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CO-SUPERVISION AGREEMENT

This PhD thesis was developed in co-supervision with Prof. Mauro Galetti, from the Ecology Department of the São Paulo State University UNESP, Brazil, following the agreement established accordingly with the UNESP Resolutions 68/08 and 62/12.

Esta tese de doutorado foi realizada em co-orientação com o Prof. Mauro Galetti, do Departamento de Ecologia da Universidade Estadual Paulista UNESP, Brasil, seguindo a convenção de co-tutela estabelecida nos termos das Resoluções UNESP 68/08 e 62/12.

Questa tesi di dottorato è stata realizzata in co-tutela con il Prof. Mauro Galetti, del dipartimento di Ecologia della Università Statale Paolista UNESP, Brasile, seguendo la convenzione di co-tutela stabilita nei termini delle Risoluzioni UNESP 68/08 e 62/12.

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Table of contents

General introduction 1 General objective 2 Study site 3 CHAPTER 1 5 Complex spatio-temporal patterns generated in an intense Mediterranean woody secondary succession: the role of past legacies 5 CHAPTER 2 31 Functional complementarity between mammals and birds as seed dispersers in a Mediterranean woodland pasture 31 CHAPTER 3 55 Natural regeneration is more effective than planted trees in concentrating seed rain and promoting recruitment in a dynamic Mediterranean woodland pasture 55 Conclusions 86 Resumo geral em português 87 Acknowledgements 91

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General introduction

GENERAL INTRODUCTION

Intensive and extensive human occupation has changed the spatial distribution and composition of the natural vegetation worldwide. However, in recent years, many formerly used lands have been abandoned, reforested, rewilded and again disturbed, creating different templates and trajectories for the evolution of secondary succession. Whether these trajectories will lead to an ecologically restored state, deviate and stabilize in an alternative state or regress to a degraded state are key issues for biodiversity conservation. A starting point to disentangle which factors and mechanisms are leading to these different templates is understand the patterns they generate, in regional, landscape and local spatial scales. In addition, the temporal scale is a very relevant component, many times required, as it will reflect the footprints left by past events, bringing back the history and giving cues to assess the ecological memory and resilience capacity of a determined site. When analyzing how fast and wide the vegetation expanded and how spatially structured this expansion was, a further question that emerge is how sessile plants are able to move, colonize new areas and ultimately generate the observed patterns. Even if some plants can expand through a spatially constrained vegetative growth, most of the pattern is fruit of the seed dispersal. While for example wind, water and gravity are important mechanisms, in Mediterranean up to 65% of the plant species rely on several animal species to complete that task. This wide range of plant-animal interactions will inevitably produce both complementary and redundant contributions in generating that vegetation pattern. Birds and mammals have a pivotal role, although few studies have so far compared simultaneously their seed dispersal services at the same spatio-temporal scale. Due to their intrinsic differences in diet, behavior and habitat use, direct comparisons are required to detect whether they are complementary or redundant in performing the seed dispersal service, as this parameters are expected to vary from one site to another due to the natural context-dependency. Notwithstanding, seed dispersal is not the endpoint explaining the observed spatio-temporal pattern, as once dispersed, seeds still have a long journey towards an effective establishment, facing several abiotic and biotic filters. These filters, especially in areas deprived of vegetation, can completely halt the dispersal template, leading to recruitment limitation. The presence of shrubs and trees scattered in these deforested areas greatly contribute to contrast these limitations, acting as hotspots of seeds and recruitment, also called the perch and nurse effect. But different trees should perform differently this role, especially if varying in their potential to attract seed dispersers or protect the recruits. Moreover, once the recruits evolve, they should also take part on that task, a potential facilitation loop that still has to be better understood. Finally, determine whether passive or active restoration are more effective in promoting ecological restoration is far from straightforward, and this thesis is an attempt to shed some light in this issue, while fulfilling some basic gaps in the knowledge of ecological interactions in the largest Mediterranean island.

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General objective

GENERAL OBJECTIVE

The general objective in this thesis was to give both landscape and local scale overview of the patterns and processes behind the woody vegetation dynamics in a gradient forest-woodland pasture considering both passive and active restoration, focusing on a detailed spatio-temporal analysis of the woody vegetation to serve as background to incorporate the role of plant-animal and plant-plant interactions in the vegetation dynamics.

To reach this objective the thesis was divided in three chapters.

In the first chapter we defined the spatio-temporal template through a detailed investigation of the evolution of the woody vegetation cover along the last 24 years. Combining photointerpretation, field sampling and spatial analysis, we reconstructed the historical background, characterizing and quantifying the woody vegetation changes up to the actual template as well as the effective contribution of natural regeneration, planted trees and past vegetation legacies.

In the second chapter we assessed the role of birds and mammals in promoting seed dispersal, the dynamic processes behind plant movement and consequent secondary succession. First we constructed the interaction matrix of birds and mammals with the plants relying on them to have the seeds dispersed, and then we assessed the quantitative and qualitative components of their seed dispersal service, both in the trophic and spatial levels.

In the third chapter we assessed the patterns of the first step towards the colonization of the deforested area, the seed rain, and assessed the final critical step, plant establishment, underneath the trees scattered in the pastureland, revealing the spatial structure of their distributions across the study plots as well as comparing whether different types of trees, including natural regeneration and human planted trees, were more effective in generating these patterns.

Additionally, beyond the main study of this thesis, I participated in other parallel researches concerning the seed dispersal interactions in urban areas and in agroforestry systems, resulting until now in one published and one submitted work, attached at the end of the thesis.

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Study site

STUDY SITE

Our study was conducted inside the “Bosco della Ficuzza, Rocca Busambra, Bosco del Cappelliere e Gorgo del Drago” (hereafter FBCD) natural reserve, a 7.397ha protected area comprising the last large remnant of forest in all western Sicily (Gianguzzi and La Mantia 2004, La Mantia et al. 2010). This reserve has a heterogeneous bioclimatic gradient, from thermo-mediterranean at the lower altitudes (350m a.s.l.) up to supra-meditterranean at the highest elevations (up to 1.613m), with a predominant meso- mediterranean climate (Rivas-Martínez 2008). Inside FBCD, our specific study site was in the Alpe Cucco (37°52' and 13°24'), a woodland pasture of 150 ha surrounded by forest remnants at the center of the Reserve (Figure 1). Alpe Cucco falls in the meso-mediterranean climate, with average rainfall of 850mm and mean annual temperatures of 14.3, with the average temperature of 9.4˚ in the coldest months (January and February) up to an average 23,5 ˚ in the hottest months (July and August). The woody vegetation cover of the forest remnants is characterized mainly by thermophilous evergreen oaks (Quercus ilex and Q. suber), deciduous oaks ( Quercus pubescens ) and to a lesser extent by maple ( Acer campestre) and manna ashes ( Fraxinus ornus ). Hedera helix is also common in the forest. The woodland pasture is composed by a heterogeneous vegetation structure, covered mostly by grasslands, with isolated woody shrubs and trees and varied-sized patches of woody vegetation, composed mostly by fleshy-fruited species (Rosaceae; Pyrus amygdaliformis, Crataegus monogyna, Crataegus laciniata, Rubus ulmifolius, Rosa canina, Prunus spinosa), dry fruited shrubs (Fabaceae; Calicotome infesta, Spartium junceum, Cytisus sp.) . Other fleshy-fruited scrubs or vines, like Asparagus acutifolius , Lonicera sp., Rubia peregrina and Daphne laureola are also present. Around the 1970 and 1980s at Alpe Cucco there was an active reforestation program through the introduction of Fraxinus angustifolia and Pinus halepensis seedlings (Gianguzzi and La Mantia 2004) , two species not occurring naturally there, planted with an irregular pattern at the southern limits of the pasture and practically absent on the northern limit. From the 21 Sicilian non-volant mammals species occurring in the main island just two rodent species ( Glis glis , Muscardinus avellanarius ) are missing at the Ficuzza reserve, while red fox ( Vulpes vulpes ), pine marten ( Martes martes ), weasel ( Mustela nivalis ), wildboar ( Sus scrofa ), fallow deer ( Dama dama ), rabbit ( Oryctolagus cuniculus ), hare ( Lepus corsicanus ), hedgehog ( Erinaceous europaeus ), crested porcupine ( Hystrix cristata ) and wild cat ( Felis silvestris ), as well as small mammals like woodmouse ( Apodemus sylvaticus ), rats ( Rattus sp .), savis’s pine vole ( Arvicola savi ) are occuring (Massa and La Mantia 2007, Vari 2008). At this reserve also occur most of the Sicilian resident and migrant birds species, with the presence of well-known frugivores, like thrushes ( Turdus merula , T. philomelos and T. viscivorus ), warblers ( Sylvia atricapilla , S. communis , S. melanocephala , S. cantillans ) robin ( Erithacus

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Study site rubecula ), redstarts ( Phoenicurus ochrurus , P. phoenicurus ) pigeons ( Columba palumbus , C. livia ), among others (Vari 2008). Livestock raising is a historical activity in FBCD and Alpe Cucco, with grazing permissions dating back to at least the end of 1800 century, while around the 1960, Alpe Cucco was subject of an active pastureland management program, including irrigation, ploughing and seeding, but due to the high costs, any kind of active management was completely abandoned at the beginning of 1990, although nowadays extensive cattle raising is still a permitted activity (A.S.F.D 1959, Bianchetto et al. 2015). At Alpe Cucco, we established three plots of 500x200 m covering the gradient from the continuous forest to the woodland pasture (Figure 1). The plots are separated by at least 300 m and at maximum 510 m. All the plots share the same broad environmental characteristics. The topography has a relatively flat relief with average slope of 10% and no abrupt changes or deep valleys. The maximum altitudinal variation among plots is 190m (880 to 1070m a.s.l.), with an average altitude of 960m. The soil is deep (> 100cm) and characterized as sub-alcaline clay dominated vertic haploxeralfs (Raimondi 1983). These three plots were the sampling units used in all the three chapters.

(a) (b)

(c) (d) 3 3

2 1

2 1

Figure 1. (a) Location of the Ficuzza Natural Reserve in Sicily (black spot), (b) forest remnant inside the reserve, (c) the three 500x200m study plots established at Alpe Cucco woodland pasture with the unpaved roads (soft linear developments) at the surroundings and (d) aerial image of 1955 showing the long term deforestation.

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Chapter 1

CHAPTER 1

Complex spatio-temporal patterns generated in an intense Mediterranean woody secondary succession: the role of past legacies

Abstract

In recent years, many Mediterranean agricultural lands have been abandoned, reforested, rewilded and ecologically restored, creating different templates and trajectories for the development of secondary succession. Here our objective was to verify how fast and intense was woody vegetation recovery and whether past legacies of woody vegetation (remnant forest, shrub patches and reforestations) influenced the current spatial pattern of woody cover in a mid-successional Mediterranean area. The study took place in three 500x200 m plots in a formerly managed and partially reforested pastureland in the Ficuzza Natural Reserve (Palermo, PA), the last large forest remnant in western Sicily. We sampled woodland and shrubland cover over a 24-year interval (from abandonment to the present), by combining current field sampling and a GIS-based interpretation of sequential high resolution satellite images and aerial photographs. The overall woody vegetation cover almost doubled through the studied period, with a balanced increase of woodland and shrubland patches. Fraxinus angustifolia reforestation contributed marginally to woodland expansion, while the major increase was due to the natural regeneration consisted mainly of five fleshy-fruited species dispersed by birds and mammals and one dry-fruited species, all of them well protected against herbivory. In two plots the woody cover expansion was correlated with initial cover, although some hotspots presented 100% of cover increase from bare areas even further than 100 m away from any woody patch. Distance from the forest was not significant, and the distance to nearest woodland patch was only at plot 2. Our results reveals that the composition and spatial configuration of past vegetation legacies can influence the secondary succession evolution. Natural regeneration contributed most, although human-made reforestation also increased the cover. Even in presence of herbivory, the vegetation greatly expanded, probably due to the absence of fire and the favorable forested landscape. We set a template for further investigations regarding mechanisms and functional traits driving these patterns.

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Chapter 1

Introduction

In Mediterranean region, the intensive long human occupation has changed the spatial distribution and composition of the natural vegetation over millennia. However in recent years, many Mediterranean agricultural lands have been abandoned, reforested, naturally rewilded and again disturbed, creating different templates and trajectories for the evolution of secondary succession (Debussche and Lepart 1992, Baeza et al. 2007, Navarro and Pereira 2012, Ceausu et al. 2015). Determine whether these different templates will lead to an ecologically restored state, deviate and stabilize in an alternative state or regress to a degraded state, as well as how fast and intense will this processes occur are definitively very complex tasks that require regional and detailed local scale spatio- temporal analysis of patterns and processes (Bonet and Pausas 2004, Pueyo and Begueria 2007, Méndez et al. 2008, Gotzenberger et al. 2012, García et al. 2014, Meli et al. 2017). The main issues to be tackled are how fast and intense can the vegetation recover in these abandoned areas, which are the local scale spatial patterns and what are the potential factors influencing this recover and shaping these patterns. There is not much information available from studies that quantified the woody vegetation cover expansion along a chronosequence in Mediterranean, but the values seems to be around 20% to 50% of surface cover after 15-30 years from the abandonment (Ne'eman and Izhaki 1996, Bonet and Pausas 2004, Pueyo and Begueria 2007, La Mantia et al. 2013). However, in many Mediterranean regions there still a large gap on this relatively basic knowledge, as the cover expansion is a context dependent process and have to be evaluated considering for example the different aspects of past land use and current disturbances that may happen in that area (Massa and La Mantia 2007, Valladares and Gianoli 2007, Méndez et al. 2008, Meli et al. 2017). Another aspect where little attention has been devoted is how dynamic and spatially structured this succession can be. These are a relevant information as the pattern is the result of the processes and can reveal important indicators of biodiversity recovery, carbon storage, control of hydrogeological risk areas and others ecosystems services, indicating for example desertification processes or the extinction of ecological interactions, specially under a global change scenario (Kefi et al. 2007, La Mantia et al. 2013, Ceausu et al. 2015). Usually abiotic variables like temperature, rain, elevation or soil Ph are the most common predictors used to answer these questions (Gallego Fernández et al. 2004, Pueyo and Begueria 2007, Reitalu et al. 2009, Martins et al. 2014). However, in local scale studies with topographically and edaphically homogenous areas where generalist plant species are dominant, these variables can be of low concern, as they are expected to not vary significantly in that scale or have low influence on the colonization potential of those plants, what have been found for example regarding tree seedling richness. Considering the situations where influent negative legacies of past land use were inherited (i.e. soil erosion and species extinction), the abundance, diversity and spatial configuration of the remnants 6

Chapter 1 of natural vegetation are the base layer for the succession development, as they will be the template for the spatial resilience and conserve what remains from the “ecological memory” of that site (Méndez et al. 2008, Johnstone et al. 2016). The presence and persistence of the seed bank, vegetative and clonal growth, arrival of new propagules through seed dispersal and further recruitment will in turn transmit the legacies of that ecological memory (Valladares and Gianoli 2007, Méndez et al. 2008, Gómez- Aparicio 2009, Navarro-González et al. 2013, Johnstone et al. 2016, McAlpine et al. 2016). These abovementioned processes are ultimately governed by fragmentation and distance constraints. For example vegetative and clonal growth usually operate through very short distance expansion waves from the extant vegetation, while seed rain, that in Mediterranean is highly dependent on animals, presents a very skewed kernel towards short distances and pre-existent vegetation cover, with rare long distance dispersal (Cain et al. 2000, Garcia et al. 2011, González-Varo et al. 2017, Jordano 2017). Notwithstanding, the generated template can be ultimately reconfigured by natural ecological filters, by human induced filters like reforestation, livestock raising or induced fires or both cases at the same time and space (Jordano and Herrera 1995, Alcántara and Rey 2003, Massa and La Mantia 2007, Meli et al. 2017). The vegetation spatial configuration is the ultimate result, leaving the footprint of each endogenous or exogenous process (Diniz-Filho et al. 2003, Legendre and Legendre 2012, Dale and Fortin 2014). Especially in a temporal analysis, measure these endogenous and exogenous processes, for example those arising from ecological interactions in the past is a very difficult task, while current measurements could not reflect exactly what happened before due to the highly dynamic nature of these interactions. So the few measurable spatial characteristics of the vegetation in the past, like the amount and type of initial cover and distances are the proxies to try to detect, at least partially, the factors shaping the patterns of the vegetation expansion. Here we want to quantify how fast and complex can the secondary succession develop in an Mediterranean montane area, and try to unravel which are the potential driving mechanisms generating the spatio-temporal patterns. Specifically we want to (1) spatially characterize and quantify the woody cover expansion along a 24 years period and (2) analyze whether the amount and type of cover, the distance from the continuous forest and to the nearest woody patch can influence the recovery of the woody vegetation.

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Chapter 1

Methods

Study site

For a complete description see general study site. Each of the three study plots was divided in 160 sub-plots of 25x25m (625m²), and these sub-plots were considered as our sampling units for the spatial analysis (Figure 1).

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2 1

Figure 1. The three 500x200m study plots established at Alpe Cucco and an example of the 160 (625m² ) sub-plots grid delimited inside each plot.

Vegetation mapping and classification

To measure the spatial pattern of woody vegetation cover across years, we created a GIS platform of the study site using a combination of very high resolution (1 pixel = 0,13m) Google Earth™ satellite images from 2016, 2015 and 2014 (http://www.google.com/earth), considered to represent the current habitat, and a 1992 aerial image with scale 1:29000 (1 pixel = 1m), obtained in digital version (800 dpi) from the Italian Military Geographic Institute. The 2016, 2014 and 1992 images were taken in summer, when the annual grasses and forbs are dry and enable a strong contrast with the woody vegetation. The 2015 image was taken in early spring, showing helpful complementary patterns of colors, such as those from flowering trees and deciduous trees without leaves. We studied the dynamic of woody vegetation 8

Chapter 1 over the last 24 years (1992 – 2016), as despite older images are available, the 1992 image was the oldest after the cessation of intense pasture management (G. Giardina, personal communication ), so it represents a conservative option to address vegetation recovery from an early stage of the secondary succession. Accordingly to the oldest aerial image available (1955), the study site was already completely deforested, with just some fragmented forest cover at the eastern (plot 1 and 3) and southern limits (plot 2). All the images were added to the GIS platform within a common UTM grid and were georefereced using the 2016 image as a template. For this procedure, we used fixed and clearly distinguishable ground control points (roads, buildings, large rocks and old trees) widespread through the area, rescaling the images to match the 2016 background (Álvarez-Martínez et al. 2014, García et al. 2014, Xu et al. 2015a). To test the magnitude of the spatial discrepancies among images, we estimated on the GIS linear distances and areas based on control points across images, and cross-checked these measures with GPS-based and direct measurements made in the field. The rescaling procedure allowed to greatly reduce the overlaying error to less than 2.5 meters, and assured that the spatial distances among control points were equal across images. To better quantify the woody vegetation cover, the 2016 image was transformed into a grayscale and resized to the same resolution of the 1992 image (1 pixel – 1m²). Then, from both 1992 and 2016 images, we manually obtained several points of spectral signature to set up threshold values for differentiating woody vegetation from surrounding non woody vegetation. This resulted in a common digital pixel intensity value of <75 for representing the woody cover in both 1992 and 2016 images. After this procedure, we used a raster calculator (QGIS) to create binary images with woody and non-woody pixels. Woody pixels were then transformed into vectors, creating polygons (i.e. patches) of woody vegetation cover. To reduce the potential noises of the images and avoid the mixed pixel problem (Tso 2003), we only considered mapped polygons larger than 3 m² (3 pixels). Our objective was to differentiate three woody cover types: woodlands patches, shrublands patches and isolated trees, shrubs and small nucleation patches of trees or shrubs (hereafter ITSN). Woodlands patches were defined as predominant tree cover >2m in height, with area larger than 50m² represented by heterogeneous dark gray texture (pixel values <40) and producing conspicuous black shadows. The species representing this vegetation type were Quercus pubescens, Quercus ilex, Acer campestris, Pyrus amygdaliformis, Crataegus monogyna, Crataegus laciniata and the planted Fraxinus angustifolia and Pinus halepensis . Shrublands patches were defined where the cover was composed mainly by shrub individuals <2m tall, with area larger than 50m², homogeneous texture, lighter gray pattern respect to woodlands (pixel values 40 – 75) and producing no conspicuous shadow, with or without isolated trees. The main species representing this vegetation type were Rubus ulmifolius , Prunus 9

Chapter 1 spinosa , Rosa canina and Calicotome spinosa. The remaining woody cover with a surface smaller than 50 m² was classified as isolated trees, shrubs and small nucleation patches of trees, shrubs or both (hereafter ITSN). As the spectral signature was not good enough to clearly differentiate the boundaries of woodlands and shrublands that may occur inside the same polygon, we manually trimmed the overall 2016 woody cover separating the different cover types in different polygons, analyzing in a detailed on screen scale of 1:250 and using the non-transformed 2016, 2015 and 2014 images. The same criteria and procedure was adopted with the 1992 image, where the polygons representing each vegetation type were cross checked with the 2016 polygons, allowing to clearly verify false changes due to misinterpretation (Álvarez-Martínez et al. 2014). To validate the mapping all polygons were numbered and checked in the field with the aid of GPS navigation and detailed maps and then the sub-plot cover values of the different vegetation types were obtained (Figure 2). The continuous forest was defined as a single polygon harboring all the dense woodland cover inside the plots that was physically linked to the continuous woodland remnant that surrounds all the Alpe Cucco and is composed predominantly by Quercus ilex and Quercus pubescens. The distances from the continuous forest and to the nearest woodland patch were calculated from the centroid of each sub-plot until the nearest border of the nearest polygon. As we were particularly interested in the patterns of the natural regeneration expansion, we differentiated the natural regeneration cover from that attributable to direct human intervention through plantation. Inside the plots reforestations were made mostly in open areas and exclusively with Fraxinus angustifolia and very few individuals of Pinus halepensis , two species not naturally present in our study site that dominate the canopy cover where planted. We mapped all individuals of these planted species based on their specific shape, color, size and texture using the 2016, 2015 and 2014 images, and checked all mapped individuals in the field. Overlaying the mapped points with the polygons of woody cover we detected those polygons where the planted trees were the unique or the predominant cover (>80%) and classified these polygons as human-induced regeneration.

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Chapter 1

Figure 2. Example of the main steps to classify the woody vegetation cover. (a) Original 1992 aerial image and delimitation of the sampling plot, (b) section of the aerial image, (c) polygons representing woody cover with digital pixel value < 75, (d) final map with cover classified in the different types and continuous forest represented by the large woodland patch.

Data analyses

Spatial structure of the woody vegetation

We were interested in quantifying the global spatial structure (i.e. degree of aggregation or patchiness) of woody vegetation cover across years. For that we used the Spatial Analysis by Distance Index (SADIE) (Perry et al. 1999), a method that provides an aggregation index ( Ia ) based in calculating the distances required to equalize the spatial distribution of any spatially located count data. Values of the index equal to 1 indicate a random spatial distribution in the data, lower than 1 indicate a regular distribution, and higher than 1 represent a clustered (i.e. non-randomly aggregated) pattern, that can be either from low values creating a gap or high values representing a patch (Perry and Dixon 2002). Beyond the global index, SADIE also provide single index values for each count data, in our case the value of the point represented by the centroid of the sub-plot, indicating at the local scale the positive (above average value vi ) or negative (below average value vj ) contribution of each value to the global

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Chapter 1 index as well as the membership of a gap or a patch, that can generally be considered significant when the value is under or above the ± 1.5 value threshold (Perry et al. 1999). We calculated separately the SADIE aggregation indexes of the 1992 and 2016 woody vegetation cover (considering only the natural vegetation in 2016). SADIE methodology also enabled us to quantify the degree of concordance between the global spatial structure of woody vegetation cover over time. For that, we used the spatial association index, Xp , a derivation of SADIE where the aggregation indexes of the two variables at the same point are directly correlated (Winder et al. 2001, Perry and Dixon 2002), in our case the aggregation indexes of the woody cover in 1992 and in 2016 at the centroid of the same sub-plot. On a second step, we excluded the woody cover dominated by planted trees and used the proportional natural regeneration expansion values (hereafter PE), calculated with the formula ( 2016 natural regeneration cover – 1992 cover)/(625 – 1992 cover ), assessing though the magnitude of cover expansion independently of the available space for this expansion, and performed another SADIE analysis specifically to characterize the spatial structure of the PE through the global and local indexes of aggregation ( Ia, vi and vj ), and locate group of sub-plots with low cover increase (coldspots) and group of sub-plots with high cover increase (hotspots). For this analysis we excluded the sub-plots with full cover in 1992 and consequent zero expansion due to lack of space, remaining 155 sub-plots at plot 1 and 152 sub-plots at plot 3, with no changes in plot 2. Once the indexes given by SADIE are continuous and correlated to each other (Winder et al. 2001, Perry and Dixon 2002), we plotted the vi and vj indexes of 1992 and 2016 woody vegetation cover and the vj and vi of the PE in to bi-dimensional contour maps, giving a more comprehensive view of the spatial pattern structure and the location of the coldspots and hotspots. Sadie aggregation index were obtained with SadieShell 2.0 and the spatial association was calculated with N_AShell 1.0 (Perry et al. 1999). Contour maps were done using the plugin contour of the software QGIS.

Factors affecting the vegetation expansion

We sought to assess whether the initial cover of woody vegetation and its spatial configuration were affecting the woody vegetation expansion at the subplot scale across the 24 years. Thus, we related PE with the amount of woody vegetation cover in 1992 in the subplot, the distance to the continuous forest and the distance to the nearest woody patch (> 50m²) from the centroid of the sub- plot. As our objective was to evaluate the factors acting on the vegetation expansion only, we excluded other than those with full cover in 1992 also those where the proportions were negative (cover retreatment), resulting in 145 sub-plots in plot 1, 152 in plot 2 and 152 in plot 3. To avoid bias in the regression models, the response variable PE was square root transformed to achieve normality and

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Chapter 1 reduce heteroscedasticity and all models were performed for each plot independently. As a qualitative predictor, we also included the predominant cover type (> 70% of the sub-plot cover), classified as 0 if there was no cover, 1 for ITSN, 2 for shrubland, 3 for mixed cover (2 or more types in the same sub-plot) and 4 for woodlands). Before running the analysis for each plot we tested the collinearity of the predictors using Pearson correlation and all predictors presented r < 0.63. We didn’t included commonly used environmental predictors like altitude, topography and soil characteristics because all plant species composing the bulk of the expansion, from shrubs to trees are present across all plots, then we assume that the eventual local scale variance of these abiotic factors are not significant for the purpose of our study. The three continuous predictors were standardized prior to the analysis. As our data was sampled on contiguous sub-plots and vegetation expansion often present a contagious pattern, we tested the dependent variable and the residuals of the models for spatial autocorrelation, as this constraint can bias the results of the regression models and violate the condition of spatial independency in the errors (Dormann et al. 2007). To assess the spatial autocorrelation of the dependent variable, we calculated the Moran’s I index with different row standardized distance classes of neighbors, departing from 36m, which includes all the immediate surrounding neighbors (borders and vertex first order) and the consequent orders of neighbors at each 36m distance classes until no more spatial autocorrelation was found. After this procedure, we performed non-spatial OLS regressions and tested for the presence of spatial autocorrelation in the residuals using Moran’s I. In the presence of autocorrelation, we then run both Spatial Autoregressive Lag and Error Models (SARlag or SARerror), enabling the regression analysis by taking in to account the spatial autocorrelation in the data through a weight matrix that incorporates, other than the value at a given sub-plot, also the neighborhood values of that location (SARlag) or of the errors (SARerr). These SAR models have been demonstrated to perform well in comparison to other methodologies (Keitt et al. 2002, Dormann et al. 2007, Kissling and Carl 2008, Beale et al. 2010). The best model was selected based on lowest AICc, highest log-likelihood values, minimum residual spatial autocorrelation and model fit (pseudo-R²). All the spatial tests and regressions were performed with GEODA 1.8 (Anselin et al. 2006).

Results

In the last 24 years, the overall cover of woody vegetation increased 90.1%, from 7.57 ha to 14.39 ha, shifting from 25.2% to 47.9% of the total study surface, respectively. However, 1.66 ha (11.5%) of the actual cover was the result of human reforestation with Fraxinus angustifolia and Pinus halepensis ,

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Chapter 1 concentrated mainly on plot 1 (24.1% of the actual cover) and plot 2 (11.3% of actual cover), with low influence on plot 3 (0.01%). We found no correlation between current cover of human-induced woody vegetation and initial woody cover in 1992 (Pearson r = 0.003, p > 0.05), suggesting that the planted cover developed almost exclusively throughout the 24 years period, independently of early woody cover. Excluding the areas covered with planted trees, the total natural regeneration cover increased 68.17%, spreading over 12.73ha or 42.4% of the total study surface. There was significant difference of the average cover increase among plots (ANOVA F = 56.61, p < 0.001), where plots 2 and 3 presented very high rate of increase in the cover of woody vegetation, with 75.90% and 84.58% respectively, while at plot 1 the woody vegetation cover increased about half in comparison with the other plots (38.41%). Woodland was the main type of woody vegetation in this expansion, contributing to the increase with 55.23% (2.85ha), followed by shrublands with 41.93% (2.16 ha), while the ITSN contributed with 2.84% (0.16ha). However, proportionally, shrublands presented the greatest expansion in relation to the initial shrubland cover, almost doubling the surface (94.92%), especially in Plot 3 (Table 1). All three plots differed on the principal vegetation type proportional increase (ex: shrubland increase respect to initial shrubland cover). At plot 1 the ITSN was by far the main type with 94.47%, at plot 2 woodlands was the main type with 158.48% and at plot 3 shrublands patches increased 189.5% regarding the initial shrubland cover (Figure 3). The only case of regression was the ITSN in plot 2 with - 48.37%, as the initial configuration of the vegetation with several widespread small patches favored the aggregation in to larger patches.

Table 1. Woodlands, shrublands and ITSN natural cover (hectares) at each plot and the total percentage increase of each vegetation type across the 24 years.

1992 2016

P1 P2 P3 P1 P2 P3 % Increase

Woodlands 1.572 1.203 1.473 2.027 3.109 1.961 67.08 Shrublands 0.412 1.185 0.682 0.637 1.832 1.974 94.92 ITSN 0.146 0.595 0.300 0.285 0.307 0.595 14.04 Total 2.131 2.983 2.454 2.949 5.248 4.530 68.17

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Chapter 1

Spatio-temporal woody vegetation structural variation The SADIE analysis indicate a highly aggregated pattern in the spatial structure of woody vegetation cover in both 1992 and 2016, with a general slight reduction of clusters of low values and a discrete increase of clusters with random patterns in the actual cover respect the initial cover pattern. Plot 1 and 2 showed quite similar values of spatial structuration with a positive 0.2 and a negative 0.04 variation in the index, while plot 2 presented a reduction of 0.53 in the aggregation index (Table 2). The values of SADIE-based association index ( Xp ) suggested strong concordance across years in the global spatial patterns of woody vegetation cover in all plots, and the spatial association was matched in both clusters of low and high cover values (Table 2, Figure 4).

250 Woodlands Shrublands ITSN

200

150

100

50 % cover change % cover

0

-50 P1 P2 P3 Figure 3. Percentage of woodland, shrubland and isolated trees, shrubs and small nucleation patches (ITSN) cover change at each plot over the 24 years period.

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Table 2. SADIE index of aggregation ( Ia ) describing the spatial structure of the 1992 cover, 2016 natural cover and proportional expansion (PE) of natural cover and the spatial association index ( Xp ) describing the degree of association of the spatial structure of the 1992 cover with the 2016 natural cover among the study plots, with their respective significance levels (*** P < 0.001, ** p = 0.003).

Ia Xp PLOT 1992 2016 PE 1992x2016

1 5.69*** 5.89*** 4.25*** 0.89***

2 4.42*** 4.38*** 3.91*** 0.65***

3 5.72*** 5.19*** 2.76** 0.79***

The global PE spatial structure was positive for clustering at all plots, despite in a decreasing rate from plot 1 to 3 and with a lower degree of aggregation related to the cover pattern found in 1992 and 2016. (Table 2). The global spatial structuration of PE is represented in each plot by the different gradients reached by vi and vj values in each sub-plot, with plot 1 and 2 presenting both positive (patch) and negative (gaps) values ranging from -10 to 10 and -9 to 10, respectively. At plot 3 the relatively lower aggregated pattern is expressed by the lowest amplitude of vi and vj values, ranging from -7 up to 7. In all plots is possible to see a complex pattern dominated by small and to a lesser extent medium clusters, with no clear signal of broad gradient-like spatial structure from the continuous forest towards open areas (Figure 5).

Spatial autocorrelation and regression model selection

From OLS and SAR models, the SAR showed the best fit for the data in all plots considering the lowest value of AICc, highest value of log-likelihood and the higher pseudo-R² (Table 3). The spatial autocorrelation in the residuals of the OLS regressions was lower than that found on the raw PE, although was significantly present in a decreasing scale from the first order up to be non significant at the 3 rd order neighbors for plots 1 and 3, and in the 4 th order in plot 2, while SARlag only eliminated the autocorrelation in plot 3. SARerr models instead were able to completely eliminate the autocorrelation at the first order neighbor for plots 1 and 3 and second order neighbor for plot 2 (p > 0.05 in all cases) (Table 3). Considering the best fit of the model parameters, we selected the SARerr model with 1 st order neighbor matrix for plot 1 and 3 and 2 nd order for plot 2 for consequent analysis.

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Figure 4. Contour maps showing the SADIE aggregation indexes of the 1992 woody cover and 2016 natural regeneration woody cover at plots 1, 2 and 3. The different values of the legend shows the specific sub-plot minimum and maximum vi and vj values.

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1 2 3

Figure 5. Contour maps showing the SADIE aggregation indexes of the proportional woody natural regeneration expansion (PE) at at plots 1, 2 and 3. The different values of the legend shows the specific sub-plot minimum and maximum vi and vj values.

Drivers affecting the vegetation expansion

The SARerr pseudo-R² values indicate that the models explained 63% of the variation in the PE in plot 1, 67% in plot 2 and 29% in plot 3 while all three plots differed in the combination of predictors that were significant. The initial woody cover was highly significant and positively affecting PE in plots 1 and 2 (p < 0.001), with a clear increasing probability of cover expansion in a single m² as the initial cover increases (Table 4). However at plot 3, even if this general increasing probability trend was also observed, the initial cover resulted to be non-significant (p = 0.33), suggesting that at plot 1 and 2 radiation expansion from the past cover is an important mechanism, while in plot 3, located just a few hundred of meters away, this seems to be not the main expansion mechanism. The higher probability of fulfillment of each m² in sub-plots with high initial cover (> 500m²) is demonstrated as only 7 from 33 of these sub-plots didn’t reached more than 600m² in 2016, although only 3 reached the full cover. Contrary to our expectative, the distance to the continuous forest presented no kind of relationship with the vegetation expansion. For plot 2, despite non significant, there is a weak sign of a negative relationship as it should be expected, but at the other plots the distance from the forest seems to be a

18

Chapter 1 completely random factor. At shorter distances (< 50m) there is a decreasing trend in vegetation expansion in all plots, continuing decreasing up to 200 m for plot 2 and 3, but as the distance increases the pattern became irregular, probably where the overall woody spatial configuration became more influent. This total lack of relationship can be represented by the greatest proportional expansion registered among all plots, occurred in sub-plots more than 230m away from the continuous forest.

Table 3. Parameters used for the model selection and comparison between non spatial OLS, SARlag and SARerr regression using the 1 st order neighbor matrix for plots 1 and 3 and 2 nd order for plot 2. Squared root proportional expansion (PE) is the response variable, while 1992 cover, distance to continuous forest, nearest woody patch and cover type are the predictors. Residuals Moran’s I p values higher than 0.05 indicate non significant spatial autocorrelation.

Log - Moran's I Model R² AICc P Likelihood Residuals OLS 0.58 -134.63 72.31 0.12 0.001 PLOT1 SARlag 0.6 -137.3 74.64 0.1 0.001 N = 145 SARerr 0.61 -140.59 75.29 -0.04 0.18

OLS 0.46 -104.84 57.42 0.39 < 0.001 PLOT 2 SARlag 0.59 -139.29 75.64 0.07 0.005 N = 152 SARerr 0.62 -150.65 80.32 -0.02 0.23

OLS 0.14 -41.75 25.87 0.16 < 0.001 PLOT 3 SARlag 0.23 -52.34 32.17 0.04 0.14 N = 152 SARerr 0.24 -55.34 32.67 0.04 0.14

Despite the distance to the nearest woody patch presented negative coefficients in all plots, confirming the general trend that as distance increases the probability of PE decreases, this predictor was significant just for plot 2 (p < 0.001). For plot 1 the effect was marginally significant (p = 0.07), but at plot 3 there was no effect (p = 0.75), suggesting that at this plot the mechanisms promoting vegetation expansion are not closely linked to short distances dispersal mechanisms. The qualitative component of the woody vegetation, represented by the cover type of the initial cover also demonstrated to be not relevant for the amount of PE in all plots, suggesting that all physiognomies have equal probability in promoting or not the colonization of new areas, even if an increasing expansion rate across the successional gradient from no cover up to woodlands was observed.

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The spatial autoregressive parameter Lambda presented highly significant values in all plots (p < 0.003 in all cases), . These values indicate a strong autocorrelation in PE under small scales, suggesting that other factors not measure here, like for example nucleation processes and contagious seed dispersal are playing a key role in the sub-plot and in their neighbors independently of the vegetation cover, type and distance effects.

Table 4. Summary of the results of the SARerr model using the 1 st order neighbor matrix for plots 1 and 3 and 2 nd order for plot 2. In bold the variables with significant p values (< 0.05).

Predictor Coefficient Std.Error z-value P

CONSTANT 0.337 0.031 10.898 < 0.001

Woody Cover 0.124 0.028 4.479 < 0.001

Distance continuous -0.004 0.030 -0.139 0.889 PLOT 1 Near woody patch -0.051 0.028 -1.825 0.068

Cover type 0.019 0.016 1.142 0.254

LAMBDA 0.345 0.117 2.947 0.003

CONSTANT 0.612 0.067 9.132 < 0.001

Woody Cover 0.077 0.019 4.138 < 0.001

Distance continuous -0.037 0.048 -0.780 0.436 PLOT 2 Near woody patch -0.068 0.020 -3.376 0.001

Cover type -0.008 0.016 -0.516 0.606

LAMBDA 0.800 0.082 9.708 < 0.001

CONSTANT 0.485 0.053 9.080 < 0.001

Woody Cover 0.054 0.039 1.376 0.169

Distance continuous -0.008 0.037 -0.209 0.835 PLOT 3 Near woody patch -0.010 0.032 -0.314 0.753

Cover type 0.018 0.023 0.761 0.447

LAMBDA 0.445 0.109 4.101 < 0.001

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Discussion Our study revealed that with the combination of active and passive restoration, in just 24 years the woody cover almost doubled in extension, even in a site with long history of land use, deforestation and in the presence of extensive grazing by domestic and wild animals. The natural regeneration was very effective in this process, evolving in a highly complex spatial structuration although no substantial changes in the global and local woody cover patterns were found. At our study site we just partially identify the factors leading and shaping the expansion, as the influence of common measurable predictors like vegetation cover type and distance to the forest, despite following an expected trend, revealed to be non-significant and the effects of the initial vegetation cover and the distance to the nearest woody patch varied even considering the relative small distances among the study plots. The natural regeneration alone was responsible for most of the total cover increase, represented mainly by woodlands and shrublands patches. While shrublands are the pioneer physiognomy that colonizes the empty spaces, woodlands were originated in two ways. One following the natural evolution from shrublands, and the other by direct establishment of arboreal individuals (e.g. Pyrus ), a sort of shortcut of the succession process composed mostly by mid-successional species. This high rate of woody natural regeneration in a Mediterranean area almost totally deforested and extensively used at least during the last 80 years seems impressive. We haven’t found studies with similar scale, land use history and disturbance level, especially long-term absence of fire, to directly compare our results. Although for example La Mantia et al. (2008), found that in the range of 16-30 years the overall woody cover increased on average 57% in north facing slopes and 32% in south facing slopes at the abandoned terraces located in Pantelleria Island in Sicily. Pueyo and Begueria (2007) analyzed the natural regeneration succession in a formerly cultivated colder and wetter montane area in Spain, and verified that in the first (non-defined) time lag, 56% and 6% of the abandoned surface evolved towards shrublands and woodlands, while at the following 20 years only 11% and 9% followed the same path. Their study encompassed a regional scale, although few information regarding the abundance and composition of the woody vegetation responsible for that regeneration is available. Ne'eman and Izhaki (1996), in a study evaluating the secondary succession in an abandoned 1 ha vineyard in Israel found that the cover of perennial woody plants achieved and maintained 82% within the vine rows and reached 21% and 50% between the vine rows after 15 and 35 years after abandonment, respectively. However, the perennial species responsible for that cover were Pistacia lentiscus , Pistacia palaestina and Rhamnus alaternus , species that have faster growth rate and achieve smaller dimensions respect to the species found in our study site. Bonet and Pausas (2004) evaluated the vegetation cover increase in abandoned terraces in a semi-arid region in Spain, and found that the woody vegetation cover increased on average 26.4% after 60 years, and less than 20% of that cover was made from endozoochoric species, 21

Chapter 1 while in our site most of the species are dispersed by animals. The climate at their site is more severe, with about half the precipitation, but also the woody species are smaller and growth relatively faster. Surprisingly, the high vegetation expansion in our study site occurred in the constant presence of grazing by cattle. Despite some neutral effects of grazing by cattle on the development of shrubland- dominated woody vegetation is reported (Bashan and Bar-Massada 2017), usually grazing and browsing poses several constraints for regeneration of woodlands (Garcia and Obeso 2003, Massa and La Mantia 2007, Smit et al. 2010, La Mantia et al. 2013, Laskurain et al. 2013, Bianchetto et al. 2015). In our site there is no information regarding the density and consequent carrying capacity for the livestock (Bianchetto et al. 2015), but probably this growth was enabled by the combination of two important factors. One is the immersion inside a large high biodiversity forest remnant. The second is the absence of human-provoked fires, creating though an optimal opportunity to assess the potential of recovery of these typical Mediterranean vegetation under a silvo-pastoral condition. Even if our study plots were separated by no more than 500m, significant differences were found in the quantitative and qualitative aspects of the vegetation expansion, especially between plot 1 and 3. These two plots had practically the same amount of initial cover arranged in quite similar spatial configuration, but plot 1 had 38% of increase dominated by isolated trees, shrubs and small nucleation patches while plot 3 had more than 84% increase largely dominated by shrublands. This finding highlight the importance of fine scale studies to detect how variable the succession process can develop in practically equal initial conditions, as well as to encourage future studies to disentangle the mechanism behind this variations. The human induced reforestation also contributed directly for the cover expansion through the growth of the planted individuals. However further investigation have to be done to assess the effectiveness of this reforestation in favoring the secondary succession, as for example, the planted species growth faster than natural regeneration ones, a positive characteristic to cover quickly the soil, although they also overcome the natural regeneration species becoming the dominant canopy layer, and are less effective in favoring spontaneous seedlings recruitment (see chapter 3).

Spatial structure of the vegetation cover and expansion The SADIE analysis demonstrated that the global and local spatial structure of the woody vegetation cover didn’t changed across time, maintaining almost exactly the clumped pattern existing in 1992. This is an expected pattern considering a scenario where short-scale diffusion and radiation mechanisms are predominant, but it is interesting that this pattern was maintained even with a very high cover expansion. At plot 1 and 2 the vegetation expansion presented a highly aggregated pattern, as should be also expected, despite in a lower degree regarding the total vegetation cover clumpiness. Nevertheless, at plot 3, where the cover almost doubled, there was also the lowest global and local 22

Chapter 1 aggregation index. This pattern probably emerged from the predominance of scattered small patches dominated by shrublands as well as a great increase of isolated individuals. Why and how the vegetation in plot 3 developed this contrasting pattern been so close to other plots, under the same initial condition and with the same pool of species is an interesting question to be addressed. Some potential explanations can arise with an analysis of community assembly differentiating the contribution of each key species, as for example Prunus spinosa and Rubus ulmifolius tend to have a contagious diffusion from pre-existing patches (Bakker et al. 2004), while Pyrus individuals can have both contagious or scattered dispersal, irrespective of the initial vegetation configuration (Fedriani et al. 2010). The high association of clusters with low PE values at the cells far from the continuous forest demonstrates that these areas are permanent coldspots, with probably some kind of dispersal or recruitment limitation acting in that scale, becoming consequently priority areas for active restoration. Contrary, the higher spatial association of high PE clusters concentrated close to the forest demonstrates that expansion through radiation was a constant over time. In a study realized in Israel, Seifan and Kadmon (2006) found that grazing by cattle changed the spatial pattern of a dominant shrub specie much earlier than any change in overall cover was detected. In our case we found the contrary, the aggregation indexes and the association indexes indicated that the overall spatial pattern of the woody vegetation found in 1992 remained relatively unchanged, even if the natural regeneration cover expanded more than 68%. However future investigations considering the patterns of single species, as they did in their study, should reveal different patterns than that found at our community level study.

Pre-existing spatial patterns as determinants of current expansion

Our model analysis corroborated the fact that the effects of spatial autocorrelation have to be considered in spatial analysis, and SAR models are effective in accounting for this issue, especially SAR error models, that were the best in accordance with a comparison made by Kissling & Carl (2008). The analysis of the spatial structure revealed some expected and many unexpected results. The pre-existent woody cover, the potentially most influent factor as a proxy of the ecological resilience and the ecological memory of the vegetation, positively influenced vegetation expansion in plot 1 and 2, as should be expected. However, again at plot 3 the presence of vegetation seems to be not relevant, as some sub-plots with high initial cover presented very low expansion (coldspots), but specially others with no or very low cover presented very high expansion (hotspots), as the two large patches located at the western extreme of the plot. Despite the general trend of positive effect of the initial cover, we found some situations where was exactly the initial cover to block the succession. For example, some R. ulmifolius patches remained practically unchanged across the 24 years and some old and large trees had 23

Chapter 1 practically no vegetation increase at their surroundings. At the first case competition for space, nutrients and light should be the main drivers, while at the second case the competition by light should be influent, but probably the lack of protection against herbivory is the main issue. The intrinsic ecology of each plant species have also to be considered, as if, for example, the seeds of a shade intolerant species germinate inside a dense cover patch it will not became an adult and consequently will not contribute to the cover increase. Contrary to our expectative, the distance from the continuous forest resulted in a very insignificant variable to predict the vegetation expansion even in shorter scales. Usually the remnant forest is the source of the seeds that will colonize the open areas, so one should expect a decreasing rate of vegetation expansion along the distance gradient. However, at our study site, the forest is constituted homogeneously by oaks ( Quercus pubescens and Quercus ilex ) and to lesser extent maple (Acer campestris ) and with the exception of Hedera helix and Ruscus aculeatus, the majority of the woody mid-successional plants species that compose the bulk of the cover increase are located in the matrix or at the forest edge, occurring in very low densities or been completely absent inside the forest. So at our site forests are not actually the source of propagules for the species composing the expansion, but they will be in the future when these mid-successional species will facilitate oak establishment in the matrix. Once this recruitment wave is established, the woody cover will tend to became more homogeneous and less diverse as the secondary succession evolves towards mature forests (Amici et al. 2013). At the other side, forests usually present higher density of seed dispersers regarding open areas, especially considering birds (Morales et al. 2013). However, judging by the rate of expansion even in areas far from the forest, at our site this density effect seems to be equalized in some way. One potential equalizing mechanism can arise because the matrix bears most of the fruits and at the same time have some level of structural complexity, been more attractive and suitable for birds. Another point is that the most important specie in terms of cover expansion (P. amygdaliformis) occurs in very low density inside the forest and is dispersed almost exclusively by mammals (Fedriani and Delibes 2009). In this case, even the longest distances among plots can be just a fraction of their daily movement ranges (Jordano et al. 2007, Gonzalez-Varo et al. 2013), and consequently the seed deposition have no distance constraints regarding the forest. It is possible that with some specific analysis considering, for example, the cover of plant species that rely on forest dwellers birds to have their seed dispersed some kind of significant relationship can emerge regarding this predictor. The proximity to some woody patch in turn revealed to be significant just in plot 2. This was not expected, as the negative relationship at increasing distances fits the ecological explanation that vegetation expansion should be more a small scale distance dependent process, where the proximity to some kind of patch or even to isolated individuals can enhance the probability of arrival of seeds at the 24

Chapter 1 neighborhood (Herrera and García 2009, Navarro-González et al. 2013). This is especially true if one consider for example that a single bramble individual or a large hawthorn can produce many thousands of fruits and that birds seed dispersers movements are directed towards areas that offers some kind of protection (Carlo et al. 2013, Morales et al. 2013, González-Varo et al. 2017). Also the distance to the nearest patch should reflect the influence of neighborhood scale woody cover, the average bird movement flying distance and seed dispersal kernel present in Mediterranean areas, where the short range seed dispersal is much more frequent than long distance seed dispersal (Jordano et al. 2007, Martinez et al. 2008, García et al. 2016). Probably, again the spatial distribution and the lack of dispersal limitation of P. amygdaliformis should have contributed to blur the effects of this predictor. Maybe refining the scale of the study using smaller sub-plots and thus including also the isolated individuals and small nucleation at the distance matrix should provide some additional information. The pre-existent cover type resulted non-significant in all plots, suggesting that isolated trees, shrubs and small nucleation as well as shrublands and woodlands patches have equal potential to promote or prevent expansion. The fact that some important species in terms of cover like P. amygdaliformis and C. monogyna were present in all cover types together with the abovementioned secondary succession shortcut from grassland directly to woodland should have contributed to this insignificance. Nonetheless, the data shows a positive trend relating increasing expansion at the increasing structural complexity of the cover. On one hand, vegetation expansion in general can be considered a phenomena where inherent spatial autocorrelation is greatly expected, as some processes like the specific individual cover increase due to natural growth, clonal reproduction and gravity or very short seed dispersal causes a radiation expansion from the previous vegetation (Honnay et al. 2002, Bakker et al. 2004). On the other hand, the expansion can be shaped by induced spatial dependence, as those created by specific environmental requirements like water availability, soil Ph, shade or specific directed seed dispersal (e.g. birds towards perches) (Verdu and Garcia-Fayos 1996, Pausas et al. 2006). However, the expansion spatial pattern of some plants that have no particular environmental restrictions for recruitment and have no kind of dispersal limitation at local scale is not governed by these inherent or induced autocorrelation, responding only, or mostly, to relatively random and non- predictive spatial effects processes independently of the number of potential predictors (Hu et al. 2012). This is the case for example of P. amygdaliformis , by far the most abundant specie, present everywhere outside the forest in all plots, thus showing no environmental restrictions. Moreover this specie is abundantly dispersed by most mammal species, which in turn have no particular constraints in depositing Pyrus seeds all around the study site (see chapter 2). Usually most studies consider a long-term and regional scale perspective to maps and describe the land-use changes and vegetation evolution after abandonment, reforestation or some kind of 25

Chapter 1 disturbance, which gives an important regional level view (Álvarez-Martínez et al. 2014). However local and fine scale investigations are also necessary, as some specific patterns not detected on large scale assessments can emerge, especially those related to local species assembly and diversity driven by short distances processes like the majority of seed dispersal events and vegetative growth, although few studies have considered this scale so far in mapping vegetation dynamics (Bakker et al. 2004, Seifan and Kadmon 2006, Chiarucci et al. 2011, García et al. 2014). Many studies using spatial analysis to explain plant richness and distribution incorporates environmental variables as predictors in their models (Kissling et al. 2007, Reitalu et al. 2009, García et al. 2014, Martins et al. 2014). However, these studies are usually made on large scale or in very heterogeneous habitats or consider for example species that are very sensible to microscale abiotic variations. In our study plots there is no apparent local scale niche limitation for the main plant species composing the bulk of the woody cover expansion, as they are widespread throughout the whole area, with no signs of abiotic-driven clustering pattern. Nonetheless, even if the total precipitation and mean temperatures seems to have no significant variations across the 24 years in our study site (data from Agrometeorological Informative Sicilian Service SIAS, 2016), the present study generated a template that can be useful to compare the vegetation evolution and their spatial patterns in future scenarios of ongoing climate change. Moreover, we set the background scenario to the development further investigations to unravel the biotic mechanisms driving the vegetation expansion, addressing particularly the importance of biodiversity and ecological interactions in shaping the spatial patterns of the secondary succession as well as the effectiveness of active and passive restoration in promoting biodiversity recovery.

26

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Keitt, T. H., O. N. Bjørnstad, P. M. Dixon, and S. Citron-Pousty. 2002. Accounting for spatial pattern when modeling organism-environment interactions. Ecography 25 :616-625. Kissling, W. D., and G. Carl. 2008. Spatial autocorrelation and the selection of simultaneous autoregressive models. Global Ecology and Biogeography 0:070618060123007-??? Kissling, W. D., C. Rahbek, and K. Bohning-Gaese. 2007. Food plant diversity as broad-scale determinant of avian frugivore richness. Proc Biol Sci 274 :799-808. La Mantia, T., M. Bellavista, G. Giardina, and I. Sparacio. 2010. Longhorn beetles of the Ficuzza woods (W Sicily, Italy) and their relationship with plant diversity (Coleoptera, Cerambycidae). Biodiversity Journal 1:15-44. La Mantia, T., L. Gristina, E. Rivaldo, S. Pasta, A. Novara, and J. Rühl. 2013. The effects of post-pasture woody plant colonization on soil and aboveground litter carbon and nitrogen along a bioclimatic transect. iForest - Biogeosciences and Forestry 6:238-246. La Mantia, T., J. Rühl, S. Pasta, D. G. Campisi, and G. Terrazzino. 2008. Structural analysis of woody species in Mediterranean old fields. Plant Biosystems - An International Journal Dealing with all Aspects of Plant Biology 142 :462-471. Laskurain, N. A., A. Aldezabal, J. M. Olano, J. Loidi, and A. Escudero. 2013. Intensification of domestic ungulate grazing delays secondary forest succession: evidence from exclosure plots. Journal of Vegetation Science 24 :320-331. Legendre, P., and L. Legendre. 2012. Numerical Ecology. Pages xii-xvi in L. Pierre and L. Louis, editors. Numerical Ecology. Elsevier. Martinez, I., D. Garcia, and J. R. Obeso. 2008. Differential seed dispersal patterns generated by a common assemblage of vertebrate frugivores in three fleshy-fruited trees. Ecoscience 15 :189- 199. Martins, I. S., V. Proença, and H. M. Pereira. 2014. The unusual suspect: Land use is a key predictor of biodiversity patterns in the Iberian Peninsula. Acta Oecologica 61 :41-50. Massa, B., and T. La Mantia. 2007. Forestry, pasture, agriculture and fauna correlated to recent changes in Sicily. Forest@ - Rivista di Selvicoltura ed Ecologia Forestale:418-438. McAlpine, C., C. P. Catterall, R. M. Nally, D. Lindenmayer, J. L. Reid, K. D. Holl, A. F. Bennett, R. K. Runting, K. Wilson, R. J. Hobbs, L. Seabrook, S. Cunningham, A. Moilanen, M. Maron, L. Shoo, I. Lunt, P. Vesk, L. Rumpff, T. G. Martin, J. Thomson, and H. Possingham. 2016. Integrating plant- and animal-based perspectives for more effective restoration of biodiversity. Frontiers in Ecology and the Environment 14 :37-45. Meli, P., K. D. Holl, J. M. Rey Benayas, H. P. Jones, P. C. Jones, D. Montoya, and D. Moreno Mateos. 2017. A global review of past land use, climate, and active vs. passive restoration effects on forest recovery. Plos One 12 :e0171368. Méndez, M., D. García, F. T. Maestre, and A. Escudero. 2008. More Ecology is Needed to Restore Mediterranean Ecosystems: A Reply to Valladares and Gianoli. Restoration Ecology 16 :210-216. Morales, J. M., D. Garcia, D. Martinez, J. Rodriguez-Perez, and J. M. Herrera. 2013. Frugivore Behavioural Details Matter for Seed Dispersal: A Multi-Species Model for Cantabrian Thrushes and Trees. Plos One 8. Navarro-González, I., A. J. Pérez-Luque, F. J. Bonet, and R. Zamora. 2013. The weight of the past: land- use legacies and recolonization of pine plantations by oak trees. Ecological Applications 23 :1267-1276. Navarro, L. M., and H. M. Pereira. 2012. Rewilding Abandoned Landscapes in Europe. Ecosystems 15 :900-912. Ne'eman, G., and I. Izhaki. 1996. Colonization in an abandoned East-Mediterranean vineyard. Journal of Vegetation Science 7:465-472. Pausas, J. G., A. Bonet, F. T. Maestre, and A. Climent. 2006. The role of the perch effect on the nucleation process in Mediterranean semi-arid oldfields. Acta Oecologica 29 :346-352.

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Perry, J. N., and P. M. Dixon. 2002. A new method to measure spatial association for ecological count data. Ecoscience 9:133-141. Perry, J. N., L. Winder, J. M. Holland, and R. D. Alston. 1999. Red–blue plots for detecting clusters in count data. Ecology Letters 2:106-113. Pueyo, Y., and S. Begueria. 2007. Modelling the rate of secondary succession after farmland abandonment in a Mediterranean mountain area. Landscape and Urban Planning 83 :245-254. Raimondi, S., Dazzi, C., Cirrito, V. 1983. Modello di studio integrato del territorio (Ficuzza-Palermo), nota n.5. I suoli. Quaderni di Agronomia 10 :89-131. Reitalu, T., M. T. Sykes, L. J. Johansson, M. Lönn, K. Hall, M. Vandewalle, and H. C. Prentice. 2009. Small- scale plant species richness and evenness in semi-natural grasslands respond differently to habitat fragmentation. Biological Conservation 142 :899-908. Rivas-Martínez, S. 2008. Global bioclimatics (Clasificación biclimática de la Tierra) (versión 01-12-2008). www.globalbioclimatics.org ., www.globalbioclimatics.org . Seifan, M., and R. Kadmon. 2006. Indirect effects of cattle grazing on shrub spatial pattern in a mediterranean scrub community. Basic and Applied Ecology 7:496-506. Smit, C., E. S. Bakker, M. E. F. Apol, and H. Olff. 2010. Effects of cattle and rabbit grazing on clonal expansion of spiny shrubs in wood-pastures. Basic and Applied Ecology 11 :685-692. Tso, B., P. Mather. . 2003. Classification methods for remotely sensed data. . CRC press. Valladares, F., and E. Gianoli. 2007. How Much Ecology Do We Need to Know to Restore Mediterranean Ecosystems? Restoration Ecology 15 :363-368. Verdu, M., and P. Garcia-Fayos. 1996. Nucleation Processes in a Mediterranean Bird-Dispersed Plant. Functional Ecology 10 :275-280. Winder, L., C. J. Alexander, J. M. Holland, C. Woolley, and J. N. Perry. 2001. Modelling the dynamic spatio-temporal response of predators to transient prey patches in the field. Ecology Letters 4:568-576. Xu, C., M. Holmgren, E. H. Van Nes, F. T. Maestre, S. Soliveres, M. Berdugo, S. Kéfi, P. A. Marquet, S. Abades, and M. Scheffer. 2015. Can we infer plant facilitation from remote sensing? A test across global drylands. Ecological applications : a publication of the Ecological Society of America 25 :1456-1462.

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CHAPTER 2

Functional complementarity between mammals and birds as seed dispersers in a Mediterranean woodland pasture

Abstract Seed dispersal is a crucial step in the reproductive cycle and the movement for a wide variety of plant species, many of them relying on the interactions with animals, particularly birds and mammals, to accomplish that task. The complex network created with these interactions generates very different patterns, which in turn are key components for the ecosystem functioning, services and ecological restoration. The Mediterranean region is one of the main sources of knowledge regarding animal mediated seed dispersal. However comparative studies of birds and mammals seed dispersal in the same spatio-temporal scale still scarce even in this well studied region. Here we reveal the complementary role of birds and mammals in providing the seed dispersal services in one of the most important remnants of natural vegetation in the largest Mediterranean island. Our results reveal that both trophic and spatial complementarity were present, including within mammals species. The seed rain density was higher in the heterogeneous fruit rich matrix than in the forest. On one hand, mammals deposited more seeds but in less dispersal event than birds and were practically the exclusive dispersal vectors of the most abundant woody species colonizing the pastureland, enhanced also by the high density of seeds dispersed by cattle. On the other hand, proportionally birds scattered much more seeds in a much less concentrated pattern in each dispersal event than mammals. Birds also were exclusive dispersers of six plant species, the second most abundant tree among them, although theirs seeds were seldom dropped in the pastureland. Consequently, by dispersing seeds of the woody vegetation in the open pastureland, mammals create a more permeable matrix, enabling though the complementary bird seed dispersal, triggering a positive cascading effect fostering the secondary succession. Additionally, our study also highlights the conflicting role of soft linear developments, which simultaneously can act as corridors or sink of seeds.

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Introduction Seed dispersal is a crucial process molding the demographical and evolutionary patterns of many plants, creating the pathway for the physical and genetic flow of the species (Nathan and Muller-Landau 2000, Wang and Smith 2002, Jordano et al. 2011, Galetti et al. 2013). Additionally, seed dispersal is also the only way for plants to colonize new areas, a key step for example in the restoration of degraded areas. Particularly, seed dispersal by animals is a widespread syndrome in many environments, reaching or overcoming 90% of plants species depending on them to have their seeds on the move, flowing through a complex network of interactions (Jordano 2000, Almeida-Neto et al. 2008, Donatti et al. 2011). This wide range of interacting species will inevitably produce both complementary and redundant contributions (Lawton and Brown 1993, Jordano et al. 2007, Bueno et al. 2013). This contrasting roles however are not mutually exclusive and can vary in intensity, as for example two species or guilds can disperse the same plant species (qualitative trophic redundancy), but one disperse just few seeds while the other hundreds (quantitative trophic complementarity), although those few are dispersed in the best microhabitat, while most of the hundreds in unsuitable microhabitats (spatial complementarity) (Jordano et al. 2011, Bueno et al. 2013, García 2016). Beyond the intrinsic community-wide parameters that can affect the seed dispersal services provided by animals, like abundance, richness and behavior, the human influence is indeed an extremely relevant factor in a changing world (Dirzo et al. 2014, Valiente-Banuet et al. 2015). This influence can be represented In many ways accordingly to the history and intensity of land use, directly filtering the diversity and abundance of the pool of species through exploitation, or indirectly by partially or totally modifying the landscape configuration, for example reducing the amount of natural vegetation and matrix permeability (Massa and La Mantia 2007, La Mantia et al. 2008, Garcia et al. 2011, Escribano-Avila et al. 2014). A widespread human structure that directly affect the matrix permeability are the linear developments, than can be grouped as heavy developments such as intensely used highways or soft developments such as the less frequented unpaved roads or firebreaks (Tewksbury et al. 2002, Levey et al. 2005, Suárez-Esteban et al. 2013b). Despite the frequent presence of soft linear developments even inside many protected areas, the role of these linear structures is still very scarcely explored regarding their effects on the seed dispersal services (Suárez-Esteban et al. 2013a, Suárez-Esteban et al. 2013b). In Mediterranean, seed dispersal by animals is also widespread syndrome, as from 20% to 65% of the plant species depend on animals to move their seeds, particularly birds and mammals (Herrera 1989, Jordano 2000). Beyond the typical variances in their diet (trophic level), mammals and birds respond differently to the landscape configuration, as for example mammals tend to be less restrictive regarding open matrix or degraded habitats, while birds tends to heavily concentrate their activity in 32

Chapter 2 woody perches (Pausas et al. 2006, Herrera and García 2009, Matías et al. 2010). These two groups are supposed to act complementarily in the seed dispersal service in both quantitative, qualitative and spatial terms, although few studies have so far compared simultaneously their seed rain at the same spatio-temporal scale (Santos et al. 1999, Jordano et al. 2007, Escribano-Avila et al. 2012). Notwithstanding, despite advanced knowledge has been accumulated since relatively long time in some Mediterranean regions (Herrera and Jordano 1981, Jordano 1987, Herrera 1989, Debussche and Lepart 1992), other Mediterranean regions, like Italy, have practically no empirical studies. This is a critical gap, firstly because the seed dispersal services, although presenting broad common patterns, tend to be highly context-dependent, as even slight differences in the species assembly, environmental conditions, land use intensity and even behavior can produce unique patterns. Secondly because the value of the ecosystem services provided be these interactions remains highly underestimated (Schleuning et al. 2015). Our study site represents the last large remnant of forest in all western Sicily, providing though a unique opportunity to assess birds and mammals seed dispersal services in a system that still conserves a relatively rich species assemblage in a variegated landscape where different trophic and spatial responses are expected to occur. In this study we aim to (1) reveal the quantitative and qualitative components of the seed dispersal service provided by mammals and birds and (2) assess the degree of complementarity between mammal species and between mammals and birds as seed dispersers, taking into account the distribution of seed dispersal interactions and the spatial patterns of seed deposition.

Methods Study site See general study site description.

Sampling Our objective was to assess the quantitative and qualitative aspects of the seed rain generated by mammals and birds, especially in relation to the two main habitats, forest and woodland pasture (hereafter WP). Complementarily, we also evaluated one specific habitat within each group: the soft linear developments (SLD, hereafter), composed by unpaved roads, for the mammals, and tree perches distributed across the matrix, for birds. To reach that objective, we used different methods to measure the seed rain, that is, the cumulative seed deposition (regurgitated seeds and seeds in animal feces) with an area-based sampling (see Escribano-Avila et al. 2012 for a similar procedure).

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The mammal seed rain was assessed through fixed-width line transects across the 3 habitats (forest, open matrix, SLD). In the forest and WP we used one 800 x 2m transect located in each habitat in each of the three plots. In both open and forest habitats, the transects begun from random points at the edge of each plot, walked until the opposite side, then walked along the border and again towards the initial edge, in a zig-zag pattern without overlaying the paths and always with different starting points (adapted from Fedriani and Delibes 2009). In the open matrix, the transects covered mostly non- woody patches, as we avoided dense woody patches impossible to walk for searching seeds. However, to cover these dense woody patches, in October 2016 we searched for mammals feces in 3m² ground areas in each of the 211 sampling points where seed traps were established (see below). For monitoring SLD seed rain, we sampled unpaved roads at the surroundings of the plots along 2.400 x 2m transects, located at the borders of the roads, with consecutive surveys in the same road separated by at least two months. For each detected feces we labeled the specie, identified whenever possible with a combination of size, color, shape and odor (Lopez-Bao and Gonzalez-Varo 2011). We performed monthly surveys along two fruiting seasons (September 2015 – February 2016 and September 2016 – February 2017, 12 surveys), walked in a constant speed by the same observer, totaling 28.8 km walked and 5.76 ha sampled in each habitat. To assess the bird seed rain in the forest and open habitats we surveyed 50 ground quadrats of 1m² in each habitat in each plot in 4 surveys (January 2016 and September, November and January 2017), totaling 600m² in each habitat. The quadrats were established randomly along the mammal transects in the forest. In the matrix, as our objective was to assess the seed rain avoiding the direct influence of woody perches (that were specifically evaluated with the seed traps), the quadrats were proportionally distributed only in grassland/bare ground considering two types of microhabitats: (i) woody vegetation, whether there were woody individuals >1.5m height inside a 5 m buffer and (ii) open, whether not in the previous condition. All fresh bird feces found in quadrats were individually collected. All individually collected feces from birds and mammals were considered as a unitary sample. All collected samples were dried in the sun and analyzed in laboratory, been carefully broken and processed using a set of metal sieves up to the minimum mesh of 2mm, where all retained seeds were identified, counted and classified as intact or mechanically predated seeds (broken, crushed). In order to specifically evaluate the role of perches and complementarily to the quadrats, at the beginning of the second fruiting season (September 2016) we installed 211 seed traps under trees scattered in the open matrix, covering from the edge of the forest to the farthest distance inside the plot, with 67 seed traps at plot 1, 77 at plot 2 and 67 at plot 3. The seed traps were made with recycled wood boxes measuring 60x40x8cm (0.24m²), with a fine-pore mesh at the bottom to retain small seeds but enable water drainage, and a 1x1cm wire mesh top cover to prevent seed predation by vertebrates. 34

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Every two months, up to March 2017, the seed traps were revised for seed occurrence, all the present seeds stored in labeled paper bags, and traps were cleaned and relocated at the same tree.

Seed dispersal interaction matrix The interaction matrix had the objective to depict all the fruit-frugivore interactions observed during our study, incorporating all the interactions observed directly in the field and the data from collected feces. Field observations were made randomly along the two fruiting seasons while performing the other experiments, where a determined interaction (e.g. species of bird consuming a species of fruit) was annotated. Data from feces were obtained from the analyses of mammals collected samples, where the species of mammals was linked to the species of plant they dispersed the seed. Bird feces data was not used as we did not identified the species. As a complementary measure to collect fruit-frugivore interactions, we used sampling stations composed by one camera trap pointed to a depot of fleshy fruits, collected from individuals of species available along the two fruiting seasons in the study site (Prasad et al. 2009). In total we used 6 camera traps, in movie mode, placed in different positions inside the study plots, both close and far from the forest, operating almost continuously along the 2 fruiting seasons, with the positions changed roughly at 30 days intervals in order to realize a heterogeneous sampling across the habitats. We report the cumulative registration along all the sampling with the camera traps. The interactions were classified as positive (seed dispersal), mixed (dispersal and predation) and negative (seed predation) based on the knowledge of the authors and the extant literature (e.g. Herrera 1989, Jordano 2000, Olesen et al. 2011, García 2016). For seeds in feces we defined predation where more than 5% of the seeds presented signals of mechanical predation (broken or crushed).

Data analysis We first sought to evaluate the variances between mammal species in different aspects of the seed rain, including the effects of habitat type in seed deposition patterns. For that, we quantified the frequency of depositions (number of feces in each habitat in the total number of feces), in order to detect eventual preferences in habitat use, the frequency of depositions with at least one seed (a dispersal event), the proportion of intact seeds in the total number of seeds in a dispersal event, as well as the abundance and richness of seeds dispersed by each mammal species in each dispersal event. The differences between mammal species in the abundance of dispersed seeds were assessed by one way ANOVA, and a post-hoc Tukey test was used to assess differences among the species (after log- transformation of the response variable to achieve normality). To analyze bird seed rain we used the same frequencies and proportions, although we only checked differences between habitats, as we were 35

Chapter 2 unable to differentiate the bird species from feces. As the data of seed abundance in bird feces did not fir to a normal distribution after log-transformation, we used the non-parametric Mann-Whitney U test to verify whether the magnitude of the seed rain differed among forest and open habitats. The differences in the proportion of feces with and without seeds were assessed through contingency tables and Chi-square. As we were interested in analyzing the cumulative seed rain generated at the dispersal events, and not temporal variations, we pooled the data from the 2 fruiting seasons for both groups. In order to have a comparable measure of bird and mammals seed rain we used the density of dispersed seeds per hectare at each habitat, as this relative variable is proportional to the sampled area, allowing though the direct comparison among these groups (see Escribano-Avila et al. 2014 for a similar procedure). The seed trap data was analyzed separately, as it was only used in the second fruiting season and this method enable to continuously sample all the cumulative dispersed seeds, including regurgitated seeds not considered in the quadrats, as well as provide no chance for seed predation. The qualitative (presence or absence) interaction matrix was made pooling all the data from direct observation, camera traps and feces collected along the two fruiting seasons.

Results Mammals seed rain We found 606 mammals feces from which we were able to identify 8 different mammal species (Table 1). All feces were collected within the transects, as we did not register any mammals feces at the open quadrats. About 53.6% of all feces contained at least one seed. Three mammal species ( Dama dama n = 91 , Erictolagus cuniculus n = 3 and Erinaceous europaeus n = 8) didn’t present any seed in their feces, and were excluded from further analyses. Of the remaining 504 feces, 63.9% contained at least one seed, with an average of 36.4 seeds (± 43.8 SD) and a maximum of 309 seeds dispersed in a single scat, totaling 12.339 seeds from 7 different plant species. The feces with seeds from a single plant species accounted for 91.7% of the total, those with 2 species for 7.7%, while just 1 red fox scat presented 3 species simultaneously. From all found seeds, just 7.5% presented signals of mechanical damage (predation), with the higher rates of predation found in crested porcupine (34.4%) and wildboar (16.2%) while cattle, pine marten and red fox presented very low rates (Table 1). There were significant differences in the mean number of seeds dispersed by each mammal species in each dispersal event (ANOVA F = 18.48, p < 0.001, df = 4) as well as in the mean richness of seeds (F = 2.72, p = 0.02, df = 4), although only B. taurus differed from the other species (Figure 2). From the total number of dispersed seeds, 11.736 belonged to wild plant species ( Pyrus amygdaliformis, Rubus ulmifolius, Rosa canina and Prunus spinosa ), while the 603 remaining were from 3 cultivated species not present in our study site ( Ficus carica n = 511 seeds in 4 feces, Morus sp . n = 86 in 2 feces, 36

Chapter 2 and Vitis vinifera n = 6 in 2 feces), all dispersed by red fox. Given that these species were only found in a few feces from just one mammal species, and since we were interested in the mammal contribution in the dispersal of the wild species, these 3 domestic species were excluded from further analyses. From the dispersed wild species, P. amygdaliformis accounted with 62% of the total number of seeds, and it was present in 240 feces from all mammal species, followed by R. ulmifolius, with 26.6% in 38 feces, R. canina, with 8.8% in 35 feces, and P. spinosa with 2.6% in 33 feces (Figure 3, 5). This last didn’t bear mature fruits at the second sampling season, as all the very few produced were aborted before maturation (R. S. Bueno personal observation ).

Table 1. Summary of the seed dispersal data for mammals and birds in Alpe Cucco. * Including 3 cultivated plant species % feces Seed Mean number % Total Specie English name Feces with N seeds density seeds (± SD) predated Richness seeds (n/ha) per feces seeds Bos taurus Cattle 132 47.7 4125 238.8 31.2 (± 43.3) 2.1 1

Dama dama Fallow deer 91 0 0 0.0 - - -

Erinaceus europaeus Hedgehog 8 0 0 0.0 - - -

Hystrix cristata Crested porcupine 39 56.4 849 49.1 21.8 (± 34.4) 34.4 2

Martes martes Pine marten 35 60 504 29.2 14.4 (± 27.8) 1.6 4

Orictolagus cuniculus Rabbit 3 0 0 0.0 - - -

Sus scrofa Wildboar 112 59.8 2374 137.4 21.2 (± 34.9) 16.2 4

Vulpes vulpes Red Fox 186 81.7 4487 224.8 24.1 (± 43.8) 3.5 7*

Mammals 606 55.7 12339 679 24.2 (± 40.4) 7.5 7*

Birds 155 76.8 435 3625 2.8 (± 3.4) 0 9

4.5 a 4 3.5 3 b 2.5 b 2 b b 1.5 1

Mean number of seeds (log) Mean of seeds number 0.5 0 B. taurus H. cristata M. martes S. scrofa V. vulpes

Figure 2. Mean number of seeds (log-transformed) of wild plant species dispersed by different species of mammals in Alpe Cucco. Different letters indicate significant differences between species after Tukey test.

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Figure 3. Frequency of occurrence of each of the wild plant species dispersed in the mammals feces.

There were significant differences between plant species in the mean abundance of seeds dispersed per dispersal event (F = 23.77, p < 0.001, df = 3), with R. ulmifolius being found with, on average, 82.1 seeds (± 77.8 SD), P. amygdaliformis with 30.3 (± 32.1), R. canina with 29.4 (± 16.3) and P. spinosa with 9.3 (± 6.1) seeds (Figure 4).

4.5 a 4

3.5 b b 3

2.5 c 2

1.5

1 Mean number of seeds (log) seeds of numberMean

0.5

0 P. amygdaliformis P. spinosa R. canina R. ulmifolius Figure 4. Mean number of seeds (log transformed) in the mammal feces from different wild plant species. Different letters indicate significant differences between species after Tukey test.

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Birds seed rain Along the 4 surveys we found 155 bird feces in ground quadrats. From all feces, 76.8% were seed dispersal events, totaling 435 seeds dispersed from nine different wild plant species, with an average of 2.8 (± 3.37 SD) and a maximum of 21 seeds in a single feces. Just 2.6% of the feces contained 2 plant species, while all the other contained only one. No predated seeds were found. The most frequent specie found in the feces was Rosa canina , present in 33.1% of the feces, followed by Hedera helix with 23.1% and Crataegus monogyna with 19.9%, while Tamus communis was the rarest specie with fruits also in the first season, present in just 1.6% of feces (Figure 5). Regarding the microhabitat of the deposition, 89.3% of the feces were found close to woody individuals and just 11.7% in open ground, while 94.9% of the seeds were deposited close woody individuals and only 5.1% in open quadrats.

Figure 5. Frequency of occurrence of the different plant species found in the mammals and birds feces.

Seed traps Along the second fruiting season, at the seed traps we collected 2314 seeds from 12 different species. C. monogyna was the most abundant specie responding for 39.3% of all seeds, followed by R. ulmifolius with 23.7%, while D. laureola and R. aculeatus were the rarest species, with only 0.22% and 0.17% of the seeds, respectively. The richness of plant species found in the feces and seed traps were 39

Chapter 2 quite similar, with only three fleshy fruited species present in the seed traps not registered in the feces, Crataegus laciniata, Daphne laureola and Pyrus amygdaliformis. Predated seeds of the dry fruited Quercus sp. were found only in the traps, as their occurrence in feces was not expected in any case. Prunus spinosa was not found in the traps as this specie did not bear mature fruits during the period sampled by the seed traps.

Seed rain across habitats Regarding the mammals feces deposition pattern across the different habitats, 42.2% of the 504 feces were found in open areas, 29% in the SLD and the remaining 28.8% in the forest (Figure 6). From the feces with at least one seed a very similar pattern was observed, with 43.2% in open areas, 30.7% in SLD and 26.1% inside the forest, with no significant difference ( X² = 3.37, p = 0.18). Cattle and red fox presented similar patterns of feces deposition among the three habitats, birds and wildboar presented similar proportions among forest and open areas and pine marten and wildboar the highest proportion in the forest and the absence from SLD, while all the other species varied in the proportions, suggesting a behaviorally driven habitat spatial redundancy, (Figure 6). Two species ( M. martes and S. scrofa ) didn’t dispersed seeds in the SLD. The seed rain abundance in the dispersal events followed the same trend, with open habitats receiving 44.8%, SLD 31.2% and forest 24% of the total seeds dispersed, with no significant differences (ANOVA F = 0.258, p = 0.77). All five mammal species contributed differently to the seed density dispersed across habitats, where at the forest wildboars were the responsible for 44.2%, at open habitats cattle responded for 36.7% and at the SLD red fox accounted for 48.7% (Figure 7). Birds feces deposition was higher in open habitats with 60.6% against the 39.4% of forests, and despite the proportion of feces with seeds was higher (75.5 against 24.5%) no significant differences was detected (X² = 2.28, p = 0.13). However, open areas received significatly higher number of seeds (Mann- Whitney Z = -2.24, p = 0.02), albeit the species richness was slightly higher in the forest, with nine species against the seven dispersed in the matrix. The two missing species in the matrix are Ruscus aculeatus and Tamus communis , two species mostly present in the forest in our study site.

Qualitative interaction matrix Pooling all the information obtained through the collected feces (mammals), camera trap registration and direct observation for both groups, we were able to register 8 mammals species interacting with 11 plant species, of which 3 domestic, and 6 bird species interacting with 11 wild plant species (Table 2, Figure 9). All bird-plant interactions can be classified as positive (seed dispersal), while 40

Chapter 2 for mammals we classified as mixed interactions when more than 5% of the seeds were found predated in the feces, and particularly one specie ( Apodemus sylvaticus ) was classified as having only negative interaction, as this species is known to be a highly specialized seed predator (Garcia et al. 2005a).

Figure 6. Frequency of dispersal events promoted by the different mammal species and birds across the different habitats.

400 5000 Forest Open SLD

4000 300

3000

200

2000

100 Numberof seeds (n / ha) 1000

0 0 B. taurus H. cristata M. martes S. scrofa V. vulpes Mammals Birds Figure 7. Cumulative seed density deposited by each mammal specie and by mammals and birds across forest, open and soft linear developments.

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Table 2. Qualitative interaction matrix of plants (rows) and birds and mammals (columns) registered combining different methods along two fruiting seasons in Alpe Cucco. O = direct observation, CT = camera trap and F = feces. In bold domestic species. Mixed influence (dispersal and predation) was classified if more than 5% of the seeds were predated. * Spitting seeds after pulp consumption. ** Eating the pulp.

Plants/Animals Sus scrofa Bos taurus Vulpes vulpes Turdus Turdus merula Martes martes Hystrix Hystrix cristata Sylvia atricapilla Sylvia communis Turdus Turdus philomelos Erithacus rubecula Columba palumbus Apodemus sylvaticus Oryctolagus cuniculus

Asparagus acutifolius O/CT O

Crataegus laciniata O/CT O CT

Crataegus monogyna O/CT O O/CT CT CT CT*

Hedera helix O/CT O O/CT O/CT CT F

Prunus spinosa O/CT CT CT F/CT F F/CT

Pyrus amygdaliformis CT** CT** CT F/O F F/CT F/CT F/CT

Rosa canina CT CT CT F/CT F F/CT

Rubia peregrina CT O

Rubus ulmifolius O/CT O O O/CT CT CT F F/CT F F/CT

Ruscus aculeatus CT CT CT

Tamus communis CT

Ficus carica F

Morus sp. F

Vitis vinifera F

Seed dispersal Seed predation Seed dispersal and predation

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1 2 3

4 5 6

7 8 9

10 11 12

Figure 9. Example of the interactions observed with the different methods. Legend: 1) Vulpes vulpes and Pyrus amygdaliformis , 2) Bird and Rosa canina , (3) Erithacus rubecula and Rubia peregrina , 4) Hystrix cristata and P. amygdaliformis , 5) Turdus merula and Crataegus monogyna , 6) Bird and C. monogyna , 7) Sylvia communis and R. ulmifolius 8) Sus scrofa and P. spinosa , 9) Turdus philomelos and H. helix (Credit: Antonino L’Ala), 10) Apodemus sylvaticus and P. spinosa , 11) Martes martes and R. canina 12) Bos taurus and P. amygdaliformis .

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Discussion In our study we revealed the strong contribution of mammals and birds in performing the crucial seed dispersal of the main plant species composing the woody secondary succession inside the last large remnant of natural vegetation in western Sicily. Our results confirm the hypothesis that in this montane Mediterranean environment there were different levels of trophic and spatial complementarity, both within mammal species as well as confronting with birds, even when sharing common plant species. The overall seed rain was more intense in the WP than on the forest for almost all species, possibly a consequence of the higher fruit abundance. Our results also highlighted the specific role of the soft linear developments in attracting a selective but intense seed rain while the tree perches were strong magnets attracting the seed rain provided by birds in the WP.

Mammals seed rain The plant-mammals seed dispersal interactions illustrated in our study comprehended four wild and three cultivated plants dispersed by five mammals, with common and different patterns regarding other studies. Our data confirmed that mammals, especially carnivores are important seed dispersers of R. ulmifolius, R. canina and P. spinosa (Herrera 1989, Rosalino and Santos-Reis 2009) , even if occurring in relatively low proportion of feces, their seeds are dispersed in high densities at spatially spread events. The appearance of seeds from the three cultivated species is intriguing, as they do not occur in our study site. There are two non-mutually exclusive hypotheses. One is the long distance seed dispersal, a known capacity of red fox (Jordano et al. 2007, Gonzalez-Varo et al. 2013), as the closest individuals of those plants are located kilometers away in the rural matrix outside the reserve. But we cannot exclude that maybe those fruits were left by humans, and red fox took advantage of that rich and easy meal. Anyway, while some studies revealed strong interactions with cultivated fruits (Lopez- Bao and Gonzalez-Varo 2011), others revealed just occasional rapports (Matías et al. 2010). At our site these were very idiosyncratic interactions, occurring in only 1.6% of just red fox feces, with no direct implications as these three species seems to be not able to recruit in the montane conditions of Alpe Cucco. Remarkably instead was the absolute dominance of P. amygdaliformis in mammals seed dispersal. We found just one study specifically analyzing Pyrus seed dispersal in Mediterranean (Fedriani and Delibes 2009), while few others reported generally this interaction, with the results demonstrating that badger ( Meles meles ), red fox and wildboars are the main vectors (Rosalino et al. 2010, Lopez-Bao and Gonzalez-Varo 2011, Perea et al. 2013, Suárez-Esteban et al. 2013b). However, contrasting patterns do exists, as for example in Donanã Biological Reserve (Spain), where most studies were conducted, both Pyrus bourgaeana and red fox occur in low densities (Fedriani and Delibes 2009) and all studies found a 44

Chapter 2 relatively low frequency of interaction and low number of seeds dispersed. Contrary, at Alpe Cucco, P. amygdaliformis is the most abundant tree in the secondary succession, red fox is the most abundant mammal (R. S. Bueno unpublished data) and badger is absent, creating a totally different template in a promising field for deeper comparisons on how density variations can shape the interactions. A novel relationship in turn is the seed dispersal of Pyrus by cattle and crested porcupine. Regardless the almost ubiquitous presence of cattle, the wide range of occurrence of wild Pyrus and the morphological fruits traits favoring large mammals consumption, no studies were found to compare our results. Even if seed fate and consequent transition probabilities have to be checked, cattle, other than retrieving nutritional rewards, is actively contributing to the diffusion of this abundant specie complementarily with the other mammals. This finding has interesting applied outcomes, as for example using Pyrus to enrich silvo- pastoral systems. Crested porcupine presented the highest rate of seed predation of Pyrus , although they do act as legitimate seed dispersers (Jordano and Schupp 2000). We found just one study reporting the seed dispersal of a dry fruited invasive species ( Helianthus tuberosus ) by crested porcupine (Mori et al. 2017).

Bird seed rain Our data highlight the complementary seed dispersal services provided by birds, with a high frequency of feces with seeds, a five times denser seed rain distributed in a diverse assemblage of species, including 6 exclusive. Making a parallel with the relationship mammals and Pyrus , birds were the unique dispersers of C. monogyna , the second most abundant tree species in the secondary succession. Despite the fruit consumption, seed dispersal and seed predation of C. monogyna by mammals have been recorded, albeit in low frequency, in other studies (Matías et al. 2010, Lopez-Bao and Gonzalez-Varo 2011, Peredo et al. 2013) at our site we never found a single seed in mammal feces, and also we never registered the fruit consumption with the camera traps. On the other side, in direct field observations and with the camera traps we registered several bird species feeding on the pulp of fallen Pyrus fruits, although we found just few clean seeds on the seed traps and only one feces with seed in a random observation. Even if Pyrus seed dispersal by pulp eating birds is not a forbidden link (Olesen et al. 2011), they may contribute to recruitment of non-dispersed seeds, as pulp removal greatly increase germination probability (Fedriani et al 2012). Regardless of the intrinsic differences in the methodologies, bird seed rain is highly concentrated under the perches present in the matrix, confronting with open areas a pattern observed in other studies (Pausas et al. 2006, Herrera and García 2009). We were not able to disentangle the specific contribution of each bird species, and consequently deeply discuss for our site the within birds complementarity and the role of richness for seed dispersal services (Jordano and Schupp 2000, Garcia and Martinez 2012). The only way to assess the species 45

Chapter 2 specific redundancy or complementarity is through DNA analysis such as barcoding, a technique that is already unravelling the fine structure of this until now general network (Jordano et al. 2007, González- Varo et al. 2014, Galimberti et al. 2016, González-Varo et al. 2017). Notwithstanding, beyond trophic complementarity, some additional aspects of functional complementarity emerged. The most abundant and widely distributed tree species leading the secondary succession in our study site is Pyrus (Bueno et al., in prep ), a case of successful combination of intrinsic robust characteristics coupled with dense and spatially unconstrained mammal seed dispersal. Many Pyrus individuals, including some isolated in the pasture, were accompanied by exclusively bird dispersed plants, like A. acutifolius , R. peregrina and Hedera helix (see Chapter 3). In turn these three plant species only occurred associated with other plants. We also found many of these exclusively bird dispersed species under C. monogyna, but this tree has a spatially constrained distribution, with few individuals found isolated in the matrix (Bueno et al., in prep ). In this way, by promoting Pyrus recruitment in the open areas, mammals are creating the suitable frontier that will gradually be enriched by bird seed dispersal, taking advantage of the structural opportunity created by mammals. The same rationale can be true for mixed dispersed species like Prunus spinosa, Rosa canina and Rubus ulmifolius . This three shrub species are also components of the frontiers of the secondary succession, but considering the avoidance of birds towards open areas, mammals are setting the same structural template as with Pyrus , but in this case they are setting also the fruiting template for bird seed dispersal, that in turn will take advantage of these fruit rich and structurally suitable stepping stones, enhancing though the probability of expansion of these and other species beyond, in a mammal- plant-bird-plant facilitation loop. The overall bird and mammals seed rain density in the forest was less than half the one falling in the open matrix, with the exception of pine marten and wild boar that deposited more seeds in the forest. Whether this seed rain will be more intense or equally distributed in one habitat or another seems to be an example of context-dependency, as even similar assemblages of seed dispersers in the same macro-region can present different seed rain patterns (Matías et al. 2010, Peredo et al. 2013, Escribano-Avila et al. 2014). Although we cannot discard eventual filtering of bird feces even in the low density understory of the forest in our site, possibly the differences are better explained by the high abundance and diversity of the fleshy fruited plants in the matrix, where this fruit rich environment act as a magnet for frugivores, increasing their visitation rate and time spent in this area, consuming more fruits and consequently recycling the seeds inside the matrix itself (Garcia et al. 2010). In any case, accordingly with our data a considerable part of the matrix seeds will fall inside the forest.. Although for birds we do not have the species-specific contribution, certainly some species should have contributed more than others, with the special contribution of thrushes ( Turdus sp. ) (Morales et al. 2013). Many 46

Chapter 2 forests reported in European and Mediterranean seed dispersal studies have considerable proportion of fleshy fruited trees and shrubs (Jordano and Schupp 2000, Matías et al. 2010, García et al. 2016), however, in Alpe Cucco, the forests are composed predominantly by two oak species ( Quercus pubescens and Quercus ilex ), intensively managed in the past, with a high density of similar sized individuals creating a very homogenous canopy structure, with practically no gaps. Adding the herbivory pressure made by domestic and wild ungulates, the result is a low density species-poor understory, where most of matrix fleshy-fruited species occurs just occasionally and hardly produces fruits (R. S. Bueno unpublished data ). Considering this situation, there is a very low probability of a seed coming from the matrix became a reproductive individual inside the forest, resulting though in a predominant sink. The only exceptions are Hedera helix and Ruscus aculeatus , two species that sustains the bulk of the fleshy fruit production inside the forest and are very scarce in the matrix. Although the secondary succession towards mature forests is followed by an overall richness decrease (Amici et al. 2013), in our site the recruitment limitation seems to be enhanced by the past land use legacies and current herbivory pressure, as our data suggest that there is no ongoing seed dispersal limitation. We didn’t find mammals feces over quadrats in the matrix. In a study in Donanã, Fedriani et al. (2010) found that wildboars tend to defecate close to adults of P. bourgaena , while badger and red fox demonstrated no clear preference. Regardless of our relative small sampled area, differently from birds, in our site apparently there is no clear correlation between woody cover and mammal deposition in the matrix, possibly a behavioral effect of Pyrus very high densities. Soft linear developments and linear clearings inside forests have been recently suggested as acting as seed corridors, favoring the dispersal of plants (Tewksbury et al. 2002, Levey et al. 2005, Suárez-Esteban et al. 2013b). Inside the Ficuzza natural reserve there are many kilometers of paved and mostly unpaved roads, a common pattern found in many protected areas worldwide. Our data showed that wild ungulates completely avoid SLD, while cattle, red fox and crested porcupine are frequent users, directing an important fraction of their seed rain along the SLD, corroborating the hypothesis of seed corridors (Suárez-Esteban et al. 2013b). Notwithstanding, all seeds falling in the middle of the unpaved road, a pattern frequently found for cattle, have obviously no probabilities of recruitment. Moreover, at our study site, all the vegetation inside a 5-10 meters buffer along the SLD is systematically removed in a measure to prevent fire. As far as this procedure continues, all the seeds dispersed will never became a reproductive individual, erasing the positive benefits and creating a strong seed sink in that range. This sink for abundant plant species with seeds dispersed elsewhere should not be an issue, although for the eventual few seeds of some rare species this could represent an important demographical bottleneck. Very few bird defecations were observed in the SLD, probably due to low bird use in this highly exposed habitat. In any case further investigations have to been made to assess 47

Chapter 2 for example the facilitation of long distance dispersal, the secondary dispersal provided by water runoff, the contribution to the recruitment just beyond the managed range or how changes in human intensity use could influence disperser’s behavior. But we are aware that fruit crop richness and abundance, their spatio-temporal variations and the recruitment transition probabilities are needed to better understand the dispersal services provided by mammals and birds. Islands usually presents lower complexity in their network regarding mainland, although tend to have different network properties like higher modularity an increasing dependency, particularly strong in small islands (González-Castro et al. 2012, Perez-Mendez et al. 2016). Whether the network structure in large islands would be closer to smaller or to mainland is an interesting future research. Along two fruiting seasons we were able to register the interaction between 27 species (13 animals with 14 plants), englobing most of the frugivorous birds, mammals and fleshy fruited plants species occurring in Sicily, the largest Mediterranean island, collaborating though to fulfill an important regional gap and opening the way for further comparative studies.

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CHAPTER 3

Natural regeneration is more effective than planted trees in concentrating seed rain and promoting recruitment in a dynamic Mediterranean woodland pasture

Abstract While many areas worldwide still been intensively used or losing their natural cover and consequent ecosystem services, land abandonment and consequent natural regeneration are an increasing trend in many European regions. Additionally many thousands of hectares were or are been actively restored. Natural regeneration has been verified to be equally or more effective than human induced regeneration in promoting ecological restoration in many deforested and degraded areas, although many abandoned or actively restored areas still present an eroded species assemblage, mainly due to dispersal and recruitment limitation. Here we compared the richness, density and spatial patterns of seed rain and different stages of recruitment under two natural regenerating trees and the two planted trees species in a woodland pasture surrounded by the last large remnant of forest in western Sicily. The vast majority of the natural regeneration trees received at least one seed, with six unique plant species, and seed rain density was four times higher than under planted trees. Planted trees in turn presented seeds in half of the individuals. The natural regeneration had five unique recruit species and a significant higher density, although planted trees indeed presented most of the individuals with at least one recruit. This heterogeneous distribution reflected in a global predominant random spatial pattern at the plot scale, with only plot 1 presenting global aggregated seed rain richness, and only overall recruitment density clumped at plot 1 and 2. We also found consistent inter and within species differences, where Crataegus monogyna presented the highest values in all parameters even excluding the high intra-specific seed rain. The earliest stage recruitment density under Pyrus amygdaliformis , and especially under the two planted trees was positively correlated with the later stages density, suggesting a potential complementary recruit-recruit facilitation, at least considering all species pooled. Under all trees we registered a decrease across the recruits life-stages, but remarkably all the 5 most abundant fleshy-fruited woody species in the landscape presented very low density of early stage recruits, even been widely dispersed by birds and mammals, a potential sign of an ongoing large scale post-dispersal recruitment limitation. Finally we propose a simple procedure to incorporate seed dispersal and plant-plant association in the evaluation of both passive and active restoration.

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Introduction Many ecosystems worldwide still suffering from strong anthropic pressure through a very intensive land-use, natural vegetation clearing and defaunation (Myers et al. 2000, Dirzo et al. 2014). Once these areas are degraded and species disappear, also do their ecosystems services, with innumerable negative consequences (Galetti and Dirzo 2013, Schleuning et al. 2015, Valiente-Banuet et al. 2015). On the other side, land abandonment is also an increasing phenomenon, particularly occurring in the northern hemisphere, leading to wide scale natural regeneration, also called passive restoration (Cramer et al. 2008, La Mantia et al. 2008, Navarro and Pereira 2012). On the top of that, many millions of hectares were actively restored with many different methodologies, a task encouraged also by several international commitments (Holl and Aide 2011, Menz et al. 2013). Recent reviews have pointed that natural regeneration can be equally or superiorly efficient in promoting biodiversity recovery and ecological restoration than active interventions (Crouzeilles et al. 2017, Meli et al. 2017), although these reviews also stated the context-dependency of the outcomes as well as the need of more studies comparing directly their efficiency when co-occurring in the same area. In Europe land abandonment is an increasing phenomenon, and particularly in Mediterranean many areas have been left aside along the last decades due to common social, economic and environmental reasons (Massa and La Mantia 2007, Plieninger et al. 2014, Ceausu et al. 2015). This abandonment clears the path for the secondary succession, enabling the gradual return of many ecosystem services, although the natural resilience capacity of each area can differ even in a short scale and often some extensive level of human interference still present (Bianchetto et al. 2015, Novara et al. 2017). At the same time, in the Mediterranean region, massive reforestation initiatives were made during the last century, aiming specially at combating environmental degradation (Gómez-Aparicio et al. 2009, Rühl et al. 2015). As in many areas worldwide, the common procedure was the plantation of seedlings from some few species, usually of late successional trees, with a predominant use of regionally or locally allochthones species. This effort generally brought improvements, for example reducing critical edaphic degradation, fragmentation and creating a more suitable heterogeneous matrix (La Mantia et al. 2002). Nonetheless, many abandoned and reforested areas still presenting a poor diversity with respect to their original pool of species, considering plants, animals and consequently also their interactions (Maestre and Cortina 2004, Méndez et al. 2008, Gómez-Aparicio et al. 2009). Seed-dispersal and establishment limitations, separately or concomitantly, seem to be the main sieves affecting plant demography and consequent ecological restoration (Herrera et al. 1994, Jordano and Schupp 2000, Gómez-Aparicio 2008). Seed limitation can simply be triggered with the absence or low production of viable propagules (source limitation), for example a result of inefficient fecundity, high abortion or pre- dispersal seed predation (Garcia 2001, Terborgh et al. 2011, Xu et al. 2015b). Once the pre-dispersal 56

Chapter 3 seed predation filtering is overcome, the seed dispersal itself becomes the next step. Beyond improving the chances to escape from density-dependence mortality, seed dispersal is the only way to promote the beneficial or sometimes obligatory movement of plants, for example to colonize abandoned or reforested areas (Schupp and Fuentes 1995, Nathan and Muller-Landau 2000). In Mediterranean, beyond the predominant oak trees species ( Quercus sp. ), up to 60% of the plant species need animals to have their seeds dispersed, an indispensable, and often underestimated interaction in the active or passive restoration pathway where with mammals and birds are the main vectors (Jordano 2000, Gómez 2003). Beyond their trophic complementarity (different fruit species in their diet), mammals generally present a less constrained seed dispersal spatial pattern, for example depositing seeds in areas deprived of vegetation or taking benefit of human-made soft linear structures like unpaved roads (Rosalino et al. 2010, Peredo et al. 2013, Suárez-Esteban et al. 2013b, Escribano-Avila et al. 2014). Birds on the other side usually disperse more seeds from a wider variety of species than mammals, although they tend to highly concentrate their seed rain, like for example under trees or shrubs (perches), with lower contribution towards areas deprived of woody vegetation (Pausas et al. 2006, García 2016). Due to this behavior, bird seed rain is a good “thermometer” to evaluate for example whether these perches, both natural or planted, are effective in attracting seeds versus a fragmented or degraded area, a basal proxy of the capacity of the deforested or degraded area in get restored (Martínez and García 2016). Once the seed dispersal limitation is overcome, the fate of the dispersed seeds is far from be secured, as post- dispersal seed predation, unsuitable microhabitat conditions, herbivory and drought are some of the further filters that can halt the evolution to further stages, generating the establishment and consequent recruitment limitation (Jordano and Herrera 1995, Mendoza et al. 2009, Schupp et al. 2010). Considering a seedling established in a suitable microhabitat, usually it will have to compete for resources (e.g. water, light, nutrients) with intra and inter specific neighbors (Verdu and Garcia-Fayos 1996, Valladares et al. 2008, Gómez-Aparicio 2009). Notwithstanding, in some hostile conditions (e.g. overbrowsing, water stress) this competitive environment could be revealed as the only suitable site, considering that seeds falling in open areas (e.g. grasslands) tends to have much lower or even null probability of long-term recruit than under the competitor (Jordano and Schupp 2000, Martínez and García 2016). In these conditions, a seed that is deposited close or under some pre-existing plant can benefit from a positive outcome, where the association is beneficial, at least in the most fragile early stages, the so-called facilitation or nurse effect (Callaway and Walker 1997, Garcia and Obeso 2003, Gómez-Aparicio et al. 2004, Bonanomi et al. 2011). However, different species, with different traits, in different climatic conditions should perform differently this nurse effect, especially in a scenario where non-native species are also interacting (Bonanomi et al. 2011). Nonetheless, even if seed dispersal limitation, recruitment limitation and facilitation are relatively well studied processes in Mediterranean, 57

Chapter 3 most studies are concentrated in some regions (e.g. Spain), while vast tracts, with their differences in species composition, abundances and land use history, still scarcely studied (Alias et al. 2010). Moreover, whether natural growing trees and planted trees are more efficient in contrasting these limitations and promote facilitation, as well as how different species perform they role in the same system still need to be better understood, as the responses should be very context-dependent, for example along different community assemblages. Here we assessed the cumulative seed rain and recruitment richness, density and their spatial structure, aiming to verify whether these parameters differed across two natural regeneration and two planted trees in a woodland pastureland surrounded by the last large forest remnant in western Sicily. We used seed traps and sampling ground quadrats focused on the two most abundant tree species composing the natural regeneration, presenting similar morphological structure but with different fruit types and dispersal vectors (birds and mammals) as well as the two abiotically dispersed species of trees previously planted in our study site. We also assessed the variations in the density and richness of recruits across the different life stages under each of the target trees, in an attempt to depict the long term recruitment potential including eventual signs of facilitation among plants. We also propose a simple qualitative method to incorporate seed rain and recruitment in the evaluation of the performance of plant species in passive and active restoration areas.

Methods Study site For a detailed description see general study area.

Trees selection In order to compare the richness and density of the seed rain (seeds dispersed by birds) and the different stages of recruitment (seedlings, saplings, juveniles) of natural regeneration (hereafter NR) against planted trees (hereafter PT), we selected two species for each group. The two natural regeneration trees, Pyrus amygdaliformis (hereafter Pyrus ) and Crataegus monogyna (hereafter Crataegus ) are the most abundant trees in the woodland pasture. These species present similar morphological traits (height, diameter, branching structure, deciduity), but are almost exclusively dispersed by mammals and birds, respectively (Bueno et al., in prep. – see Chapter 2). The PT are Fraxinus angustifolia (hereafter Fraxinus ) and Pinus halepensis (hereafter Pinus ), both dry-fruited wind dispersed species that differs in their morphological structure regarding the natural regeneration trees, with Fraxinus presenting a higher mean height, a lower density canopy with few ramifications while Pinus presents a dense, evergreen canopy with the highest height of all species. Fraxinus corresponds to 58

Chapter 3 more than 99% of the planted individuals, None PT species occurred naturally at Alpe Cucco. Seeds and recruits from the above-mentioned species will be referred will the abbreviated full name (e.g. C. monogyna ).

Bird seed rain To evaluate the magnitude of the bird seed rain, we selected 201 individual trees distributed across the three study plots ( Crataegus N = 61, Pyrus N = 68, Fraxinus N = 62 and Pinus N = 10). Both Crataegus and Pyrus individuals had quite similar height (3.65 ± 0.92 and 4.04 ± 1.35 SD) and diameter of the canopy (3.69 ± 1.38 and 4.08 ± 1.74; Mann Whitney: Z= -1.44, p = 0.15, and Z= -1.28, p = 0.19, respectively for height and diameter). Fraxinus and Pinus presented a mean height of 5.49 ± 1.60 and 9.63 ± 3.05 and canopy diameter of 4.01 ± 1.69 and 7.5 ± 2.27, respectively, differing in both aspects (Mann Whitney: Z= 4.01, p < 0.001 , and Z= 3.93, p < 0.001, respectively for height and diameter). Under each tree we installed one seed traps (2 under each Pinus ), made with recycled wood boxes measuring 60x40x8cm (0.24m²), with a fine-pore mesh at the bottom to retain small seeds but enable water drainage, and a 1x1cm wire mesh top cover to prevent seed predation by vertebrates. The seed traps were heterogeneously distributed throughout all plots covering from the edge of the forest to the furthest distances in the matrix, with 67 seed traps at plot 1, 77 at plot 2 and 67 at plot 3. To isolate the effect of each tree species, the seed traps were located only under monospecific crowns, without large fleshy-fruiting shrubs underneath the canopy and no other species of fleshy fruits above the traps. Seed traps were checked every two months, and all present seeds were collected and identified with the aid of a reference collection at the University of Palermo.

Plant recruitment To characterize the woody plants recruitment, both in terms of abundance and richness of seedlings, saplings and juveniles, under each of the sampling trees we established three 1m² quadrats, distributed in an standardized design, with 2 quadrats on the left and one on the right side of the trunk, following a south-north axis. For Pinus we established 4 quadrats, 2 on each side of the trunk. At each quadrat we counted and identified at the species level (using reference photographs when needed) all woody plant recruits, differentiating in 4 height size classes: 1 (5-10), 2 (11-50), 3 (51-100) and 4 (> 100 cm). We also included non-woody fleshy fruited plants like Ruscus aculeatus and Arum italicum. The classes 1 and 2 represent the early establishment stage, as well as the most mortality-prone stages, whereas the classes 3 and 4 represent juvenile individuals with a high survival probability. For species that usually present multiple stems, like Asparagus acutifolius , Rubus ulmifolius and Ruscus aculeatus , a single individual was considered when a stem patch was clearly separated by at least 25cm from each 59

Chapter 3 other. For Prunus spinosa , a species that usually present clonal growth, we assumed that each trunk/stem separated by at least 25cm was a different individual.

Data analysis To assess whether seed rain and recruitment differed among NR and PT as well as within each species, we used the number of seed species and the density of seeds (number per m2) present in the seed traps, and the number of recruit species and the density of recruits (number per m2) present in the ground quadrats as response variables. None of these variables met the requirements for parametrical analysis, and thus, we used repeated pairwise Mann Whitney U test to compare whether richness and density differed. We used Spearman correlation to test the level of association between the densities of the individuals of the smallest class 1 with the density of the classes 3 and 4 across the different tree species. To assess the spatial distribution of the dispersed seeds and recruits at the trees along the plots we used spatial analysis by distance index (SADIE) methodology (Perry et al. 1999). With this approach the count data of each georeferenced point-based sampling, represented in our study by richness and density of each sampling tree in each study plot, are moved until the values are equally distributed across the sampling points, resulting in a global aggregation index ( Ia ) and their respective p values (obtained through randomization procedure), identifying both clusters with low values or high values. We used this index to calculate the global index (all species pooled) for each plot as well as to compare whether the spatial distribution of the seed rain and recruitment richness and density varied within each tree species across each plot. As Pinus were highly aggregated and unequally distributed (6 in plot 1 and 4 on plot 2, absent in plot 3) we excluded this species from the species-specific analysis. Sadie aggregation index were obtained with the software SadieShell 2.0. At the end, we present a potential effectiveness index to be calculated in areas under active restoration. The objective is to incorporate, at least qualitatively, the presence of interactions (seed dispersal and plant-plant co-occurence) as a global and specific indicator of the effectiveness of the restoration and the species used. The index was calculated with the proportions of observed plant species that were registered in the seed traps and on quadrats for each of the tree species, from the total pool of species registered in all trees. Then taking the average index of the two species composing natural regeneration ( Crataegus and Pyrus ) and plantation ( Fraxinus and Pinus ) we obtained the global index, ranging from 0 (no seed dispersal/association) to 1 (all observed seed dispersal/associations). Also for each plant species we did the same procedure, but considering the presence in seed traps and quadrats for each of the four trees, in a rank from 0.1 (very rare) to 1 (omnipresent).

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Results

Bird seed rain In total 2314 seeds from 12 different fleshy fruited species were collected in the seed traps (Tables 1, 5). Seeds from wind dispersed plants ( Acer campestris n = 152 , and Fraxinus angustifolia n = 689) were also present, but were not considered in the following analysis. The average seed rain density was 45.7 ± 5.74 (SE) seeds/m² with an average richness of 2.58 ± 0.12, ranging from 1 up to 8 species in the same trap. Five species accounted for more than 93% of the seeds, with C. monogyna the most abundant with 39.4% of the seeds, although R. ulmifolius and R. canina were fairly the most abundant species in all trees excluding Crataegus (Figure 1). The seed rain under NR was more dense and richer than the one falling under the PT (Mann Whitney Z = -6.25 p < 0.001 and Z = -6.36 p < 0.001) (Table 1). Crataegus trees alone received 68% of seeds. Even excluding the high intra-specific Crataegus seed rain (51.9% of the seeds belonging to C. monogyna ), this tree species still received 54.3% of the remaining seeds. Both Crataegus and Pinus presented 100% of chance to receive at least one seed, while 73.5% of the Pyrus and 46.8 % of Fraxinus traps followed the same pattern. Crataegus was superior in both seed rain density and richness than Pinus (Z = -2.29, p = 0.02 and Z = -2.31, p = 0.02) and fairly superior regarding Pyrus and Fraxinus (p < 0.001 in all cases). Pyrus in turn presented higher density and richness than Fraxinus (p < 0.001 in both cases) while both presented lower values than Pinus (p < 0.001 in all cases).

Table 1. Natural regeneration ( Crataegus and Pyrus ) and planted ( Fraxinus and Pinus ) focal trees, number of seed traps installed in each tree species, area sampled with the traps, probability of dispersal (percent of traps with at least 1 seed), mean density (± SE) of seeds and richness of species (total number of species).*2 traps per individual Mean Probability of N Density Tree Species N Traps Area m² richness dispersal (%) seeds (m²) (total) Crataegus 61 14.64 100 1580 107.9 (15.7) 3.6 (12) Pyrus 68 16.32 73.5 449 27.5 (4.9) 2.1 (11) Fraxinus 62 14.88 46.8 123 8.3 (1.7) 1.5 (6) Pinus 20* 4.8 100 161 33.7 (12.3) 2.3 (4) Natural regeneration 129 30.96 86.1 1703 65.5 (8.6) 2.9 (12) Planted 82 19.68 47.6 610 14.4 (2.3) 1.7 (6)

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Figure 1. Proportional contribution of the five most abundant species for the total number of seeds sampled under natural regeneration individuals ( Crataegus and Pyrus ) and planted trees ( Fraxinus and Pinus ). Other species comprehend the 7 remaining species that accounted to less than 7% of the seeds, not evenly present in all trees.

Recruitment We found 1903 recruits of 18 plant species inside the quadrats, with an average density of 3.09 ± 0.24 (SE) individuals/m² (Table 2). Seven plant species, all fleshy fruited, accounted to more than 82% of the individuals, where the most abundant was Prunus spinosa with 18.4% (Figure 2). The rarest species was Ulmus minor with just 0.05%. The pattern varied across the different tree species, with R. aculeatus been the most abundant recruit under Crataegus (22.5%), P. spinosa under Pyrus and Fraxinus (19.8% and 36.3%) and R. ulmifolius under Pinus (27.6%) (Figure 2). The late successional oak trees ( Quercus pubescen and Q. ilex ) accounted to 6% of the recruits, where 84.3% were equally distributed under the NR trees, while Acer campestris represented just 0.15%, one under Crataegus and two under Pyrus . The height class 2 (11-50 cm) was the most represented with 34.2% of the individuals, followed by class 1 (5-10 cm) with 28.4%, class 3 (51-100 cm) with 26.3% and the tallest class (>100cm) with 11.1% (Figure 3). A. acutifolius was the specie with the most equalized density distribution along the 4 size classes, from 0.04/m² at class 4 up to 0.18/m² at class 1, while for example P. spinosa had 0.02/m² at class 1 and 0.33/m² at class 3, the highest density of a single species considering all classes (Figures 3, 4). The oak trees followed the typical decreasing trend, with 46.6% at class 1, 37.2% at class 2, 14.4% at class 3 and 1.7% at class 4.

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Table 2. Tree species, number of individuals analyzed, area sampled with the quadrats, probability of recruitment (percent of individuals with at least one recruit), mean density (± SE) of recruits and richness with the total number of recruit species. Probability of Mean Sampled N Density Tree species N recruitment richness area (m²) recruits m² (%) (total) Crataegus 61 183 96.7 887 4.8 (0.5) 4 (17) Pyrus 68 204 75.1 509 2.5 (0.3) 3 (16) Fraxinus 62 186 70.5 315 1.7 (0.3) 3 (13) Pinus 10 40 90 192 4.8 (1.2) 4 (10) Natural regeneration 129 387 85.2 1396 3.6 (0.3) 3.5 (18) Planted 72 226 73.2 507 2.2 (0.3) 2.5 (13)

Figure 2. Proportional contribution of the 7 most abundant species for the total number of individuals sampled under natural regeneration individuals ( Crataegus and Pyrus ) and planted trees ( Fraxinus and Pinus ). Others species comprehend the 11 remaining species that accounted to less than 18% of the individuals not evenly present in all trees.

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Figure 3. Density (number of recruits per m²) of the seven most abundant species in each of the 4 size classes. Panel A shows the general demographical trend including all species.

Figure 4. Mean (± SE) recruitment density in each of the 4 size classes registered in the quadrats sampled under natural regeneration individuals ( Crataegus and Pyrus ) and planted trees ( Fraxinus and Pinus ).

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Concordance of seed rain and recruitment Natural regeneration had higher probability to have at least 1 recruit regarding PT (X² = 4.09, p = 0.04) and the overall recruitment density and richness was also higher in NR regarding PT (Z = -3.04 p = 0.002 and Z = -2.82 p = 0.004 respectively) (Figure 5). Crataegus had higher density and richness of recruit regarding Pyrus as well as Pinus regarding Fraxinus (p < 0.001 in all cases), although in the comparison of Crataegus with Pinus and Pyrus with Fraxinus no significant differences in the richness and density of recruits were found (p > 0.05 in all cases).

Figure 5. Mean (± SE) values of seed rain and recruitment density and richness registered in the seed traps and in the quadrats sampled under natural regeneration individuals ( Crataegus and Pyrus) and planted trees ( Fraxinus and Pinus ). Note the different scales.

The seed rain and recruitment richness and density presented predominantly random spatial patterns across the species in all plots, with just 5 cases resulting significant for aggregation (P < 0.05), where three and two cases at the same plots for Crataegus and Fraxinus , respectively, and one case for Pyrus at plot 1 (Table 3).

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Table 3. SADIE index of aggregation Ia (P-value) of seed rain and recruitment richness and density calculated for each of the tree species across the three study plots.

Seed rain Seed rain Recruitment Recruitment PLOT density richness density richness

1 1.07 (0.34) 0.87 (0.67) 1.33 (0.08) 1.19 (0.18) Crataegus 2 0.63 (0.97) 1.02 (0.37) 0.99 (0.40) 0.78 (0.81) 3 1.36 (0.08) 1.54 (0.03 ) 1.59 (0.03) 1.64 (0.02) 1 1.33 (0.12) 0.83 (0.69) 1.73 (0.03) 1.37 (0.10) Pyrus 2 0.97 (0.45) 1.01 (0.38) 1.32 (0.11) 1.26 (0.14) 3 1.43 (0.07) 1.15 (0.22) 1.12 (0.25) 0.76 (0.85) 1 2.24 ( 0.002 ) 1.08 (0.31) 1.57 (0.49) 1.76 (0.02) Fraxinus 2 1.19 (0.20) 1.04 (0.34) 0.69 (0.90) 0.83 (0.69) 3 0.96 (0.45) 0.96 (0.46) 0.57 (0.93) 0.97 (0.44)

Plant-plant association Excluding Crataegus , all other tree species presented significant positive correlation between the density of recruits from class 1 with the density of recruits from class 3 and 4 (Table 4). However just F. angustifolia presented strong positive correlation when considering just the individuals from the class 4, and Pinus presented a marginally significant positive correlation (p = 0.07), suggesting that the recruitment abundance under these trees could be more dependent on some kind of facilitation provided by taller recruits of other species, especially the most abundant recruits of class 4 ( P. spinosa , R. ulmifolius and R. canina ). Conversely, at the analyzed fruiting season, the densities of seed rain and recruitment were only concordant within the two NR trees (Table 4).

Table 4. Spearman indexes (p-value) correlating for each different trees the density of recruits from the height class 1 with the pooled density of recruits from classes 3 and 4 and only class 4 and the correlation between the seed rain density and recruitment density. In bold significant values (p ≤ 0.05).

CLASS 1

Seed rain x Class 3 / 4 p Class 4 p p recruitment

C. monogyna 0.11 0.38 -0.13 0.31 0.29 0.02

P. amygdaliformis 0.39 0.001 0.08 0.47 0.34 0.003

F. angustifolia 0.31 0.01 0.32 0.01 0.07 0.57

P. halepensis 0.59 0.05 0.56 0.07 0.29 0.40

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1.83 (0.01) 0.81 (0. 79) 0.86 (0. 64)

1.41 (0. 08) 0.7 (0. 95) 1.04 (0. 35)

Figure 6. Distribution of seed rain richness and density of the four tree species across the three study plots. The size of the circle represents proportionally each value. In the background the woody vegetation cover. In the right upper corner the respective global SADIE aggregation index Ia (p values) considering all species.

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2.3 (0. 002) 1.25 (0. 13) 1.5 (0. 06)

1.96 (0.005) 1.34 (0. 08) 1.54 (0. 05)

Figure 7. Distribution of recruitment richness and density of the four tree species across the three study plots. The size of the circle represents proportionally each value. In the background the woody vegetation cover. In the right upper corner the respective global SADIE aggregation index Ia (p values) considering all species.

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1 2 3

4 5 6

7 8 9

Figure 8. Example of the methods and the situations reported in the text. Legend: 1) Seed traps and sampling quadrats under Crataegus monogyna , 2) Class 2 (10 – 50cm) Asparagus acutifolius (3) Class 1 (05 – 10cm) Quercus ilex growing protected by a class 3 (50 - 100cm) Ruscus aculeatus 4) Pyrus amygdaliformis and Crataegus monogyna differentiated only by the fruit type, with equal imbricated branching structure 5) Planted Fraxinus angustifolia with no recruitment underneath 6) Old individual of P. amygdaliformis in a tree-shape structure with no recruits underneath 7) C. monogyna with highly imbricated branching structure providing elevated protection against large herbivores 8) C. monogyna seed captures in the seed trap 9) Example of imbricated structure provided by recruit-recruit associations under the non-protective Quercus pubescens.

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Discussion In our study we revealed the magnitude in which natural regeneration was superior than human PT in both richness and density of seed rain and recruitment in a woodland pasture surrounded by the last large forest remnant in western Sicily. Beyond the variations among these two groups, all four tree species presented different patterns, including differences within individuals of the same species, although with a common dominant random spatial pattern across all the study plots. Considering the high proportion of trees, especially the NR, that received seeds and have recruits underneath, seems that, in a community-level, at the observed fruiting season, a weak local (tree level) and landscape (plot level) seed dispersal and recruitment limitation occurred. Many of the analyzed trees, especially from NR, presented a relative high accumulated diversity underneath, despite the expected overall decrease trend in recruiting along the size classes. However, the most abundant fleshy-fruited shrubs occurring in our study site presented an inverted trend along the size classes, suggesting a stronger filtering at the early stages generated by some kind of post-dispersal limitation.

Bird seed rain Most of the trees evaluated in our study received at least one seed, with the global SADIE index suggesting a predominant community-level spatial randomness in both seed rain richness and density along the study plots. Although this pattern is expected to suffer inter-annual variations (Hampe et al. 2008), for example in a temperate woodland pasture, García et al. (2013) found a highly clumped pattern of seed rain for three bird-dispersed tree species, including C. monogyna, while Morales et al. (2013) also found the clumped pattern for simulated seed rain in this same system. Possibly, in our site, regardless the lower diversity of bird seed dispersers, the higher spatial heterogeneity of the woody cover and consequent fruit abundance in the pastureland, with less empty spaces, could be a potential explanation for this difference, considering that also their pastureland have fleshy fruited plants. Interestingly however, a predominant random pattern of density and richness of seed rain was also found in a totally covered plot inside the Atlantic Forest (Rother et al. 2015). The majority of the bird- dispersed fleshy fruited species occurring inside the study plots were represented in the seed rain, even if just five species corresponded for the bulk of seeds. Excluding P. spinosa that did not fructified, the first three and the fifth most abundant species in the seed rain, C. monogyna , R. ulmifolius , R. canina and A. acutifolius were the most abundant fruit species in the matrix, while complementary, the fourth most dispersed species, H. helix was the most abundant fruit in the forest (R. S. Bueno, unpublished data). Nonetheless, seed density is just a partial indicator of the strength of the interactions, as R. ulmifolius and R. canina, species with the highest density in all trees except Crataegus , have several seeds per fruit (Herrera 1989), while C. monogyna , H. helix and A. acutifolius roughly 1 or 2, which can 70

Chapter 3 be traduced in much more time spent visiting those species. Also phenology matters here, as all these abundant species overlap just partially their fruiting seasons peaks (Gyan and Woodell 1987), avoiding strong competition for frugivores, diluting though the proportion of seeds dispersed. Clearly, NR species were superior in concentrating seeds from a wider variety of plant species than the PT, especially confronting with the predominant Fraxinus . We found a considerable amount of C. monogyna seeds under Crataegus trees , a common pattern found also in other bird dispersed plants (Herrera and García 2009, Carlo et al. 2013). Even if we could not differentiate if it was inter or intra- individual dispersal, in any case, Crataegus trees presented the highest density of heterospecific seed rain, undoubtedly been the most effective perch. Although presenting just one seed species less than Crataegus , Pyrus presented more than four times less seeds, distributed in a proportion quite similar to the PT, leading to an interesting point. Both species share the same morphological characteristics, with similar height, canopy size, architectural disposition of the branches, as well as lose their leaves in late autumn, often been hardly differentiated at distance in the field, presenting though no clear structural differences as a perch. Indeed, a crucial difference do exists, as Crataegus bear small fruits heavily consumed and dispersed by a wide variety of birds species, while Pyrus larger fruits, widely dispersed by mammals, represents more an occasional meal for pulp eating birds (Fedriani and Delibes 2009, see also Chapter 2). In this way, we can infer that differences in fruit type should be the main explanation for the differences, a pattern also found in dioecious species (Garcia et al. 2005b, Escribano-Avila et al. 2012). From the four species, Fraxinus was the one that performed poorly the role of perch in terms of seed rain richness and density, regardless of been widespread across the surface of plots 1 and 2. We do not know exactly why this pattern was observed, but a combination of factors can be hypothesized. Contrary to the other NR trees, Fraxinus have dry wind dispersed fruits, offering though no reward for frugivores. Most of the individuals are surrounded by a more attractive fruit rich neighborhood that could act as magnets deviating the birds towards these other perches. Although Fraxinus individuals have many horizontal non-imbricated branches apparently more suitable for perching, the canopy is less dense than Crataegus or Pyrus , probably resulting in a higher degree of exposition and consequent avoidance by birds. Anyway further studies have to been made to assess for example whether this pattern is consistent across time, if different contexts (e.g: low density of more attractive neighbors) could generate a different pattern or even if this PT are serving as stepping stones fostering the seed dispersal further away. Contrary, the planted Pinus individuals presented the second highest density of seeds after Crataegus . This could be an outcome of morphological differences, as in our site Pinus individuals can be twice as higher than other trees, especially of NR ones, a parameter known to influence bird activity (Jordano and Schupp 2000, Martínez and García 2015). Another potential factor could be that, contrary to the other species, Pinus are evergreen, providing a dense shelter in all 71

Chapter 3 seasons. Notwithstanding, all the seed rain belonged to just 4 species, and 8 of the 10 individuals were immersed in woody patches, a favorable scenario for seed dispersal. Moreover, Pinus individuals were observed to be highly used just by some few bird species (Jordano and Schupp 2000), and generally P. halepensis plantations present worse performance than natural vegetation in several aspects (Maestre and Cortina 2004). For example, Zapata et al. (2014) found that just a very small fraction of the dispersed seeds from 3 fleshy fruited shrubs, including A. acutifolius , were deposited under the canopy of an old P. halepensis forest. In any case, we are aware that our small sample size limits the interpretation of the results for this specie. Additionally, Prunus spinosa, one of the most abundant woody species in our site, with fruits avidly consumed also by birds (Chapter 2), practically presented no mature fruits during the fruiting season sampled with the seed traps, a considerable gap in our data.

Recruitment, concordance and facilitation Most of the individuals analyzed in our study presented at least 1 recruit underneath, and the overall seed rain density was correlated with recruits density. A similar high presence of recruits was found under different trees, including C. monogyna, in a study in Sardinia, Italy (Alias et al. 2010) although a different pattern, with lower recruits and uncoupled seed – recruitment density was found in montane Mediterranean areas in Spain (Mendoza et al. 2009, Andivia et al. 2017). In the landscape scale, the recruitment clumped spatial pattern was uncoupled with the random seed rain pattern, as some trees with few or none seed arriving presented some or many recruits, with the inverse also observed. This spatio-temporal uncoupling seems to be a recurrent event inside the seed dispersal - recruitment system (Jordano and Herrera 1995, Traveset et al. 2003, Garcia et al. 2005b, Gómez- Aparicio 2008), although consecutive random patterns across years were also observed elsewhere (Rother et al. 2015). While seed rain is a highly dynamic process, changing immediately with changes in fruits and frugivores, in a stable system like ours, where for example fire is absent, recruitment is a lagged cumulative event, leading to alternation from concordance and discordance. The higher superiority of NR in promoting restoration has been highlighted recently as a general pattern, where many reasons do exist (Crouzeilles et al. 2017, Meli et al. 2017). In our site the PT did presented a considerable seed rain and a reasonable density of recruits, contributing indeed attract seeds and promote recruitment in the woodland pasture. But comparatively, their richness and density values were much lower than the NR trees, especially considering the most abundant Fraxinus . Beyond the presence or absence of fleshy fruits, architectural morphology seems to be playing a determinant role (Küppers 1989). If undisturbed, all four species considered in our study will tend to growth with typical tree shape, with a straight non or low-ramified trunk ending in a ramified canopy. However, in the presence of herbivory, these species can present different response mechanisms. Pinus have very 72

Chapter 3 low morphological plasticity, dying or continuing growing in the tree-shape format in a much slower rate under herbivory (Zamora et al. 2001). Fraxinus , with its very palatable leaves, usually dye in the presence of strong herbivory in the younger stages, even if some level of response through basal ramification can exist, although usually not creating an impenetrable barrier (R. S. Bueno, pers. obs.). Conversely, both Crataegus and Pyrus , beyond having thick and sharp spines, strongly respond creating a very complex imbricated structure, with several branches departing from all parts of the trunk and in all directions (R. S. Bueno, pers. obs.). Surely, this natural imbricated structure is much more protective against herbivory, and probably will produce a stronger umbrella effect against water stress, the two most common recruitment filters in Mediterranean communities (Jordano and Herrera 1995, Rey and Alcántara 2000, Garcia 2001, Gómez-Aparicio et al. 2008). However this protective effect would be stronger against large mammals, as small herbivores like rabbits and specially rodents can access practically all areas (Bakker et al. 2004). In our site rabbits and hares are not abundant but small rodents such as Apodemus sylvaticus are (R. S. Bueno unpublished data). These small rodents are important factors to be considered when talking about recruitment, as they are capable of strongly shuffle primary dispersal while unconstrained by the imbricated vegetation (Garcia et al. 2005a, Pons and Pausas 2006, Smit et al. 2008). Most of the recruit species in our study had a general decreasing density trend across the size classes, that can be initially explained by the expected natural demographical pyramid (Jordano and Herrera 1995). However, the functional traits of the trees and recruit seem to also matter here. For example, established individuals of climbing species like A. acutifolus and R. peregrina and strictly umbrofilous species like R. aculeatus were the most abundant under the imbricated Crataegus structure, while contrarily, the non-climbing light demanding Prunus spinosa was by far the dominant recruit under Fraxinus . However, we verified that once these P. spinosa individuals growth in structural complexity, they became capable by themselves in create an imbricated structure (Bakker et al. 2004), allowing though climbing, umbrofilous or herbivory sensible species to occur, in a facilitation loop no longer dependent only on the perch traits (Olff et al. 1999, Smit and Ruifrok 2011). Although this hypothesis need to be checked with further species-specific analysis, this recruitment-level association could be playing an important role in generating the observed Pinus high density and richness values, given that this species, with their right non-ramified trunk, offer no kind of herbivory protection, and usually presents low recruitment underneath (Maestre and Cortina 2004). Additionally, beyond the morphological and physiological changes occurring along plant growth (Navas et al. 2010), this evolution surely will bring microclimatic variations, as observed even in non woody species (Soliveres et al. 2010). We found a considerable number of trees with a relatively high assemblage diversity (up to 6 species) of established recruits. Which are the above and below ground mechanisms allowing this co-existence is an 73

Chapter 3 interesting frontier to be explored, especially considering the ontogeny of perches and their recruits under this dynamic and multivariate structural complexity. We are aware that the abundance of class 4 recruits can be extrapolated just partially to the other individuals in our site, as there were a considerable number of trees, especially of Crataegus and Pyrus , that had large fruiting shrubs associated (mainly R. canina, R. ulmifolius and A. acutifolius ), that were deliberately not included in our sample to avoid bias in the seed rain data. Although we cannot discard that some of the recruits of the smaller classes could have been originated by the reproductive individuals of the taller classes, the class 3 is a quite robust representation of the established stage in all cases, also because it encompasses species that rarely growth beyond (ex. R. aculeatus and D. laureola ). In an applied perspective, the abovementioned morphological trend can be highly useful, for example in active restoration. Assuming a fenced area where seedlings of Pyrus and Crataegus , were planted. The herbivory exclusion should make the seedlings to naturally growth with few or no ramifications at lower levels, a pattern also observed in other species (Pausas et al. 2006). But eventually, after some time, herbivores (wild, domestic or both) browsing pressure suddenly became continuously or randomly present, where the lower ramification of the planted individuals will provide few or no protection for eventual recruits. Considering the morphological tradeoff, a good management practice could be permit a controlled level of browsing, at a determined stage of plant growth, after establishment, in order to shape the architecture versus this protective nurse mood (Garcia and Obeso 2003), that should guarantee higher probabilities of recruitment of the further dispersed or planted species. On the other side, protecting them until they became a true tree (e.g. with individual shelters) could be an interesting management practice to enhance the natural value of silvo-pastoral systems where production is the main objective, leaving the space for grasslands while providing fruit resources for the wild as well as domestic animals (see chapter 2). One of the most intriguing results however is the very low density of class 1 and 2 recruits, respect to classes 3 and 4, of the most abundant shrubs ( P. spinosa, R. canina, R. ulmifolius ) and trees (Crataegus and Pyrus) occurring in our site. Albeit our lack of data regarding P. spinosa seed dispersal on traps, all three shrub species have their fruits avidly consumed by a wide range of mammals and birds (Chapter 2) and their seeds were found in all trees, which suggest that some kind of post-dispersal filtering is occurring. Pyrus in turn is fairly the most abundant tree species and yearly produces large amount of fruits whose seeds are widely and viably dispersed by most of the mammals, including cattle (see Chapter 2). While this large mammal should avoid intricate spiny vegetation, many of the sampled quadrats were accessible to Pyrus main disperser, red foxes (see Chapter 2), suggesting that seed dispersal limitation should also be of low concern. While later stages should be simply limited by for example light constraints (Olff et al. 1999), at least for the very young seedlings (e.g. class 1), even the 74

Chapter 3 higher shading promoted by the imbricated vegetation should not be a full constraint, and herbivory by large mammals in many cases should be low or zero. Complementarily, all species have almost no seedlings and very few saplings in the pastureland (R. S. Bueno per. obs .). Even considering that a reasonable seedling mortality could occur (Kollmann and Grubb 1999) and that small mammals can largely predate seeds and browse seedlings (Bakker et al. 2004, Smit et al. 2010), this post-dispersal bottleneck have to be deeply investigated, as negative shifts in the demography of these plants would represent an enormous change in the whole landscape, for example hindering the secondary succession and ecosystem services they provide. Our results corroborated the findings that tree directed seed dispersal and perch-recruit and recruit-recruit interactions are key processes molding the secondary succession also in our mesic Mediterranean woodland pasture. Notwithstanding, most facilitation studies evaluated the effect of dry-fruited shrubs species, (e.g Retama, Cistus), on late successional tree species (e.g Quercus sp ., Pinus sp . and Juniperus sp .) (Castro et al. 2002, Gómez-Aparicio et al. 2008, Smit et al. 2008, Cuesta et al. 2010, Andivia et al. 2017, Costa et al. 2017), where community-wide studies incorporating a variety of fleshy-fruited species are more rare (i.e. Gómez-Aparicio et al. 2004, Siles et al. 2010, Rey et al. 2016). In this sense our study set the template for deeper investigations about the role of facilitation in this Mediterranean woodland pasture, both from the nurse as from the recruit perspective, and indicate Crataegus and Pyrus as excellent options to enhance the potential of success of either passive or active restoration as well as enrich silvo-pastoral systems.

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Table 5. Families, species, growing habit and main dispersal syndrome of the plants species found in the seed traps (ST) and quadrats (Q) under the two natural regeneration and two planted trees species, with their respective qualitative evaluation indexes (0 poor – 1 good). Mixed = birds and mammals. * Quercus sp. - potential species Q. pubescens . NA = no mature fruits during sampling.

Natural regeneration (0.70) Planted trees (0.42) Crataegus (0.72) Pyrus (0.67) Fraxinus (0.47) Pinus (0.37) Dispersal Total Family Specie Habit ST Q ST Q ST Q ST Q syndrome Index Aceraceae Acer campestris Tree Wind x x x x x 0.6

Araceae Arum italicum Shrub Birds x 0.1

Araliaceae Hedera helix Liana Birds x x x x x x x x 1.0 Asparagaceae Asparagus acutifolius Liana Birds x x x x x x x 0.9

Dioscoraceae Tamus communis Liana Birds x x 0.3

Fabaceae Calicotome infesta Shrub Gravity x x 0.3

Fagaceae Quercus ilex Tree Mixed x x x x 0.5

Fagaceae Quercus pubescens Tree Mixed x* x x* x x* x x* x 1.0 Oleaceae Fraxinus angustifolia Tree Wind x x x x 0.5

Oleaceae Fraxinus ornus Tree Wind x x 0.3

Rosaceae Crataegus laciniata Tree Birds x x 0.3

Rosaceae Crataegus monogyna Tree Birds x x x x x x x 0.9

Rosaceae Prunus spinosa Shrub Mixed NA x NA x NA x NA x 1.0 Rosaceae Pyrus amygdaliformis Tree Mammals x x x x x x 0.8

Rosaceae Rosa canina Shrub Mixed x x x x x x x x 1.0 Rosaceae Rubus ulmifolius Shrub Mixed x x x x x x x x 1.0 Rubiaceae Rubia peregrina Liana Birds x x x x x x 0.8

Ruscaceae Ruscus aculeatus Shrub Birds x x x x x x 0.8

Thymelaeaceae Daphne laureola Shrub Birds x x x x 0.5

Ulmaceae Ulmus minor Tree Wind x 0.1 Total 20 12 17 11 16 6 13 5 10 76

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CONCLUSIONS

• The combined effect of passive and active restoration brought fast recovery even in a long-term deforested silvo-pastoral system, although natural regeneration was the main component. This natural regeneration was developed in a spatially structured way, maintaining the overall clumped pattern even after a very strong expansion. • The spatial analyses revealed the structure of the vegetation changes across time, detecting hotspots and coldspots of regeneration, been valuable tools to understand the landscape and local scale patterns and process and consequently planning of active restoration actions. • Mammals and birds had a pivotal role in the observed secondary succession, dispersing the vast majority of the species composing the succession, a highly valuable ecological service. Additionally, birds and mammals performed a complementary role while differing in the diversity of species, quantity of seeds and habitat of deposition, with some degree of modularity in the network. • Even within mammals there was functional complementarity, especially regarding the habitat of deposition, where cattle, red fox and crested porcupine dispersed more seeds in open areas and were the unique to disperse seeds in the soft linear developments, while wild boar and pine marten deposited most seeds in the forest respect to open areas. • Fruit-rich heterogeneous landscapes are very important in maintaining biodiversity and enhancing secondary succession, while in our site the soft linear developments were acting as linear recruitment sinks due to fire-prevention measures. • In the studied fruiting season, a high proportion of trees in the woodland pasture received at least one seed and presented at least one recruit, even those located far from the forest. However, natural regeneration trees received more seeds and presented a higher accumulated abundance of recruits than planted trees, especially when comparing to the most abundant planted tree Fraxinus . Beyond the higher richness and abundance, a sub-set of the seed and recruit species were only found under natural regeneration. • Fruit type and tree branching architecture seems to be important drivers leading to higher seed rain and recruitment under natural regeneration and planted trees, respectively. • There was a partial spatial discordance among seed rain and recruitment in the landscape and local scale, where seed rain was mostly regularly or randomly distributed, both considering the general index with all species pooled, but also comparing the different parameters within each species. Recruitment instead presented a mixed general pattern, been either random or aggregated along the plots, while the species specific patterns were predominantly random. • Even with consistent seed dispersal by both birds and mammals, the most abundant woody species occurring in the woodland pasture presented very low densities of early stages recruits, a potential sign of a recent post-dispersal strong filtering. • Together with seed dispersal, plant-plant associations are important drivers in generating the observed secondary succession, fostered by consequent recruit-recruit facilitation. • Plant-animal and plant-plant interactions, such as seed dispersal and facilitation, are key determinants in both passive and active ecological restoration, and are essential aspects in the evaluation of restoration effectiveness.

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RESUMO GERAL EM PORTUGUÊS

Na região Mediterranea, a longa história de uso e ocupação humana alterou profundamente a distribuição espacial e composição da vegetação nativa. Contudo, recentemente muitas áreas tem sido abandonadas, reflorestadas, restauradas e novamente degradadas, criando diferentes cenários e trajetórias para o desenvolvimento da sucessão secundária. Determinar se estes diferentes cenários levarão para um estado de restauração ecológica, desviar e estabilizar em um estado alternativo ou retornar a um estado degradado, bem como quão rápido e intenso este processo ocorrerá é uma tarefa difícil que requer uma profunda análise espacial e temporal dos padrões e processos gerados ao longo desta sucessão. Um primeiro passo é analisar os padrões espaciais gerados ao longo do tempo, pois estes padrões, além de darem informações a respeito da intensidade da dinâmica, representam de forma explícita o resultado cumulativo dos processos atuantes em determinada área. Embora existam estudos avaliando os padrões da sucessão secundária, a maior parte foi realizada em grandes escalas e pouca atenção tem sido dada à estrutura espacial. Analisando o padrão, uma pergunta que surge é como este foi gerado, considerando que plantas são organismos sésseis. Mesmo que algumas plantas apresentem um crescimento vegetativo, esse padrão é na maior parte fruto da dispersão das sementes. No Mediterraneo até 65% das espécies de plantas necessitam de animais, especialmente aves e mamíferos, para terem suas sementes dispersadas, o que ressalta a ampla importância desta interação ecológica para a sucessão secundária e consequente restauração ecológica. Contudo, apesar da importância destes dois grupos, poucos estudos avaliaram na mesma escala espacial e temporal o papel de aves e mamíferos como dispersores. Todavia, a dispersão das sementes geralmente não é o fator final na determinação dos padrões da vegetação, visto que após a dispersão existem diversos filtros bióticos e abióticos que podem alterar completamente o padrão gerado pelos dispersores. Esses filtros são particularmente ativos em áreas privas de vegetação, sendo que em diversas situações sementes que caem perto de uma planta pré-existente possuem maiores chances de recrutar, seja pela maior proteção contra a herbivoria seja pela melhoria das condições microclimáticas, facilitando o desenvolvimento. Adicionalmente, muitas espécies de aves evitam áreas privas de vegetação, concentrando portanto a chuva de sementes embaixo da vegetação pré-existente. Mas plantas diferentes podem exercer essa facilitação em modo diverso, especialmente onde espécies são ativamente introduzidas pelo homem. Considerando áreas em processo de regeneração natural, essa introdução possibilita a comparação da eficácia das espécies introduzidas e daquelas crescendo naturalmente em promover a restauração ecológica, visando otimizar os investimentos e aumentar a probabilidade de sucesso.

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O objetivo geral desta tese é dar uma perspectiva integrada em escala da paisagem e local sobre os padrões e processos que governam a sucessão secundária em um gradiente de vegetação, considerando a regeneração ativa e passiva, focando em uma análise espacial e temporal detalhada e na incorporação do papel das interações animal-planta e planta-planta na dinâmica da vegetação.

A presente tese foi realizada dentro da Reserva Natural “Bosco Ficuzza, Rocca Busambra, Bosco del Cappelliere e Gorgo del Drago”, uma reserva de 7.400ha englobando o maior remanescente florestal em toda a Sicília ocidental. Especificamente o estudo se concentrou em uma área chamada Alpe Cucco. Esta área de aproximadamente 150 ha, localizada no centro da reserva, foi desmatada quase totalmente já no início do século 20, sendo consequentemente objeto de ações ativas de reflorestamento e atualmente encontra-se em regeneração natural, com predomínio de gramíneas entremeadas com árvores isoladas e fragmentos de vegetação lenhosa rodeados pelo grande remanescente florestal. Existem concessões de pastoreio ativas, consistindo portanto em um sistema silvo-pastoral. Em Alpe Cucco foram estabelecidos três plotes de 500x200m abrangendo o gradiente da floresta para a área aberta, sendo que estes plotes compreendem a área amostral desta tese. A escala temporal compreende de 1992, período em que as atividades de manejo da área se encerraram e a sucessão secundária não foi mais alterada, até o presente.

O primeiro capítulo desta tese teve como objetivos caracterizar o padrão espacial e temporal da sucessão secundária da vegetação lenhosa e verificar qual a influência dos remanescentes de vegetação pré-existentes na configuração espacial e intensidade da regeneração. Os métodos utilizados foram fotointerpretação, análises em SIG, análises espaciais por índice de distância, autoregressões simultâneas e levantamentos em campo. Os resultados demonstram que a vegetação quase dobrou em extensão ao longo dos 24 anos, com um crescimento balanceado das fisionomias arbórea e arbustiva, com a maior contribuição oriunda da regeneração natural composta predominantemente por espécies dispersadas pelos animais. A estrutura espacial geral permaneceu quase que inalterada mesmo diante a grande expansão, mantendo o aspecto agregado. Em dois plotes houve correlação da expansão com a vegetação pré-existente, enquanto a distância para o remanescente florestal e tipo de fisionomia resultaram não significativos. Os resultados demonstram que mesmo em uma situação de desmatamento antigo e em presença de herbivoria por animais domésticos e nativos, a regeneração natural, com um auxílio do reflorestamento estão promovendo uma restauração intensa da área, com um desenvolvimento espacialmente estruturado com pontos com maior ou menor grau de regeneração. Os resultados demonstram que análises deste tipo podem ser muito úteis para planejar ações de restauração, bem como direcionar corretamente os esforços em uma maneira espacialmente explícita.

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Resumo geral em português

O segundo capítulo teve como objetivo revelar o papel das aves e mamíferos na dispersão de sementes, verificando o grau de complementaridade trófica e espacial destes dois grupos e construindo a matriz de interações. Os métodos utilizados foram coleta de fezes diretamente no campo em transectos e plotes distribuídos homogeneamente entre a floresta e a área aberta, armadilhas fotográficas com frutos e armadilhas de sementes nas árvores especificamente para as aves. Os resultados revelam que aves e mamíferos possuem um papel complementar seja em nível trófico que em relação a distribuição espacial das sementes nos diversos habitats, complementaridade também observada entre as espécies de mamíferos. De um lado mamíferos depositaram mais sementes em cada defecação e em ambientes mais abertos, enquanto as aves dispersaram mais espécies de plantas e em maior intensidade, embora com maior restrição espacial. Mamíferos são os dispersores exclusivos da espécie arbórea mais abundante, enquanto as aves são as dispersoras exclusivas da segunda espécie arbórea mais abundante. Em ambos os grupos a maior parte das sementes foi dispersada na matriz silvo-pastoral, provavelmente um reflexo da maior abundância de frutos em relação à floresta. Aves e mamíferos são os responsáveis pela dispersão das sementes de quase todas as espécies de plantas que compõem a sucessão secundária, oferecendo consequentemente um enorme serviço ambiental, atuando de forma complementar e insubstituível.

O terceiro capítulo teve como objetivo verificar a riqueza, densidade e padrão espacial da chuva de sementes e diferentes estágios de recrutamento embaixo de duas espécies de árvores regenerando naturalmente e duas espécies plantadas na área de pastagem. Os métodos utilizados foram armadilhas de sementes, levantamento da vegetação recrutando embaixo da copa das árvores e análises espaciais por índices de distância. Os resultados mostram que a maioria das árvores regenerando naturalmente recebeu ao menos uma semente, com seis espécies únicas, enquanto somente metade das árvores plantadas receberam uma semente, e em geral com uma densidade quatro vezes menor. Com relação ao recrutamento, a regeneração natural apresentou maior densidade e cinco espécies exclusivas, embora mais de dois terços das árvores plantadas também apresentaram ao menos uma plântula. A estrutura espacial global da chuva de sementes e do recrutamento revelou-se predominantemente aleatória nos plotes de estudo, e uma correlação positiva entre a densidade e riqueza da chuva de sementes e do recrutamento foi verificada somente nas árvores da regeneração natural. Houve diferenca significativa entre as espécies que compõe a regeneração natural, com Crataegus monogyna apresentando os maiores valores em todos os parâmetros. A densidade de recrutamento dos estágios iniciais foi positivamente correlacionada com a densidade de recrutas dos estágios mais avançados, sugerindo uma facilitação independente da espécie de árvore. Os resultados também demonstram a baixa densidade de recrutamento das espécies mais abundantes que compõe a sucessão secundária,

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Resumo geral em português indicando um potencial gargalo atuando recentemente que poderá gerar profundas mudanças na paisagem se persistente no tempo.

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Acknowledgements

ACKNOWLEDGEMENTS

First of all I want to thanks my parents, Mario and Rosangela, since the beginning encouraging me to discover, respect and love nature and great enthusiasts of my pathway in ecology since my bachelor course, the initial step that brought me to this PhD. Then, I thank my wife Alba, that accompanied me tightly in all phases along this journey, since those in the Atlantic Forest, been the responsible for my immersion in the wonderful Sicily, and so to this PhD, just leaving the field to assume with natural and lovely dedication the amazing and energy demanding role of mother. Consequently, I thank my daughter Flora, that with her positive vibrations, delightful happiness and well slept nights gave me the extra energy to perform the concomitant role of father and PhD candidate! Here I also mention Alba’s family, Rossella, Franco and Daniela for giving me all the support to go forward with this thesis/parenting, my sister Mayra who shared with me since the beginning the ecological way of life while adding many new perspectives and my aunt Eliana, a fundamental support in the Brazilian side! This PhD journey begun with my search about seed dispersal studies in Sicily and Italy, where all the paths leaded, not to Rome, but to contact Tommaso La Mantia. I noted that Tommaso was a pioneer in studying seed dispersal, but amazingly, I discovered that Tommaso has an incredible knowledge network, where agriculture, forestry, vertebrates, invertebrates, soil, carbon, social and historical perspectives are all strongly linked! Since the beginning Tommaso supported me in all steps way beyond the academic and financial help, presenting me to the Sicilian landscape from varied perspectives, including many interesting people in his also vast interaction network, up to carrying with me hundreds of seed traps at Ficuzza. Doing a PhD in another country is quite a challenge, especially considering the whole new fieldwork and bibliographical environment, so thanks Tommaso for letting this journey possible, including the friendship developed in these years. I want also to thanks Professor Bruno Massa for sharing his enormous knowledge as one of the main wildlife and biodiversity conservation researchers in Italy. Again, I thanks Mauro Galetti, with whom I constructed my ecological basis along my bachelor and master and now supporting me in the Brazilian side of this PhD. Here I mention also Pedro Jordano, who I met thanks to Mauro, and with whom I first begun to think and talk about seed dispersal and ecological interactions in the Mediterranean long before this PhD. Thanks both for all the inspirations including the Frugivory Course in Brazil. A very special thanks goes to Daniel García, which helped me a lot along this PhD, from the organization of the ideas, definition of the sampling up to the final thesis, sharing his deep knowledge in ecological interactions and spatial analysis. Daniel demonstrated to be a very dedicated supervisor, reviewing carefully my work, and very importantly, pointing out crucial improvements that I must made

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Acknowledgements to enhance the quality of the study. Also thanks for coming here in Sicily and receiving me so kindly in Oviedo, presenting the Cantabrian Mountains, or the Atlantic Forest of Europe! I want to show my gratitude to Giovanni Giardina, presenting me to Ficuzza while sharing his vast historical and ecological knowledge of the region, as well as to all the effort he and his wife Ana Maria dedicate to save wildlife and increase awareness about nature conservation. I thanks the UNIPA colleagues, Emilio, Giovanna, Sebastiano, Silvia, Adele, Alessio and Filipa that kindly received me, helped in all academic procedures and issues and shared many aspects of the Italian and Sicilian culture, gastronomy included of course! Finally I thanks the University of Palermo for all the institutional support and to conceiving me the fellowship that allowed the development of this work.

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