental conditions (Payo-Payo et al. 2018). Urbanisation is one of the most prevailing causes of habitat transformation worldwide and a main driver of global change. Although animal communities are usually simplified and homogenised in these new habitats (Sol et al. 2014), cities can also act as predator-free refuges for the many species able to colonise them (Rebolo-Ifrán et al. 2017). This colonisation of urban environments by birds has been related to their interindividual variability in fear of humans (a repeatable and heritable behaviour which is correlated with exploration and antipredatory behaviour and can be considered as a personality trait; Carrete and Tella 2013; Carrete et al. 2016), such that urban life would select for fearless individuals (Carrete and Tella 2010; Carrete and Tella 2017). In urban areas, these individuals can improve their demographic parameters, as predation risk is lower, and establish larger population densities than in rural habitats, even changing the habitat selection pattern of a species (Carrete and Tella 2011; Møller 2012). However, due to the role of behaviour, conspecific density and predation pressure on the dispersal propensity of individuals, urbanisation can deeply affect not only the demography but also the spatial structure and dynamics of rural and urban populations. In spite of this, studies comparing breeding dispersal behaviour of individuals living in both habitat types are scarce (Marzluff et al. 2016) and no one has deeply explored the mechanism provoking these differences. Here, using the burrowing owl Athene cunicularia as a study model, we assessed the importance of an individual’s traits (age, sex, and behaviour), previous breeding experiences (breeding output and nest predation) and conspecific density in determining individual breeding dispersal behaviour in rural and urban birds. We specifically considered how an individual’s personality affects site fidelity and breeding dispersal distances, discussing which changes associated with urban life (i.e. reduction in predation pressure, increments in conspecific density or selection of individuals tolerant towards humans) can explain differences in the dispersal patterns of rural and urban birds. Our results showed that rural birds were less faithful to their breeding territories and dispersed at greater distances than urban ones. Our findings support Breeding dispersal in urban and rural owls 127 the personality-dependent dispersal hypothesis and a role for the behavioural skewness associated with urban invasion in explaining changes in dispersal patterns of urban and rural birds, highlighting the potential of urbanisation to cause population structuring by altering individual’s movements. Material and methods Study species and area The burrowing owl is distributed across American open landscapes, breeding in burrows excavated by the owls themselves or by mammals. Breeding pairs are territorial and show diurnal activity, and are easily located in the surroundings of their nests (Carrete et al. 2016). In our study area (ca. 5,400 km2 of rural and urban areas around Bahia Blanca city, Argentina), rural owls breed in large extensions of natural grasslands and pastures dedicated to extensive livestock grazing and low-intensive cereal crops, where human presence is extremely low and mostly restricted to a few paved or unpaved roads (Rebolo-Ifrán et al. 2015). Urban owls, conversely, excavate their nests in small private and public gardens in urbanised residential areas, unbuilt spaces among houses, curbs of streets and large avenues, and are in constant contact with homeowners, children, pedestrians and intense car traffic. The city is immediately surrounded by large and flat rural extensions, with no obstacles preventing owls from moving between habitats (Carrete and Tella 2013). Moreover, as owls are able to excavate their own burrows, there are no habitat constraints (e.g., availability of nesting structures) that can limit their dispersal movements. From 2006 to 2016, we annually monitored the breeding population of the species in the study area, totalling ca. 2,200 urban and 3,000 rural nests during the whole period. The location of all occupied nests was used to calculate an annual aggregation index for each breeding pair as their relative position within the spatial distribution of all breeding pairs32. This index, which reflects conspecific density, was obtained as Si= Σ exp (-dij) (with i ≠j), where dij was the linear distance between pairs i and j. Territories Chapter 3 128 were repeatedly visited to assess breeding success (i.e. breeding pairs successfully producing at least one fledgling) and productivity (i.e. the number of young fledged per breeding attempt), and to look for signs of predation such as the presence of corpses or plucked owl feathers at the entrance of the nests (see Rebolo-Ifrán et al. 2017 for a more detailed methodology). During this period, we also captured ca. 2,000 adults and chicks using bow nets and ribbon carpets to mark them with plastic colour-numbered rings readable at distance. Individuals were sexed based on plumage characteristics (Carrete and Tella 2011) and, when needed, by molecular procedures (Rodriguez- Martínez et al. 2014). Resightings of marked birds were done during an intensive population monitoring program lasting from 2007 to 2016, surveying all known breeding sites as well as unoccupied but suitable areas. Fear of humans is indicative of the risk that individuals are willing to take in our presence, and has been shown to be key to understanding avian urban invasion (Carrete and Tella 2011). This behaviour is highly repeatable along an individual adulthood (Carrete and Tella 2013), heritable (Carrete et al. 2016) and linked to exploration and antipredatory behaviours (Carrete and Tella 2017), and is thus a consistent predictor of individual personality. We measured fear of humans of breeding birds during the chick-rearing period as the distance at which individuals flee when approached by a human (so-called flight initiation distance, hereafter FID), following standard protocols (see details in [Rebolo- Ifrán et al. 2017; Carrete et al. 2016]). Both single and average values of FID were used (when more than one measure was obtained from a single individual in the same or different years), given the high repeatability of this behaviour (Carrete and Tella 2013). Statistical approach We used Generalized Linear Mixed Models (GLMM) to compare site fidelity (logistic link function, binomial error distribution) and dispersal distances (log-transformed, identity link function, normal error distribution) between rural and urban owls and to explore the effects of individual traits (sex, age, and FID), previous breeding experience (breeding success, productivity and predation), and conspecific density on these parameters. We considered that a bird remained faithful to its previous-year breeding site when it stayed in the same nest or in its immediate surroundings (radius=10m) Breeding dispersal in urban and rural owls 129 between successive breeding events. This distance was established based on the GPS location error (3-8 m) and given that holes at distances 10 m can be different entrances to the same burrow. For individuals moving farther than 10 m (categorized as dispersers), we measured their dispersal distances as the straightline between two consecutive breeding sites. We assessed the relative contribution of individual traits, previous experience and conspecific density in determining the dispersal patterns of rural and urban burrowing owls using an information-theoretic approach on two main datasets. First, we performed models using the group of individuals of known age (captured as chicks in their nests), to explore the role of age in dispersal. Then, as most individuals were captured as adults and their age was unknown, we ran a second set of models without considering the effect of age. Models were built using a different combination of variables in interaction with habitat, but including alternatively only one descriptor of an individual’s previous experience due to their high correlational causation (predation is the main cause of breeding failure in the study species, thus affecting breeding success and productivity, see details in Rebolo- Ifrán et al. 2017) and multicollinearity. All models included “individual” and “year” as random terms to control for pseudoreplication and potential interannual differences, respectively. Model selection was performed using the Bayes Information Criterion, BIC (Burnham and Anderson 2002). Within each set of models (which includes the null model), we calculated the ΔBICi (as the difference between the BIC of model i and that of the best model) and the weight (w) of each model. Models within 6 BIC units of the best one were considered as alternatives and used to perform model averaging (MuMIn package; Barton 2017). BIC penalizes larger models more heavily than other criteria such as the Akaike Information Criteria (AIC) and so will tend to prefer smaller models sometimes losing some weak relationships. Thus, we also used the AICc (Akaike Information Criterion corrected for small sample sizes) to checked the consistency of our findings (results obtained using AICc are only shown in Supplementary Materials). All continuous variables were centred before modelling to properly estimate their main effects regardless of whether we include the interaction (Grueber et al. 2011). Chapter 3 130 We considered that a given effect received no, weak or strong statistic support when the 95% confidence interval (CI) strongly overlapped zero, barely overlapped zero, or did not overlap zero, respectively. Complementarity, we calculated the coefficient of determination, R2, as a measure of the variance explained by a model (Nakagawa and Schielzeth 2012). Statistical analyses were conducted in R 3.1.2 (R Development Core Team R 2008). Results We recorded 866 breeding dispersal events in 130 rural and 334 urban owls. Rural birds were less faithful to their breeding sites (rural: 39%, urban: 50%; 2= 6.23, d.f. = 1, p=0.0126; Figure 1a) and, when they dispersed, did so at greater distances than urban birds (median rural: 112m, range: 13-7,500m, median urban: 76.5m, range: 11- 6,900m; F1,348 = 40.67, p < 0.0001; Figure 1b). Breeding dispersal in urban and rural owls 131 Figure 1. (a) Proportion of burrowing owls showing site fidelity (1) or changing their breeding sites between successive years (0) in rural (grey bars) and urban (black bars) habitats. (b) For individuals changing their breeding sites, the accumulated proportion of dispersing urban (grey line) and rural (black line) individuals as a funciton of distance is also shown. The maximum dispersal distance observed is indicated by a point (grey and black, for urban and rural birds respectively). Vertical dashed lines show mean distances for urban (grey line) and rural (black line) birds. Chapter 3 132 Our reduced dataset of birds ringed as chicks show that age was not related to site fidelity or dispersal distance among urban and rural birds (Table 1 and S1). Table 1. Alternative models (∆BIC < 6) obtained to assess the relative importance of individual’s traits (age, sex and behaviour, measured as FID), previous breeding experience (breeding success, productivity and predation in the previous year t-1) and conspecific density on the dispersal pattern (site fidelity and dispersal distances) of rural and urban (habitat) burrowing owls Athene cunicularia. Models were run using information from individuals of known age (ringed as chicks). See Table S1 for alternative models obtained using the Akaike Information Criterion corrected for small sample sizes (AICc). site fidelity Df BIC ΔBIC weight null 3 211.19 0.00 0.36 productivity(t-1) 4 213.96 2.78 0.09 predation(t-1) 4 214.13 2.94 0.08 breeding success(t-1) 4 214.31 3.13 0.08 habitat 4 215.31 4.13 0.05 sex 4 215.55 4.36 0.04 aggregation 4 216.07 4.89 0.03 FID 4 216.16 4.97 0.03 habitat*FID 5 216.40 5.22 0.03 dispersal distance Df BIC ΔBIC weight null 4 75.44 0.00 0.68 habitat 5 78.25 2.81 0.17 Breeding dispersal in urban and rural owls 133 Thus, we relied on our larger sample including all individuals to assess the relative importance of an individual’s traits, previous experience and conspecific density on the dispersal pattern of individuals. Using this dataset, we obtained alternative models including individual traits as well as descriptors of previous experience (Table 2). After model averaging, we found strong support for an effect of individual behaviour on site fidelity of rural birds and of conspecific density on site fidelity of urban and rural ones (Table 2; Figure 2), shyer rural individuals and birds breeding at higher conspecific densities having a higher probability of changing their breeding sites between successive years than their counterparts (R2 = 0.16). Habitat, and breeding success and productivity in the previous year received strong support to explain variability in the dispersal distance of all individuals (R2 = 0.46), urban birds, and individuals breeding successfully or having more chicks moving less than rural, and unsuccessful owls (Table 2; Figure 2). Models obtained using AICc show similar results, also supporting a role for conspecific aggregation in site fidelity of urban birds and sex on dispersal distance (females dispersing further than males; Table S2). Table 2. Relative importance of an individual’s traits (sex and behaviour, measured as FID), previous breeding experience (breeding success, productivity and predation in the previous year t-1) and conspecific density on the dispersal pattern (site fidelity and dispersal distances) of rural and urban (habitat) burrowing owls Athene cunicularia. Estimates and 95% confidence intervals (2.5% and 97.5%) were assessed after model averaging. We considered that a given variable has no, weak or strong support when the 95% confidence interval strongly overlapped zero, barely overlapped zero, or did not overlap zero (in bold), respectively. Models were run using all individuals of unknown age, as age has not received statistical support (see Table 1 and S1). Models shown are those used for model averaging (ΔBIC ≤ 6). See Table S2 for results obtained using the Akaike Information Criterion (ΔAICc < 6). Chapter 3 140 patterns of individuals. At an interspecific level, previous studies have suggested a relationship between FID and descriptors of natal dispersal or range distribution (Lin et al. 2012; Møller and Garamszegi 2012). Here, we provide the first evidence, at the individual level, that breeding dispersal is also personality-dependent in a bird species, suggesting that changes in ecological conditions associated with urban life (increments in breeding success mainly through predation release, but also the selection of humantolerant phenotypes) can dismantle this relationship, favouring site fidelity and short dispersal movements. This change in breeding dispersal behaviour is likely contributing to the genetic structure detected between three different urban and one panmictic rural populations of burrowing owls, but also between urban cores separated by a few kilometres (Mueller et al. 2018). Our study has been performed using information on breeding dispersal at the individual level, controlling for the lack of independence in these data by including individual as a random term. These individuals, which belong to two separate groups (urban and rural), were compared and differences discussed in the context of changes associated to urban life. It is true that our study has been performed in only one urban-rural pair of populations, which prevent us to emphatically assess that differences in the dispersal patterns of our study units are due to urbanization. However, the contrasted characteristics of both habitats are tightly linked to their degree of urbanization, and differences observed among individuals living in urban and rural areas across the world have shown similar patterns than those obtained here and which have been related to dispersal in the present study (i.e., the bolder behaviour of urban individuals (Evans et al. 2011; Atwell et al. 2012; Miranda et al. 2013; Hardman and Dalesman 2018), the higher conspecific density of urban cores (Marzluff et al. 2001; Chace and Walsh 2006; Rodewald and Shustack 2008; Rodewald et al. 2011), the higher breeding parameters of urban compared to rural populations (Stracey and Robinson 2012) or the colonization of urban areas from a pool of rural individuals (Evans et al. 2009; Miranda et al. 2013). Thus, it is very likely that the dispersal patterns described here can be extended to other urban-rural areas. Further research, Breeding dispersal in urban and rural owls 141 however, is needed to make stronger generalizations to properly understand the ecological and evolutionary consequences of these differences in dispersal between urban and rural birds and its implications for population structuring and gene flow between urban and rural populations. References Atwell JW, Cardoso GC, Whittaker DJ, Campbell-Nelson S, Robertson KW, Ketterson ED. Boldness behavior and stress physiology in a novel urban environment suggest rapid correlated evolutionary adaptation. Behav Ecol. 2012; 23, 960–969. doi: 10.1093/beheco/ars059. Barton K. MuMIn: Multi-Model Inference. R package version 1.40.0. 2017. https://CRAN.R-project.org/package=MuMIn. Bowler DE, Benton TG. Causes and consequences of animal dispersal strategies: relating individual behaviour to spatial dynamics. Biol Rev. 2005; 80, 205-225. doi: 10.1017/S1464793104006645. Burnham KP, Anderson DR. Model selection and multimodel inference. A practical information-theoretic approach. (New York, Springer-Verlag, 2002). doi: 10.1007/978- 1-4757-2917-7_3. Carrete M, Tella JL. Individual consistency in flight initiation distances in burrowing owls: a new hypothesis on disturbance-induced habitat selection. Biol Lett. 2010; 6, 167–170. doi: 10.1098/rsbl.2009.0739. Carrete M, Tella JL. Behavioural correlations associated with fear of humans differ between rural and urban burrowing owls. Front Ecol Evol. 2017; 5, 54. doi: 10.3389/fevo.2017.00054. Carrete M, Tella JL. High individual consistency in fear of humans throughout the adult lifespan of rural and urban burrowing owls. Sci Rep. 2013; 3, 3524. doi: 10.1038/srep03524. Chapter 3 142 Carrete M, Tella JL. Inter-individual variability in fear of humans and relative brain size of the species are related to contemporary urban invasion in birds. PLoS One. 2011; 6, e18859. doi: 10.1371/journal.pone.0018859. Carrete M, Martínez-Padilla J, Rodríguez-Martínez S, Rebolo-Ifrán N, Palma A, Tella JL. Heritability of fear of humans in urban and rural populations of a bird species. Sci Rep. 2016; 6, 31060. doi: 10.1038/srep31060. Chace JF, Walsh JJ. Urban effects on native avifauna: a review. Lands Urban. Plan. 2006; 74, 46–69 (2006). doi: 10.1016/j.landurbplan.2004.08.007 Clobert J, Galliard L, Cote J, Meylan S, Massot M. Informed dispersal, heterogeneity in animal dispersal syndromes and the dynamics of spatially structured populations. Eco Lett. 2009; 12, 197-209. doi: 10.1111/j.1461-0248.2008.01267.x. Cote J, Fogarty S, Tymen B, Sih A, Brodin T. Personality-dependent dispersal cancelled under predation risk. Proc R Soc B. 2013; 280, 20132349. doi: 10.1098/rspb.2013.2349. De Meester N, Bonte D. Information use and density-dependent emigration in an agrobiont spider. Behav Ecol. 2010; 21, 992–998. doi: 10.1093/beheco/arq088. Denoël M, Dalleur S, Langrand E, Besnard A, Cayuela H. Dispersal and alternative breeding site fidelity strategies in an amphibian. Ecography. 2017; 41 (9) 1543-1555. doi: 10.1111/ecog.03296. Dingemanse NJ, Both C, Van Noordwijk AJ, Rutten AL, Drent PJ. Natal dispersal and personalities in great tits (Parus major). Proc R Soc B. 2003; 270, 741-747. doi: 10.1098/rspb.2002.2300. Evans J, Boudreau K, Hyman J. Behavioural syndromes in urban and rural populations of song sparrows. Ethology. 2010; 116, 588–595. doi: 10.1111/j.1439- 0310.2010.01771.x. Breeding dispersal in urban and rural owls 143 Evans KL, Gaston KJ, Frantz AC, Simeoni M, Sharp SP, McGowan A, Dawson DA, Walasz K, Partecke K, Burke T. Independent colonization of multiple urban centres by a f formerly forest specialist bird species. Proc R Soc B. 2009; 276, 2403-2410. doi: 10.1098/rspb.2008.1712. Fogarty S, Cote J, Sih A. Social personality polymorphism and the spread of invasive species: a model. Am Nat.2011; 177, 273–287. doi: 10.1086/658174. Forero MG, Donázar JA, Blas J, Hiraldo F. Causes and consequences of territory change and breeding dispersal distance in the black kite. Ecology. 1999; 80, 1298-1310. doi: 10.2307/177076. Fraser DF, Gilliam JF, Daley MJ, Le AN, Skalski GT. Explaining leptokurtic movement distributions: intrapopulation variation in boldness and exploration. Am Nat. 2001; 158, 124-135. doi: 10.1086/321307. Ganey JL. Apprill DL, Rawlinson TA, Kyle SC, Jonnes RS, Ward J JP. Breeding dispersal of Mexican spotted owls in the Sacramento Mountains, New Mexico. Wilson J Ornithol. 2014; 126, 516-524. doi: 10.1676/14-004.1 Greenwood PL, Harvey PH. The natal and breeding dispersal of birds. Annu Rev Ecol Syst. 1982; 1, 1-21. www.jstor.org/stable/2097060. Grueber CE, Nakagawa S, Laws RJ, Jamieson IG. Multimodel inference in ecology and evolution: challenges and solutions. J Evol Biol. 2011; 24 (4), 699-711. doi: 10.1111/j.1420-9101.2010.02210. x. Hammill E, Fitzjohn RG, Srivastava DS. Conspecific density modulates the effect of predation on dispersal rates. Oecologia. 2015; 178, 1149-1158. doi: 10.1007/s00442- 015-3303-9. Hardman SI, Dalesman S. Repeatability and degree of territorial aggression differs among urban and rural great tits (Parus major). Sci Rep. 2018; 8,5042. doi: 10.1038/s41598-018-23463-7. Chapter 3 144 Harris S, Ramnarine IW, Smith HG, Pettersson LB. Picking personalities apart: estimating the influence of predation, sex and body size on boldness in the guppy Poecilia reticulata. Oikos. 2010; 119, 1711–1718. doi: 10.1111/j.1600- 0706.2010.18028. x. Jones KA, Godin JGJ. Are fast explorers slow reactors? Linking personality type and anti-predator behaviour. Proc R Soc B. 2009; 277, 625–632. Léna JP, Clobert J, de Fraipont M, Lecomte J, Guyot G. The relative influence of density and kinship on dispersal in the common lizard. Behav Ecol. 1998; 9, 500–507. doi: 10.1093/beheco/9.5.500. Lin T, Coppack T, Lin QX, Kulemeyer C, Schmidt A, Behm H, Luo T. Does avian flight initiation distance indicate tolerance towards urban disturbance? Ecol Indic. 2012; 15 30–35. doi: 10.1016/j.ecolind.2011.09.018. Marzluff JM, Bowman R, Donnelly R. Avian ecology and conservation. A historical perspective on urban bird research: trends, terms, and approaches. Kluwer Academic Publishers, Norwell, MA. pp. 1–17 (2001). doi: 10.1007/978-1-4615-1531-9_1. Marzluff JM, DeLap JH, Oleyar MD, Whittaker KA, Gardner B. Breeding dispersal by birds in a dynamic urban ecosystem. PLoS One. 2016; 11, e0167829. doi: 10.1371/journal.pone.0167829. Miranda AC, Schielzeth H, Sonntag T, Partecke J. Urbanization and its effects on personality traits: a result of microevolution or phenotypic plasticity? Glob Change Biol. 2013; 19 (9), 2634-2644. doi: 10.1111/gcb.12258. Møller AP, Garamszegi LZ. Between individual variation in risk-taking behavior and its life history consequences. Behav Ecol. 2012; 23, 843-853. doi: 10.1093/beheco/ars040. Møller AP, Díaz M, Flensted-Jensen E, Grim T, Ibáñez-Álamo JD, Jokimäki J, Mänd R, Markó G, Tryjanowski P. High urban population density of birds reflects their timing of urbanization. Oecologia. 2012; 170, 867-875. doi: 10.1007/s00442-012-2355-3. Breeding dispersal in urban and rural owls 145 Mueller JC, Kuhl H, Boerno S, Tella JL, Carrete M, Kempenaers B. Evolution of genomic variation in the burrowing owl in response to recent colonization of urban areas. Proc R Soc B . 2018; 285, 20180206. doi: 10.1098/rspb.2018.0206. Nakagawa S, Schielzeth H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol Evol. 2012; 4, 133–142. doi: 10.1111/j.2041-210x.2012.00261.x. Newton I, Marquiss M. Fidelity to breeding area and mate in sparrowhawks Accipiter nisus. J Anim Ecol. 1982; 51, 327-341. doi: 10.2307/4327. Pasinelli G, Müller M, Schaub M, Jenni L. Possible causes and consequences of philopatry and breeding dispersal in red-backed shrikes Lanius collurio. Behav Ecol Sociobiol. 2008; 61, 1061-1074. doi: 10.1007/s00265-006-0339-1. Payo-Payo A, Genovart M, Sanz-Aguilar A, Greño JL, García-Tarrasón M, Bertolero A, Piccardo J, Oro D. Colonisation in social species: the importance of breeding experience for dispersal in overcoming information barriers. Sci Rep. 2017; 7, 42866. doi: 10.1038/srep42866. Payo-Payo A, Sanz-Aguilar A, Genovart M, Bertolero A, Piccardo J, Camps D, Ruiz-Olmo J, Oro D. Predator arrival elicits differential dispersal, change in age structure and reproductive performance in a prey population. Sci Rep. 2018; 8, 1971. doi: 10.1038/s41598-018-20333-0. R Development Core Team R. A language and environment for statistical computing. 2008.http://www.R-project.org Rebolo-Ifrán N, Carrete M, Sanz-aguilar A, Rodríguez-Martínez S. Links between fear of humans, stress and survival support a non-random distribution of birds among urban and rural habitats. Sci Rep. 2015; 5, 13723. doi: 10.1038/srep13723 Chapter 3 146 Rebolo-Ifrán N, Tella JL, Carrete M. Urban conservation hotspots: predation release allows the grassland-specialist burrowing owl to perform better in the city. Sci Rep. 2017; 7, 3527. doi: 10.1038/s41598-017-03853-z. Rodewald AD, Shustack DP. Urban flight: understanding individual and population-level responses of Nearctic-Neotropical migratory birds to urbanization. J Anim Ecol.2008; 77, 83–91.doi: 10.1111/j.1365-2656.2007.01313.x. Rodewald AD,Kearns LJ, Shustack DP. Anthropogenic resource subsidies decouple predator-prey relationships. Ecol Appl.2011; 21, 936–943. doi: 10.1890/10-0863.1. Rodriguez-Martínez S, Carrete M, Roques S, Rebolo-Ifrán N, Tella JL. High urban breeding densities do not disrupt genetic monogamy in a bird species. PLoS One. 2014; 9, e91314. doi: 10.1371/journal.pone.0091314. Serrano D, Tella JL, Forero MG, Donázar JA. Factors affecting breeding dispersal in the facultatively colonial lesser kestrel: individual experience vs. conspecific cues. J Anim Ecol. 2001; 70, 568-578. doi: 10.1046/j.1365-2656.2001.00512.x. Sih A, Bell A, Johnson JC. Behavioural syndromes: an ecological and evolutionary overview. Trends Ecol Evol. 2004; 19, 372–377. doi: 10.1016/j.tree.2004.04.009. Sih A, Cote J, Evans M, Fogarty S, Pruitt J. Ecological implications of behavioural syndromes. Ecol Lett. 2012; 15, 278–289. doi: 10.1111/j.1461-0248.2011.01731.x. Sol D, González‐Lagos C, Moreira D, Maspons J, Lapiedra O. Urbanisation tolerance and the loss of avian diversity. Ecol Lett. 2014; 17, 942-950. doi: 10.1111/ele.12297. Stracey CM, Robinson SK. Are urban habitats ecological traps for a native songbird? Season-long productivity, apparent survival, and site fidelity in urban and rural habitats. J Avian Biol. 2012; 43, 50–60. doi: 10.1111/j.1600-048X.2011.05520.x. Tucker MA, Böhning-Gaese K, Fagan WF, Fryxell JM, Van Moorter B, Alberts SC, ... Bartlam-Brooks H. Moving in the Anthropocene: Global reductions in terrestrial mammalian movements. Science. 2018¸ 359, 466-469. doi: 10.1126/science.aam97 III| Appendix