Effects of Vineyards and Olive Plantations on Reptiles in the Agroecosystem of Southern Judea Lowlands

Ben-Gurion University of the Negev

Faculty of Natural Sciences

Department of Life Sciences

Effects of vineyards and olive plantations on reptiles in the agroecosystem of Southern Judea Lowlands

Thesis submitted in partial fulfillment of requirements for the Master of Science degree

Kesem Kazes

Under the supervision of Prof. Yaron Ziv and Dr. Guy Rotem (Ben-Gurion University of the Negev)

תמוז תשע"ז July 2017 2

Ben-Gurion University of the Negev

Faculty of Natural Sciences

Department of Life Sciences

Effects of vineyards and olive plantations on reptiles in the agroecosystem of Southern Judea Lowlands

Thesis submitted in partial fulfillment of requirements for the Master of Science degree

Kesem Kazes

Under the supervision of Prof. Yaron Ziv and Dr. Guy Rotem (Ben-Gurion University of the Negev)

Author's signature: Date: 08.07.2017

Advisor's signature: Date: 08/07/2017

Advisor's signature: Date: 8.7.17

Head Graduate Teaching Committee: Date: 10.7.2017 3

Effects of vineyards and olive plantations on reptiles in the agroecosystem of Southern Judea Lowlands

By Kesem Kazes

Thesis submitted in partial fulfillment of requirements for the Master of Science degree, Ben- Gurion University of the Negev, 2017

Abstract

The current intensification and expansion of agriculture worldwide cause damage to wildlife in various ways. Agriculture poses a particularly severe threat upon reptiles, an important group with a key position in the trophic web and the ability to serve as a useful bioindicator group of ecosystem health. Maintaining biodiversity and supporting healthy reptile populations within agroecosystems require knowledge about the effects of different agricultural crops on biodiversity, and about the mechanisms underlying these effects. However, the effects of many crop types on reptile diversity remain unknown. This problem is particularly valid for the Mediterranean basin, which encompasses a great value to biodiversity. In this field study, we have examined the local effects of two understudied common crop types in Mediterranean regions, intensively-cultivated vineyards and intensified-traditional olive plantations, on reptile diversity patterns in a Mediterranean agroecosystem. We focused on habitat structure and ambient temperature as possible important determinants of reptile diversity. Additionally, we attempted to assess predation risk in the different habitats, yet this attempt was not successful. We compared between an array of revisited sampling plots representing each crop to plots in adjacent natural patches in relation to reptile diversity measurements, species composition, structural elements, structural heterogeneity and several soil-surface temperature variables. The vineyards, olive plantations and natural patches exhibited significantly different structural properties and heterogeneity, which were associated with the observed diversity patterns and species composition. The natural patches were characterized in the highest structural heterogeneity, and hosted the greatest species richness and diversity. In contrast, the intensive vineyards were the least heterogenic, highly bare and were revealed as severely hostile areas for reptiles. However, the more traditionally cultivated olive plantations were intermediately heterogenic, and were discovered as a unique habitat, hosting a community with an exceptionally 4 high proportion of specialist species, associated with their prominent structural features. This community was similarly abundant to the one in adjacent natural patches and was characterized in a high level of evenness. Nevertheless, it hosted a lower species richness and diversity. No consistent trends were found in relation to the soil surface temperature. In light of our results, I recommend implementing buffer-strips of natural land cover between and within these crops in order to prevent habitat fragmentation. Additionally, a more wildlife-friendly cultivation management should be used, including the careful enhancement of habitat heterogeneity.

Acknowledgments

This study would not be carried out without the help of many people. I thank Yaron and Dr. Guy Rotem for their supervision, and for giving me the opportunity to study issues which are dear to my heart. I thank the rest of my lab members for numerous useful advices, discussions and great (both mental and physical) support at each step of the way: to Yonathan, Merav, Amir, Irith, Noa, Ittai, and of course, to Zehava. You made the sometimes-difficult way pleasant. I also thank my bosses, Prof. Shai Meiri and Dr. Revital Ben-David Zaslow, for all their help.

I thank Prof. Amos Bouskila and Yael Bogin for their guidance, for helping me design the study at the beginning of the way, for the help in the data analysis and for all they have taught me. Many thanks are given to Boaz Shacham, to Itay Tesler and to Aviad Bar for contributing from their knowledge, giving useful advices and helping along the study. I thank Prof. Ofer Ovadia, Anat Zafrir and Stav Livne for their help in the serpentine depths of statistical analysis. Jim Hines has also contributed important insight concerning the data analysis, and Claudia Corti and Marta Biaggini have shared their valuable studies; I thank them very much.

My thanks are given to the farmers and cowboys of Luzit and Beit-Nir, who shared valuable information, were willing to help at any way possible (including pulling us from the mud at the middle of the night), and made us feel so welcome: to Reuven and Moshe, Yehuda, Boaz, Dudi, Yankale and all the others. A special thanks is given to Moshe Biton of blessed memory, who passed away prior to writing these lines. I am sorry he could not see the fruits of the study which he has enabled.

I thank all the brave people who participated in the laborious fieldwork: to Nevo Sagi, Oz Rittner, Shachar Tzuk, Hadar Ben-Shushan, Lior Ventura, Snir Halle, Simon Jameson, Boaz Shacham, Zehava Seigal, Adi Avneri, Ariel Drabkin, Naama Rahamim, Uri Sivan, Alma Mastbaum, Tal Dagan and Sam Rutman. I thank Oz for also photographing, sharing knowledge and numerous advices. Further thanks are given to the Ministry of Agriculture and Rural Development for funding this study, and to the rangers of the Nature and Parks Authority (and particularly Uri Kaizer) for their help.

Finally, a great appreciation is given to my family; to Dar for editing, to Einat for proofreading, and to Yakov for all he gave. Thank you for your support at every step of the way. 6

Table of contents

Introduction ...... 7 Research objectives ...... 12 Methods ...... 14

Study area...... 14 Study organisms ...... 15 Focal crops ...... 16 Olive plantations ...... 16 Vineyards ...... 18 General design ...... 19

Reptile sampling ...... 20

Assessments of environmental variables ...... 22

Habitat heterogeneity...... 22 Ambient temperature ...... 22

Predation risk...... 23 Data processing and statistical analysis ...... 23

Reptile diversity patterns ...... 23 Environmental characteristics ...... 28 Linking environmental characteristics to reptile diversity patterns ...... 29 Results ...... 31

Reptile diversity patterns ...... 31

Environmental characterization and linkage to reptile diversity patterns ...... 41

Discussion...... 49

References ...... 61

תוכן העניינים ...... 71

תקציר ...... 72 7

Introduction

The global human population and its per-capita consumption rate are rapidly increasing. In order to meet the growing demand of humanity for food and products, agriculture is expanding and intensifying at the expense of natural ecosystems worldwide, and in Israel specifically. Today, approximately 40% of all areas on earth (and 24% of the lands of Israel) are dedicated to agriculture (The World Bank Group 2016). The intensification and expansion of agriculture cause damage to wildlife in various ways, including habitat loss, fragmentation and chemical pollution, which in turn result in biodiversity loss (White et al. 1997; Benton et al. 2003; Green et al. 2005). Therefore, the expansion of modern agriculture is a major participant in the current severe decline in global biodiversity, known as the biodiversity crisis (Norris 2008).

Two main approaches exist concerning the challenge of protecting biodiversity under the threat of agricultural development: Land Sparing and Land Sharing (Skutelsky 2010, Phalan et al. 2011). The Land Sparing approach refers to a spatial separation between agricultural areas and natural areas, which are designated to conservation. It encourages maximal yield production in the agricultural lands using intensified cultivation, in a way that will enable limiting their area and leaving maximal space left untouched (Skutelsky 2010). The Land Sharing approach, on the other hand, suggests integrating distinct patches (i.e. distinct areas which differ from their surroundings) of natural ecosystems into agricultural areas, to create a heterogeneous ‘agroecosystem’. Biodiversity, when maintained at the resulting mosaic, is essential for the function of the entire agroecosystem. In order to enable optimal incorporation of the agricultural patches into the ecosystem, it is necessary to reduce the damage induced by the agricultural cultivation upon the natural systems using wildlife friendly farming methods (Skutelsky 2010). Such methods include, for instance, minimizing the effects of pesticides on non-target organisms (Green et al. 2005). In return, the agricultural systems might benefit from ecosystem services provided by the natural patches, such as biological pest control and pollination (Green et al. 2005; Skutelsky 2010).

The current conservation policy in Israel tends to favor the Land Sharing approach, similarly to the European manner (Skutelsky 2006). As concluded by Cox & Underwood (2011), this state seems inevitable in many Mediterranean areas, since the rate of formal protected-area expansion is outraced by anthropogenic habitat conversion. They demonstrated that managing unprotected 8 areas in a manner which enables native species to persist, a considerable portion of plant species diversity might be maintained. Therefore, gaining knowledge of how wildlife is affected by the presence of agricultural patches in various Mediterranean agroecosystems is of great importance for developing improved strategies for biodiversity conservation and sustainable land use. Nevertheless, the influence of some common agricultural crops is still understudied in respect to certain taxa. This problem is particularly severe in the case of the Mediterranean basin, which was defined as one of the leading biodiversity hotspots in the world (Myers et al. 2000), yet suffers from agricultural impacts for thousands of years (Ribeiro et al. 2009). In spite of the its high ecological importance and vulnerability, most studies concerning agroecosystems' biodiversity were conducted in temperate regions in Europe and in tropical areas in Central America (Porat 2011).

Reptiles constitute one of the taxonomic groups which are affected most severely by agriculture. According to IUCN data, approximately 25% of the red-listed reptile species (excluding species categorized as 'Least Concern') are threatened specifically by agriculture (Norris 2008). This raises a particularly urgent concern since reptiles are globally declining at alarming rates (Gibbons et al. 2000). Monitoring reptile diversity in agroecosystems is thus essential for diminishing their global declines.

In recent years, reptiles are increasingly appreciated as an index of biodiversity and of ecosystems health (Paggetti et al. 2006; Maza 2008; Porat 2011), and were previously described as ‘heralds of environmental quality’ (Gibbons et al. 2000). In many ecosystems and in agroecosystems in particular, reptiles serve as key links among trophic levels – being predators of different invertebrates, small mammals and other reptiles, and preyed upon by birds and large mammals (Biaggini et al. 2009; Porat 2011). Thus, changes in their population densities may have cascading effects on other trophic levels (Biaggini et al. 2009). Moreover, due to their ecological and physiological constraints, low dispersion ability and small home ranges, reptiles are regarded as extremely sensitive to habitat changes (Ribeiro et al., 2009), and more prone to the risks associated with landscape change in comparison to other vertebrate taxa (White et al. 1997). However, they are rarely studied in the Mediterranean, and the status of many species remains unknown (Carpio et al. 2015). 9

Mitigating the negative effects of agricultural intensification on wildlife and on reptiles in particular, requires understanding of the mechanisms underlying the widespread declines in farmland biodiversity. These mechanisms may operate on various spatial scales, from large (e.g., across regions) to small (e.g., within patches). The most prominent mechanism responsible for these declines at multiple scales is probably the loss of ecological heterogeneity. When focusing on the smaller scales, it is the loss of heterogeneity in habitat structure (Benton et al., 2003). One of the basic notions of ecology is that structurally complex habitats increase species diversity (e.g. MacArthur & Wilson 1967) by providing more niches and more possibilities for co- existence of different species (Tews et al. 2004; Moreno-Rueda & Pizarro 2007).

In a literature review, Tews et al. (2004) have shown that 85% of all studies which explored the relationship between animal species diversity and habitat heterogeneity found positive relationships between the two. For instance, habitat heterogeneity has been shown to be the most prominent environmental variable influencing species richness of terrestrial vertebrates in general in south-eastern Spain (Moreno-Rueda & Pizarro 2007) and of lizards in particular (in western North America; Pianka 1967). This sort of positive relationship between habitat heterogeneity and reptile diversity was also reported from a Mediterranean agroecosystems (Porat 2011). Agricultural intensification promotes habitat homogeneity, as a result of processes such as monocultivation and the use of agrochemicals (Benton et al., 2003).

Along with the effect of modified heterogeneity on diversity patterns, the alteration of habitat structure by agriculture might induce farther changes in communities via the effect on additional structural features. Based on the ecological niche concept sensu Hutchinson (see Whittaker et al. 1973), structurally-different habitats are expected to host different assemblages of species. Two of the main theories concerning the mechanisms underlying this phenomenon are the theories of habitat selection and of species sorting. While the former emphasizes the ability of individuals of a species to disperse and colonize habitat patches based on their expected fitness in those patches, the latter refers to the random (undirected) distribution of organisms, followed by site- specific mortality (Binckley & Resetarirs 2005). Regarding reptiles, several studies have demonstrated that some influential structural properties are related to vegetation (e.g., Pianka 1967; Castilla & Bauwens 1992; Jellinek et al. 2004) and rock (Castilla & Bauwens, 1992; Michael, 2008) coverage and type. For example, in Mediterranean ecosystems, both Castilla and 10

Bauwens (1992) and Porat (2011) have shown that a relatively high vegetation coverage and some rock coverage make a patch preferable as a habitat for reptiles. Therefore, agricultural modification might result in alternation of the reptile community structure inhabiting different agricultural habitats.

Another important conservation concern in agroecosystems should be the expected shift in species composition from specialist to generalist species in anthropogenically-modified habitats (Attum et al., 2006; Hawlena & Bouskila, 2006). Specialist species are characterized by a set of adaptations to features of a certain habitat. Thus, they are usually less tolerant to disturbance and have high fidelity to particular habitats. Generalist species have more flexible habitat requirements and less specific adaptations, at the potential benefit of having a higher fitness in a greater variety of environments (Attum et al., 2006). Thus, landscape alterations might favor generalists. This might profoundly affect species composition, may cause changes in relative abundances of species and can induce species replacement (Hawlena & Bouskila, 2006).

Yet these community-level changes in agroecosystems are actually induced by the effects of land use on habitats’ suitability and quality for individuals. Such changes in habitat quality are associated with changes in various environmental factors, which in turn may be strongly affected by habitat structure. Two of the main environmental variables which are repeatedly hypothesized to determine habitat quality for reptiles, due to their influence on individual physiology and activity, are ambient temperature and predation risk (e.g., Huey 1991; Castilla & Bauwens 1992; Porat 2011).

Regarding ambient temperature, reptiles are ectotherms, regulating their body temperature actively by timing their daily and annual activity periods, by changing their location and by adjusting their posture during activity (Bouskila & Amitai 2003; Porat 2011). Furthermore, oviposition-site selection by females may affect the offspring's fitness and development according to the thermal properties of the habitat (Spencer 2002). Structurally complex habitats provide reptiles with a variety of thermoregulatory possibilities (Castilla & Bauwens 1992; Porat 2011) for achieving the suitable temperature range required for intact activity, survival and reproduction. The replacement of the native vegetation with an agricultural crop with different structure and phenology, along with the agricultural practices themselves (e.g., plowing, harvesting) change the thermal properties of the habitat (Saunders & Hobbs 1991). Such changes 11 were previously found to strongly affect reptile communities (Pike et al. 2011) and habitat preference (Webb et al. 2004) via their thermoregulatory consequences. However, the effect of the thermal quality of the habitat on relative abundance is rarely studied in relation to squamates (Diaz 1997).

With respect to predation, agricultural land use has been hypothesized to increase the predation pressure which reptiles are subjected to, via increased presence of predators (Biaggini et al. 2009; Porat 2011; Rotem et al. 2011), higher reptile detectability and lowered quality of available refuges (Biaggini et al. 2009). Predation pressure is affected by the habitat's heterogeneity, which therefore has further consequences to the habitat's quality. Heterogeneous habitats offer a variety of available refuges for reptiles, who may choose different retreat-sites, according to variables such as their species, interspecific competition (Langkilde & Shine 2004) and the time of day (Goldsbrough et al. 2006). In a Mediterranean agroecosystem, Biaggini et al. (2009) have found evidence to a strong influence of habitat structure on the predation risk threatening lizards of the species Podarcis sicula in vineyards and in olive plantations. Predation pressure, as evaluated by tail break frequency, was lower in olive plantations, which was the more structurally complex habitat examined. The type of habitat also reflected at the lizards’ escape behavior: the lizards used the olive trees as refuges and suffered of lower predation risk in the olive plantations, even though predator presence seemed to be higher in this habitat.

However, reptiles (and reptile diversity in particular) are very poorly studied in olive plantations (Carpio et al. 2015) and even more rarely in vineyards, although they are both very common crop types in the Mediterranean (Loumou & Giourga 2003). In recent years, there is an increasing recognition of the need to reduce the negative effects of intensified vineyards and olive plantation on ecosystems (e.g., BiodivERsA project VineDivers). In a study on reptile diversity in several prominent land-uses in central Italy, for instance, Biaggini and Corti (2015) have found that intensively-managed olive plantations and vineyards hosted only one reptile species. Nevertheless, traditionally-cultivated olive plantations hosted the highest reptile diversity among the agricultural land-uses examined, being nonetheless lower in comparison to diversity in vegetation stripes between fields. Yet there is still a lack of knowledge about specific changes in reptile communities associated with these crops and about the mechanisms underlying those 12 changes. Particularly, reptile communities inhabiting vineyards and olive plantations in Israel have not been characterized to date.

Research objectives

In light of the above, the main objective of this study was to understand the effects of vineyards and olive plantations on reptiles inhabiting the Mediterranean region of Israel. That is, in order to promote the establishment of an efficient conservation management for reptiles in Mediterranean agroecosystems, in accordance with the Wildlife Friendly Agriculture approach. I studied the effects on reptiles focusing on the structural properties of these agricultural habitats, and on the local (within-patch) scale.

Specifically, this study had three main goals. The first goal was to characterize the environmental properties of the agricultural habitats (mainly in terms of structure, and secondarily in relation to thermal properties and predation risk), and to compare them to natural patches. I hypothesized that the structural heterogeneity of the habitat is negatively affected by agricultural cultivation, while its hostility towards reptiles is positively related to it. Therefore, intensified vineyards were expected to be highly homogenous, to be characterized in severe predation risk and in extreme and homogenized ambient temperatures, which are unavoidable to reptiles due to the lack of shelters. The more traditionally-cultivated olive plantations were expected to be more structurally complex, and to be characterized in lower predation risk and temperature severity. Nevertheless, both crops were expected to be more homogenous in comparison to natural patches, in which the lowest predation risk and highest thermal quality were expected.

The second goal of this study was to compare the reptile communities in the focal agricultural habitats to those inhabiting natural patches, with respect to diversity patterns and species composition. I hypothesized that reptile diversity patterns are strongly affected by agricultural cultivation, its intensity and their consequences to habitat structure, thermoregulatory possibilities and predation risk. According to this hypothesis, I anticipated that increased cultivation intensity will result in lowered habitat quality and in meeting the requirements of a decreased variety of species. The enhanced hostility will reflect in lower reptile diversity and abundance at the agricultural patches. Specifically, I predicted that intensified vineyards support the lowest reptile diversity among the types of habitats under consideration, while olive 13 plantations might sustain higher diversity. However, both crops were expected to support lower diversity in comparison to the natural patches.

Additionally, I hypothesized that structural features, and especially vegetation and rock coverage and type, are important determinants of particular reptile species presence at these habitats, and therefore influence the reptiles’ species composition. I anticipated that the properties of the habitats would influence generalist species less harshly than specialist species, and thus generalist species will be more abundant at the agricultural patches. Nevertheless, I anticipated that olive plantations would support abundant populations of specialist species which are associated with their prominent structural features (especially large trees which are scarce in the natural Mediterranean shrubland), e.g. arboreal species.

The final goal of this study was to investigate how differences in the structure, temperature and predation risk of those habitats are related to the observed diversity patterns. According to the hypotheses above, I predicted a decrease in reptile diversity and abundance with an increase in average temperatures and in predation risk. In contrast, I anticipated that an increase in reptile diversity and abundance will be related to an increase in habitat heterogeneity, and in temperature range and variation.

Methods

Study area

The study was conducted in the northern part of Southern Judea Lowlands, central Israel (WGS84 coordinates 31.668275N 34.879696E; Fig. 1a). This hilly area is located in the extraordinarily biodiverse Mediterranean basin (see Introduction). Climatically, the Judean Lowlands area is included in the Mediterranean region (350-550 mm annual rainfall; Skutelsky 2011). Nevertheless, biogeographically it constitutes a crossing zone of several biogeographical regions: Mediterranean, Saharo-Arabian and Irano-Turanian (Stern 2004). Thus, it is characterized in a particularly high biodiversity (including high reptile diversity; Rotem 2014), and hence has a high conservational value.

Figure 1. A map of the research area and sampling plots. (a) The study location at Southern Judea Lowlands, at which the study plots are located at Luzit and Beit-Nir as shown in (b). An example of a pair of agricultural (here, an olive plantation) and natural patches is given in (c). The two latter photos were taken from Google Earth, 2015.

Southern Judea Lowlands is a landscape mosaic consisting of agricultural patches (mainly olive plantations, vineyard and field crops; Stern 2004; Skutelsky 2011) and natural patches under different levels of grazing pressure by cattle, sheep and goats (Skutelsky 2011). The vegetation in the area has been profoundly influenced by anthropogenic activity for thousands of years, including agricultural cultivation and grazing. Today, the natural patches consist of Mediterranean garrigue, scrub-steppes and Maquis (Stern 2004). This agroecosystem has been 15

vastly studied in the past in relation to various taxa, including beetles (e.g. Yaacobi et al. 2007), spiders (Gavish et al. 2012; Gavish & Ziv 2016) and reptiles (e.g. Rotem et al. 2013, 2016). The knowledge gained on it, combined with its patchy nature and ecological value, make the Southern Judea Lowlands area a good model system for studying the effects of agriculture on Mediterranean ecosystems in general, and for exploring land-sharing opportunities to conserve biodiversity in particular.

Study organisms

Reptiles were chosen as an indicator group for the effects of anthropogenic modifications on biodiversity in general (e.g., Maza 2008; Todd & Andrews 2008) and of agriculture in particular (e.g., Paggetti et al. 2006; Ribeiro et al. 2009; Porat 2011) in many ecological studies, and not in vain. Reptiles constitute a diverse group in terms of habitat requirements, inhabiting a wide range of habitats – including a variety of agricultural habitats (e.g., Porat 2011). They belong to a range of functional groups and various trophic levels. Furthermore, they are quite easy to identify (even to the species level), and the ecology of many species is well known. Therefore, the rate of their occurrence may provide information on habitat use (Paggetti et al. 2006) and properties. Moreover, their physiological and ecological constrains (see Introduction) make them sensitive to environmental changes and quality at the local scale (Ribeiro et al. 2009). Being widespread in Mediterranean areas, they have been proposed by Paggetti et al. (2006) as useful indicators in agroecosystems located in such areas.

Israel is one of the world's richest countries considering reptile species per unit land area (e.g., Roll et al. 2009). Agriculture in particular has been noted as one of the main threats to this exceptional diversity (Dolev & Perevolotsky 2002; Bar & Haimovitch 2011; Werner 2016). In the Mediterranean region of Israel, the essential need for protecting reptiles in agroecosystems is particularly true for species which are at risk of extinction (Dolev & Perevolotsky 2002; IUCN 2016). Among them are Günther's Cylindrical Skink (Chalcides guentheri(, the Mediterranean Spur-thighed Tortoise (Testudo graeca) and Festa's Skink (Ablepharus rueppellii festae). The characteristics described above, combined with their high conservational value (see Introduction), make reptiles a worthy focal group for investigating the effects of agricultural crops on biodiversity in Mediterranean areas. 16

Focal crops

The study focused on two common agricultural crop types in the Mediterranean basin: vineyards and olive plantations. Although both the olive tree and the grape vine have long history of cultivation in the Mediterranean region (EFNCP 2000; Terral et al. 2010) and are raised as monocultivations (EFNCP 2000), they greatly differ in some plant characteristics. Yet most importantly, they differ in cultivation practices. These differences might have substantial implications for their properties as habitats for wild animals, and make them appropriate for studying the effects of agricultural intensification on biodiversity.

Olive plantations

The olive tree (Olea europaea) is an evergreen plant of the Oleaceae family (Graziani et al. 2006). It has a long history of cultivation in the Mediterranean basin, and it still dominates the area's rural landscapes nowadays. Until recent decades, olive plantations were all traditionally cultivated, with minimal or no chemical inputs, no irrigation and a limited use of machinery or none at all. During the last decades, more intensive practices have started to be implemented in the olive plantations, and today intensified-traditional and intensive modern plantations may be found in many Mediterranean areas (EFNCP 2000; Loumou & Giourga 2003; Sokos et al. 2013).

The olive trees encompass the potential to serve as high quality habitats for wild animals. The trees' growth is very slow and they might live for centuries, providing a stable microenvironment. The older trees' trunk becomes perforated and twisted, with thick, easily-crumbled bark. This morphology makes the trees very suitable for arthropods and small-sized vertebrates (Graziani et al., 2006). Additionally, the trees provide a shading canopy which exists all year long, and the large amount of dead leaves piles on the ground of the plantations provide dwelling-sites for many organisms (K. Kazes, personal observations). Indeed, olive plantations are regarded quite stable environment when compared with other agricultural ecosystems, which support diverse fauna and native Mediterranean flora, as demonstrated in several studies (some are reviewed in Loumou & Giourga 2003). 17

As a result of their particular plant characteristics and farming practices, the low-input traditional plantations were recognized as potentially having the highest value to biodiversity and most positive effects on the environment (e.g., water management in upland areas), while at the same time having the least negative effects on the environment. The intensified traditional and modern intensive plantations were described as potentially having the least value to biodiversity and greatest negative environmental impacts (EFNCP 2000), the latter being demonstrated in practice (e.g., in relation to soil erosio, Gómez et al. 2009; herbecaous plant diversity, Solomou & Sfougaris 2013).

In Israel, olive cultivation is characterized by a variety of management types. The most extensive one is the traditional dry farming management of olive for oil production. This is the type of management practiced in most olive plantations in Israel, covering approximately 250,000 dunams of land. The traditional plantations are usually small and embedded in the natural Mediterranean landscape. They are not artificially irrigated, and usually fertilizers, pesticides and herbicides are not applied in them either. The growth of herbaceous vegetation is oppressed to some extent using tillage, which is applied between the rows of trees (Amdor et al. 2015).

The more intensive practice management types in Israel include plantations for oil and for table olives, covering approximately 81,000 dunams of land, and include many plantations in Southern Judea Lowlands. These practices involve a varying amount of artificial irrigation (according to the type of crop and climate), ranging from none to 900 cubic meters of water for dunam per year, and usually the application of chemical inputs to some extent (Amdor et al. 2015). This study was conducted in intensified-traditional plantations representative of the cultivation regime carried out in many plantations in the study area (Fig. 2). They are not irrigated nor fertilized, yet they are treated with herbicides and with a pesticide against the olive fruit fly (Bactrocera oleae). Nevertheless, their management seldom requires the utilization of heavy machinery, and some native vegetation usually persists inside the plantations and contributes to their heterogeneity. 18

Figure 2. Typical appearance of an olive plantation in the study area, which remains quite stable during all year long.

Vineyards

The grapevine (Vitis vinifera) is a perennial plant of the Vitaceae family (Terral et al. 2010). Vineyards cover small areas around the globe relative to other crops, yet they are commonly raised at ecologically sensitive regions, mainly in the diverse Mediterranean areas (Rosenfeld & Avisar 2012; Rosenfeld et al. 2015). This poses a risk to biodiversity, since vineyards are raised as a homogenous monocultivation (Rosenfeld & Avisar 2012), and most commonly with an intensive regime of soil fertilization and pesticide use. Frequently, the growth of other plants inside the vineyard is prevented by mowing, herbicide use, or a combination of both (Skutelsky 2011; Rosenfeld & Avisar 2012; K. Kazes, pesonal observations). Thus, the soil is highly bare, and when inter-row vegetation does exist, it consists of only a few plant species (Winter et al. 2016).

The mentioned practices frequently involve the extensive use of heavy machinery (Winter et al. 2016; K. Kazes, personal observations), thus the vineyards are characterized in high levels of disturbance. The intensive cultivation practices applied in them have been shown to inflict severe damage to local biodiversity (e.g. arthropods; Skutelsky 2011). Additionally, the vines provide less shade then olive trees and only for a few months a year (April to September, when they are covered with foliage), the soil in vineyards is highly plawed and eroded, and most rocks are removed. Therefore, the 19

vineyards constitute highly exposed and structurally homogeneous systems, which offer scarce shelters from predators and thermoregulatory opportunities for reptiles (Fig.3).

Figure 3. Typical intensively-managed vineyards in our study area during (a) early spring; typical pysiognomy during most of the year (photo: Merav Shemesh) and (b) late spring, with maximal foliage.

Wine production has increased during the last decades, mostly due to the increase in the demand for high quality wines. Israel is one of the smallest wine producers in the world, yet the extent of its wine production is rapidly growing in comparison the other countries (Rosenfeld & Avisar 2012). In light of the environmental and conservational issues associated with intensive vineyard management, these trends might have considerable consequences towards local biodiversity. Since most vineyards in Israel are intensively cultivated and only the minority are organic, this study focused on intensively-managed vineyards. All of the vineyards we sampled were designated for wine-grapes production.

General design

Each type of crop was represented by 5 plots of identical size (100 x 50 m), which were located in two proximate settlements in Southern Judea Lowlands (Fig. 1b): Luzit (WGS84 coordinates 31.687323N 34.886638E) and Beit-Nir (31.679419N 34.823600E). As a control, each plot was paired with a plot of the same size in an adjacent natural patch (Fig. 1c), for a total of 20 sampling plots. The plots' borders were marked using colorful flags and ribbons.

Reptile sampling

In order to characterize the reptile communities in the different habitats, we conducted 7 reptile surveys in the study plots, during March to October 2015 and March to April 2016 (Table 1). The times of the surveys were included in the main activity season of reptiles in Israel. We used two complementary methods to survey reptiles: line transects and active searching.

Table 1. Reptile surveying periods during the study.

Survey no. Dates 1 31/03/2015 - 08/04/2015 2 26/04/2015 - 02/05/2015 3 05/06/2015 - 10/06/2015 4 07/07/2015 - 18/07/2015 5 29/09/2015 - 05/10/2015 6 06/03/2016 - 23/03/2016 7 31/03/2016 - 10/04/2016

Line transects were conducted by walking at a moderate pace along the flagged long axis of the sampling plot. Two transects were conducted at each plot during a single survey, simultaneously when two observers were present in the plot, or one immediately after the other in the case of a single observer. 10 meters separated between the two transects, in order to maximize observations number and to avoid resightings. At any observation, we recorded the individual’s species, age, and the microhabitat in which it was first found at. This method mainly allowed the detection of reptiles which were active above ground, with a minimal disturbance to the habitat and its inhabitants. However, while using this method, in some cases a difficulty arises in identifying the observed reptiles to species level or distinguishing between individuals.

Active search was performed immediately after completion of the transect survey, and under a time limitation. In order to normalize the surveying effort to the number of observers, when the search was conducted by one person, the searching period was maximal (60 minutes) in comparison to a search conducted by several observers (60 minutes / number of observers). During the search, we actively searched for reptiles by turning over shelters (stones, tree 21

barks, piles of leaves, etc.) that are present in the plot. All of the shelters turned were returned to their original position in order to avoid damage to the habitat. We attempted to capture any reptile observed during the search, and recorded different parameters: species, sex (when possible), age, mass, body length measurements, and microhabitat. Any reptile captured was released after the measurements near the location where it was found. As in the transect, we also recorded observations at dead individuals, molts and eggs. Remains of dead individuals were marked and molts were collected, in order to avoid recording them repeatedly. The active search method allows the detection of inactive, cryptic and fossorial reptiles, in addition to reptiles which are active above ground. It allows a further investigation of the individuals captured and therefore their certain identification. Nonetheless, it causes disturbance to the habitat and might be stressful (and even dangerous) to the animals.

These two methods were found to be the most efficient for finding the fullest list of species occurring in a similar agroecosystem (Porat 2011). Additionally, a surveying method combining the two we used was found to be the most efficient method for reptile surveying in olive plantations specifically (Carpio et al. 2015). The plots were surveyed in pairs, with one agricultural and one adjacent natural plot surveyed one as soon as possible after the other, in a changing order. Usually each pair of plots was surveyed on the same day, yet on some rare occasions they were not, due to confusions between the plots. In order to avoid the influence of the survey timing on the results, at each survey we changed the order in which the study plots were sampled.

The distance and time limitations provided the transects and the active search with the required normalization. During the study period, we also recorded any random observation in a reptile in the sampling plots, in which we recorded the species observed, whether the individual was active, the microhabitat and, when possible, its age and sex. Recording random observations was found to be an efficient tool for assessing reptile diversity in a similar ecosystem (Porat 2011). Nevertheless, these records were not used for the data analysis, due to the lack of normalization by distance or time limitation.

Assessments of environmental variables

I assessed two environmental characteristics of the studied habitats, which were previously found to have important consequences for reptile ecology (see Introduction): habitat heterogeneity and ambient temperature. I attempted to assess an additional influential environmental variable, level of predation risk, which was not successful.

Habitat heterogeneity

We recorded the relative coverages of 7 prominent structural elements along 50 m transects in each study plot, and to a distance of 15-20 cm at each side of the transect. Two transects were conducted at each plot, along its wide axis, and were separated by 40 m. Habitat heterogeneity was calculated as the Shannon’s index of diversity (Tews et al. 2004; Porat 2011) of the different relative covers. When possible, Shannon Index was calculated based on the average coverages for the two repetitions in each plot. In the minority of the plots, though, the index was calculated based on one transect, due to loss of data. This method for heterogeneity assessment enabled a quantitative comparison between the habitats. Nevertheless, it lacks in accuracy and its complexity leads to differences in data collected by different observers (as in the case of this study).

Tews et al. (2004) highlighted the necessity of selecting biologically meaningful variables in studies of habitat heterogeneity effects, which they termed ‘keystone structures’. Therefore, the structural elements recorded during the sampling were selected due to their biological importance to reptiles, as well as their prominence at the landscape. They included: the dominant woody plant species in the habitat (olive trees, grape vines, or Sarcopoterium spinosum shrubs in the natural patches); woody vegetation other than the dominant plant; herbaceous vegetation; rocks; stones; bare soil; and dead plant matter.

Ambient temperature

We measured the soil surface temperatures along the long axis of each study plot, using a digital temperature gun, on every reptile survey. At each plot, 10 temperature measurements were taken, with approximately 20 m separating between the measuring 23

locations. At each location, we took one measurement in a random surface point exposed to sun and in one random shady point. On some occasions, data was not possible to collect completely due to equipment malfunctions or cloudiness. Thus, for the data analysis, I used data collected in plots and surveys which included the complete set of measurements. These data was composed of measurements collected during surveys 3 and 4 (Table 1) in 18 out of the 20 plots. Based on them, I calculated the average soil surface temperature in shade and in sun; the total average in the plot; the temperature range in sun and in shade; the total temperature range in the plot; the temperature variation in sun and in shade; and the total temperature variation in the plot.

Predation risk

In many reptiles, caudal autotomy has been described as an effective anti- predator strategy, and therefore tail break frequency is often used to evaluate predation risk in this group, as it indicates the frequency of close encounters with predators (e.g., Corti et al. 2009; Pianka & Parker 1972; Santos et al. 2011; although see Medel et al. 1988). At each observation at a reptile of a species capable of tail autotomy during the surveys, we recorded its tail status (original, cut or regenerated) in order to evaluate the tail breakage frequency for each species in the different habitats. Unfortunately, as described in the Results chapter, there is a lack of data in the vineyards and strong differences between communities inhabiting the rest of the habitats. Thus, it was not possible to compare tail breakage frequencies of the same species in different habitats.

Data processing and statistical analysis

Reptile diversity patterns

I summed the total number of observations occurring at each study plot throughout the study in order to calculate total reptile abundance and species richness per plot. Only observed reptiles which were identified to species level were included in the count. All analyses were done on normalized data (collected during the transects and active search combined). Individual reptiles which were first observed during the transect and then resighted during the active search were noted and counted once. In cases in which there was a possibility of noting the same individual during the transect and the active search, I omitted one of the observations from the analysis. The 24 total number of observations at the plot was referred to as total abundance, since in this study area (Rotem et al. 2013) and in a similar ecosystem (Porat 2011) the amount of recaptures was found to be negligible. I included observations at dead individuals and molts which could be identified to species level in the count. When possible, I also calculated species diversity using Fisher's alpha index of diversity (Fisher et al. 1943). All diversity measurements and analyses were produced using PRIMER-E version 6.1.6 (Clarke & Gorley 2006), except for the diversity profiles and VIF analysis (as described later).

I assumed that in some cases, reptiles are capable of moving between the agricultural patches and adjacent natural patches. Moreover, I assumed that in most cases, the agricultural patches' communities originated from the natural patches' communities. Due to the dependency between the agricultural and adjacent patches' communities, their diversity measurements were compared using Wilcoxon's matched pairs test. This non-parametric test was used due to the small sample sizes, although the data did violated the assumption of variances homogeneity when comparing the vineyards to adjacent natural patches, and transformations did not increase homogeneity. In order to verify that any differences found between the two types of agricultural habitats do not derive from differences in adjacent natural patches, I also compared the two types of natural patches to each other. I assumed independency between these two types of patches, based on the assumption that no movement can occur between them. That is, due to the large distance between them (Fig. 1) and the limited dispersal ability of most reptiles (Huey 1982). Therefore, the diversity measurements in these two types of patches were compared using Mann-Whitney U test. All of the statistical analyses were done using STATISTICA v12.5.192.7 (StatSoft, Inc. 2014).

In order to compare the species composition in the different habitats, I used several means.

1. Hierarchical clustering. In this technique, the study plots were successively grouped based on a similarity matrix, to form a dendrogram with the x axis representing the full set of plots and the y axis defining the similarity levels at which two plots or groups are considered to have fused. I used a similarity matrix produced by calculating Bray-Curtis similarity coefficient between each pair of plots, according to the abundance of each species. Then, I used group-average linking between their coefficients for the clustering. 25

The abundance data was square-root transformed in order to upweight the presence of rare species (Clarke & Warwick 2001). 2. Analysis of similarities (ANOSIM) test. A non-parametric permutation test which allowed a statistical comparison of the similarity between the different habitats (both globally and pairwise). I used one-way ANOSIM test, which was based on the same similarity matrix described above. The ANOSIM procedure produces two main values: R, which indicates the degree of discrimination between habitats (the higher the value, the larger the difference in species assembly); and the p-value of the test (Clarke & Warwick 2001). 3. Non-metric multidimensional scaling (NMDS). I used this technique in order to construct a configuration of the study plots in a way that states the relative similarity between their species composition. I used two-dimensional NMDS which was based on the similarity matrix described previously, and restarted the NMDS algorithm for 50 times. This technique was described as more appropriate to describe biotic data in comparison to other ordinations (e.g., PCA; Clarke & Warwick 2001). 4. Similarity percentages (SIMPER) analysis. I used this routine in order to decompose average Bray-Curtis dissimilarities between all pairs of plots, one from each habitat, into percentage contributions from each species to the dissimilarity in species assemblages of different habitats (Clarke & Gorley 2006). 5. Diversity profiles. A graph which conveys different meaningful aspects of a community, and allows their comparison to those of other communities. Various types of diversity profiles were discussed in the past, and I followed (Leinster & Cobbold 2009) whom diversity profile describes the dependency of their diversity measures family qDZ(p) in the sensitivity parameter, q. The diversity profiles were produced using an R code developed by the authors and implemented in RStudio v0.99.491 (RStudio Team 2015). The R code takes into account a similarity matrix, describing the similarity between species. In order to give all species an equal weight in the community relative to their abundance, I used a similarity matrix describing no similarity between the species.

At each part of the diversity profile graph, some familiar diversity measurement (e.g., Shannon's entropy) can be derived from qDZ(p), with q represents the community's 26

insensitivity to rare species. For instance, the left-hand end of a diversity profile gives information about species richness and rare species. When q is small, qDZ(p) is affected almost as much by rare species as common ones, and hence represents species richness when q=0. The right-hand tail gives information about dominance and common species: when q is large, qDZ(p) is barely affected by rare species, and thus represents the community's evenness when q=∞. Therefore, when a diversity profile of a specific community is wholly above that of another, we can conclude that it is more diverse in any manner. However, when the diversity profiles of two communities cross, the locations of the crossings give meaningful information about how the communities differ.

To address the issue of shift in composition from specialist to generalist species, I developed the Average Specialism Index (SI) with A. Bouskila (Ben-Gurion University, Israel) and B. Shacham (the Hebrew University of Jerusalem, Israel), following the work of Bar (Kutiel) and Cohen (2002). The index represents the average level of habitat-specialism of the species observed and is calculated for each study plot (p). The equation of the index is:

푛 ∑푖=1 푆푅푖퐸푖푝 (1) 푆퐼푝 = 푁푝

Where 푆푅푖 is the general habitat-specialism rank attributed to species i (as elaborated below), and 퐸푖푝 is the existence (1) or absence (0) of species i in/from plot p. The sum of their products for the n species observed in the plot is divided by 푁푝, the total species richness in plot p.

The species-specific SR score is an additive rank composed of three scales, each ranked 1-4 according to the rationale presented in Table 2, with an increasing rank indicating an increase in specificity. Finally, I calculated the SI score for each plot and compared the different habitats using a Kruskal-Wallis test. Again, this non-parametric test was used because of the small sample size, although the data violated the assumption of variances homogeneity, and transformations did not increase homogeneity. I then tested the differences between each pair of habitats using Tukey's HSD test. A high SI score indicates a high proportion of specialist species in relation to generalists.

Table 2. The ranking system for calculating the SR score, representing the degree of habitat-specialism per species.

Rank Scale I: distribution pattern (Dolev Scale II: affinity to biomes Scale III: affinity to certain & Perevolotsky 2002) (B. Shacham, personal structural elements, e.g., trees, communication) rocks (B. Shacham, personal communication) 4 Endemic mainly to a particular region Affinity mainly to one of the High affinity in Israel following: arid, shrub-steppe, garrigue, maquis/forest 3 Single distribution pattern type (e.g., Affinity mainly to two of the Medium affinity Mediterranean) above-mentioned 2 One main distribution pattern type Affinity mainly to three of Low affinity and penetration to another region, or the above-mentioned several subspecies with different distribution patterns 1 Wide distribution which includes Exists in all of the above- Negligible affinity most of Israel mentioned

An important source of variation in any wildlife-monitoring program (Wintle et al. 2004), and in herpetological surveys in particular (Mazerolle et al. 2007), is detectability (i.e., the probability of detecting a species when it is present; McDiarmid et al. 2012). Indeed, many reptile species are nocturnal, have cryptic color patterns, live underground, and may be conspicuous only during certain times of the year or under particular weather conditions, so their detectability is smaller than 1.0 (Mazerolle et al. 2007). One of the major determinants of species detectability are habitat characteristics (Guillera-Arroita 2016), thus the number of individuals of a species recorded can be influenced by how detectable that species is in a specific habitat (McDiarmid et al. 2012). Therefore, differences in numbers of animals observed may be due to inequities in detection rather than to differences in population size and occurrence. Assuming that the detection probability of all species equals 1.0 in all situations may thus lead to erroneous conclusions (Archaux et al. 2012). Hence, in order to validly compare the reptile diversity measurements between the different habitats, it is crucial to take detectability under consideration. 28

Reducing the risk of misled conclusions about difference in diversity between habitats can be achieved simply by visiting the same plot a number of times or by installing several subplots (i.e. replicating counts) and calculating the total number of different species ⁄ individuals (Archaux et al. 2012), as was implemented in this study. This strategy decreases the type I error risk due to an increase in the mean detection probability. Additionally, I estimated the detectability of each observed species in each habitat using a method which was found to be the least biased when the number of repeated visits is small – the binomial mixture MLE (maximum likelihood estimation) method (Wintle et al. 2004). The maximum likelihood equations are given in Johnson et al. (1992) following the work of Kemp and Kemp (1988):

푛 (2) 0 = (1 − 푃̂) + 푃̂(1 − 푝̂)푣 푁

(3) 푥̅ = 푣푃̂푝̂

푛 Where p and P are detection and occupancy rates, respectively, 0 is the observed proportion of 푁 sites where the species was not observed, and 푥̅ is the mean number of observations per site after v visits to all N sites. The MLE values were calculated using an Excel spreadsheet developed by M. A. McCarthy and B. A. Wintle (University of Melbourne, Australia; unpublished) which is described in (Wintle et al. 2004).I then compared the detection probabilities of the species each pair of habitat shared using Wilcoxon's matched pairs test. I used this pairwise test in order to account for the dependency of detectability on the species (Guillera-Arroita 2016). When differences in detectability between habitats are revealed, it is advisable to use diversity estimators rather than raw counts (Archaux et al. 2012), although here there was no necessity to use such estimators (see Results).

Environmental characteristics

I compared the structure of the different habitats using similar techniques I used in order to compare the reptile communities. I used the hierarchical clustering method to construct a dendrogram based on a similarity matrix which was built according to the relative cover proportions of the different structural elements we measured. I used a similarity matrix produced by calculating the Euclidean distance between each pair of plots, since this coefficient is more suitable for analyzing environmental data (Clarke & Warwick 2001). Again, I used group- 29 average linking for the clustering. I tested whether the differences in the physical structure of the different habitats are significant (and their extent) using ANOSIM, based on the same similarity matrix. Additionally, I examined the contribution of each structural element to the dissimilarity in structure using the SIMPER routine. I also compared structural heterogeneity and some selected temperature variables (see below) between the habitats using Kruskal-Wallis and Tukey's HSD test.

Linking environmental characteristics to reptile diversity patterns

As described previously, 9 temperature variables were calculated in order to test their relationship with the reptile diversity patterns (see Assessments of environmental variables section). I calculated all of them due to the uncertainty concerning which of them are the most important for reptiles. However, many of them were expected to be highly correlated. To avoid including redundant variables in further analyses, I performed a variance inflation factor (VIF) analysis in RStudio v0.99.491 (RStudio Team 2015), using a package described in (Zuur et al. 2010). The routine allows the removal of variables which are found redundant due to high collinearity (here: average temperature in sun, total average temperature, temperature range in shade and total temperature range).

I examined the remaining temperature variables (average temperature in shade, temperature range in sun, temperature variation in sun, temperature variation in shade and total temperature variation) in addition to habitat heterogeneity as potential explanatory variables for the reptile diversity patterns using three procedures, as follows. In the first two, the environmental data was log-transformed and normalized to a common scale prior to the analyses.

1. BEST (Bio-Env-Stepwise). The BEST procedure is aimed to find the 'best' match between the multivariate among-sample patterns of an assemblage (here, the similarity matrix of reptile diversity) and that from environmental variables associated with those samples. The extent to which these two patterns match reflects the degree to which the chosen abiotic data 'explains' the biotic patterns (Clarke & Gorley 2006). The degree to which they match is quantified using a rank correlation coefficient. Here, I used the Spearman coefficient (ρ; Clarke & Warwick 2001). The analysis was conducted on a similarity matrix (based on Euclidean distances). I conducted the analysis for all possible 30

combinations of environmental variables. The BEST procedure's significance was examined using a permutation test, repeated for 999 times. 2. Principal components analysis (PCA). PCA is an ordination widely used to describe environmental data, and is more appropriate for this purpose than other ordination types (e.g., NMDS; Clarke & Warwick 2001). When applying this procedure on the environmental data, the plots, regarded as points in the high-dimensional variable space, were projected onto a 'best-fitting' plane, composed of principal components (new axes). The purpose of the new axes (PCs) is to capture as much of the variability in the original space as possible. The extent to which the first few PC's allow an accurate representation of the true relationship between the plots in the original space is summarized by the '% variation explained'. The coordinates of the plots on the PC axes are called the principal component scores (Clarke & Gorley 2006). The PCA's output presented the environmental variables' vectors upon the new plane, thus allowing visualizing the plots in relation to these variables. At the same time, it enabled the illustration and quantification of the association between the variables (as reflected in the ordination of vectors). I later plotted reptile diversity measurements against the PCs which captured most of the variation, using linear regression (as described below), since they provide a summary for the environmental data (Clarke & Warwick 2001). 3. Linear regression. I tested the relationships between the diversity measurements (species richness, total abundance) and each environmental variable individually using simple linear regressions, as commonly applied in reptile diversity studies (e.g., Pianka 1973; Porat 2011). These relationships were not tested separately at each type of habitat due to the small sample size. The relationships between the PCs produced in the PCA and the diversity patterns were tested using multiple linear regressions. The relationships with reptile diversity were not examined due to lack of data in the vineyards (see results). Species richness and total abundance were square-root transformed in order to increase normality and variance homogeneity in the simple regressions.

Results

Reptile diversity patterns

We recorded a total of 359 observations at reptiles in the study plots during the surveys (in both normalized methods and random observations combined). These reptiles belonged to 21 species and 10 families (Table 3), including 2 species categorized as vulnerable to extinction (IUCN, 2016). These two species could be found at the natural patches, while one of them was also found at the olive plantations. No threatened species were found at the vineyards (Table 3). All of the results bellow (apart from Table 3) are based on 229 normalized observations (at 20 species), recorded only during the transects and the time-limited active search.

Examination of detectability showed that the detectability in the olive plantations (0.15±0.08; mean±SE) is similar to that of shared species in adjacent natural patches (0.12±0.04), though it tends to be slightly higher (Wilcoxon's matched pairs test: Z=0.67, p=0.5). The detectability in these natural patches (0.2±0.05) was higher in comparison to shared species in the natural patches adjacent to the vineyards (0.1±0.05), yet not significantly (Z=1.78, p=0.07). Therefore the comparison of diversity measurements between habitats, as presented above, is valid. Nevertheless, I could not validly compare detectability in the vineyards to other habitats. Since all of the observations in the vineyards are single observations, the detectability for all 3 species found in them was constant (MLE = 0.002). The vineyards constitute an extremely exposed habitat which offers scarce hiding opportunities for reptiles (Figure 3), yet the detectability of the species found in them was very low. This contradiction is derived from the tight relationship between detectability and abundance (McCarthy et al. 2013) and not from an actual detection ability, which is non-questionably very high in this case. Thus statistical comparison of the detectability in the vineyards to the other habitats is erroneous and redundant.

Total reptile abundance was significantly and drastically lower in the vineyards, with a mean value of 0.6 individuals (± 0.24) per plot, in comparison to adjacent natural patches, with an average of 11±2.43 (Wilcoxon’s matched pairs test: Z=2.02, p<0.05; Fig. 4a). In contrast, reptile abundance in the olive plantations (15.2±3.43) was similar to the abundance in the adjacent natural patches (19±4.66; Wilcoxon’s matched pairs test: Z=0.67, p=0.5; Fig. 4b). Reptile abundance in the natural patches adjacent to the olive plantations tended to be moderately higher 32 in comparison to the natural patches near the vineyards, though this difference was not significant (Mann-Whitney U test: adjusted Z=0.84, p=0.39; Fig. 4c).

Species richness per plot was also significantly lower in the vineyards, with an average of 0.6 (±0.24) per plot, in comparison to adjacent natural patches, with a mean value of 4.6 (±1.08) (Wilcoxon’s Matched Pairs Test: Z=2.02, p<0.05; Fig. 5a). As opposed to total abundance, species richness in the olive plantations (4.4±0.51) was significantly lower in comparison to adjacent natural patches (8.4±0.98; Z=2.02, p<0.05; Fig. 5b). Species richness in the natural patches adjacent to the olive plantations tended to be higher than in the natural patches near the vineyards, and this difference was near-significant (Mann-Whitney U test: p (exact)=0.055; Fig. 5c). 33

Total

are

near olives

Natural

and classification

ames

plantation

Olive

vineyard

near

Natural

are marked are asterisk.an marked with

species in speciesthe in different of types surveyedhabitats and their

Vineyard

(2016)

IUCN

ing ing

English names are the from missing former.

ppellii

accord

Eumeces schneideri

Chalcides ocellatus

guentheri*

Chalcides

Ablepharus

Unidentified species

laevis

Phoenicolacerta

Ophisops elegans

guttatus

Ptyodactylus

kotschyi

Mediodactylus

chamaeleon

Chamaeleo

Stellagama stellio

Pseudopus apodus

Scientific name

common

when

o extinction

)

fingered

eyed Lizard

toed gecko

hameleon

ulnerable t

Gold Skink

Skink

Ocellated (Bronze)

Cylindrical Skink

Günther's

eyed skink

Rueppel’s Snake

Lebanon Lizard

Snake

Gecko

Sinai Sinai Fan

Thin

Mediterranean

Common Common

Agama

Roughtail Rock

Lizard

European Glass

Common name

Bar Haimovitch 2013 &

(

of observationsof (including occasional observations) at the reptile

also

Scincidae

Lacertidae

Phyllodactylidae

Gekkonidae

Chamaeleonidae

Agamidae

Anguidae

Family

ation. Species categorized as v

2016) and

Sauria

Suborder

Commutative numbers

Squamata

Order

according to (Uetz

taxonomic classific

Table 3

359

Total

132

near olives

Natural

106

plantation

Olive

117

vineyard

near

Natural

Vineyard

collaris

Testudo graeca*

Unidentified species

Telescopus fallax

melanocephalus

Rhynchocalamus

Platyceps

nummifer

Hemorrhois

Eirenis rothii

lineomaculatus

Eirenis

jugularis

Dolichophis

Daboia palaestinae

Unidentified species

Heremites vittatus

Scientific name

Marked

thighed

Tortoise

Spur

Mediterranean

Snake

Mediterranean Cat

Snake

Palestine Kukri

Racer

Collared Dwarf

Snake

Coin

Racer

Roth's Dwarf

Racer

Crowned Dwarf

Snake

Large WhipLarge

Palestine Viper

Bridled Mabuya

Common name

Testudinidae

Colubridae

Viperidae

Scincidae

Family

Ophidia

Sauria

Suborder

continued

pecies richness

Total s

Total abundance

Testudines

Squamata

Order

Table 3

Reflecting both richness and abundance, species diversity (Fisher's alpha index) was significantly lower in the olive plantations (2.63±0.41) in comparison to adjacent natural patches (7.23±1.15; Wilcoxon’s Matched Pairs Test: Z=2.02, p<0.05; Fig. 6a). Species diversity in the natural patches adjacent to the vineyards (3.36±0.95) was also lower in comparison to the natural patches near the olive plantations (Mann-Whitney U test: p (exact) <0.05; Fig. 6b). Since all of the observations in the vineyards were single observations at a single species (in each of the plots in which observations did occur), Fisher's alpha index, as most species diversity indices, was mathematically impossible to calculate. Therefore they could not be compared to the other habitats in terms of species diversity.

Hierarchical clustering of species composition in the study plots showed that the species composition in the olive plantations was distinct, similar to the other communities by only 19.99% (Fig. 7). It significantly differed from the species composition in adjacent natural patches (ANOSIM: R=0.92, p<0.01), and additionally from the species composition in the natural patches near the vineyards (R=0.82, p<0.01). Species composition in the natural patches adjacent to the olive plantations also significantly differed from the species composition in the natural patches near the vineyards, yet more moderately than in the latter cases (as indicated by the lower R and higher p values: R=0.32, p<0.05). These two types of habitat did not form discrete clusters in the hierarchical clustering analysis (Fig. 7). An NMDS ordination showed eminent interspersion of plots representing each habitat type in a similar manner (Fig. 8). Since only 3 reptiles were found in the vineyards throughout the whole study, there is no reptile community per se which inhabits the vineyards and might be compared to the other habitats. Therefore the vineyards were omitted from all species composition analyses.

Three species prominently dominated the olive plantations' community: the skink Ablepharus rueppellii (35.06% of the observations), the gecko Mediodactylus kotschyi (24.67% of the observations), and the lacertid lizard Phoenicolacerta laevis (23.37% of the observations). M. kotschyi was not found at the natural patches, and an average of 12.42% of the dissimilarity 38 between the olive plantations' community and the natural patches' community was attributed to this species (SIMPER analysis). A. rueppellii and P. laevis were less abundant in the natural patches (4.1% and 3.41% of the observations, respectively), and contributed averages of 14.31% of and 11.07% to the dissimilarity between their communities and the olive plantations' community. Both at the natural patches near the olive plantations and near the vineyards, the dominant species was Ptyodactylus guttatus (an average of 39.59% of the observations), which contributed 13.78% of this dissimilarity.

Figure 8. NMDS ordination based on Bray-Curtis similarities (calculates for root-transformed abundances), presenting the reptile community's species composition in 15 study plots (n=5 for each habitat). Stress = 0.12 . The symbols signify the type of habitat: ( ) = olive plantation; ( ) = natural near an olive plantation; ( ) = natural near a vineyard. The overlaid circles denote 20% ( ), 40% ( ) and 60% ( ) similarity between clusters.

The communities' diversity profiles (Fig. 9) reaffirmed that species richness was the highest in the natural patches adjacent to the olive plantations, as the left-hand end is the highest for that community. Species richness was slightly lower in the natural patches adjacent to the vineyards, and the lowest in the olive plantations. The diversity profile for the natural patches near the olives community is entirely above the other two, and therefore is the most diverse by all diversity parameters represented in the profile. The profiles of the olive plantations and of the natural patches adjacent to the vineyards intersect, thus we cannot infer which community is more diverse. While being poorer in species, the olive plantations' community is more even in comparison to the natural patches near the vineyards, as indicated by the higher right-hand end in the profile of the former. The steeper drops in the diversity profiles of the natural patches communities close to the left-hand tail of the graph (0 < 푞 < 15) show that they have more rare species in comparison to the olive plantations' community. 40

A comparison of the Average Specialism Index (SI) between the habitats, based on the calculated specialism ranks, SR (Table 4), revealed an overall significant difference between the average specialism level of the species in the different habitats (Kruskal-Wallis test: H(3,18)=10.39, p<0.05; Fig. 10). The specialism level in the olive plantations (mean value 7.56±0.23) was higher in comparison to adjacent natural patches (5.96±0.19). This difference was near- significant (Tukey's HSD test: p=0.06). Moreover, it was significantly higher in comparison to the vineyards (5.33±1.2, p<0.05) and to the natural patches adjacent to them (5.84±0.26, p<0.05). The specialism level in the vineyards was the lowest among the habitats, yet it differed significantly only from the olive plantations. Due to high variation caused by the small sample size (n=3), it did not differ significantly from the specialism level in adjacent natural patches (p=0.87) nor in the natural patches near the olive plantations (p=0.79). The specialism level in the two types of natural patches was similar (p=0.99).

Table 4. Specialism ranks (SR) for the species observed during the study. A high Specialism rank indicates a high degree of habitat specialism, and vice versa.

Species Specialism rank Species Specialism rank

Chalcides ocellatus 3 Ptyodactylus guttatus 6

Rhynchocalamus 4 Ophisops elegans 6 melanocephalus

Testudo graeca 4 Platyceps collaris 6

Pseudopus apodus 5 Telescopus fallax 6

Eumeces schneideri 5 Ablepharus ruppellii 7

Daboia palaestinae 5 Heremites vittatus 7

Dolichophis jugularis 5 Chamaeleo chamaeleon 8

Eirenis lineomaculatus 5 Chalcides guentheri 8

Eirenis rothii 5 Phoenicolacerta laevis 9

Stellagama stellio 6 Mediodactylus kotschyi 10

Environmental characterization and linkage to reptile diversity patterns

In order to examine whether the observed diversity patterns and differences between communities might be attributed to the structural properties of the habitats, I explored the differences in their prominent structural elements (specified in Fig. 12). Hierarchical clustering of the relative cover proportions of different structural elements in the study plots showed that 42 the different habitats had significantly distinct structures (ANOSIM: global R=0.893, p<0.0005; Fig. 11). The two types of natural patches were the most similar in structure (R=0.724, p<0.01) while the largest dissimilarity was found between the vineyards and the natural patches adjacent to the olive plantations (R=1, p<0.01). Plot O5 was located in an untreated olive plantation, and therefore its structure was more similar to that of the natural patches in comparison to the other olive plantations (Fig. 11). Most (54.41%) of the dissimilarity between the two types of natural patches was attributed to the relative cover of the thorny shrub, Sarcopoterium spinosum (SIMPER analysis). Its cover was higher in the natural patches near the vineyards (27.8% on average) in comparison to the natural patches adjacent to the olive plantations (7.97%). As opposed to that, the natural patches adjacent to the olive plantations were richer in herbaceous vegetation (28.04%) in comparison to the natural patches near the vineyards (18.6%; Fig. 12). This difference contributed additional 15.39% to the dissimilarity between them (SIMPER analysis).

Figure 11. A dendrogram presenting the relative similarity (Euclidean distance) between the composition of structural elements (relative cover proportions) in the study plots. The symbols signify the type of habitat: ( ) = olive plantation; ( ) = natural near an olive plantation; ( ) = natural near a vineyard; ( ) = vineyard. Each type of habitat is structurally distinct. 43

vineyard

olive plantation Habitat natural near vineyard

natural near olives

0% 20% 40% 60% 80% 100% Average relative cover herbaceous vegetation cover olive tree cover vine cover Sarcopoterium spinosum cover woody vegetation cover rock cover stone cover dead plant matter cover bare soil cover

Figure 12. Relative cover proportions (between-plot average) of the main structural elements in the different habitats (n=5 for each habitat).

Variance inflation factor (VIF) analysis showed that several soil-surface temperature variables were highly correlated with others: temperature range in shade, total temperature range in a plot, average temperature in sun ant total average temperature in a plot. Therefore, these variables have been omitted from the environmental variables analyses. BEST analysis of the matching between the community patterns and the heterogeneity in addition to the remaining temperature variables, showed that the highest correlation between the environmental and biotic data was achieved for the combination of two environmental variables: structural heterogeneity and average temperature in shade (ρ=0.318). However, this correlation was not significant (p=0.14).

Principal component analysis (PCA) for the same set of environmental variables showed some separation between two groups of plots, which were similar in their environmental characteristics. One group consisted of the two types of agricultural habitats, while the other group consisted of the two types of natural patches. The grouping was week, implying low separation between the groups. The analysis revealed that the first principal component PC1 explained 43.3% of the total variance between the study plots. It mainly represents a gradient of homogeneity in temperature measured in sun or in shade, as it was strongly and negatively correlated with temperature variation in sun and in shade, and with temperature range in sun. 44

PC2 explained additional 23% of this variance. It mainly represents a gradient in structural heterogeneity and similarity between temperatures measured in sun and in shade, since it was positively correlated with structural heterogeneity and average temperature in shade, while being negatively correlated with the total temperature variation in the plot (Table 5, Fig. 13).

Table 5. Coefficients defining the first two principal components (PCs) in the PCA analysis (eigenvectors).

Variable PC1 PC2 Structural heterogeneity -0.28 0.617 Temperature range in sun -0.59 -0.129 Temperature variation in sun -0.593 -0.156 Temperature variation in shade -0.463 0.122 Total temperature variation -0.011 -0.34 Average temperature in shade 0.086 0.669

The "natural" plots tended to be more structurally diverse and to have higher similarity between temperatures measured in sun and in shade (mean score on PC2 = 0.62) in comparison to the "agricultural" ones (mean score = -0.62). Furthermore, the "agricultural" plots tended to have higher homogeneity in temperatures measured in shade or in sun (mean score on PC1 = 0.89) in comparison to the "natural" plots (mean score -0.89). Both species richness (Fig. 14a) and total reptile abundance (Fig. 14b) tended to increase with a decrease in homogeneity of soil-surface temperatures in shade or in sun (PC1) and with an increase in structural heterogeneity and similarity between temperatures in sun and in shade (PC2). These trends appeared steeper in the case of species richness (Fig. 14). Nevertheless, no significant relationship was found between 2 species richness and PC1 (linear regression: F2,15=2.98, adjusted R =0.19, p=0.08) nor PC2 (p=0.14). No significant relationship was found between total reptile abundance PC2 (linear 2 regression: F2,15=2.17, adjusted R =0.12, p=0.58) and PC1 either, although it was near- significant in the latter case (p=0.06). 45

Figure 13. PCA ordination based on Euclidean distance, representing 6 environmental variables (all log- transformed) measured in the study plots. The symbols signify the type of habitat: ( ) = olive plantation (n=5); ( ) = natural near an olive plantation (n=5); ( ) = natural near a vineyard (n=4); ( ) = vineyard (n=4). The vectors show the correlations between the environmental variables and the principal components. PC1 and PC2 cumulatively account for 66.4% of the total variance between plots.

Figure 14. Surface plots presenting (a) species richness, S, and (b) total reptile abundance, N, in each study plot against PC1 and PC2 (n=18). Total abundance tends to near-significantly increase with a decrease in PC1 (p=0.06) and insignificantly with an increase in PC2 (p=0.58). Species richness insignificantly increases with a decrease in PC1 (p=0.08) and with an increase in PC2 (p=0.14).

A particular examination of each environmental variable revealed a significant difference in structural heterogeneity between some of the habitats (Kruskal-Wallis test: H (3, 20) = 11.35, p<0.05). Habitat heterogeneity (Shannon's index) was significantly lower in the vineyards (mean value of 1.66±0.04) in comparison to the natural patches adjacent to them (1.85±0.03) and to the olive plantations (1.88±0.03; Tukey's HSD test: p<0.01). It also seemed to be lower in the vineyards in comparison to the olive plantations (1.76±0.04), though this difference was not significant (p=0.21). The heterogeneity of the olive plantations was insignificantly lower in comparison to adjacent natural patches (p=0.11) and to natural patches near the vineyards (p=0.25). Both types of natural patches were characterized by similar heterogeneity (p=0.96; Fig. 15).

A positive relationship was found between species richness and structural heterogeneity (linear 2 regression: F1,18=11.77, adjusted R =0.36, p<0.005; Fig. 16a). Total reptile abundance also significantly increased with increasing heterogeneity, though less sharply (F1,18=5.77, adjusted R2=0.2, p<0.05; Fig. 16b). In both cases, one plot in a vineyard ("V5") was unique among the 47 other vineyards in its high level of heterogeneity (Shannon's index = 1.79), yet only one reptile was found in it. Additionally, one plot in an olive plantation inhabited a very large population of P. laevis, although it was slightly less heterogenic in comparison to the other olive plantations (see the outlayers in Fig 16).

Only one of the soil-surface temperature variables, temperature variation in shade, was found to significantly differ between habitats (Kruskal-Wallis test: H (3,18) = 8.44, p<0.05). It was significantly lower in the olive plantations (mean value of 6.2±1.78) in comparison to adjacent natural patches (13.64±1.86; Tukey's HSD test: p<0.05) and to natural patches adjacent to the vineyards (15.06±2.31; p<0.05). This variance was lower in the vineyards (6.88±1.32) in 48 comparison to adjacent natural patches (p<0.05), yet not in comparison to the natural patches near the olive plantations (p=0.09). The two types of natural patches did not differ in the variance in temperature (p=0.94), as well as both types of agricultural habitats (p=0.99; Fig. 17). However, no significant relationship was found between any of the temperature variables and species richness nor total abundance using linear regression.

Discussion

The results of this study indicate that intensive vineyards and intensified-traditional olive plantations have clear and different impacts on local reptile diversity, which distinguish them from natural Mediterranean patches. The intensive management in the vineyards has disastrous consequences for reptiles, reflected both in extremely low abundance (Fig. 4a) and species richness (Fig. 5a) in comparison to adjacent natural patches. Furthermore, one of the three reptiles found in the vineyards throughout the study (a Telescopus fallax) was dead, seemingly as a result of injury (Fig. 18). These results coincide with the predictions and with the results of previous studies, which showed a decrease in reptile diversity in intensive land-uses which do not conserve original land cover (Porat 2011) and in vineyards in particular (Biaggini & Corti 2015). Mortality caused by machinery during agricultural activity was previously recorded at this agroecosystem (G. Rotem, personal communication). Our results are strengthened by the fact that we found no evidence for reproduction of reptiles in the vineyards (while finding eggs and juveniles in adjacent natural patches).

Figure 18. A dead Telescopus fallax, one of the 3 reptiles found in the vineyards during the study.

As opposed to the vineyards, the more traditionally-cultivated olive plantations sustained a diverse reptile community. In one aspect, that of evenness, this community was even superiorly diverse in comparison to the natural patches near the vineyards (Fig. 9), which might contribute to the stability of the community (Wittebolle et al. 2009). Nevertheless, species richness (Fig. 5b) 50 and species diversity (Fig. 6b) in the olive plantations were significantly lower in comparison to adjacent natural patches, as expected. A decrease in local species richness in olive plantations was also reported by Biaggini and Corti (2015). Atauri and De Lucio (2001) also found a negative correlation between reptile species diversity and the area of olive groves in Spain, this time at the landscape scale. However, I found that reptile abundance in the olive plantations was similar to that found in adjacent natural patches (Fig. 4b). This surprising result indicates that olive plantations in our study system serve as a high-quality habitat for some species. Differently from the vineyards, I also found evidence for reptile reproduction in the olive plantations, which coincide with this conclusion. Nonetheless, the similar abundance might have been related to the insignificant trend showing a somewhat greater detectability in the olive plantations, which requires further examination.

The species composition was also affected in different manners by the vineyards and by the olive plantations, as predicted. Although the vineyards do not host an actual reptile community, some insights may be drawn from our findings. Firstly, we did not find any threatened species in the vineyards (Table 3). One of the three species which have been found in them (Table 3), Chalcides ocellatus, is a transient species which was the most generalist species found during the study, and none of the three species were highly specialized (according to their Specialism ranks; see Table 4). Although insignificant due to the negligible sample size, it seems that there is a trend favoring more generalist species in this habitat in comparison to natural patches (Fig. 10). Such species can more likely stand the harsh conditions in the vineyards and attempt to cross them. Yet since only 3 individuals were observed in the vineyards throughout the study, I believe that these species were only crossing, and that the vineyards' environment does not allow the settlement of even transient species.

The olive plantations, on the other hand, host a unique assemblage of species (Fig. 7, Fig. 8), including one threatened species. Their community is dominated, quite evenly, by three species, and includes many others (Table 3). Two of the dominant species, Phoenicolacerta laevis and Mediodactylus kotschyi, are the most highly-specialized species observed throughout the study, and the third one (Ablepharus rueppellii) is not a highly-generalized species either (Table 4). Therefore, the average specialism degree in the community was significantly higher in comparison to most of the other habitats. It was only near-significantly higher in comparison to 51 adjacent natural patches (Fig. 10), yet due to the nature of our field study (i.e. uncontrolled conditions, high variation between the plots and the number of replications), I believe this result might be biologically meaningful. This high level of specialism suggests that the olive plantations' unique structure may 'compensate' for the negative influences of cultivation (e.g. disturbance).

Moreover, these findings indicate that the olive plantations might be highly valuable for reptile diversity, particularly in relation to two of the dominant species. The first one, M. kotschyi, is a gecko which inhabits in Israel mainly large trees (Bouskila & Amitai 2003). Such trees are quite rare in the Mediterranean scrubland, and accordingly this species was not observed at any of the natural patches. The patches of olive trees, on which the gecko is very well-camouflaged (Fig. 19a), might enable this species to persist at the landscape. They are also valuable for A. rueppellii (Fig. 19b), which includes a subspecies which is present in northern Israel (A. r. festae) and is vulnerable to extinction (Dolev & Perevolotsky 2002). This species was very abundant in the olive plantations at our study (Table 3). The ground of these plantations is constantly covered by a thick layer of dead leaves, in which this species favors dwelling (Bouskila & Amitai 2003). Abundant populations of this species in a similar ecosystem, and for the same reason, were found in almond plantations (Porat 2011). Although the threatened subspecies does not occur at our study area, it might react similarly and positively to the presence of olive plantations in shrubland-dominated areas. Hence, it might be interesting to examine the influence of olive plantation on this subspecies in northern Israel, as part of its conservation efforts.

Figure 19. Two of the dominant species in the olive plantations. (a) The gecko Mediodactylus kotschyi, highly camouflaged upon the crumbling bark of the olive tree. (b) The skink Ablepharus rueppellii, active among the fallen olive leaves on the ground (photo: Oz Rittner).

Indeed, I have found strong evidence for the effect of the different habitats' structure on reptile communities. The agricultural habitats significantly differed in their structure from each other and from the natural habitats (Fig. 11, Fig. 12), which accounts for the unique species composition in the olive plantations. Apart from the two species mentioned above, the main species found in the plantations are also associated with vertical structural elements (i.e. P. laevis and Stellagama stellio, the former being also associated with abundant vegetation; Bouskila & Amitai 2003). An additional arboreal species, Chamaeleo chamaeleon, was also observed in the olive plantations (Table 3); Hódar et al. (2000) have previously noted the suitability of the olive plantations as activity and oviposition sites for this species. It seems that these findings distinguish the olive plantations from other tree crops, in which the communities are composited by open, bare-habitat species instead of arboreal and forest species (Gardner et al. 2007; Porat 2011).

In the case of the vineyards it is not possible to tie the assemblage of species to the habitat structure, for the reason previously mentioned. Nevertheless, my results show that they are characterized in a low coverage of herbaceous vegetation (which is usually also sparse) and a high proportion of bare soil, with almost no rocks (Fig. 12). Considering that no woody vegetation exists inside the vineyard apart from the vines, this habitats offers scares shelters for reptiles, both from predators and from weather. It is interesting to mention, that though the 53 herbaceous vegetation inside the olive plantations is as scarce as in the vineyards (Fig. 12), the herbivorous species Testudo graeca was recorded in the plantations (even feeding on the herbaceous vegetation), but not in the vineyards (Table 3).

The two types of natural patches, near the olive plantations and near the vineyards, also differed in some aspects of reptile diversity. Species richness was near-significantly higher in the natural patches adjacent to the olive plantations (Fig. 5c), and here again I believe this result might be biologically meaningful. Although similar abundances of reptiles were observed in these habitats (Fig. 4c), the abundance in the natural patches near the vineyards tended to be slightly (and insignificantly) lower in comparison to the natural patches adjacent to the olive plantations. Incorporating these differences, species diversity was significantly lower in the natural patches near the vineyards (Fig. 6b). The species assemblages in these habitats were quite similar, as indicated by both hierarchical clustering (Fig. 7) and NMDS ordination (Fig. 8), and both communities were dominated by the gecko Ptyodactylus guttatus (Table 3). Nonetheless, some differences were found between their communities' species assemblages, which resulted in a significant difference according to an ANOSIM test.

These results may also be related to the structure of these habitats, which were more similar to each other than to the agricultural habitats (Fig. 11, Fig. 12) yet significantly distinct according to an ANOSIM test. Large rocks were more abundant in the natural patches in comparison to the agricultural habitats (Fig. 12), explaining the dominance of P. guttatus, which favors them as activity and oviposition sites (Bouskila & Amitai 2003). The main differences distinguishing between their structures were a higher proportion of the thorny shrub Sarcopoterium spinosum in the natural patches adjacent to the vineyards, while the natural patches near the olive plantations were more abundant with herbaceous vegetation (Fig. 12).

When abundant, the S. spinosum shrubs create dense, almost non-traversable flats (Fig. 20), in which clear observations at reptiles may be very difficult to attain. This is evident in our results, which show more than twice the amount of observations at unidentified reptiles in the natural patches near the vineyards in comparison to the other type of natural patches (Table 3). As mentioned in the Methods section, observations at reptiles which were not identified to species level were omitted from the data analysis. Additionally, the results did reveal an insignificant trend of lower reptile detectability in this habitat in comparison to natural patches near the olive 54 plantations, which might be meaningful in this case. Therefore, I believe that at least part of the difference in reptile diversity patterns between the natural habitats can be partially attributed to this difference in structure.

Figure 20. An example of a nearly impenetrable flat of the thorny shrub S. spinosum, abundant in a 'natural' sampling plot next to a vineyard.

Notwithstanding, the dramatic influence of the vineyards on reptile diversity cannot be explained in the differences in diversity patterns between the two types of natural patches. Hence, those differences should be certainly considered as concerning from a conservation point of view, due to the possible effects of the vineyards on their natural surroundings. Hostile agricultural patches have been reported to inflict damage on the herpetofauna of adjacent natural areas via processes such as ecological traps (Rotem et al. 2013) and the spread of pesticides (Davidson & Knapp 2007), thus this issue requires further investigation through a controlled study. Either way, the natural patches sustained richer and more abundant reptile communities in comparison to the agricultural patches, including two species which are vulnerable to extinction (Table 3). I have found numerous evidence of their suitability for reproduction of several species, in addition to supporting species which were not observed inside the agricultural habitats (Table 3). These findings emphasize the importance of protecting the Mediterranean shrubland in Israel in order to conserve the local herpetofauna, which was already stressed by Maza (2008) and Porat (2011), yet these areas continue declining (Sorek & Perevolotsky 2016).

Along with the effect of habitat structure on the species composition, the results also support the predicted positive relationship between reptile diversity and habitat heterogeneity. The structural heterogeneity was high (and similar) in the two types of natural patches, while being 55 significantly lower in the vineyards. The level of heterogeneity of the olive plantations was intermediate, and did not differ significantly from either of them (Fig. 15). As expected, positive and significant relationships were found between the level of heterogeneity and reptile abundance and richness (Fig. 16), as indicated by many previous studies (see Introduction). Habitat heterogeneity was found to best (yet insignificantly) explain the observed diversity patterns in the BEST analysis, hence the relationship is stronger than in the case of any of the temperature variables. It is noteworthy that one of the plots in the natural patches adjacent to the vineyards, NV5, was the least heterogenic among the natural plots (Shannon's index = 1.79), and also hosted the smallest amounts of individuals and species.

Apart from heterogeneity, the BEST analysis revealed that the second most correlative environmental variable with the diversity patterns is the average soil-surface temperature in shade. Nevertheless, this variable did not differ significantly between the habitats, as opposed to the variation in temperature in shade. This variable had significantly higher values in the natural patches in comparison to the agricultural ones (Fig. 17), as predicted by the reduced heterogeneity, and indicating lower thermal quality in the agricultural habitats. However, and not as expected, no significant relationship was found between this variable (nor any other temperature variable) and reptile diversity measurements using linear regression.

Such mismatch between the thermal quality of a habitat and reptilian preference has been reported by Diaz (1997), which compared the thermal quality of two sites for populations of the lizard Psammodromus algirus and its effect on their behavior and abundance. Although the differences in the thermal quality of the sites did affect the lizards' behavior, their abundance was similar in both sites. The researcher concluded that there might be more important determinants of habitat quality for these lizard populations, such as food availability or predation pressure. Perhaps a longer and more extensive temperature-data collection is needed in order to infer more robust conclusions concerning the thermal quality of the habitats than that was enabled under the limitations of our study. Nevertheless, such additional factors may be more important in our study system as well. For instance, the vineyards were extremely poor in invertebrates considering what is expected in the area, as has been verified by an entomologist (O. Rittner, personal communication). This might indicate very low food availability for reptiles, and an additional examination of such environmental aspects is needed. 56

Furthermore, the relationship between reptile diversity patterns and environmental variables is possibly more complex, and might be better examined as a part of an entirety of variables, as implemented in analyses such as PCA. Our PCA analysis showed that the agricultural plots are characterized in greater structural homogeneity in comparison to the natural plots (Fig. 13), which agrees with the formerly described heterogeneity analysis (Fig. 15). Moreover, they were characterized by a greater difference between temperatures measured in sun and in shade, yet also by a greater homogeneity in the temperatures measured in sun or in shade. These results suggest that the agricultural habitats offer less thermoregulatory possibilities for reptiles, and that the thermal conditions on the ground are more extreme. It is possible that the vertical complexity of the olive trees somewhat compensates for the unfavorable thermal conditions on the ground, enabling the relatively high reptile diversity, particularly in relation to species which are capable of climbing and are associated with vertical elements. In fact, vertical complexity of the habitat has been demonstrated to be more influential on lizard species richness in North America than horizontal heterogeneity by Pianka (1967). As opposed to the agricultural habitats, this analysis suggests that reptiles may enjoy an improved thermal quality on the ground level in the natural habitats.

Taking this complexity into account using the principal components, my results show an increase in reptile richness and abundance with an increase in habitat and ground-temperature heterogeneity (Fig.14). This relationship is near-significant (p=0.06) only for the aspect of decreasing reptile abundance with increasing homogeneity in temperatures measured in sun or in shade (Fig. 14b). Nevertheless, the decrease in species richness was also close to significant (p=0.08) and due to the nature of this study these results might be meaningful. Additional investigation is needed in order to examine whether the vertical complexity of the olive trees is influential in this case, and 'disrupt' the trends found in relation to habitat heterogeneity and thermal quality.

It is possible that the relationships between reptile diversity and the environmental variables examined here are only artifacts of the influences of untested differences between the habitats (e.g. toxicity of pesticides, soil quality). Nonetheless, my results suggest that the degree of structural heterogeneity can definitely serve as a reliable predictor of reptile diversity in agricultural landscapes. Conservation-wise, we should aim to increase in the heterogeneity of 57 agricultural habitats; such increase might result in enhanced reptile diversity through other mechanisms.

This study involved a variety of technical difficulties. I feel that one of them deserves a special attention due to its importance to future studies. The use of flag for marking the study plots (see Methods) was found very ineffective in the natural patches, since the flags were visually hard to detect among the dense vegetation. Moreover, they attracted large herbivores that attempted to feed on them. Therefore the markings were frequently missing or moved, and remarking the plots was highly time-consuming. This caused slight displacement of the plots during the study period and occasional confusion between plots, in addition to putting the herbivores at risk. Thus, I highly recommand to avoid this marking method in future studies conducted in medditerranean ecosystems, or in other ecosystmes with dense vegetation or the presence of large herbivores.

Furthermore, the amount of observations at reptiles which the analyses were based on was small. This is partially due to the lack of experience of many of the observers. Additionally, the first year of research was very poor in terms of reptile activity in the Mediterranean areas of central Israel (B. Shacham, personal communication). This is reflected in the amount of observations during the two reptile surveys cunducted in the second year of study, which was similar to the amount of observations obtained during 5 surveys in the first year. In future herpetological field- studies of this nature, I recommend using non-revisited sampling plots, in order to increase sample size and reduce the variation caused by site-specific effects.

In spite of the small sample size and high variation in results, some clear conclusions may be drawn from this study. Intensive vineyards constitute extremely hostile areas for reptiles of the Mediterranean. Above of not being suitable habitats for inhabitance, it seems that reptiles even refrain from crossing them, or unable to do so due to the danger involved. Similarly to what was previously deduced for certain groups of beetles (Skutelsky 2011), this study demonstrates that these vineyards consist a barrier in the landscape for reptiles. Therefore, they might induce habitat fragmentation and inflict damage upon the fragmented populations remaining at surrounding natural patches. Such a process may promote a regional decline of reptile populations at the long term. That is particularly concerning in light of the rapid increase in wine production in Israel (Rosenfeld & Avisar 2012). 58

In contrast, intensified-traditional olive plantations sustain a quite diverse reptile community, which is complimentary to the communities persisting in natural patches. Such complementarity is one of the central considerations in prioritizing areas for conservation (see, for instance, Justus & Sarkar 2002). These plantations seem to constitute a particularly valuable land-use for some species, which are least abundant in surrounding natural patches. These include one species which includes a threatened subspecies. This supports one of the main key hypotheses proposed in relation to landscape moderation of biodiversity patterns and processes (Tscharntke et al. 2012). The hypothesis suggests that the differential response of different species to land-use might require different conservation approaches in order to protect endangered species, along with more abundant ones. The incorporation of olive plantations at the landscape to some extent, under a wildlife-friendly management, might thus increase reptile diversity at the landscape scale.

Notwithstanding, it is possible that a substantial improvement in the effect of vineyards on reptile might be accomplished. Nowadays, there is an increasing recognition at the importance of reducing the vineyards' negative impacts on their environment using a sustainable management (Rosenfeld & Avisar 2012). Reducing their hostility towards biodiversity in general and reptiles in particular, might be beneficial for the farmers themselves. Firstly, winegrowers recognize the fact that sustainable management is not only beneficial for the ecosystem, but may also increase the quality of the grapes (Brodt & Thrupp 2009; Rosenfeld & Avisar 2012). Sustaining biodiversity, along with additional ecosystem services, might also provide the farmers with biological pest and disease control (Rosenfeld & Avisar 2012), and especially in the case of reptiles (Valencia-Aguilar et al. 2013), which frequently feed on common agricultural pests (e.g. rodents and invertebrates).

These advantages might reduce the need in chemical inputs, reduce the environmental pollution and improve the appearance of the agricultural landscape (Rosenfeld & Avisar 2012), which is important especially in the case Southern Judea Lowlands. In this area, an agriculture based on rural tourism (e.g. wineries and olive presses) is increasingly developing (Skutelsky 2011). A more wildlife-friendly management might certainly contribute to the olive plantations as well, as along with the described above, they still host a lesser reptile diversity in comparison to their natural surroundings. Some species observed in these natural patches were not observed in the 59 olive plantations at all (Table 3), which might indicate that these agricultural areas are not appropriate for them.

In order to protect reptiles in Mediterranean agroecosystems, I therefore recommend enhancing the connectivity between natural patches, using buffer strips of native vegetation and land cover (e.g. rocks) between and within the crops. Biaggini & Corti (2015) have concluded similarly, after finding a positive influence of connectivity on reptile richness and abundance in native- vegetation buffer strips between agricultural patches. Such buffer strips sustained the greater reptile diversity among the land-uses tested in that study, and were also found valuable by Porat (2011). Atauri and De Lucio (2001) have found a positive correlation between the regional reptile richness and the area covered with by a variegated crop mosaic with hedgerows. Interestingly, in a narrow buffer-strip located inside an olive plantation, we frequently observed the dominant species in the natural patches, which was not present in the olive plantations themselves (P. guttatus). Thus, implementation of structural elements which are absent in the olive plantations and vineyards in such way, may reduce fragmentation. Such vegetated strips may also substantially decrease chemical runoff and soil erosion (Arora et al. 1996). Yet unfortunately, these elements are not implemented regularly, and especially in the vineyards in our study system, which form continuous hostile areas in many cases.

Additionally, as explained earlier, I recommend increasing the structural heterogeneity of the olive plantations by the retention and supplementation of vegetation and rocks within them. The use of inter-row strips of cover crops (or continuous ones), for instance, is a common strategy for enhancing the persistence of natural enemies of agricultural pests within perennial crops (Paredes et al. 2015). This conservation practice might be useful in the case of olive plantations in Israel, and feasible since their management seldom requires the use of heavy machinery. It has also been demonstrated as an efficient strategy for increasing biodiversity and soil quality in a vineyard in Israel (Rosenfeld et al. 2015). However, this conservation practice should be only used jointly with a reduction in cultivation intensity, and especially the use of heavy machinery (due to inflicting possible massive injury and mortality) and pesticides, which may cause poisoning in reptiles (Smith et al. 2007). Increasing the appeal of a hostile agricultural habitat for reptiles might result in an ecological trap (Rotem et al. 2013). Due to their intensive cultivation, 60 vineyards encompass a higher potential of becoming an ecological trap if a more holistic, wildlife-friendly management is not applied.

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תוכן העניינים

הקדמה ...... 7 מטרות המחקר ...... 12 שיטות ...... 14 אזור המחקר ...... 14 אורגניזם המחקר ...... 15 גידולים חקלאיים מוקדיים ...... 16 מטעי זיתים ...... 16 כרמים ...... 18 מערך כללי ...... 19 דגימת זוחלים ...... 20 הערכת משתנים סביבתיים ...... 22 הטרוגניות בית הגידול ...... 22 טמפרטורת הסביבה ...... 22 סכנת הטריפה ...... 23 עיבוד הנתונים וניתוח סטטיסטי...... 23 דפוסי מגוון הזוחלים ...... 23 מאפיינים סביבתיים ...... 28 קישור המאפיינים הסביבתיים לדפוסי מגוון הזוחלים ...... 29 תוצאות ...... 31 דפוסי מגוון הזוחלים ...... 31 אפיון הסביבה והקשר לדפוסי מגוון הזוחלים ...... 41 דיון ...... 49 מקורות ספרותיים ...... 61

תוכן העניינים )עברית( ...... 71

תקציר )עברית( ...... 72

השפעתם של כרמים ושל מטעי זיתים על זוחלים במערכת האגרואקולוגית של שפלת יהודה הדרומית

מאת קסם קזס

חיבור זה מהווה חלק מהדרישות לקבלת התואר "מגיסטר" בפקולטה למדעי הטבע, אוניברסיטת בן-גוריון בנגב, 2017

תקציר

התפשטותה ותיעושה העכשוויים של החקלאות ברחבי העולם, מזיקים לחיות-הבר במגוון דרכים. החקלאות מהווה איום חמור במיוחד עבור הזוחלים, קבוצה חשובה בעלת עמדת-מפתח במארג המזון, המחזיקה ביכולת להוות קבוצה אינדיקטורית שימושית עבור בריאות המערכת האקולוגית. השמירה על המגוון הביולוגי ועל קיומן של אוכלוסיות זוחלים בריאות במערכות אגרואקולוגיות, דורשים ידע אודות השפעתם של גידולים חקלאיים שונים על המגוון הביולוגי, ועל המנגנונים העומדים בבסיסן של השפעות אלה. למרות זאת, השפעתם של גידולים חקלאיים רבים על זוחלים עדיין איננה ידועה. בעייתיות זו הנה נכונה במיוחד באגן הים- התיכון, האוצר ערך עצום עבור המגוון הביולוגי. במחקר שדה זה, בחנו את השפעתם של שני גידולים שכיחים באזורים ים-תיכוניים שלא נחקרו די עד כה, כרמים המעובדים בצורה אינטנסיבית ומטעי-זיתים אינטנסיביים-מסורתיים, על דפוסי מגוון הזוחלים במערכת אגרואקולוגית ים-תיכונית. התמקדנו במבנה בית-הגידול ובטמפרטורת הסביבה כשני משתנים אפשריים חשובים הקובעים את מגוון זה. בנוסף, ניסינו להעריך את סכנת הטריפה לה חשופים הזוחלים בבתי הגידול השונים, אך נסיון זה העלה חרס. השווינו בין מערך של חלקות מחקר עם ביקורים חוזרים שייצגו כל סוג של גידול חקלאי לחלקות בשטחים טבעיים סמוכים, ביחס למדידות מגוון זוחלים, הרכב המינים בחברה, אלמנטים מבניים, הטרוגניות מבנית ומשתני טמפרטורה של פני-הקרקע. הכרמים, מטעי-הזיתים והשטחים הטבעיים הציגו תכונות והטרוגניות מבניים שונים במובהק, שהיו קשורים לדפוסים הנצפים במגוון הזוחלים ובהרכב המינים. הכתמים הטבעיים אופיינו בהטרוגניות המבנית הגבוהה ביותר, וכן בעושר ומגוון המינים הגבוהים ביותר. לעומת זאת, הכרמים האינטנסיביים היו ההומוגניים ביותר, חשופים ביותר, והתגלו כאזורים עוינים מאוד עבור זוחלים. עם זאת, מטעי הזיתים המעובדים בצורה מסורתית יותר, היו הטרוגניים במידת ביניים, והתגלו כבית-גידול ייחודי, התומך בחברה בעלת יחס גבוה במיוחד של מינים מתמחים אשר קשורים במאפייניהם המבניים הבולטים. חברה זו לא נפלה בשפע שלה מזאת שבשטחים הטבעיים הסמוכים ואופיינה ברמת שוויוניות גבוהה. אף על פי כן, היא אופיינה בעושר ובמגוון מינים נמוכים יותר. לא נמצאו מגמות עקביות ביחס לטמפרטורת פני-הקרקע. 73

לאור התוצאות, אני ממליצה ליישם רצועות-חיץ של תכסית טבעי בין ובתוך שטחי גידולים אלה, במטרה למנוע את קיטוע בית הגידול. בנוסף, יש להשתמש בממשק עיבוד חקלאי ידידותי יותר לחיות-בר, הכולל הגדלה זהירה של ההטרוגניות המבנית בשטחי החקלאות.

אוניברסיטת בן-גוריון בנגב

הפקולטה למדעי הטבע

המחלקה למדעי החיים

השפעתם של כרמים ושל מטעי זיתים על זוחלים במערכת האגרואקולוגית של שפלת יהודה הדרומית

חיבור זה מהווה חלק מהדרישות לקבלת התואר "מגיסטר" בפקולטה למדעי הטבע

מאת קסם קזס

תמוז תשע"ז יולי 2017