Scientific and Applicative Aspects of:

Ecological Restoration of the Sand Dune System at North-Western Negev: Restoring Aeolian Activity and Faunal Response

Thesis submitted in partial fulfillment

of the requirements for the degree of

“DOCTOR OF PHILOSOPHY”

by

Udi (Ehud) Columbus

Submitted to the Senate of Ben-Gurion University

of the Negev

21.10.13

Beer-Sheva

Table of context Abstract ...... 3 Introduction ...... 7 Ecological restoration ...... 8 Sandy habitats and their unique features ...... 9 Animals in sandy habitats ...... 10 North-western Negev dunes: Geography, geology and geo-political history ...... 12 Impact of habitat changes on dune-fauna ...... 14 Rationale of manipulation and research questions ...... 16 Methods ...... 17 Study area ...... 17 Manipulation and experimental design ...... 17 Taxonomic groups and sampling methodology ...... 20 Optimal foraging as an indicator of environmental quality and change ...... 22 GUD experiments ...... 23 Digitations of orthophoto for spatial analysis ...... 24 ...... 25 Statistical analysis ...... 25 Software ...... 25 Model selection analysis using AICc ...... 26 Reptile combined score method ...... 27 Rodent abundance estimation ...... 27 Results ...... 28 Overview ...... 28 Conceptual model of dune stabilization process ...... 28 Background ...... 28 Model's description ...... 29 Manipulation-related data and analysis ...... 33 Environmental variables - Aeolian activity, BSC cover, perennial cover ...... 33 Beetle community ...... 38 Trajectories and magnitude of effects ...... 40 Dominant species and indicator species ...... 46

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Reptile community ...... 47 Rodent community ...... 50 GUD analysis ...... 56 Faunal response through time ...... 59 Climate / precipitation annual variability ...... 61 Spatial analysis of shifting sand cover ...... 62 Discussion ...... 64 Changes in environmental variables and their potential effect ...... 64 Beetle community ...... 67 Reptile community ...... 69 Rodent community ...... 70 GUD experiments ...... 72 Spatial analysis of shifting sand cover and its potential impact ...... 73 Conclusions ...... 74 Management recommendations ...... 76 Concluding statement ...... 77 Future suggested studies...... 77 LITERATURE CITED ...... 79 Appendix 1 ...... 89 Appendix 2 ...... 90 Appendix 3 ...... 93 Appendix 4 ...... 99 102 ...... תקציר

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Abstract The modern era has brought about an unprecedented human population growth, accompanied by global economic development. This has put an enormous pressure on natural ecosystems worldwide. One major aspect of this pressure is the species diversity crisis. The rate of species loss in the 21st century is far above the rate of species extinction in the past centuries, when human activity was less industrialized and more locally confound. In the face of this environmental crisis, the classic approach of wildlife conservation is no longer sufficient. While in the past, setting aside nature reserves and wildlife refuges was the main course of action by conservationists, nowadays a more proactive approach is needed This proactive approach is ecological restoration, which advocates for a controlled, well-defined intervention in the degraded ecosystem in order to restore some key functions, processes or organisms. Such an intervention can be either stopping / removing a human-made disturbance or deleterious process; or reactivating a prolonged traditional practice, such as livestock grazing, which have ceased recently. When reactivation is not feasible, some mechanical action mimicking the traditional practice is often used. This was the case in the Agur Sands Nature Reserve (ASNR) – part of the north-western Negev sand dune system.

This system is experiencing an ongoing stabilization process of its dunes during the last three decades. Since grazing practice by Bedouins and their livestock had stopped, the dunes are gradually stabilizing: sand aeolian activity is reduced, vegetation cover is increasing, and biogenic soil-crust (BSC) is establishing on dunes’ surface. This process is seemingly accompanied by some faunal changes, mainly a population decline of some psammophilic (sand-loving) species, and a concurrent increase of more generalist species. Conservation-wise, the greatest concern is for the rare and unique species, which can be found nowhere else in Israel except for this system – such as the horned viper or the Negev tortoise.

In order to ‘turn the wheel back’ and reverse the dune stabilization process along with its faunal implications, I have conducted an ecological restoration practice on eight dunes within the Agur Sands Nature Reserve. On each of those dunes I had employed a manipulation that consisted of breaking up BSC in situ along the dune crest, with partial removal of vegetation cover. BSC breaking was done using a designated soft-tillage 3 device towed by a light All-terrain-vehicle. On each dune a strip of 200 m x 50 m was tilled along the dune’s crest. Two research plots were established on each dune: a manipulation-plot within the manipulated strip, and another plot ~100 m apart, along the same dune – as its paired control. Manipulation took place in June 2010 and approximately 1-year pre-manipulation records and 2-year post manipulation records were taken from the study site for most variables. Records were of both physical and faunal attributes of the dune. Physical attributes: sand mobility (using erosion pins) and BSC cover (assessed both directly via visual assessment and indirectly via penetrometer). Faunal response was measured through monitoring three faunal communities: rodents, reptiles and ground beetles. Perennial vegetation cover was also recorded as an environmental variable.

Data of the different taxa were collected using Sherman traps for rodents, dry pitfall traps for beetles, and a combination of pitfall traps transects and track trails for reptiles. In addition, experiments of giving-up densities (GUD) were conducted aimed at detecting changes of gerbil foraging behavior. These experiments were done using the known and tested method of providing a sand-seed mixture in trays as an artificial food patches.

My main results are divided into the geomorphologic aspect of the dunes and the faunal responses by the 3 different taxa explored in this study. First and foremost, I found that aeolian activity was significantly higher on manipulated plots, and this difference between treatments was evident throughout the study period (after manipulation took place). However, the divergence between treatments decreased through time, and almost leveled-off after 16 months. In general, aeolian activity was higher in wintertime and lower in other seasons. The two other measures of dune stabilization: BSC cover and soil penetrability, were also affected by the manipulation. As BSC cover decreased on manipulated plots due to its breakage by the soft-tillage device, soil penetrability concurrently increased. Manipulated plots also had lower perennial vegetation cover, due to the manipulation practice, although no pre-manipulation measurements of vegetation cover were taken to establish cause and effect for that matter. Ground beetles were dominated by tenebrionidae and carabidae throughout this study. Total abundance was highly variable between seasons and between years. On average, manipulated plots showed a decrease in abundance compared to control. Species composition was slightly 4 different between control and manipulation, and this difference increased over time for the fall community but not for the spring community. Two indicator species were found to significantly change their relative abundance following manipulation: Blaps nitens with a preference to control plots and Erodius spp. with a preference towards manipulated plots. Reptile community showed the highest divergence between treatments (PRC analysis) just following the manipulation practice, but in the next two sample sessions communities converged to a close similarity again. The species-specific response to manipulation was highly divergent among the reptiles. Rodents showed two main responses: 1. GA/GP ratio (initials for the 2 predominant species on the dunes) was 3.4 times higher on control plots which means that both species perceived the manipulation as a habitat change; 2. When Gerbillus gerbillus (a known indicator species for shifting sand) reappeared in the dune system, it had a clear preference towards manipulation. The main result of the GUD experiments was that Gerbillus andersoni had lower GUDs in manipulated plots in two out of three seasons. Another interesting finding was that G. pyramidum preferred the open habitat upon the bushy habitat, but only on control plots. Spatial analysis revealed that although the southernmost latitude (dunes 1, 2) had the highest shifting sand cover, as expected from the regional trend, there was no clear south-north gradient in the rest of the study area. It also showed that the distance from any plot to its nearest sizeable patch of shifting sand was highly variable, even within the same latitude.

To conclude the results we can see two main aspects of the manipulation: 1. Sand aeolian activity was significantly higher on manipulated plots. Breaking up BSC in situ with partial removal of perennial vegetation had triggered sand mobility on dune crests; 2. Faunal response as recorded for three ubiquitous and important communities in the study area (i.e. rodents, reptiles and beetles) was partial and complex. All three taxa had shown some kind of composition change following manipulation, either in their species identity or in the relative abundance of dominant species (which are also good indicator species in the case of beetles and rodents). High temporal variability and medium spatial variability in the recorded abundance, richness and composition within the study area, have potentially masked some subtle responses of the manipulation.

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This research was highly applicative by its nature. One of its declared goals was to come up with long-term management recommendations for the INPA staff (Israel Nature and Parks Authority), who manage the ASNR and other reserves within the northwestern- Negev dune system. Assuming that we share the same conservation goals, I would recommend the following management practice: 1. Upscaling the manipulation practice to include several whole dunes (but still breaking BSC on the crest only). This way a larger continuous habitat of shifting sand is created with all the known benefits associated to it, such as decreased edge effect, easier dispersal and so forth. 2. Continuing to monitor faunal response, with emphasis on focusing on unique and rare psammophilic species. This will give the managers a better picture on the cost-to-benefit ratio of the entire project. The ultimate goal of the management is usually the conservation and restoration of these species. 3. Implementing the manipulation practice at the mid- to north-range of the current study. At the southern range, dunes seem to have increased aeolian activity without mechanical intervention because of the recent long-term drought. 4. Monitoring the effect of manipulation on annual vegetation which is a key player in dune system due to the production of a large biomass of seeds for granivores and of dry (dead) material for the detrivores, such as tenebrionids.

Generally, I believe that breaking the BSC on dune crests, accompanied by partial removal of vegetation, does have a positive effect on faunal communities as a whole and on psammophilic species in particular. However, if the prolonged drought continues (which by now should be termed a climate shift towards hyper-aridity), destabilization of the dunes might occur on its own, and costly restoration acts may become redundant.

Key words: Negev, dune system, dune stabilization, ecological restoration, GUD, sand aeolian activity, biological-soil-crust, eco-geomorphology, rodent community, reptile community, ground beetle community.

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Introduction Biodiversity in general and species diversity in particular are decreasing worldwide. This phenomenon has been termed ‘the sixth mass extinction’ (Leakey and Lewin 1995). It is widely accepted that a major part of this decline is anthropogenic (e.g. Myers 1993, Leakey and Lewin 1995, Pimm et al. 1995, Brooks 2000, Orr 2003, Hansen 2010). Human activity such as habitat destruction, habitat fragmentation, hunting and fishing, water and soil contamination, invasive species and land degradation are responsible for the loss of myriad species in this modern era. Acknowledging our responsibility for this tragic loss, ecologists and wildlife conservationists alike were looking for ways to mitigate and restrain this phenomenon. It was recognized that mere conservation efforts are no longer sufficient. Assigning nature reserves and wildlife refuges aside have approached their effective limits. Legislative measures for the protection of nature values were also of limited effect. This is how the ecological restoration discipline emerged (SER 2004, Young et al. 2005). This proactive approach advocates for a controlled, well- defined intervention in the degraded ecosystem in order to restore some key functions, processes or organisms (Hobbs et al. 2005, van Andel et al. 2006, Falk et al. 2006, Hobbs and Cramer 2008).

Species diversity is mainly decreasing due to habitat change. One way by which habitats are changed through human activity is when land use is changed. When people decide to start using a patch of land in a different way from which it was used before, it affects all physical and biological attributes within this patch. For example, livestock grazing on formerly ungrazed lands has a grave impact on habitat diversity. The opposite case, though not as common, is no less harmful.

Cultural ecosystems are ecosystems managed by traditional, sustainable cultural practices (Clewell and Aronson 2008). Reciprocity exists in these ecosystems between cultural activities and ecological processes, such that human actions reinforce ecosystem health and sustainability (SER 2004). In this kind of ecosystems, faunal communities are evolved to meet the conditions imposed by the human practice (e.g. grazing livestock). Therefore, ceasing a long-lasting grazing practice may alter specific habitats and whole landscapes. This is the case in the north-western Negev sand dune system, which is

7 experiencing an ongoing stabilization of its dunes due to a land-use change. The associated deleterious impact on its faunal communities had led us to the conclusion that an implementation of some sort of ecological restoration is needed in the north-western Negev sand dunes. In the following sections, I will first describe the relatively new field of restoration ecology, following by a description of sandy habitats and their fauna. Then, I will portray the north-western Negev dune system and the process of dune stabilization it undergoes. Finally, I will explain the advantages of using optimal foraging theory in rodent community as a mean to study habitat changes and quality.

Ecological restoration Ecological restoration (ER) is a relatively new applied field, defined as the process of assisting the recovery of an ecosystem that has been degraded, damaged, or destroyed (SER 2004). The three major themes of restoration are restoration of species, restoration of whole ecosystems or landscape and the restoration of ecosystem services (Ehrenfeld 2000). However, restoring abiotic conditions to their historical state before degradation had started may not be sufficient in order to achieve a successful restoration of a system. Ignoring changes in biotic factors and feedbacks between biotic and abiotic factors that have developed in the degraded state, may be a critical error by restorationists (Suding et al. 2004). These feedbacks can make a degraded system resilient to restorative change. Suding et al. (2004) suggest that some degraded systems may be in an alternative stable state and that the dynamics of the degraded state are very different than those of the pristine or target state. They argue that the trajectory to recovery will probably be different from that of degradation. In such systems, restoration efforts may need to manipulate more than the single factor or process that led to the original collapse (Zedler 2000, Chambers and Linnerooth 2001, Adema et al. 2002, Beisner et al. 2003).

Most literature describing the ecological restoration of degraded or disturbed habitats or sites, is dealing with moving a certain ecosystem towards a late successional stage (see Suding et al. 2004). The human impact usually causes a 'drawback' in the natural ecological succession. Therefore, the management practice is aimed at putting the natural process back on its track, or even accelerating it (SER 2004, Davis and Slobodkin 2004, Hobbs et al. 2005). However, in the north-western Negev dune system, human impact (i.e. grazing livestock) was the natural process and a common practice for centuries (Meir 8 and Tsoar 1996, Tsoar 2008), and the fauna evolved in this system was one adapted to a shifting sand habitat. Therefore, stopping the grazing caused the succession to move forward to an undesired state in which it is now, where psammophilic species are losing ground. Hence, restoring this system means reversing the successional process or at least slowing it down, unlike the common practice in most restoration projects worldwide.

Many restoration projects show unsatisfactory results because of an unrealistic and naïve approach by the restorationists. A few misconceptions or 'myths' of restoration ecology (Hilderbrand et al. 2005) are: to expect complete restoration on human time scale, expect the restored system to return to the exact state of pre human disturbance, and assume that supplying the mere physical structure needed will result in a self-assemble of biotic composition and function. Although implementing an ER practice on those dunes might be beneficial for some faunal communities in general, and for psammophilic species in particular, one should not expect a complete shift in the ecosystem within a short period (such as a limited ecological research) for several reasons: 1. The reference plots (control, unmanipulated) are also changing through time; 2. Ecosystem dynamics takes long time, sometimes measured in decades; 3. The chosen manipulation is affecting one factor of the system, while many others are not being controlled (such as climate regimes). Nonetheless, some ecological changes are expected to occur, even at the short period of a typical ecological research (e.g. 2 years), since some ecological parameters are more prone to respond to habitat changes than others.

Sandy habitats and their unique features Sandy habitats constitute around 6% of the global land surface area (Tsoar and Pye 1990). On average, about 20% of the world's arid zones are covered by aeolian sand (Lancaster and Hallward 1984). Most of the major northern hemisphere sand seas are concentrated in the sub-tropical and in the middle-latitude hot and cold desert belts (Tsoar and Pye 1990), including the great Sahara desert belt. This desert belt includes the Sinai and the Negev north-western sands at its eastern tip. For a sand sea or dune-field to form, three basic requirements need to exist (Tsoar and Pye 1990): a) availability of a large supply of sand; b) sufficient wind energy to transport the sand or rework it in situ; and c) suitable topographic and climatic conditions maintained over a long period to allow accumulation of a large thickness of sand. A sand dune length can extend between 1 m 9 and several tens of km in length and its height may range from less than 1 m to more than 150 m. Sand dunes as geomorphological units have ecological importance, as their dimensions, shape, direction and magnitude of movement, topsoil physical composition and other attributes may affect most biological entities and processes. For example composition and richness of the flora and fauna are affected by all these dune attributes, and also dispersal abilities, biotic interactions and so forth. Dunes also define the different habitats in the sandy environment. There are several dune types classified usually by the cover of vegetation, shape, size and orientation of the dune axis relatively to the wind directions and the long-term sand transport resultant (see Hunter et al. 1983). Each of these dune types may be regarded as a whole different habitat by some of the dune inhabitants.

Sand, and particularly shifting sand, is a challenging substrate for most plant species (Danin 1991). This is due to the low cohesiveness of the grains and the low field capacity, and for the fact that sand is considered an inert soil with almost no nutrients in it (Tsoar 1997, Tsoar and Zohar, 1985). However, arid sandy habitats that are under low wind power confer some advantages that may render it a better habitat for many plants and animals (Noy-Meir 1973, Tsoar 2013). In particular, the high rate of infiltration due to coarse particles prevents the evaporation of water at depths deeper than 30 cm. Thus, plants that develop long enough roots are guaranteed better conditions compared with a non-sandy substrate (Noy-Meir 1973, Tsoar et al. 2008). In addition, sand maintains relatively constant and stable conditions of temperature and humidity below the surface. Thus, allowing many animals to avoid the harsh conditions of the desert by burrowing into the sand and becoming active during the chillier hours of the day or night (for examples, see Noy-Meir et al. 1985, Whitford 2002).

Animals in sandy habitats Although sandy habitats in arid landscape seem to provide better habitat for plants and animals, desert ecosystems are inhabited by a highly specialized fauna, adapted to extremely low water availability, high UV radiation, and temperature extremes (Noy-Meir et al. 1985, Punzo 2000). On top of all the aforementioned adaptations needed for desert conditions, animals inhabiting the sandy habitats need to contend with an unstable / mobile substrate. This demands special adaptations for locomotion, borrowing, foraging ever- 10 changing patches of food and so forth. One example of special adaptations for moving on sand is enlarged feet surface. This can be achieved either by sheer size (compared to body mass) or by enlarged projectiles on the foot (dense and long foot-hair in mammals, long and serrated toes in lizards, hairy or serrated tarsus in ground-dwelling arthropods). Many psammophilic species also exhibit behavioral adaptations for the sandy habitat. The most conspicuous animal groups in deserts are reptiles, small mammals (particularly rodents), birds, tenebrionid beetles and ants (e.g. Cloudsley-Thompson 1996). In particular, ground beetles, rodents and reptiles are three animal groups that show high adaptation and present relative high abundances and diversity in sandy habitats. Unfortunately, although the sandy habitat fauna is well studied in other places, Filser’s review (2008) of the fauna of north-western Negev states that almost nothing has been published regarding this specific area, with two exceptions: Mahn (1994) and Henschel (1998) surveyed darkling beetles and sand-borrowing spiders, respectively. A more recent study of ground beetle community was conducted by Renan (2009).

A beetle community is very rich and abundant compared to other taxonomic groups. It is also diverse by means of different trophic levels and different ecological niches occupied by its members (Kremen et al. 1993). For all these reasons, this group is frequently considered as a reliable indicator of habitat richness and complexity in many studies. However, current knowledge of this group at the north-western Negev sands is very limited (Renan 2008, Filser and Prasse 2008). Tenebrionidae is the most abundant beetle family in arid systems (Ayal and Merkl 1994, Cloudsley-Thompson 1996). Renan (2008) has identified 99 tenebrionid species in all north-western Negev sands, 58 of which were classified as rare or very rare in Israel. The richest assemblage of tenebrionid beetles was found in the Agur sands – 70 species. Renan has also found that different beetle community composition is typical for different habitats on the same dune: shifting-sand habitat is characterized by psammophilic species that are almost entirely absent from the stabilized habitat just meters down-slope of the dune. On the stabilized interdune, the beetle community is characterized by more generalist species that have penetrated the dune system from nearby loess and limestone habitats (Renan et al. 2008). Although species identity is quite similar for those neighboring communities, the relative abundance of their components differs substantially. In particular, the presence of the

11 shifting-sand and the semi-stabilized habitats are crucial for supporting the high diversity of beetles in this system.

There are long-term data regarding species compositions and relative abundance of different species of reptile and rodent communities in the ASNR (Y. Ziv, A. Bouskila. unpublished data). Rodent communities are known to be rich with abundant populations across desert ecosystems (Kelt et al. 1996), and Negev rodents are no exception. Rodent studies have been conducted in sandy habitats of Israel for several decades (e.g. Abramsky and Sellah 1982, Abramsky and Rosenzweig 1984) and particularly in the north-western Negev sands (e.g. Kotler and Brown 1988, Kotler et al. 1992a, Ziv et al. 1992, Brown et al. 1994, Abramsky et al. 1997, Brown et al. 1997). Several studies have shown that different gerbil species present similar habitat preference towards the semi-stabilized habitat, however different secondary preference to either the shifting-sand habitat or the stabilized interdune habitat (e.g. Kotler 1985, Brown et al. 1994, Ziv et al. 1995). It has been also shown that other psammophilic animals choose their preferred habitat according to the stabilization level of the sand on the dune (Renan et al. 2008 for carabid beetles, Zaady and Bouskila 2002 for lizards). This aspect of gerbil ecology makes them an excellent model group for exploring how the stabilization process affects psammophilic animals in the long run. We can also use this well-studied group to explore how a habitat change by some manipulation may act to enhance sustainability of psammophilic populations, given the differential impact expected according to their known habitat preference.

North-western Negev dunes: Geography, geology and geo-political history The north-western Negev dune system is an integral part of the Sinai sand dunes. The dunes' sand was derived dominantly from the Nile Delta and by sea currents to the shores of Sinai. From the beach the sand has migrated inland and westward in several waves between 18,000 and 11,500 years ago (Wenkart 2006, Tsoar et al. 2008, Roskin et al., 2011, Muhs et al., 2013). The main dune-type of this system is called vegetated-linear- dunes (VLD). It results from the low wind capacity and the typical wind directions that characterize this region (Tsoar et al. 2008, Tsoar 2013). The resulting parallel VLD (70- 200 m apart) form four characteristic sub-units: crest, north-facing slope, inter-dune and south-facing slope (fig. 1.1). Each of these sub-units has its own abiotic (e.g. solar radiation, dune aspect and slope) and biotic attributes (e.g. microphitic cover, vegetation 12 cover). Each of these sub-units may be considered as a distinct habitat by different taxa, according to their innate preferences and needs (Danin 1978, Renan 2009, Ziv et al. 1993b).

Crest North slope Crest South North slope Southslope slope Interdune Interdune

Fig. 1.1: typical formation of a VLD composed of four characteristic sub-units. Photo by Zehava Siegal

Linear dunes occur on both sides of the Israeli-Egyptian border and are subject to the same climatic regime and geo-morphological history. However, nowadays there is a clear distinction between the two dune-systems of both sides due to a separate and distinct anthropogenic activity in the last three decades (figure1.2). This difference is apparent both to the naked eye, and from the air through remote-sensing (e.g. Karnieli and Tsoar 1995). Apart from a few short periods between the establishment of the state of Israel (1948) and the withdrawal of Israel from the Sinai Peninsula (1982), throughout

Revivim Egypt Study Agur site sands

Ashalim

Nizzana

Fig.1.2: Satellite image of the study area. Modified from GoogleEarth 2009. The study site is 13 situated at the heart of the sand dune ecosystem, and is about 3-4 km east of the Egyptian border. the last couple of centuries, the north-western Negev and Sinai dunes were subject to the same human pressure and the same kind of land-use. The common practice in that period was a moderate-to-high grazing and shrub-gathering pressure by Bedouin and their livestock (Tsoar 2008). This traditional practice involved both the impact imposed by the livestock (eating plants and trampling of soil-crusts) and that of the herders (gathering of woody material for fire and transient constructions). Since 1982, no significant grazing has occurred on the western part of the Israeli side. Ever-since, the dunes of the north- western Negev are subject to an ongoing stabilization process (Meir and Tsoar 1996, Seifan 2009, Siegal et al. 2013) which includes increase in vegetation cover and of biological soil crusts (BSC) and a significant decrease of sand mobility.

Impact of habitat changes on dune-fauna All of the physical changes caused by dune stabilization have a direct or indirect impact on the dune fauna. Dune stabilization results, or correlates, with increased vegetation cover (both perennial and annual), an increase in the surface-area occupied by BSC, and in its developmental stage (whether the crust composed of thin cyanobacterial layer, or a thick rich community of algae, lichens and mosses). Consequently, it causes a habitat change for different faunal communities by affecting resource availability and types, shelter accessibility and the mere substance on which (or in which) the animals move. The species which are affected the most by these habitat changes are those who are specifically adapted to the gradually diminishing shifting-sand habitat. Those species -- sometimes called ‘extreme-psammophiles’ -- are usually unique (i.e. specialists) to sandy habitats and do not occur elsewhere in the Negev. Most often they are rare, endemic or both (Ziv et al. 2008). Even if these species are able to maintain viable populations in the stabilizing dunes when alone, they are likely to be competitively excluded by more generalist species occupying the stabilized interdunes. However, the level of stabilization is not uniform across the whole dune system, and is mainly affected by the south-north climatic gradient. The proportion of shifting sand dunes or patches of mobile sand, out of the total area, is increasing as you go south (Yair et al., 2008). The isolated patches of mobile sand can be considered as 'ecological islands' for extreme psammophiles. The degree of isolation (i.e. the distance to the nearest neighbor) affects dispersal abilities of different species, gene flow, and other features of population dynamics (Levins 1969,

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Hanski 1999). It can also affect foraging efficiency of species with large home ranges that use the mobile sand as a primer foraging habitat. There is evidence for population declines of some psammophilic species over the last decades, such as the endangered Negev tortoise (Testudo werneri) and Buxton's Jird (Meriones sacramenti; Bartan 2009) and the Lesser Egyptian gerbil (Gerbillus gerbillus; Y. Ziv, personal communication). Although it is hard to pinpoint their decline to the ongoing stabilization process, there is some support to the needs of the Negev tortoise for a heterogeneous landscape, including shifting sand (Bartan 2009). In addition to demographic changes resulting from the habitat change, one may find a whole scope of behavioral changes caused by the changing dune status, such as foraging behavior of rodents (see 'Methods').

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Rationale of manipulation and research questions Acknowledging the potential deleterious effect of dune stabilization on the fauna of the north-western Negev dune system, I was looking for some restorative act which could halt dune stabilization and possibly even turn the wheel back. After consulting with the INPA personnel (the managers of this nature reserve) we have decided that breaking biogenic soil crust mechanically, and at spatially designated areas (i.e. dune crests) will be more effective than just restoring grazing activity on the dunes. As soil crust on the dunes developed to such a degree (both by surface roughness and by land cover) that affected water runoff (Yair 1990, Kidron and Yair 2008), plant germination (Prasse and Bornkamm 2008) and aeolian sand activity (Zaady 1999, Veste et al. 2001), only an innovative management could be appropriate to a successful restoration. ER acts to uncover the disappearing shifting-sand habitat and sustain its associated fauna. I used a designated soft tillage device towed by a light ATV (All-terrain-vehicle) to break the biological soil crust (BSC) on dune crests as a measure of ER. Consequently, in this study I ask:

1. Does the breakage of BSC enhance aeolian activity? 2. Do rodents, reptiles and beetles perceive the manipulation treatment as a habitat change? 3. Which ecological aspects are affected by the manipulation (abundance, richness, diversity, community structure and composition) for each community? 4. Is there any spatial effect (mainly geographic gradient, but not only) on the response of faunal communities to the manipulation? 5. What is the temporal dynamics of the different responses observed? Are they short- lived or long-lasting, and is there a fundamental difference between communities? 6. Apart from treatment, which environmental variables are the key factors affecting the 3 faunal communities, and especially the beetle community (the most diverse and abundant one of the three, to which a more complex analyses can be conducted)? 7. Is rodent’s foraging behavior affected by the treatment? If so - can we use such a change to predict future demographic change (see next section for a thorough explanation of this concept)?

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Methods

Study area The north-western Negev sands are located along the eastern (Israeli) side of the border between Israel and Egypt, north of Nizzana and south of the 'Gush Shalom' settlements (figure 1). Its natural boundary on the south and east lies along the road connecting Be'er Sheva with Nizzana. The research focused on the area where dune stabilization is high, but has also a high restoration potential – the Agur Sands Nature Reserve (ASNR). This reserve is under a very low grazing pressure thus suffering from the lack of crust- breaking agents. This region is characterized by VLD formation (see ‘Introduction’) and a sharp gradient of average annual precipitation from north (coastal plain: 170 mm) to south (Nizzana: 90 mm); (Yair et al. 2008, Siegal 2009). Annual rainfall fluctuates greatly from year to year all over the area. Rainstorm events occur mainly between November and March and are mostly of small amounts (below 5 mm; Yair et al. 2008). A north-south gradient of biogenic soil crust, with respect to thickness, complexity and crust species diversity, is also evident, where the thicker, more complex crusts are found in the north (Zaady et al. 2010). As a result, within ASNR, I chose areas along a south- north stabilization gradient in order to test a manipulation of choice on a range of stabilization levels of the dunes. South of the study site the dunes are still partially active, hence manipulation is less needed and will probably have less impact on faunal communities there. In contrast, north of the study site stabilization process has taken over, such that no 'ecological islands' of shifting sands are found as potential source of psammophilic species, to disperse onto the manipulated plots. The selected dunes are located approximately 2-3 km from the border, in the ASNR.

Manipulation and experimental design The manipulation employed on the dunes included breaking of the biogenic soil crust on the dune's crest with some extension to the upper dune's slopes in a consistent setup. Breaking soil crust can be achieved through a number of different means, starting with simple foot trampling by the research staff, and ending with heavy machinery (e.g., tractors). We established manipulated plots by breaking the crust using a soft tillage device, attached to an ATV (figure 2). This technique was chosen in order to minimize

17 harm to the dune structure and its current inhabitants, and yet to allow it to be feasible on large scale manipulation at a reasonable cost and time. The ATV is of light-weight and has wide tires compared to heavy tractors, which results in a relatively low impact on the dune (other than the crust breaking). Apart from breaking BSC, this practice has also caused the removal of some portion of perennial cover and dry annual cover. This dual effect is essential in bringing the dune crest closer to a state of shifting sand. The end result of the manipulation is shown in appendix 1.

I applied a Before-After-Control-Intervention design (BACI, Gotelli and Ellison 2004) to enable tracking changes in time, while controlling for independent environmental changes in space. Overall eight dunes were selected in the study site, each having two 5050 m plots -- manipulated and control. The selected dunes were deployed in pairs along a south-north gradient: every pair at different latitude, about 3 km apart from the next pair. Total range of all plots was approximately 9 km (figure 3). Although this range is relatively small when referring to climatic conditions, it exhibits a 20 mm difference of multi-year annual rainfall average from north to south (Siegal 2009). The manipulation has been applied to a larger area of 50200 m along the dune crest (which includes the manipulation plot within it). This was done in order to minimize edge effect and create sizeable habitat for psammophilic species, especially rodents, which have larger home ranges compared to the other monitored groups. Control plots were situated close to the manipulated plots in a pair-wise design (figure 3). The distance between each control plot and its matched manipulated plot was ~100 m, and both were located on the same dune. Overall, I sampled rodents, reptiles and arthropods in each plot (see detailed explanation for each taxonomic group below). Monitoring period was between August 2009 and August 2012, while the manipulation itself took place at June 2010.

18

Fig. 2: A designated soft-tillage device towed by an ATV. This device was designed such that it breaks BSC at first contact using a rake, followed by a rolling cylinder that crushes the leftover clods. As shown in this photo, dry annual plants are also removed from the surface.

200m

50m C

Border

dune

C = CONTROL

manipulation

monitored plot

Nizzana N

Fig.3: Experimental design. Selected dunes on image are plotted schematically.

19

Taxonomic groups and sampling methodology I have examined three animal groups that are ubiquitous in this dune system: ground beetles, rodents and reptiles. I have also collected data on annual and perennial plants within the plots as environmental factors that may potentially affect the faunal communities. Rodent and reptile identification in the field and learning their measurement protocols were made by manual field guides and experts’ help (Y. Ziv for rodents, B. Shacham for reptiles). Ground beetle identification was made with a reference collection and direct assistance of I. Renan.

Fig. 4: A schematic diagram showing the trapping and monitoring set-up of reptiles and beetles within each dune. Blue circles denote large reptile pitfalls. Dashed diagonal line indicates reptile track-trail. Dashed parallel lines denote the transect path for diurnal reptiles and green circles represent small beetle pitfalls. Rodent traps were omitted from the diagram for simplification (but see text).

 For tracking rodents I used 20 standard Sherman traps on each plot for 3 consecutive nights per monitoring session. Following capture, each individual was identified for its species, sex and age. Its body mass was recorded and It was marked with color on their abdomen and released in situ. Rodents were monitored twice a year (summer and winter), when possible.

20

 Reptiles were monitored using an array of complementary methods (figure 4 and pics. in appendix 3):

1. Track trails were established by dragging a tire along the sand across the plot, in order to identify nocturnal species. Identifying specific footprints and quantifying them is a good indicator for specific activity levels. Trail length is approximately 75 m. 2. Big pitfall traps (12 l buckets) were deployed, 10 traps per plot. The traps were open during the night, and checked on the following morning. 3. Transects are a common method for spotting and identifying diurnal reptiles. I ran two parallel transect lines in each plot. The distance between a transect line and the plot's boundary was 15 m and between the paired lines it was 20 m.

 Beetles were sampled using dry pitfall traps. All live material was collected and brought to the lab, where taxonomic identification took place (appendix 3), using reference collection. 20 traps were deployed in each plot, in an array of ten pairs – one under a bush and the other in the open vicinity. Each trap was opened for 2-3 consecutive days in each session, three sessions per year (autumn, winter and spring).

 Soil crust recovery rates of biogenic soil crusts, following manipulation, were assessed by monitoring 25 quadrates of 11 m each, within each manipulated plot. The measurements from each manipulation plot were compared to the paired control plot and to the before-treatment measurement. Monitoring the crusts was done by using two methods: estimating crust cover-percentage of each quadrate (by eye) and taking eight measurements of soil solidity in each quadrate, using standard penetrometer (appendix 3).

 Sand mobility on each plot was measured using erosion pins (9 per plot) which were inserted shortly after manipulation took place. Those thin metal rods were inserted into dune surface such that above-ground length was exactly the same for

21

all to begin with. Every 3 months, measurements were taken to detect changes in surface height due to erosion or sand accumulation.

Optimal foraging as an indicator of environmental quality and change Foraging theory is a well-studied area of ecology (e.g. Charnov 1976, Brown 1988) and has many implications for different basic and applied fields, such as population ecology, community ecology, behavioral ecology and others. One of the key elements of optimal foraging theory is patch use. According to that theory, where food resources are patchily distributed, a forager leaves a patch when its energetic gain is equal to its total costs (Brown 1988). Brown (1988, 1992) has shown that an optimal forager should leave a patch (natural or artificial, such as a seed tray) when the value of its harvest rate, H, equals the sum of its metabolic C, predation, P, and missed opportunity costs of foraging, MOC ( i.e., H=C+P+MOC). Consequently, resource patches have been used to measure quitting harvest rates of desert rodents (Brown 1988, Kotler et al. 1992b, Brown et al. 1994). Such Manipulated resource patches can be made by mixing a measured amount of seeds in a large volume of sand placed in a tray. Desert rodents foraging in these resource patches experience diminishing returns to harvest effort; the longer a forager spends in a patch, the lower the rate it finds new seeds (Kotler and Brown 1990). At some point, the depleting seed tray will no longer return enough gain for the forager, and it will quit the patch to seek another, or to participate in a different activity (Charnov 1976). The giving-up density (GUD) of seeds left behind in a tray provides a surrogate for its quitting harvest rate (Brown et al. 1994) and can serve as an indicator of habitat preference, predation risk and competition.

In recent years new applications of the GUD technique have been demonstrated, such as using changes in GUDs over time to inform interpretation of actual population trajectories (Whelan and Jedlicka 2007), estimating environmental quality through GUD differences between habitats (Olsson and Molokwu 2007) and using change of GUDs with population-density to reveal carrying capacity (Morris and Mukherjee 2007, see Kotler et al. 2007). GUDs in many cases reflect between-environment differences in habitat suitability (Charnov 1976, Olsson and Holmgren 1999, Olsson and Molokwu 2007). In particular, Olsson & Molokwu (2007) showed that: a) Richer environments result in higher GUD values compared to poorer environments, and b) GUD differences 22 between safe and risky patches within a given environment are higher in richer environments. 'Richer' in this context may be manifested not only by means of more available food, but also by other habitat-quality factors, such as distance between patches and traveling cost. These recent applications of GUDs demonstrate the potential use of this method for testing manipulation studies aiming for a habitat change. Despite its many benefits, the GUD technique relies on several presumptions and considerations that should carefully be assessed before its use and once again when drawing conclusions from its results. These presumptions include the ability to identify correctly the species of the last forager of the patch/ tray, and knowing its territorial behavior (i.e. whether the species in question displays ideal free distribution or ideal despotic distribution). Another drawback of the GUD is when you find a difference in the harvest rate, to which of the components of the equation should you attribute it: C, P, or OMC ?

GUD experiments The GUD experiment protocol was adopted from Kotler et al. (1990) with minor adaptations. A mixture of 5 l sand and 3.5 g of sterilized millet seeds were placed in 80×50 cm aluminum trays. In every plot an array of 9 such trays was deployed, roughly half of them under bushes and half in the open habitat (in cases where bushes were sparse, this ratio was not kept, and more trays were put in the open). The trays were placed before sunset and were monitored and collected next morning. After a night of foraging, each tray and its surroundings was meticulously scanned for gerbil footprints in order to identify which species of gerbil had foraged the tray, and in particular, which was the last forager (to whom the GUD values can be assigned). A 3-grade certainty level was given to each record in accordance with the in-situ recognition ability due to footprints quality. Each tray’s content was then sifted, cleaned from debris and seed husks and weighed with a semi-analytical scale. The net seed weight left by the forager was assigned as the GUD value. By applying GUD experiments for rodents on both manipulated and control plots and in both safe and risky patches, I could test whether manipulated plots are perceived as a 'better quality' habitat from the rodent’s perspective.

23

Digitations of orthophoto for spatial analysis An orthophoto of the study area was taken in October 2010, three months after manipulation took place (figures I-V). Polygons of shifting sand cover around each monitored dune were manually digitized. Classification of the shifting sand was done using ERDAS software prior to the digitation.

I

24

Figs. I-V: Digitized orthophoto of the study area, with shifting sand patches colored in yellow. Semi- stabilized patches are in orange. Classification of the shifting sand was done using ERDAS software. In figures II-V each monitoring plot is marked as black square and labeled according to its dune number and treatment (C=control, M=manipulation). A 300 m radius is illustrated around each plot for spatial analysis calculations (see text).

II III

IV V

Statistical analysis

Software Statistical analyses were performed using Statistica 11 software for the more standard comparisons and analyses. For calculating similarity indices and diversity indices for faunal communities, I used Primer 6 software (Clarke and Gorely 2006). For AICc model evaluations I used “R” program (R Development Core Team 2008). For the PRC analysis of the reptile community I used Canoco 4.5 software (ter-Braak 1995). Plots

25 were created either in ‘excel 10’ or in ‘R’, except for the PRC figure which was constructed with Canoco.

Model selection analysis using AICc Method: in order to identify the variables that are most important in affecting some key beetle community features, I used "Multi-model inference – relative importance of predictor variables" (Anderson 2008, chapter 5). Unlike (old) classical statistics, there is no significance level to which we refer in order to decide whether the effect is real or not, but rather one compares the relative importance of each variable in the model to decide how much the evidence in his data supports the suggested model (Anderson 2008). My data include for each sample, a set of response variables and six explanatory variables: Treatment (manipulation vs. control), categorical time (Pre/post manipulation), Season (three levels: winter, spring and fall), Geographic latitude (four levels A-D; A being the southernmost, D the northernmost), Perennial cover; lag (time passed from the pre- manipulation observation until the current one, in years. Values are 0,1,2.) and Dune (treated as a random effect). Another variable -- sand mobility -- replaced the pre/post variable in the 2nd stage of the analysis, in which I used difference values ('post' minus 'pre' for each season) instead of the original values recorded. As sand mobility measurements were recorded only post-manipulation, their values are treated as a 'post'- 'pre' difference as well. I have conducted this analysis for four different response variables: abundance, richness, Margalef's richness index (denoted as Dmg; this index takes the relative abundance of the sample into account, by dividing total richness in the sampling unit by the ln function of the total abundance: S-1/ln(n)) and Fisher's alpha index. This diversity index is defined by S= α*ln(1+ n/α) where S is number of taxa, n is number of individuals and α is the Fisher's alpha. In another analysis of delta values (table 2), where Fisher’s alpha could not be used, I have used 3 similarity indices as a mean to evaluate a change in community structure. For each response variable I have formulated a complete set of models, including all possible combinations of the explanatory variables + a null model (Y~1), resulting in a 32 model set for each response variable. Using the R program (R Development Core Team 2008), I have computed the AICc values and relative weights of each model in the set. Then, for each explanatory variable I summed up the AICc weights from all models in which it appears. This

26 calculated value enables the comparison and ranking between variables (within a specific model set), and hence their relative importance as predictor variables for the response variable at hand.

Reptile combined score method Data gathered by all three methods were combined to a single score for each reptile species at each sample. This method was adopted from Shacham (2010). All scores are standardized to a 0-5 activity scale, in which 0 means no activity detected at a specific sample and 5 means this is the most active species of all samples combined for a specific method. Next, I combined scores from all methods by assigning the highest score of the three methods to the combined matrix. The rationale for this step is the assumption that activity level of any specific species is best revealed by one of these complementary methods more than the other, and thus should be further used in different analyses.

Rodent abundance estimation Capture-recapture data of a close population (i.e. no birth / death, immigration / emigration occurs between subsequent trappings – subsequent nights in this study) enable performing a good estimation of total population size, based on the proportion of recaptures in the second visit of the sampling site (Chapman 1951, Seber 1982). Using the Chapman estimator, which corrects for a bias at a small sample size, I calculated estimated population size of gerbils for summer 2011 session. This estimation (N=52.7) was almost the same as the ‘new individual count’ of this session (counting only unmarked individuals throughout the session; N=51) and deviated at one individual or less at any particular dune. Therefore, I decided to use and present the more natural estimator of ‘total new individuals per sample’ (3-4 subsequent nights per plot) as ‘abundance’ for all sessions in this study. A more reliable estimation technique requires tagging and identifying separate individuals, which was not feasible in the scope of this study.

27

Results

Overview

This chapter is divided into two major sections: the first is a more basic-theoretical part, elaborating on a conceptual model I have constructed for the dune stabilization process. This part is a stand-alone section of my PhD thesis – with its own background and discussion. The second section presents all my fieldwork data in an ordered fashion. During this study I have gathered ample data, spanning almost three years (nearly one year pre-manipulation and about two years post-manipulation), including three taxonomic groups, several geomorphologic variables, vegetation cover and an aerial photo of the study site. In addition, I conducted three GUD experiments for assessing gerbil foraging behavior and dynamics. In order to follow this complexity of data, I divide it to several sub-chapters, beginning with the physical / environmental variables, followed by the faunal communities, and concluding with the spatial analysis of the shifting sand. The discussion chapter follows the same order, with a concluding paragraph for synthesis and recommendations.

Conceptual model of dune stabilization process

Background Although many studies have been conducted on the process of dune stabilization (e.g. Tsoar et al. 2008, Tsoar 2008, Guo et al. 2008), and some of them have incorporated theoretical models for this process (Hugenholtz and Wolfe 2005, Yizhaq et al. 2007, Nield and Baas 2008, Baas and Nield 2010) none of them is applicable for the western- Negev sand dune system. These dunes are covered by BSC and have specific characteristics that are unique for this region, and none of those models incorporate BSC into their equations. A recent theoretical model, developed by Kinast et al. (2013) incorporates BSC and vegetation cover on dunes. It shows how two states of dune stability can arise under grazing and non-grazing regimes (specifically shown for the sandfield of the Israeli-Egyptian border region). Their model also predicts that without grazing or its equals, the system has dual stable states of either crust-covered dunes or vegetation-covered dunes. However, all quantitative models are very simplistic by their

28 nature and incorporate very few factors. Identifying the main players taking part in this region allow us to better understand the major forces and processes shaping the dune system in general and the stabilization process in particular. I present a schematic conceptual model that explicitly underlines the relations between the main players in this system and shows how manipulating BSC may have the potential of restoring the shifting sand habitat.

Model's description The key player of dune stabilization in arid landscape is BSC, as elaborated in an earlier section (unlike most models which present vegetation cover as the major driving force). As BSC cover increases and becomes thicker and more developed (in a successional process), the dune becomes more and more stabilized. However, some ecological factors either promote BSC establishment and propagation on the dune or slow it down and even prevent it altogether. Wind intensity plays a double role in opposing dune stabilization: high wind power does not allow establishment of both vegetation and BSC and, when established BSC is broken (by animal or machine), it propels the loosened sand and thereby recreates shifting sand habitat on the dune. Pioneer perennial plants such as Stipagrostis scoparia and Artemisia monosperma have the key role of reducing surface wind power to a level which allows BSC establishment. However, plant-BSC relations are very complex and phase dependent. Since both groups belong to the Plantae kingdom (sometimes referred to as macrophyta and microphyta), they potentially compete for light and water. Crust also inhibits germination of some perennial plants (Huang and Gutterman 1998, Prasse and Bornkamm 2008, Langhans et al. 2009). Whether annual plant germination and growth is facilitated or inhibited by BSC is still under debate (Kadmon 1994, Zaady et al. 1997, Belnap et al. 2001, Yair 2008a). Since both plants and BSC need water for their existence, rainfall constitutes a primer characteristic factor in every dune system. Below a certain threshold (roughly long-term average of 50 mm, Tsoar et al. 2008) no vegetation survives on the dunes and therefore all dunes remain mobile. However, if rainfall annual average is above this threshold, and the region suffers from frequent droughts, the higher plants (macrophyta) dry out much sooner than the BSC. The seed bank is another player that cannot be ignored -- it is the source of future plant biomass, but it is also a staple diet component for many granivores, such as

29 gerbils and ants. The amount of seeds available for animal consumption is regulated by wind and loose sand, which expose and cover the seeds alternately (Ben-Natan et al. 2004). Seed ability to germinate is controlled by rainfall amount and distribution, but also by the presence of BSC (see above).

Although the rate of BSC establishment and propagation is regulated by external factors, such as rainfall, wind and vegetation cover (Zaady 1999, Zaady et al. 2010, Kidron et al. 2000, 2010, 2012, Guo et al. 2008) the trajectory is clearly towards increasing level of dune stabilization. Hence, without some soil breaking agents, such as grazing animals or human machinery, all dunes in this region will become stabilized sooner or later. The action of crust breakage must be accompanied by sufficient wind events, which will carry away the loose soil and debris. Otherwise, the next rainy season will foster a BSC recovery (Kidron et al. 2008, 2012).

All of the above descriptions depict how ecological components interact with physical factors to regulate the geomorphologic process of dune stabilization. This can be schematically illustrated as shown in figure 1.1a.

The existing animal community on the dunes is composed of the regional xeric species pool, filtered by the local and temporal conditions. The main factor determining the specific community structure and composition in the dune field is soil type – i.e., the existence of shifting loose sand or stabilized BSC cover. The shifting sand ‘filters’ the psammophilic species from the non-psammophilic ones, which usually have a wider range of distribution. As a result, on shifting dunes (or patches) we find a psammophilic- dominated community. As dunes become stabilized, we expect a gradual community change towards a non-psammophilic dominated community (figure 1.1b). Apart from the different BSC cover, while a dune becomes stabilized it also changes in additional aspects: it possesses higher plant cover, seed renewal is lower and total landscape heterogeneity becomes lower (for the lack of shifting sand habitat). All of these changes together comprise a habitat change, which leads to changes in faunal communities on the dune (especially on the dune crest). Regarding gerbil community structure, different species have different preferred habitats, or at least secondary habitats (Rosenzweig and Abramsky 1986, Ziv et al. 1995). Because of inter-specific competition, I predict that

30 while on the semi-stabilized dune we would find both common species (GP and GA) to coexist, on the shifting dune GP will be dominant, and the extreme-psammophile GG will also be present (figure1.2). On the other end, totally stabilized dune will be dominated by GA, and GG will be absent entirely. This hypothesis is partly supported by a field test by Wasserberg et al. (2007).

31

Increase biomass

Fig. 1.1a: Conceptual model of dune stabilization process at north-western-Negev sand-dune system. Each of the mechanisms appearing next to the arrows is further explained in details in the text.

32

Fig. 1.1b: Conceptual model part II: the way the stabilization level of the dune filters xeric species pool into psammophilic and non-psammophilic dominated communities. The animal community structure is a continuum, lying between the two extremes shown in the figure and so is the state of the dune.

Fig. 1.2: Rodent community model. The basic stabilization model elaborated to include rodent community structure. Arrows and circles in green highlight the added parts to the basic model (figure1.1a).

Manipulation-related data and analysis

Environmental variables - Aeolian activity, BSC cover, perennial cover Aeolian activity on dune crests was measured via erosion pins (see methods). Previous work on shifting dunes at the same area (Allgaier 2008) has shown a marked seasonal change in sand movement across dune crests, due to the seasonal change of the major sand-moving wind directions. Following the same methodology, I tested whether the 33 studied dunes were subject to aeolian activity as well, and whether the breaking BSC treatment had managed to increase aeolian activity on the dune crests. As shifting sand may either be deposited or eroded around a single pin at different times, records of height-alteration may cancel each other if a simple mean is used to evaluate overall aeolian activity at a specific point. Hence, I have calculated 3 different cumulative measures in order to evaluate overall aeolian activity on each plot: cumulative mean of absolute shift, cumulative variance of shift and cumulative range of activity (the difference between highest deposition to deepest erosion per plot). As all 3 measures are highly correlative and show the same trend, I display here only the first one – mean of absolute shift (figure 2.1).

12

10

Control

8 Manipulation

6

4

2 Mean of absolute shift (cm) shift absolute of Mean

0 1 2 3 4 5 6 7 8 Dune

Fig. 2.1: Average of sand mobility per dune - cumulative data. Error bars denote standard error. Even with dune 6 included, the difference between the two treatments is highly significant (one-tailed paired t-test, t=-4.08, p=0.002; when dune 6 is excluded: t=-5.73, p=0.0006).

Figure 2.2 demonstrates the change in aeolian activity through time. In all records activity was higher on manipulated plots compared to control, as measured by the relative change from one record to the next one. Although the overall pattern is identical for both treatments (i.e. control and manipulation), because they both respond to the same wind regime, they differ in the magnitude of wind effect over the sand mobility. Strong winter

34 winds boost aeolian activity in both treatments but much more on the loosened sand of manipulated plots. The following three sessions show stability in control, whereas manipulation exhibits a sharp decline compared to winter. Next winter (16-20 months post-manipulation) boosted activity once again, only to a milder extent. This time activity levels continued to rise into the summer, and the gap between treatments stayed almost the same.

3.5 Control 3 Manipulation 2.5

2

1.5

1

Mean of absolute shift (cm) shift absolute of Mean 0.5

0 0 4 8 12 16 20 24 28

Time - since manipulation (months)

Fig. 2.2: Change in mean absolute sand shift per dune, through time. Each record is relative to the last monitoring session. The strongest shift is during winter months (5 months after manipulation and between 16-20 months AM).

I also evaluated dune crest stability through BSC cover – both by penetrometer and by visual assessment (figures 2.3 and 2.4 respectively; see methods). Although these two techniques are complementary, the former has some advantage, for its objectivity and for its ability to measure crusts that exist also within 10 mm deep or so. Due to missing data I present only the analysis of the last 2 sessions.

35

2.5 control manipulation

2

1.5

1

Mean toughness Mean 0.5

0 1 2 3 4 5 6 7 8 Dune

Fig. 2.3: Soil toughness, taken two years after manipulation, by treatment and dune. Higher toughness scores reflect higher BSC cover and/or BSC thickness and complexity.

Measures were taken in July 2012, exactly two years after the manipulation, using a standard penetrometer. Lowest difference between treatments is at dunes 6 and 7. Dune 7 was heavily grazed prior to this session, hence its low values compared to dune 8 which is located on the same latitude. This can be seen in particular in the control plot. Paired t-test for treatment yields a significant result (one-tailed; t=11.3, p<0.001).

70

60 control

50 manipulation 40 30

BSC cover (%) cover BSC 20 10 0 1 2 3 4 5 6 7 8 Dune

Fig.2.4: Mean BSC cover by treatment and dune, taken at July 2012. Cover was assessed visually at 25 grids per dune of 1 square meter. Paired t-test for treatment yields a significant result (t=4.29, p=0.002 (one-tailed)). 36

As expected, these two evaluation techniques are highly correlated with adjusted R2= 0.80, and linear regression of p<0.001. Nonetheless, differences between plots within each dune (i.e. treatment) are more pronounced visually than by measuring soil toughness. This difference is demonstrated in the photos of dune 4 at appendix 1.

Perennial cover is another key feature of dune crests. It affects aeolian activity by blocking or reducing wind power, and has a large impact on faunal communities as a provider of food and shelter. The manipulation practice carried out on the dune crests had reduced perennial cover by cultivating the upper dune surface, so all small to medium sized bushes and perennial herbs were plowed up. In order to see the magnitude of the impact, I have measured every bush remaining in the plots and calculated its perimeter. Figure 2.5 shows the difference between control and manipulation plots.

12%

10% control

8% manipulation 6%

4% Perennial cover Perennial

2%

0% 1 2 3 4 5 6 7 8 A B C D Latitude and dune number

Fig. 2.5: perennial cover by treatment and dune. Asterisk shows significant difference.

Excluding dune 6, all dunes exhibit marginal to significantly higher perennial cover in control plots. Larger differences between treatments are present in southern and northern latitudes, while midrange latitudes show very minor differences. Differences were highly significant for dunes 1,2,5,7 and 8 (exact binominal test for goodness of fit; p<0.001). Other perennial attributes that were explored are species richness and Fisher’s α. Richness showed no difference between treatments. Fisher’s α also showed close values for all pairs of plots, except for dune 2 (plot 2m=4.18, 2c=1.84). 37

Beetle community In general, the beetle community inhabiting the study area is composed of more than 80 species (Renan 2009). In this study I have collected 6321 individual beetles, of which 6282 were identified at least to the level of family, and the majority to the level of genus and species. The rest has been recognized at least as morpho-species, which enables richness and diversity calculations. In total, I have identified 69 different species. 84% of the species belonged to three families: Tenebrionidae, Carabidae and Curculionidae (figure 2.6). These data were collected during 8 sessions – twice before, and six times after manipulation.

1% 2% 2% 2% 3% 3% Tenebrionidae 3% Carabidae Curculionidae

17% 49% Elateridae Buprestidae Coccinelidae 18% Histeridae Dermestidae Anobiidae Cryiptophagidae

Fig. 2.6: Beetle family distribution by species richness.

In order to identify the variables that are most important in affecting some key beetle community features, I used the 'Multi-model inference – relative importance of predictor variables' (see methods). This method tests through AICc relative scores, which of the explanatory variables included in the model set is more important in affecting the different response variables (table 1).

38

Table 1: Sum of AICc weights for all models in the set, including a specific variable. Full model set= 32 models. n=126. Values with X 0.85 are bald marked.

Response Exp lanat- var. ory variable Abundance Richness Dmg Fisher

Treatment 0.93 0.34 0.26 0.32

Pre_post 1.00 0.49 0.18 0.77

Season 1.00 1.00 1.00 1.00

Geo. Latitude 1.00 0.86 0.06 0.01

Lag 0.87 0.29 0.10 0.13

Table 1 shows that season is the most important predictor variable for all response variables. Treatment has a strong effect only on abundance. Pre-post is equally important for abundance, but 2nd ranked for Fisher's α. Geographic latitude is important for both abundance and richness (ranked 2nd with a value of 0.86). Lag is a good predictor for abundance only. Another way of analyzing these data is treating them as differences (delta values) instead of ultimate values (see methods). This way I can compare the community change through time, using different similarity indices (table 2).

Table 2: Sum of AICc weights for all models in the set, including a specific variable. Response variables are calculated as delta values -- differences between matched seasons per plot, including a new explanatory variable – sand mobility and 3 new response variables. Full model set= 64 models. n=64. Values with x>=0.85 are bald marked.

Response Explanat - var. Abundance Richness Bray-Curtis Jackard Sorensen ory variable difference difference similarity similarity similarity

Treatment 0.97 0.43 0.86 0.80 0.82 sand mobility 0.76 0.33 0.53 0.62 0.68

Season 1.00 1.00 0.81 0.80 0.97

Geo. Latitude 1.00 0.99 1.00 1.00 1.00

Perennial cover 1.00 0.97 0.99 0.99 0.99

Lag 0.89 0.87 0.92 0.71 0.74

39

Table 2 is very similar to table 1 as it is based on a subset data of the former analysis. The second analysis informs us also on the importance of the sand mobility: it has a mild effect on abundance and none on richness. Its effect on the three similarity indices is questionable as the sum of its AICc weights ranges between 0.53 and 0.68 and is far less than the scores of other explanatory variables. Treatment is definitely affecting abundance-difference and probably affecting the similarity indices, but less than other variables (ranked 4th in all three indices). Lag has some effect on all 5-response variables, but has the highest impact on Bray-Curtis similarity index and the weakest effect on Jackard index. According to this analysis, Geographic latitude and perennial cover are the two most important variables that totally affect all the response variables. Season affects abundance-difference and richness-difference alike, and also makes up an important variable for Sorensen similarity.

Trajectories and magnitude of effects As has been already concluded from table 1, Season and Lag are significant variables and therefore each season’s community should be analyzed separately. In the winter community (figure 2.7a) abundance was higher on manipulated plots in the first year post-manipulation in all latitudes, and this difference remained only on ‘C’ latitude for the second year. Additionally, the winter population decreased dramatically throughout the study area in 2012. For the spring community (figure 2.7b) the picture is very complex. First, at pre-manipulation (all plots included), no latitude effect is present. In year one post-manipulation, there is a treatment effect only on latitude ‘C’, in which control abundance is higher than manipulation. In the second year's post-manipulation, control abundance is higher on ‘B’, lower on ‘A’ and similar at ‘C’ and ‘D’ – which means that a treatment-latitude interaction exists. In the fall community (figure 14c) the lag difference is very obvious. Pre-manipulation abundance (fall 2009) was much higher than the 2 following years. In year one post-manipulation control abundance was higher than manipulation for B-D and close to zero for both treatments on ‘A’. In fall 2011 the beetle populations were very low, but nonetheless, a treatment-latitude interaction is clear for C-D latitudes. Across seasons, on B latitude, the treatment-difference in abundance was the highest. I could not find any local attribute to explain this finding. On the 40 southernmost plots (denoted as 'A' in the graph) the treatment difference was the smallest, as the difference between plots pre-manipulation was the lowest (in terms of shifting sand cover).

a) Winter community

30 lag legend:

25 1 = one year post 2= 2 year post 20

15 1-C 10 1-M

Mean abundance per plot per abundance Mean 5 2-C 2-M 0 A B C D Geographic latitude (south to north)

b) Spring community 140 lag legend: 120 0 = pre-manipulation 100 1 = one year post 2= 2 year post 80

60 0-C 1-C

40 1-M Mean abundance per plot per abundance Mean 20 2-C 2-M 0 A B C D Geographic latitude (south to north)

41

c) Fall community lag legend: 250 0 = pre-manipulation 1 = one year post 200 2= 2 year post

150

0-C 100 1-C 1-M

Mean abundance per plot per abundance Mean 50 2-C 2-M 0 A B C D Geographic latitude (south to north)

Fig. 2.7: Mean abundance per plot in winter (a), spring (b) and fall (c) communities by geographic latitude (x-axis), treatment (diamonds vs. squares) and lag (numbered). Note that y-axis scales differently for each community.

Although geographic latitude has some real impact on richness according to the AICc tables, differences in richness values are very small, as can be seen in figure 2.8, with northernmost plots (denoted as D) having the lowest richness, with no clear gradient.

42

Fig. 2.8: Beetle species richness per plot by geographic latitude. Black line denotes mean value, rectangles denote one standard error and empty circle denote a suspected outlier.

Species Richness on the other hand, is highly affected by season, as shown in figure 2.9. Spring richness is significantly higher than fall and winter richness values, as expected from the literature (Crawford 1991, Ayal and Merkl 1994, Costa and Costa 1995, Punzo 2000). When referring to community structure, as manifested in Fisher's α values, we can see big differences between seasons (figure 2.10). Fall values are significantly lower compared to spring and winter, due to the very high dominance of one genus (and within it especially one species) in the fall community – Blaps spp.

Fig. 2.9: Species richness by season. Marking same as fig. 2.8 Fig. 2.10: Fisher’s α by season.

The community similarity between paired control and manipulation plots within each dune is depicted in the following graphs, (figures 2.11 and 2.12 for fall and spring, respectively). The X axis represents the geographic latitude, and the time in which the similarity index was calculated compared to manipulation day is shown by different symbols. The overall picture is quite complex, but some intriguing insights are revealed. First, we can see (more in figure 2.11, somewhat less in figure 2.12) that pre- manipulation similarity is always higher than post-manipulation similarity. This means that breaking BSC on dune crests not only changed the physical attributes of the sandy habitat, but also changed community compositions of ground beetle communities. One year following manipulation, similarities decreased more on the northern and less on the southern plots for the fall communities (figs. 2.11 and 2.13). This incomplete geographic

43 gradient (because D is not as sharp a decline as C) was more pronounced after 2 years post-manipulation, whilst the gradient has become complete. Figure 2.11 also shows that in the north the plots were more similar to begin with, and less similar at the end. Spring communities however, display a different picture (figs. 2.12 and 2.14). First, the similarity indices are very inconsistent within each pair of dunes comprising a latitude group (low homogeneity). Second, there is no clear geographic gradient. Third, while the fall community showed a consistent trend of change in time, the spring community has shown an increase in similarity after two years, following the decrease of the first year. This phenomenon may be attributed not only to the new state of the manipulated plots, but also to the overall higher mobility of sand in the area, i.e., in both the control and manipulation plots.

Within dune similarity - fall community

100

80

60

40

20 Curtis similarity index similarity Curtis - pre post - one year Bray 0 A B C D post - 2 years Geograpic latitude (south to north gradient) Fig. 2.11: Within dune similarity of fall community in paired control-manipulation plots, by latitude and time (lag).

44

Within dune similarity - spring community

100 90 80 70 60 50

40 Curtis similarity index similarityCurtis

- 30 pre 20 post - one year Bray A B C D post - 2 years Geograpic latitude (south to north gradient)

Fig. 2.12: Within dune similarity of spring community in paired control-manipulation plots, by latitude and time (lag).

Figures 2.13 and 2.14 are derived directly from figures 2.11-12, and allow a much clearer perception of the changes over time. Each bar within a lag series (black or grey) represents a separate dune.

Similarity change over time, Similarity change over time, Fall community Spring community 1 2 3 4 1 2 3 4 10 10

0 0 Curtis) - -10 -10 -20 -20 -30 -30 -40 -40 -50 -50 -60 -60 -70 -70 Similarity delta (Bray delta Similarity South-North geographic gradient South-North geographic gradient

delta 1 year delta 2 year

Figs. 2.13 (left) and 2.14 (right): within-dune similarity change over time of the fall and spring beetle communities, by latitude.

Each latitude has 2 dunes, represented as 2 bars of the same color. Delta values on the Y-axis are pre-minus-post difference in Bray-Curtis45 similarity index.

Dominant species and indicator species In order to identify differential response to treatment, I have put all the species of the spring community on a control-manipulation phase graph (figure 2.15). Consequently, each point represents the difference in species counts between spring 2010 (pre- manipulation) and spring 2012 (post). If (annual) changes over time are equal for both treatments, points should be aligned along the unity line.

150

Erodius sp.

100

Manipulation Blaps Zophosis sp. 50 nitens

0 -150 -100 -50 0 50 100 150 200

Control -50

-100

-150

Fig. 2.15: Two-year difference in abundance (April 2010 – April 2012) by treatment. Each point represents a different beetle species (n=56). Unity line is dashed.

Two species were found to deviate significantly from the unity line: Blaps nitens and Erodius sp.(could not be identified to the species level; most likely includes several close species) (Fisher’s exact test, p=0.002 and p=0.009, respectively). Both are tenebrionids. Their preferred treatment is opposite – Erodius increased more on manipulated plots while Blaps increased more on the control plots. These two genera are also the most dominant ones in my dataset, which makes them an excellent indicator species for the

46 manipulation success. Their different preference for shifting sand versus stabilized stratum is well known and documented (e.g. Renan 2009).

Reptile community Reptile community and activity levels were assessed through three complementary methods: pitfall traps, tracks trails and transects (direct observations; see Methods). In total, 14 species were identified and analyzed: two gecko species, three skinks, two sand- lizards, one agama, two vipers, three colubrid snakes and one chameleon. Two more species of conservation interest– Varanus griseus (monitor lizard) and Testudo werneri (Negev tortoise), were observed sporadically around the plots and within the study area range, but their tracks along the within-plot track trails were too few to analyze. The most abundant and active species, both by total activity and by incidence, was Sphenops sepsoides – a skink with very short legs, well adapted to moving and foraging in a sandy habitat. A total of 189 individuals were caught in the pitfall traps throughout the study. A summarizing table of all the pitfall catches is given below (table 3). The proportion of catches was equal between control and pre-manipulation plots (paired plots on each dune) – 34 each for the two sessions of pre-manipulation combined. Just after manipulation (August 2010 session) the proportion shifted significantly to 35:19 towards control plots (exact binominal test; p=0.04), but returned to near equality for the next three sessions. For an evaluation of the whole reptile community change through time, data from all three methods were combined to form a relative score for each species in each sampling session (see Methods). The new combined scores were then analyzed for a PRC (principal response curve; Van den Brink and Ter Braak 1998, 1999) which places the control community on a base line (Y=0) and plots the calculated PRC score of the manipulated community on the same axes. This provides the opportunity to evaluate its distance from the origin at each time point (i.e. sample session) as shown in figure 2.16.

47

Table 3: pitfall catches of reptiles, by species and plot (dune and treatment). The 3 bottom species comprise diurnal fauna, of which the catches are accidental, and sampling effort is uneven.

Dune no. 1 2 3 4 5 6 7 8 Total Total Species Grand C M C M C M C M C M C M C M C M C M total

Stenodactylus sthenodactylus 6 0 6 1 3 3 5 0 6 2 4 1 6 1 3 2 39 10 49

Stenodactylus petrii 5 2 3 2 1 1 2 3 3 6 5 2 4 1 0 2 23 19 42 Sphenops sepsoides 11 6 4 4 2 1 2 7 3 4 0 2 4 4 2 0 28 28 56 Chalcides ocellatus 1 0 1 2 1 0 0 1 0 0 0 0 0 0 0 0 3 3 6 Lytorhynchus diadema 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1

Nocturnal fauna Nocturnal Cerastes cerastes 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 2 2 Cerastes vipera 0 0 0 1 0 1 0 1 2 0 0 0 0 0 0 0 2 3 5

Trapelus savingii 1 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 3 1 4

Acacthodactylus longipes 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 2 3 Diurnal Acacthodactylus scutellatus 0 1 1 0 0 4 1 4 0 3 2 2 0 0 0 3 4 17 21 1 10 15 11 7 10 17 15 17 11 7 15 6 All species combined 24 1 6 7 103 86 189 All nocturnal species 23 8 14 11 7 6 9 13 14 13 9 5 14 6 5 4 95 66 161 combined

Fig. 2.16: PRC of the reptile community. Control scores are the baseline and triangles represent the relative scores of the manipulation community. Black vertical line show when manipulation took place.

48

Figure 2.16 shows that manipulation and control plots are very close at the 1st session as expected (pre-manipulation). In April 2010 they diverge for unknown reason and just after manipulation the difference in community composition is the highest. The next two sessions show convergence of the two communities to a close community composition.

Acanthodactylus scutellatus Acanthodactylus longipes

Cerastes vipera Lytorhynchus diadema Chalcides ocellatus Sphenops sepsoides

species name species Stenodactylus petrii Stenodactylus stenodactylus Trapelus savingii

-6.0 -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 (post-pre) delta catches Manipulation Control

Fig. 2.17: Pitfall catches – values on X axis are total catches of ‘post-manipulation’ minus total catches of ‘pre-manipulation’ of each species by plot type. Displaying only delta values instead of actual catches enables to control for population dynamics through time. Values are normalized by sample effort.

As can be seen from figure 2.17, each species responds differently to the time passed and to treatment. The 2 most striking results are the apparent preference of S. sepsoides for control plots and the opposite responses of the 2 congener Stenodactylus species for treatment.

Focusing on a single species, which is both unique to sandy habitats and endemic to the Sinai-Negev sandfield, -- the horned viper (Cerastes cerastes) -- is of special interest from the conservation aspect and in line with the study’s objectives. Because of its

49 relative big body size (compared to its congener, the common sand viper) it does not fall into reptile pitfalls. In order to detect its activity levels I used its well-distinguishable tracks on the track-trails of the plots. As seen in figure 2.18 its activity level increased through time in both treatments, but much more so in the manipulation. The change seen in manipulation is not significant due to the high variance between dunes (KW test: H=0.36, p=0.083).

9 8

7

6 5 pre 4

Activitylevel 3 post 2 1 0 Control Manipulation Treatment

Fig. 2.18: Horned viper activity level by treatment and time. Pre- to post-manipulation difference in both treatments is not significant at a level of α=0.05, but at manipulation it is close to significance (KW test: H=0.36, p=0.083).

Rodent community In general, the rodent community inhabiting the study area is composed of 6 psammophilic species: Two prominent gerbil species: Gerbillus andersoni allenby (GA) and G. pyramidum (GP). A third gerbil species – G. gerbillus (GG) -- is less common and was trapped only during the later sessions. Jaculus jaculus (common jerboa) is quite abundant on the dunes, but is not trappable with Sherman traps, thus was ignored in this study. G. henleyi and Meriones sacramenti are another two species that are found at the ASNR but were very seldom caught, partly because of my focus on dune crests, which is

50 not their preferred habitat, and partly for their relative rarity. Rodent data were collected during 6 sessions – twice before manipulation, and 4 times after. In total I had 551 individual trappings, of which 322 were new individuals (excluding recaptures). Table 4 summarizes rodent community data with different dependent variables (rows) and different explanatory variables (columns).

51

Table 4: Rodent data collected at the Agur study site during summer 2009 – summer 2012. All data are calculated as mean per sample (i.e. one season of sampling) and not per plot, as total counts were very low. Hence, no SD is shown. Only 3 prevailing species are shown – GA, GP and GG. GH and MS had very sporadic records.

By Treatment (mean per sample) By Season (mean per sample) By Geography (south to north) By Sex m/f Ecological variable Control Manipulation Difference Winter Summer Difference A B C D Male Female ratio

total 29.83 23.83 6 61 50 11 79 71 70 112 174 148 1.18

pre 4 6 -2 4 16 -12 2 2 6 9 12 8 1.50 Abundance post 42.75 32.75 10 118 61.33 56.67 77 69 64 103 162 140 1.16

total 3.47 1.14 3:1 1.60 2.40 -80% 1.29 2.10 1.92 2.24 2.10 2.02 1.04 GA/GP pre 8/0 11.00 NA 3.00 16/0 NA 2/0 2/0 7/0 8 12/0 7.00 NA ratio post 3.26 0.97 3.4 factor 1.56 2.11 35% 1.21 2.00 1.67 2.06 1.94 1.91 1.02

total 9 17 8 6.5 3.25 100% 15 6 0 5 15 11 1.36 GG pre 0 0 0 0 0 0 0 0 0 0 0 0 NA presence post 9 17 189% 13 6.5 100% 15 6 0 5 15 11 1.36

total 36.7 38.9 2.2 g 38.9 37.1 1.8 g 37.31 38.60 36.93 38.27 39.83 35.52 4.3 g

GP body pre no data 29 (n=1) NA 29 no data NA no data no data no data 29 no data 29 NA mass (g) 1.12 post 36.27 39.08 8% 39.1 37.1 5% 37.31 38.60 36.93 38.56 39.83 35.67 factor

52

In the next section I will address the results displayed in table 4, highlighting the more ecologically important ones with respect to the dissertation’s objectives:

Abundance: ignoring pre-manipulation difference, due to the very low gerbil counts, control plots had 10 individuals more on average than did the manipulation plots (paired t-test, one- tailed: t=2.35, p=0.05). This holds for all species together, and may imply higher carrying capacity in control plots. Seasonal changes in abundance are in opposing directions before and after manipulation, mainly because of very high year-to-year differences (not shown in this table) and cannot reveal any repeating pattern. Geographic latitude shows that the northernmost plots have a higher rodent density than the rest of the study area, but this trend is not significant (figure 2.21). Considering only GA numbers on the control plots, a steady increase is visible from south to north (figure 2.19). This gradual increase is marginally significant (one-tailed chi-square, χ=6.06, df=3, p=0.054). Sex ratio is 1.18, but this might be a result of differential capture rates and not of actual sex bias within the population (e.g males have larger home ranges and different spatial behavior than females and hence are more prone to be trapped; Krasnov et al. 2005).

GA/GP ratio: in the two pre-manipulation samples only one individual of GP was trapped so no spatial analysis can be made. After manipulation, GA/GP ratio was 3.26 and 0.97 in control and manipulation plots respectively. This shift of a 3.4 factor suggests that both species perceived the manipulation as a habitat change. Although the ratio difference was present in all post-manipulation sampling sessions, it was significantly high in summer 2010 (just after the manipulation) and decreased as time passed (figure 2.20). This ratio was lower at the southernmost plots (‘A’ latitude), at about 30-40% less than the three other latitudes. GG presence: no GGs were trapped or seen at the study area and at the greater north-western Negev sand system during the first three trapping sessions (summer ’09, winter ’10 and summer ’10). Only in winter 2011 a few individuals of GG were trapped, a phenomenon that has been observed in other rodent studies at the ASNR (Y. Ziv, personal communication). Subsequent sessions yielded even lower numbers, but allowed nonetheless some crude comparisons. About twice as many individuals were trapped on manipulated plots compared to control plots. Although the 2011's winter-session was twice as productive as the mean of the two subsequent summer sessions, it was highly correlated with the overall abundance of

53 those seasons (i.e. GA and GP also doubled at this winter). Geographically, 15 out of 26 individuals were trapped on latitude A; whereas the rest are divided between B and D. Sex ratio was 1.36.

GP body mass: during pre-manipulation sessions, only 1 GP individual was trapped, hence pre-post manipulation comparison cannot be done. Post-manipulation values show that individuals trapped on manipulated plots were 8% heavier on average than those on control plots. This difference is significant (ANOVA test: F=4.43, p=0.038) but is highly variable among years and seasons (figure 2.22). The highest difference was recorded in winter 2011, and this issue is further elaborated in a following section. Mean winter body mass is not significantly different than mean summer values, (ANOVA test: F=2.27, p=0.13). Geographical differences in body mass were not significant either by latitude or by ‘single dune’ (not shown in the table). Males were heavier than females by a factor of 1.12 which is also highly significant (ANOVA test: F=10.7, p=0.001).

50 45 40

35 30 25

20 GA Abundance 15 GP 10 5 0 C M C M C M C M A B C D Latitude and treatment

Fig. 2.19: Species count by geographic latitude and treatment. 'A' is southernmost and 'D' is northernmost. Treatment abbreviation: C=control, M=manipulation. 'C' latitude was corrected by omitting dune 6 and doubling dune 5 scores.

54

16

14 12 control 10 manipulation 8 6 total 4

GA/GP ratio per season per ratio GA/GP 2 0 summer '10 winter '11 summer '11 summer '12 Time

Fig. 2.20: GA/GP ratio by treatment and time during post manipulation.

GA/GP ratio is derived from the graph shown in figure 2.19. The treatment impact on this ratio is clearly visible for all latitudes, although at 'D' latitude GA remains the prevailing species for both treatments. In all latitudes the GA/GP ratio decreases from control to manipulation, due to simultaneous decrease in GA counts and increase in GP counts.

80

70

60

50

40 GA

30 GP Abundance 20 GG

10

0 A B C D South North Geographic latitude

Fig. 2.21: Species count by Geographic latitude and species. Detailed reference is in the text.

55

Body mass is a measure taken by default whenever a rodent is trapped. I found that during summer time there was no significant difference in body mass of either species, but in winter, GP body mass was 9 grams heavier in average on manipulated plots than on control (figure 2.22).

50 C M 45

40 35 30 25 20 n=7 n=27 n=6 n=15n= 16 n=2 n=9 n=14 15 Mean body mass (g) mass body Mean 10 5 0 summer '10 summer '11 summer '12 winter '11 Time

Fig. 2.22: GP mean body mass per season and treatment. Labels within bars denote sample size. Error bars are standard error.

GUD analysis In total, 653 trays were foraged by gerbils during 3 sessions that took place during October 2010, July 2011 and June 2012. After omitting records in which the foraging species were identified with a low certainty level, and 2 trays that were foraged by J. jaculus, 584 trays were left for the GUD analyses. More trays were foraged on the control plots (335) than on the manipulated plots (318). Significantly more trays were foraged at the open habitat than under or next to bushes (370:272 respectively; Exact binominal test, P<0.001). Of the higher certainty identification data, 74% of trays were foraged by GA, 20% by GP, 3% by both species, and 4% by GH. There was a large difference in GUD values between sessions, both by their absolute values and by the difference between species within each session (see figure 2.23)

56

0.60

0.50

0.40

0.30

0.20 GA mean GUD (gr)GUD mean GP 0.10

0.00 C M C M C M October 2010 July 2011 June 2012 Time and treatment

Fig. 2.23: Mean GUD values by time, treatment and foraging species. C=control, M=manipulation. Error bars are standard error.

Two results are noticeable: July 2011 values are significantly lower than the two other sessions (ANOVA, p<0.001), and GP values at 2010 on the control plots are significantly lower than GA values (t-test, df=88, p=0.02). This difference disappears on manipulated plots, and is not evident at other sessions. Regarding treatment effect, in the 2010 session, GUD values for GA are significantly lower on manipulation than on control plots (ANOVA, p=0.015). Treatment × site interaction was significant for the two species combined and for GA alone (nested ANOVA, F=5.55, p=0.019; see figure 2.24) but not for GP. Treatment × latitude interaction was even more significant than by site for both species combined (nested ANOVA, F=5.63, p<0.001), whereas treatment effect of “B” latitude (i.e. dunes 3,4) was the most distinct from the other latitudes.

57

0.50 a 1 b

0.40 2 A

3 B

0.30 4 C 5 D 0.20 mean GUD mean 6 7 0.10 8

0.00 C M C M Treatment Treatment

Fig. 2.24: GUD values in the control and manipulated plots by site and latitude. C=control, M=manipulation. a) treatment × site interaction for GA data. Each line represents different dune; b) treatment × latitude interaction for GA+GP data. Both interactions are significant (see text).

Regarding micro-habitat, there was a difference in open / bush values for GP only, more on the control plots (ANOVA, p=0.038), and less on the manipulation (ANOVA, p=0.16; figure 2.25). Although the latter is not statistically significant, it has an opposite trajectory (higher values of GUD at open habitat) than the mean values of control plots. Treatment × microhabitat interaction for GP is significant (nested ANOVA, F=3.99, p=0.02).

0.60

0.50

0.40

0.30

GUD BUSH 0.20 11 * OPEN 111 135 52 0.10 32 16 65 108 0.00 GA GP GA GP C M

Fig. 2.25: GUD values by treatment, species and micro-habitat. Labels within bars denote sample size. C=control, M=manipulation. Error-bars are standard-error of the sample.

58

Faunal response through time I found significant changes in all faunal communities studied, both by year (annual) and by season (see above). In this section I explore whether those changes follow a constant trajectory and whether they are either magnified or diminished through time. One way to control the high seasonal changes in abundance is looking at ratios.

Rodents: The high GA/GP ratio seen just after manipulation (summer 2010, three month post manipulation; figure 2.20) decreased sharply by the next winter, and stayed at those levels for the next two sessions/ years. The control-to- manipulation ratio of the former analysis (a ratio of a ratio; figure 2.26) provides a slightly different pattern.

8.00 7.00 6.00 5.00 4.00 3.00 2.00 1.00

C to M C toratio ofGA/GP index 0.00 summer '10 winter '11 summer '11 summer '12 Time

Fig. 2.26: Control/manipulation ratio of the GA/GP index. Dashed line is a 1:1 ratio.

The high ratio remained for a year and a half after the manipulation and then fell drastically, with a moderate rebound in the following year.

Beetles: Another way to control for annual change is by looking at a community structure index, which is less prone to temporal variation then abundance, such as Fisher’s α values. Figure 2.27 shows how this index changes for the spring community within a three-year period. We see that although there is quite a big annual variation in this index, the difference between treatments follows a constant trajectory and within two years the ratio turns around from being higher on the control plots to be higher on the manipulated plots.

59

12.00

10.00

8.00

6.00 Control

4.00 Manipulation Fisher's alpha Fisher's 2.00 delta

0.00 Spring 2010 Spring 2011 Spring 2012 -2.00 Time

Fig. 2.27: Spring beetle Fisher’s α over time. Dashed line represents manipulation time. Green triangles represent the delta between control and manipulation values.

Reptiles: A different pattern of activity levels at each dune exists, even within the same latitudes – as exemplified by figure 2.28 (total activity level derived from track trail alone; nocturnal fauna). This figure presents activity levels in 4 out of 8 dunes. Dune 1 (left diagram) shows an immediate response just after manipulation (July 2010) of a higher reptile activity on the manipulated plot. This habitat preference disappears in the next spring session.

16 16

14 Dune 1 14 Dune 2 12 12 10 10 8 8 6 6 4 4

Control Manipulation Activity Activity level (tracks) Activity Activity level (tracks) 2 2 0 0 Sep.09 Apr.10 Aug.10 May 11 Aug.11 May 12 Aug.12 Sep.09 Apr.10 Aug.10 May 11 Aug.11 May 12 Aug.12 Year and Month Year and Month

Fig. 2.28: Reptile activity levels calculated from tracks data, by time and treatment, at 4 separate dunes. Empty diamonds are control and full squares are manipulation. Note that not all sampling sessions are included in each of the dunes shown here.

60

20

Dune 4 Dune8 15 15

10 10

5 5 Activity Activity level (tracks)

0 Activity level (tracks) 0 Sep.09 Apr.10 Aug.10 Aug.11 May 12 Aug.12 Sep.09 Apr.10 Aug.10 May 12 Aug.12 Year and Month Year and Month

Dune 2 (right diagram on previous page; at the same latitude as dune 1) shows an opposite response, which is gradually decreased for the next 4 sessions. On dune 4 (left diagram above) we see again a preference towards manipulation, but this trend stays for the next 2 years. On dune 8 (right diagram above) no preference is evident for the whole study period. Dunes 5 and 7 (not shown in the graph) showed alternating preference, and dune 7 showed a decreasing preference towards manipulation.

Climate / precipitation annual variability I intended to obtain on each and every dune the precise rain measurements. This however did not yield the expected results, due to some technical and logistical problems. Using some crude analysis of five meteorological stations scattered around the Haluza sands in addition to the incomplete records I measured myself, provides a very good picture of the great annual variability of rain amounts throughout the study period. In the winter of 2009-2010 the total precipitation was about 120-130 mm. Winter of 2010-2011 summed up to a meager 30- 35mm; and the next winter (2011-2012), summed up to 45-60 mm. This sharp decline of about 75% from pre-manipulation sessions to post-manipulation sessions (apart from August 2010 which was post-manipulation), can explain the importance of ‘lag’ (annual variability) at the AICc-model selection (tables 1 and 2) as an explanatory variable for beetles. Annual rain amount is known to affect herbivore communities through the annual vegetation biomass and also through the grain-yield of perennials. This later aspect is also a very crucial impact on a rodent community in deserts, which is primarily granivorous. One should also recall that during droughts, the temporal and spatial distribution of rain events is very stochastic, which may mask any geographical gradient apparent at larger scales (Siegal 2009).

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Spatial analysis of shifting sand cover As already mentioned in earlier sections, no evidence was found for a geographic south-north gradient, not for the environmental variables, nor for the faunal responses. The lack of gradient, however, does not signify that latitude by itself has no effect on response variables, as shown by tables 1 and 2, and figures 2.5, 2.6 and 2.19. So far, I have analyzed the geomorphologic state of the plots themselves. In order to further explore and analyze the spatial heterogeneity and distribution of shifting-sand cover around the plots, I used GIS geo- processing procedures on an orthophoto of the study area, taken at October 2010 (three months post-manipulation). After manual digitation of the patches of shifting sand up to 300 m around each plot (see methods), I have used an R script to conduct two separate analyses to calculate: 1. the percentage of shifting sand in varying radii (75-300 m) around each plot (figure 2.29); and 2. the minimal distance of each plot to a mobile patch of at least 400 m2, and the size (total area) of this nearest neighbor polygon (figure 2.30). This minimal patch area of mobile sand was chosen as a threshold to ensure that patches can sustain psammophilic species either as a 'source habitat' or at least as a 'sink habitat' allowing dispersal and emigration processes from the monitored plots.

60% buffer radius 50% 300 40% 200

30% 150

100 20% 75

10% Porportionfromtotalbuffer area 0% 1 2 3 4 5 6 7 8 A B C D Latitude and dune no.

Fig. 2.29: Proportion of shifting sand cover around different dunes at varying buffer radii. Paired plots within each dune were averaged. A-D denote south-north latitude gradient, respectively.

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The most conspicuous result of the first analysis (figure 2.29) is that latitude A (dunes 1,2) is surrounded by much higher shifting sand cover than all the rest. Furthermore, in dunes 1,3,4 and 6, as buffer radius increases, the proportion of sand cover increases as well. In dunes 2 and 8, 150 m radius has the highest proportion of sand cover. Dune 7 is exceptional in two aspects: proportion rises as buffer decreases, but this holds only for the control plot (resolution by treatment is not shown in the graph). In dunes 3, 4, and to a lesser extent 5 and 6 (latitudes B-C), radii of 75 m and 100 m around plots have zero or close to zero shifting sand cover. This can have a real impact on beetle dispersal ability and also on that of some reptile species.

150 120,000 120 12,000

)

125 100,000 ) 100 10,000

2

2

100 80,000 80 8,000

75 60,000 60 6,000

50 40,000 (m) distance 40 4,000

distance (m) distance

Polygon Polygon area(m^ Polygon Polygon area(m^ 25 20,000 20 2,000

0 0 0 0 1c 1m 2c 2m 3c 3m 4c 4m 5c 5m 6c 6m 7c 7m 8c 8m 1m 3m 4m 5m 7m 8m plot plot distance to nearest patch distance to nearest patch area of nearest patch area of nearest patch

Fig. 2.30: Minimal distance (meters) from each plot to a patch of shifting sand (of a minimum size of 400 m2), and the area of the nearest polygon / patch. Left graph includes all plots. Right graph omits control plots, as well as dunes 2 and 6, to achieve a higher resolution of the rest. Dashed lines on the left graph mark thresholds of 25 m and 75 m, which might have some dispersal significance (see text).

In order to assess potential dispersal limitations for faunal communities from active dunes surrounding the plots to the manipulated plots themselves, we should look at the two response variables together. The main outcome from the above graph is that plot '4m' has the worst dispersal potential; and plot '2m' has the best by far. '5m' is the next highest in dispersal potential.

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Discussion The aims and challenge of my study were two-fold. On one hand I wished to restore the sand dune ecosystem in ASNR by restoring its aeolian activity and monitoring its effect on three faunal communities ubiquitous in this system. Conservation-wise, I was most interested in the demographic response of the psammophilic species, which seemed to suffer the most from the dune stabilization process. On the other hand I strived to enhance our understanding of the main factors and processes shaping and influencing this system. The focus of my research was to explore the eco-geomorphologic interaction by investigating how sand aeolian activity, dune stabilization and faunal responses interact.

Changes in environmental variables and their potential effect All environmental variables measured in this study have shown that manipulation had a significant effect on the studied dunes – both on their physical attributes, such as aeolian activity, and their biotic (floristic) attributes, such as perennial vegetation cover and BSC cover. These three factors (aeolian activity, perennial cover and BSC cover) are key players in the dune stabilization process (see conceptual model, figure 1.1a). Their trajectory following manipulation (i.e. enhanced aeolian activity, reduced BSC cover and reduced perennial cover) suggests a significant decrease in the rate of dune stabilization and even a reversal effect in some dunes (i.e. destabilization). All of this contributes to an increase in the proportion of the shifting sand habitat in the ecosystem, as evident from the spatial analysis, and consequently an increase in the landscape heterogeneity.

The increase in the cover of shifting sand patches on dune crests, at the expense of BSC and vegetation cover, can have a profound effect on faunal communities. Loose sand substrate is an entirely different habitat from stabilized, crusted dune surface. It affects animal movement (e.g. gerbils with special adaptations to enhanced mobility on sand – (Mendelssohn and Yom- Tov 1999, Shenbrot et al. 1999), psammophilic geckos -- (Cloudsley-Thompson 1991a, Zaady and Bouskila 2002). As this change affects movement ability of both predators and prey species, it may also affect their interactions (Abramsky et al. 1992, Kotler et al. 1992a, Brown et al. 2001). The shifting sand also alters burrowing and camouflage ability (e.g. Cerastes vipera and Cerastes cerastes). It affects the hydrological regime of the dune by altering the runoff/ infiltration ratio (Yair et al. 2001, Kidron et al. 2003, Almog and Yair 2007). This, in

64 turn, directly affects water availability for vegetation on the crest, and indirectly its availability all over the dune (Allgaier 2008, Yair 2008a). In addition, germination success of new seedlings is much higher in bare sand compared to crusted sand for many shrub species. On a broader scale of time and space, shifting sand habitats are more productive and can sustain higher biomass than other non-sandy habitats of the same climatic region (Noy-Meir 1973). Shifting sand also enables resource renewal, especially for granivores (Ben-Natan et al. 2004), thus enabling the co-existence of congener gerbils, and a richer rodent community (Ziv 1991, Kotler et al. 1993, Ben-Natan et al. 2004, Wasserberg et al. 2006).

In addition to all these apparent ecologically beneficial impacts caused by dune manipulation, the reduction of perennial cover may play an important role in its effect on dune fauna. Perennial cover affects faunal communities (e.g. ground beetles) in two main aspects: bushes are a source of food for different guilds (as grains, leaves, or dead tissue) and may act as refuge and shelter from predators and solar radiation. In addition, several results (figure 2.5) relate to how perennial cover is affected by both treatment and geographic latitude: 1. Apart from dune 6, the plant cover within each geographic latitude-treatment combination is quite uniform, which suggests that some local factors are affecting this variable; 2. A latitude (south) and D (north) show a significant reduction in plant cover when comparing manipulation plots to control plots within each dune. In total, apart from dune 6 (in which we know the manipulation was not as efficient as in other dunes), all dunes show lower values of perennial cover on manipulated plots compared to the control plots; 3. The magnitude of the treatment effect on plant-cover reduction was as follows: A, > D, > C and a minor or no effect in B. No south-north gradient is apparent. If only control plots are examined, we obtain a right-skewed u-shaped pattern, with the highest scores in the south, medium to low values in the middle, and higher values again in the north. Although one might expect a south-north gradient in accordance with the precipitation gradient, this is true only for a long-run (multi- year) average. In fact, the last few years were very poor in precipitation and had sporadic, and therefore geographically stochastic, rain events. Less vegetation means fewer food resources and less refuge and cover. But while potentially reducing herbivore abundance, it can also alter community composition and provide advantage to xeric and psammophilic species over generalist ones (Crawford 1991, Ayal and Merkl 1994, Cloudsley-Thompson 1996).

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However, one should not expect the whole spectrum of the aforementioned potential effects to be found in the manipulated plots of my study sites. This is for several reasons, such as the scale and extent of the manipulation practice, magnitude of the effects, and some confounding effects (e.g. high seasonal variation or prolonged drought effect). Referring to the scale and extent of the manipulation, one should notice that manipulation took place only along dune crests, leaving dune slopes and inter-dunes in their semi-stabilized to stabilized states. Thus, the resulting habitat change was partial and discontinuous. Nonetheless, some results do accord with those effects, and are discussed further on.

One key question regarding any ecological restoration project is how long the desired effect/s last following manipulation (Many good examples at Cabin 2011). Does it need continued maintenance, and if so, how often? With respect to the dune system, Yair (2008a) showed that following crust removal from the dune (same dune system, some 15 km south of my study site), crust recovery was very slow, and after three years, a thin BSC was established. Eight years after his manipulation no perennials were recovered yet, and the biological component was purely cyanobacterial. His results, however, have limited relevancy with my study for two reasons: 1. The manipulation practice was much more aggressive, comprising total removal of the upper 10 cm of topsoil; 2. The manipulation quadrates were situated on the interdune corridor and on the slopes, where wind power is much weaker, and hence sand drift-potential (DP) is very small. The manipulation in my study involved breaking BSC in situ, leaving the reproductive bodies of the microphytes (spores etc.) on the dune surface. Moreover, as manipulation is never precise and complete, small patches of unbroken crust were left in the plots. Following the manipulation practice we could not know which process will be realized first: removal of the loosened topsoil by the wind (along with the BSC reproductive bodies) or a significant rain event, which will initiate a re-establishment of cyanobacteria on the dunes. In order to allow the wind to play its role, we decided to implement the manipulation during summer time with sufficient wind events above the threshold speed for sand movement and before the next rains come. Eventually there was no re-establishment of BSC during my study period, and the manipulation was a one-time event. Although direct comparison could not be made between Yair's study and mine, two important conclusions made by Yair (2008) are of relevance. The deposition of the mineral component does not require an earlier stage of biological filaments on the surface, and full recovery of

66 developed crust (including lichens and mosses) following grazing disturbance is estimated at 15-20 years. Although the effect on aeolian activity was long-lasting in my study, the faunal response following manipulation varied a lot between and within groups, and is elaborated below.

Beetle community Ground beetles comprise a substantial part of desert fauna, by virtue of both their sheer biomass and species diversity (Cloudsley-Thompson 1991b, Punzo 2000, Renan 2009). The two most conspicuous families of epigeic beetles in general, and desert beetles in particular, are Tenebrionidae and Carabidae (Ayal and Merkl 1994, Mahn 1994, Punzo 2000). In this study they comprised 49% and 18% of the total species count, respectively. Their share of total beetle biomass was even higher (88% and 8%, respectively) but a high seasonal and annual variation exists.

Using AICc model selection technique I explored whether treatment type affected various ecological response variables and compared the magnitude of its effect to other explanatory variables included in the full model set. I compared the relative importance of each variable in the model to decide how much the evidence in my data supports the suggested model (Anderson 2008). Treatment type was an important factor in affecting beetle abundance, but not in affecting richness or diversity indices. Furthermore, several other explanatory variables -- categorical time (pre/post-manipulation), seasonality and latitude affected abundance more than treatment. When data are rearranged as delta values, such that seasonality effect is omitted (i.e. each sample is compared to other samples of the same season only; see methods), treatment is revealed to affect similarity indices as well, mainly the Bray-Curtis index. This result signifies that when comparing beetle composition from the same season of different years, manipulated plots resemble each other more than they resemble control plots. Essentially it implies that the composition and structure of beetle communities on manipulated plots is somewhat different than their counterparts on control plots, and that this difference is maintained over time. However, the effect of perennial cover and latitude is much greater on the community richness and similarity indices, which means that local factors in the immediate surroundings of each plot are mainly responsible for beetle composition and community structure. Interestingly, sand mobility, which was predicted to

67 be of major importance for the beetle community, showed only mild effect on abundance- difference and almost no effect on other response variables. A partial explanation might be that the mechanism in which the manipulation affected beetle community was through removing perennial cover (as evident by the high score obtained by the model selection analysis) and not through changing the substrate attributes. The other response variables -- Richness and Dmg -- showed similar trends, as expected since the second is a derivative of the former. Both are highly affected by season and not at all by treatment, pre-post or lag (table 1). One striking difference is how geographic latitude affects those two variables: while it is seemingly an important predictor for richness per-se, it is a very poor predictor for Dmg, suggesting that the source of richness comes from the sheer biomass of rich samples (i.e. the more specimens are found in a sample, the more likely it is to include rare species). When correcting the richness value for the sample size (which is exactly what Dmg index does) the latitude no longer seems to affect beetle richness. Perennial cover is also an important predicting variable for richness, as it changes habitat attributes, increasing heterogeneity and corresponding ecological niches. Fisher's α, as a species diversity index, was also highly affected by season, as community structure change dramatically between seasons. Geographic latitude does not predict at all Fisher's α values, whereas it is a predictor of richness and abundance. This can be explained by the spatial scale on which communities operate. Environmental differences over a 9.5 km range (the difference between A-D latitudes) may affect ecological features such as biomass (i.e. abundance) or richness, but are less likely to affect a more fundamental entity such as community structure. This is more likely to change when the landscape features are changed; on a broader scale. Season is a very effective predictor of the Sorensen index, which is a presence-absence based index, meaning that the identity of species in a given sample is determined strongly by the season at which the sample is taken.

In summary, all five explanatory variables (except sand mobility) seem to affect some or all response variables tested above, and therefore could make good predictor variables for beetle community changes. The most effective predictors (which were present in all models with significant weights) were season for the crude data (table 1) and latitude and perennial cover for the differential data (table 2). Across seasons, on B latitude, the treatment-difference in

68 abundance was the highest. However, I could not find any local attribute to explain this finding.

The importance of season and latitude as inferred from the multi-model analysis emphasizes that the sand dune system is highly affected by both spatial and temporal variability, influencing the ecological entities of the ground beetle community. When data is analyzed in order to reveal some subtle effects – seasonal changes may mask it altogether and data analysis should be conducted with extra care. Treatment, the main goal of this study, was shown to have a strong effect on abundance, no effect on richness and community structure (as indicated by Fisher’s α), and some intermediate effect on composition (as indicated by the similarity indices). The fact that the manipulation had some meaningful effect on beetle communities was not fully supported by sand mobility scores as this variable did not come up as a good predictor in this analysis.

Reptile community Looking at the entire reptile community composition compared between treatments, as revealed by the PRC technique, two main conclusions may be drawn. First, there is a temporal dynamics in the similarity between control and manipulation plots, both before and after manipulation. Second, the highest dissimilarity between treatments in community composition was in August 2010, about two months after the actual manipulation. However, the two subsequent sessions converged back the two ‘communities’ into high similarity. This suggests that the reptile fauna on manipulated plots had suffered some kind of disturbance following dune manipulation (possibly death and emigration), but have recovered to a nearly previous status within one year. It also implies that this kind of manipulation does not have a strong impact on reptile communities in the long run, which may answer the concern some conservationists have raised regarding the harmful impact of such a manipulation on the dune’s reptile fauna (G. Wein, personal communication). Nonetheless, if we study the possible effect on specific species, we should focus on the extreme psammophiles of this community. One of these is the wedge-snouted skink which has many special adaptations to sandy habitats and is quite abundant on the dunes. As evident by the pitfall trap data, it was caught in larger numbers in the control plots. This result is somewhat unexpected, given its set of special adaptations to sand. It is possible that this species needs the semi-stabilized

69 habitat with the higher perennial cover as a refuge from predators (Renan and Bouskila – unpublished data). Another extreme psammophile of great conservation importance is the horned viper (Cerastes cerastes). According to the activity levels evaluated by its tracks, it tended to prefer the manipulated plots. Since this large viper can travel long distances each night, a more profound study of its ecology and natural history is required in order to assess its prospective response to a large-scale manipulation.

Looking at the spatial effects of the manipulation study on the reptile fauna, we see a wide spectrum of responses in nocturnal fauna activity, with no clear geographic pattern (figure 2.28). Each dune displays a different time×treatment×latitude interaction. In total, it appears that although for most dunes the manipulation was perceived as a significant habitat change by reptiles, local attributes at each dune dictates the length and magnitude of the impact of the manipulation.

Rodent community Post-manipulation data show significant higher counts of gerbils (all species combined) in control plots compared with manipulated plots. This may imply higher carrying capacity in control plots. Considering that most records are of Gerbillus andersoni (GA), which prefers the semi-stabilized dunes over shifting sand (Ziv et al. 1993a, Ziv et al. 1995, Wasserberg et al. 1996), this finding is not surprising. There is a significant south-north rise (geographic latitude gradient) in abundance for GA in control plots, which is not observed for G. pyramidum (GP) or GA in manipulated plots (figure 2.19). This means that the whole range of dunes in the study site is somewhat homogeneous for GP, but not for GA. Several studies have shown the differential habitat preference of GA and GP on sand dunes (Abramsky et al. 1990, Ziv et al. 1993a, Ziv et al. 1995, Wasserberg et al. 1996, Wasserberg et al. 2005). Consequently, the ratio of GA/GP may provide an excellent ecological indicator for detecting a habitat change as perceived by psammophilic species. Combining all post-manipulation records together, this ratio is 3.4 higher in the control relative to the manipulation, indicating a clear habitat change from the rodents’ perspective. Considering the temporal dynamics of this ratio, we see that the difference between treatments was very sharp just after manipulation (summer 2010), decreased for the next two sampling sessions, and leveled off after one year. One explanation is that as time passes, the manipulation effect fades away, presumably due to

70 re-stabilization of the dunes. Another complementary explanation is that control plots are also being destabilized through aeolian activity, due to the severe drought. The combined processes make the control-manipulation difference vanish. The ratio on the southernmost dunes was closer to that of manipulated plots on their own, owing to the state of control plots in that region, which is fairly mobile (see spatial analysis section).

While GP prefers the shifting sand habitat only as a secondary choice, G. gerbillus (GG) is considered an extreme psammophilic, highly preferring this habitat. It has pronounced adaptations for moving efficiently on shifting sand (Mendelssohn and Yom-Tov 1999). It had been totally absent from the northwestern Negev dune system for several years (Y. Ziv, unpublished data) for unknown reason and reappeared only in winter 2011. In my study, it was trapped in manipulated plots twice as much as in the control, and was found in the southern dunes (“A” latitude) three times more than other latitudes. Owing to the low numbers at hand, no statistical significance is present, but the trend is highly suggestive of manipulation as a favorable treatment for this species, as predicted by the conceptual model (figure 1.1a). This finding is encouraging from a nature conservation perspective, as GG is one of the rare and unique species that we strive to sustain in this dune system.

Significant body mass difference was found for GP, whose individuals trapped in manipulated plots were 8% heavier than those trapped in control plots. This difference existed in two seasons out of four, and could have been discarded as a random fluctuation. However, winter 2011, in which the difference in body mass was most pronounced, was also a fairly rainy season with plentiful food and a rebound of rodent populations. Higher density of GP means fierce competition between individuals over food resources, and under such conditions the population can exhibit an “ideal despotic distribution” (Fretwell and Lucas 1969, Fretwell 1972) or an ideal preemptive distribution (Pulliam and Danielson 1991). For either case, the dominant individuals take over the preferred habitat, and as density increases, subordinate individuals are pushed into the less preferred habitat. As population declines and competition is released, this pattern disappears and hence no body mass differences occur. Krasnov et al. (2001) have shown that another species of gerbil – G. dasyurus – occupying the Negev mountain ridge, showed differential body mass during winter time, according to the habitat type it was inhabiting. In their study, in the preferred habitat, gerbils were 16% heavier on

71 average than in the poorer, less preferred habitat. This body mass difference was found only during wintertime and early spring, as is the case in my study. The decrease in body mass in the semi-stabilized control plots might be the result of a reduced rate of seed renewal mechanism due to the winter typical wind regime and moist sand (Kotler et al. 2004). Another factor responsible for lower body mass in winter might be the higher cost of thermoregulation in the cold winter nights (Krasnov et al. 2001, Kotler et al. 2004).

GUD experiments GUD has proven to be an excellent tool for testing optimal foraging behavior of rodents in general, and following some environmental change (e.g. habitat manipulation) in particular. This technique has been used in many studies worldwide and especially in the sandy habitats of Israel for several decades. GUD is known to be density-dependent under certain conditions (Rosenzweig 1981, China et al. 2008). As population density increases, the quality of the habitat decreases due to resource competition and interference. This phenomenon might be responsible for the lower GUDs of the July 2011 session compared with the two other sessions, following its respective higher gerbil counts (see rodent community results). The lower GUDs in manipulated plots compared with those of control plots in October 2010 are well in line with the results of China et al. (2008). They showed experimentally that at low densities, a stabilized sand habitat (i.e. control plots in my research) gives rise to high GUD values, whereas semi-stabilized dune habitat GUDs are constantly low (density-independent). They showed this for the same gerbil species explored in this study. They explain their results as a case of ‘safety in numbers’ – i.e. increases in prey density for a fixed number of predators spreads the burden of predation among more individuals. So prey aggregation should reduce risk (Rosenzweig et al. 1997). Results from June 2012, though not significant, showed the same trend at low gerbil densities. Another possible explanation posited by China et al. (2008) for the treatment effect on GUD refers to ideal despotic distribution (Fretwell and Lucas 1969, Fretwell 1972) or ideal preemptive distribution (Pulliam and Danielson 1991). For either case, the dominant individuals monopolize the preferred habitat, and as density increases, subordinate individuals are pushed into the less preferred habitat. Although this hypothesis was not supported by their data, it might have stronger evidence from this study. During rodent sampling of summer 2010 and winter 2011, GP's body mass was significantly higher for individuals trapped in manipulated plots. Although this difference was found only

72 for GP and not for GA, it suggests that such behavior is possible among the gerbil community, and given the right circumstances, it might be displayed by GA as well.

Regarding the bush / open microhabitat use (figure 2.25), the results suggest that for GP the open habitat is safer on the control plots (giving rise to lower GUDs), whereas the bush habitat is safer on manipulated plots. The main predators in this dune system are foxes, owls and snakes. Foraging under bushes or in their vicinity helps avoiding foxes and owls, which rely on their vision to detect gerbils and have a successful hunt. On the other hand, allocating more time in the open habitat is considered a snake avoidance tactic. In summertime both groups of predators are active and hence GUDs are predicted to be similar on both micro- habitats (Mukherjee et al. in press). However, as mentioned above, this is not the case at my study site. One possible reason is that vegetation cover on manipulated plots is significantly lower than on control plots. This increases the risk of fox and owl predation in the open and makes the sparse vegetation less prone to snakes on the manipulated plots. The opposite is true for the control. In general, the GUD results suggest that the treatment-microhabitat interaction is a manifestation of predation risk trade-off between two groups of predators that have a distinct efficiency at different vegetation-cover levels. This hypothesis however has no empirical basis thus far and should be explored in future studies.

Detecting behavioral changes, such as foraging efficiency of gerbils, may also be applied to forecasting of population dynamics in the near future (Morris et al. 2009), and become an important conservation tool for managers. By using GUD results as a behavioral indicator for the purpose of estimating future demographic changes, I attempted to show the viability of such a tool.

Spatial analysis of shifting sand cover and its potential impact The natural shifting sand cover in this system (excluding the manipulated quadrates) is not distributed evenly across the landscape. It has a south-north gradient on a larger scale (Nizzana to Gaza) following the precipitation gradient such that in the southern, more arid dunes, the BSC establishment is less effective and hence more dune area exhibits shifting sand cover. On a local scale however, (i.e. at my study area) the validity of this gradient had to be tested. The manipulated quadrates on the different dune crests (four times the size of the plots themselves) may act as ecological islands, separated from other similar habitats, if they

73 are surrounded mostly by stabilized dunes. On the other hand, large patches of shifting sand around them create continuous corridor of shifting sand. Which of these two scenarios take place affects dispersal abilities of the dune psammophilic fauna and other population dynamics. As shown in figure 2.30, the manipulated plots of dunes 3, 4, 7 and 8 are above the 25-m threshold, which may imply a dispersal limitation for beetle communities. Plot 4m is also above the 75-m threshold, which indicates dispersal limitations for most reptiles, and even some rodents. Although no correlation was found between distance-to nearest-patch of mobile sand and reptile activity level, there is one piece of evidence to support the dispersal limitation hypothesis. Comparing activity levels in manipulated plots just after manipulation (August 2010), to their control counterparts, we see that dune 4, which is exceptionally far from the nearest mobile patch (107 m), is also exceptional in its decreased activity level (-38, compared with a range of +30 to [-16] for all other dunes). This finding means that the arbitrary threshold of 75 m may not be of ecological importance, and that a ‘100 m distance’ is a more appropriate dispersal limit threshold. Another important conclusion is that in the same latitude plots may have very different dispersal limitations, as is the case for '1m' and '2m' (nearest patch for each is different in an order of magnitude) and also for '7m' and '8m'. I could not find any meaningful correlation between either ‘distance to nearest mobile patch’ or ‘area of nearest mobile patch’ to any faunal community measure (i.e. abundance, richness or composition).

Conclusions In the course of this study a challenging ecological restoration project was carried on. An attempt was made to augment the proportion of shifting sand crests or patches on the crests, such that extreme psammophilic species can sustain their populations, and an overall increase in biodiversity is reached. In order to assess whether these goals were achieved, I will address my research questions one by one:

1. Does the breakup of BSC enhance aeolian activity? Yes, it definitely does. 2. Do rodents, reptiles and beetles perceive the manipulation treatment as a habitat change? Yes, but each group perceives the manipulation to a different extent and is affected by it in a different way.

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3. Which ecological aspects are affected by the manipulation (abundance, richness, diversity, community structure or composition) for each community? For beetles – abundance, community structure and composition; for reptiles – abundance of specific species and therefore also community structure; for rodents – abundance and community structure. 4. Is there any spatial effect (mainly geographic gradient, but not only) on the response of faunal communities to the manipulation? In the course of this study, no geographic gradient was found, possibly due to the drought effect. However, I have shown that the southern part of the ASNR has a much higher aeolian activity. I have also shown that the distance between mobile crests or patches may constitute a barrier for dispersal and thus limit recolonization rates following disturbance. 5. What is the temporal dynamics of the different responses observed? Are they short-lived or long-lasting, and is there a fundamental difference between communities? Most effects were short-lived and within a year the response variable was back to its pre-manipulation level, or it had leveled-off at a new, slightly different state. However, temporal dynamics showed a high interaction with latitude, especially for beetles. 6. Apart from treatment, which environmental variables are the key factors affecting the three faunal communities, and especially the beetle community? Season, latitude and perennial cover are the three most important environmental factors on the dunes. This means that the sand dune system is both spatially and temporally variable which affects all the faunal communities. 7. Is rodent foraging behavior affected by the treatment? If so - can we use such a change to predict future demographic changes? Yes – as evident from the GUD results, foraging efficiency and quitting harvest rate were altered for GA but not for GP. This effect was significant in 2010, not significant in 2012 and absent altogether in 2011. As discussed earlier, I could not establish foraging behavior change as an indicator of demographic change due to lack of sufficient data. However, the trends do show that it has potential as a conservation tool for managers.

Ecological restoration is an attempt to restore some reference state of the ecosystem through processes that divert the current trajectory of the system to a more desired one. A successful restoration is one that does not need a constant intervention of the managers, but allow the

75 natural processes to shape the system through complex interactions. In the northwestern Negev dune system the undesired trajectory is the ongoing dune stabilization process. The intervention employed on these dunes in my research was breaking up the BSC in situ, with a partial removal of vegetation cover. This action have increased aeolian sand activity on the dunes and reversed the geomorphologic trajectory to the desired direction. However, in order to decide if the ecological aspect of the dune system has also shifted to a more desired state or direction (since we should not expect the system to resume its exact historical state), a long- run monitoring program is required. This program should focus on the populations of the psammophilic species that presumably suffered the most from the dune stabilization. My current findings of the faunal response to the manipulation suggest that some ecological attributes do change following the higher aeolian activity. Nonetheless, as any other ecological restoration project, a long-term monitoring is required in order to evaluate its success, along with an adaptive management.

Management recommendations This research was highly applicative by its nature. One of its declared goals was to come up with long-term management recommendations for the INPA staff, who manage the ASNR and other reserves within the northwestern-Negev dune system. Assuming that we share the same conservation goals, I would recommend the following management practice: 1. Provided that the stabilization process persists on the dunes, I would recommend upscaling the manipulation practice to include several adjacent whole dunes (but still breaking BSC on the crest only). This way a larger continuous habitat of shifting sand is created with all the known benefits associated to it, such as decreased edge effect, easier dispersal and so forth. This upscale should be regarded as a preliminary case study, as the long-run ecological outcomes of this kind of manipulation are not clear-cut, and extensive and expensive restoration project all over the ASNR is not advisable at this stage. 2. Continuing to monitor faunal response, with emphasis on focusing on unique and rare psammophilic species. This will give the managers a better picture on the cost-to-benefit ratio of the entire project. The ultimate goal of the management is usually the conservation and restoration of these species. 3. Implementing the manipulation practice at the mid- to north-range of the current study. At the southern range, dunes seem to have increased aeolian activity without mechanical

76 intervention because of the recent long-term drought (Seigal et al., 2013). 4. Monitoring the effect of manipulation on annual vegetation which is a key player in dune system due to the production of a large biomass of seeds for granivores and of dry (dead) material for the detrivores, such as tenebrionids.

Generally, I believe that breaking the BSC on dune crests, accompanied by partial removal of vegetation, does have a positive effect on faunal communities as a whole and on psammophilic species in particular. However, if the prolonged drought continues (which by now should be termed a climate shift towards hyper-aridity), destabilization of the dunes might occur on its own, and costly restoration acts may become redundant.

Concluding statement Ecological restoration of dune systems is feasible. However, this kind of practice is never a one-time event. As environmental conditions change through time and unexpected outcomes of manipulation arise, an adaptive management approach is strongly advised. The bi-stability paradigm (Tsoar 2005, Yizhaq et al. 2007, 2009) states that without a significant climate change, and without biotic or mechanical breakup of the BSC, dune stabilization is irreversible in the north-western Negev dunes. However, it is very probable that we are in the beginning of such a climate change due to the long-term drought. In such a case, ecological restoration is either redundant or its central goals should be reconsidered. A manipulation such as I conducted may serve as a good trigger that starts activity of the dune sand, but economic considerations may render it a redundant project if dune destabilization occurs on its own.

Future suggested studies This study has advanced our understanding of the north-western Negev dune system in general, and of dune stabilization process and its effect in particular. However, in many ways it was only a preliminary study – unraveling the key elements and interactions participating in this unique system. In order to enrich the basic ecological knowledge, and improve our ability to sustain species diversity, I suggest to further conduct some ecological studies in the same system. These studies may include: looking at how a changing habitat (temporal or spatial) affects faunal interactions (predator-prey, spp. co-existence, generalist-specialist replacement); looking at the rate of crust formation under different artificial rain regime

77 experiments (total amount, distribution and timing); focusing on unique and endangered species (Savingy’s agama, Horned viper); conducting an applicative experiment: trying different methods of breaking up the BSC and measuring the rate of BSC reestablishment and annual plant germination. Another path that should be explored is turning the current conceptual model of dune stabilization into a quantitative model. Such a model would enable making predictions as to different scenarios.

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Appendix 1 Manipulation effect on a dune crest: A. on the left of the ATV the vegetation is removed and BSC is broken and crumpled. On the right the dune surface is still intact. Photo was taken on 17/6/2010.

A.

B. Dune 4 demonstrate the different sand mobility levels between its control plot (left) and its manipulated plot (right). Photos were taken on December 2010.

B.

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Appendix 2 Summarizing tables for all 3 groups monitored in this study: A. beetles, B. reptiles, and C. rodents.

A. Beetle data. Not all species' names are valid scientific names. Some which were not identified to the species (and sometimes to genus) level, were given a code name. Latitudes are denoted as A-D according to the coding in the main text. Treatment code is M=manipulation, C=control.

Latitude and treatment A B C D Total Family Genus_species C M C M C M C M abundance Anobiidae Ptinus_sp. 0 1 0 0 0 0 0 0 1 Buprestidae Acmaeoderella_chrysanthemi 0 0 1 1 0 0 0 0 2 Acmaeoderella_despecta 0 0 0 0 1 4 10 12 27 Acmaeoderella_maculipennis 1 0 0 0 11 4 9 6 31 Acmaeoderella_sp. 1 0 5 3 2 7 1 0 19 Carabidae Amara_arabica 1 2 0 0 1 0 0 0 4 Amara_cottyi 0 1 0 0 3 1 0 1 6 Amara_sp. 1 0 0 0 0 0 0 0 1 Anthia_sexmaculata 4 3 13 42 7 2 1 2 74 Cymindis_suturalis 0 4 4 3 9 4 3 0 27 Discoptera_arabica 3 11 0 0 0 0 0 0 14 Graphipterus_serrator 9 14 19 9 8 15 68 24 166 Graphipterus_small 0 0 0 0 1 1 3 0 5 Heteracantha_depressa 0 0 0 0 0 1 0 0 1 Negevomasoreus_groneri 11 21 16 14 44 46 36 27 215 Platyderus_languidus 0 1 1 0 1 0 0 1 4 Scarites_striatus 0 2 0 0 0 0 0 0 2 Coccinelidae Lithophilus_ovipennis 0 0 0 1 0 0 0 1 2 Lithophilus_sp. 0 1 0 0 1 0 0 0 2 Cryiptophagidae Atomaria_gibbula 1 0 0 0 0 0 0 0 1 Curculionidae Borborocoetes_sp. 2 4 13 4 27 25 3 3 81 Brachycerus_spinicollis 3 6 20 19 0 1 1 1 51 Curculionidae sp. 0 0 0 0 0 1 0 0 1 Curculionidae sp.1 1 5 0 1 1 0 1 1 10 Curculionidae sp.2 1 0 3 0 0 0 0 0 4 Curculionidae sp.3 0 0 0 1 0 0 0 0 1 Curculionidae sp.4 0 0 0 1 0 0 0 0 1 Curculionidae sp.5 0 0 0 1 0 0 0 0 1 Dermestidae Attagenus_lobatus 0 0 0 0 1 0 1 0 2 Elateridae Cardiophorus_negevensis 1 4 2 6 2 2 2 6 25 Isidus_letourneuxi 4 0 2 0 1 1 1 3 12 Histeridae Histeridae sp. 0 1 0 0 0 0 0 0 1 Scarabaeidae Pleurophorus_sp. 0 2 0 0 0 0 0 0 2 Subrinus_sp. 0 1 0 1 0 0 0 0 2

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Tenebrionidae Adelostoma_sp. 0 1 0 0 1 2 1 2 7 Adelostoma_sulcatum 3 1 0 3 2 2 4 3 18 Adesmia_bicarinata 0 0 0 0 0 0 0 1 1 Adesmia_metalica 11 19 16 45 39 48 26 31 235 Arthrodeis_rotundatus 2 1 5 0 6 3 6 8 31 Blaps_bifurcata 2 5 1 1 0 1 0 0 10 Blaps_nitens 219 252 884 468 517 350 430 408 3528 Blaps_sp. 6 11 10 27 59 33 11 16 173 Catomus_acutipennis 8 7 11 6 1 5 0 0 38 Erodius_hebraicus 1 3 0 1 0 0 0 0 5 Erodius_puncticollis 2 0 0 0 3 6 0 0 11 Erodius_sp. 68 93 11 29 87 51 53 72 464 Erodius_sp.1 0 1 0 0 0 0 0 0 1 Erodius_sp.2 0 1 0 0 0 0 0 0 1 Eurycaulus_henoni 16 20 15 30 26 51 22 16 196 Eutagenia_cribricollis 3 0 1 0 6 1 1 6 18 Gonocephalum_sp. 0 0 0 0 0 0 0 1 1 Machlopsis_crenatocostata 3 8 5 1 12 13 12 7 61 Mesostena_angustata 9 8 14 6 10 7 6 2 62 Omophlus_ocularis 0 0 0 1 0 1 0 0 2 Pimelia_angulata 0 0 0 0 0 1 0 0 1 Pimelia_sp. 1 0 0 1 0 2 0 0 4 Pimelia_theveneti 3 4 10 5 5 1 4 2 34 Prionotheca_coronata 4 5 3 0 12 1 2 2 29 Pseudoseriscius_maculosus 0 0 1 0 10 4 2 3 20 Pterolasia_squalida 12 9 7 8 7 14 10 16 83 Scaurus_puncticollis 1 3 5 3 1 1 0 2 16 Stenosis_comata 4 3 0 0 17 19 0 0 43 Tenebrionidae_sp. 0 0 0 0 0 0 1 1 2 Tentyrina_orbiculata 6 7 7 4 13 8 7 10 62 Zophosis_bicarinata 22 27 5 24 13 12 8 7 118 Zophosis_pharaonis 1 3 1 3 0 0 0 0 8 Zophosis_punctata 0 0 0 0 0 0 0 1 1 Zophosis_sp. 27 67 27 21 15 17 13 11 198 Total 478 643 1138 794 983 769 761 716 6282

B. Reptile combined data. Values represent highest score for each monitoring method as described in the Methods chapter, normalized for sampling effort and standardized for 0-5 scale. Shades of green fill correspond to scores (darker is higher) for easier visualization.

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זיקית נחושית חומט חרדון נחש כיפה מטבעון שנונית עכן עכן קטן נחש שנונית נחושית ישימונית ישימונית עינונית רפואי חולות מדבר מצרית חרטומים חולות חולות חולות רביבים מצויה & Species' name: Hebrew scientific Stenodac Stenodac Sphenops Acacthod Lytorhyn Cerastes Cerastes Acactho Spaleros Macroprot Trapelus Scincus Chalcides Chamaeleo Plot Treat- tylus tylus sepsoides actylus chus vipera cerastes dactylus ophis odon savingii scincus ocellatus chamaeleon Pre/ Post Season Year no. ment sthenoda petrii scutellatus diadema diadema cucullatus pre Sep. 2009 1 c ctylus 2 2 3 0 0 0 0 longipes0 0 0 0 0 0 0 pre Apr. 2010 1 c 4 4 4 4 3 1 0 0 1 0 0 0 0 0 post Aug. 2010 1 c 4 0 5 4 1 0 0 4 0 0 2 0 0 0 post May 2011 1 c 0 2 1 3 1 0 0 4 0 0 0 0 0 0 post Aug. 2011 1 c 0 0 3 3 2 2 0 4 0 0 0 0 2 0 post May 2012 1 c 2 3 1 0 2 0 0 2 0 0 0 0 0 2 pre Sep. 2009 1 m 0 0 4 0 0 0 1 0 0 0 0 0 0 0 pre Apr. 2010 1 m 0 0 3 2 0 0 0 3 1 2 0 2 0 0 post Aug. 2010 1 m 2 2 4 3 3 2 2 3 0 0 2 1 0 0 post May 2011 1 m 3 2 3 3 0 0 0 4 0 0 0 0 0 0 post Aug. 2011 1 m 0 0 3 2 0 2 2 4 2 0 0 0 0 0 post May 2012 1 m 1 2 2 3 1 2 0 2 0 0 0 0 0 0 pre Sep. 2009 2 c 0 0 0 0 0 0 0 0 1 0 0 0 0 0 pre Apr. 2010 2 c 2 0 4 0 2 0 0 2 1 1 0 1 0 0 post Aug. 2010 2 c 4 2 5 4 2 1 1 0 1 0 2 0 0 0 post May 2011 2 c 2 2 3 3 3 0 2 0 0 0 0 0 0 0 post Aug. 2011 2 c 0 2 3 2 1 0 0 2 0 0 0 0 0 0 post May 2012 2 c 2 1 3 0 1 2 0 0 0 0 0 0 0 0 pre Sep. 2009 2 m 0 0 0 0 0 0 0 0 0 0 0 0 0 0 pre Apr. 2010 2 m 0 2 4 2 2 2 0 0 0 2 0 0 0 0 post Aug. 2010 2 m 2 1 4 3 2 0 1 0 2 1 0 0 3 0 post May 2011 2 m 3 2 0 3 0 0 0 2 0 0 0 0 0 0 post Aug. 2011 2 m 0 2 3 3 0 0 2 3 0 0 0 0 0 0 post May 2012 2 m 0 1 3 0 0 2 0 2 0 0 0 0 0 0 pre Sep. 2009 3 c 2 0 2 0 0 0 0 0 0 0 0 0 0 0 pre Apr. 2010 3 c 0 0 5 0 2 0 0 0 2 2 0 0 0 0 post Aug. 2010 3 c 2 0 5 4 1 1 1 0 0 0 2 1 2 0 post May 2011 3 c 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post Aug. 2011 3 c 0 2 4 4 0 0 0 0 2 1 0 0 0 0 post May 2012 3 c 2 1 1 0 2 0 0 0 0 0 0 0 0 0 pre Sep. 2009 3 m 2 0 2 4 0 0 0 0 0 0 0 0 0 0 pre Apr. 2010 3 m 2 1 4 4 0 3 0 0 0 0 2 0 0 0 post Aug. 2010 3 m 2 0 4 4 3 0 3 0 2 3 2 0 1 0 post May 2011 3 m 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post Aug. 2011 3 m 0 2 3 3 2 0 0 0 0 0 0 0 0 0 post May 2012 3 m 0 0 3 0 1 2 2 3 0 0 0 0 0 0 pre Sep. 2009 4 c 0 0 2 0 0 0 0 0 0 0 0 0 0 0 pre Apr. 2010 4 c 4 2 4 2 1 3 2 0 0 3 0 0 0 0 post Aug. 2010 4 c 0 2 4 5 3 0 0 2 0 0 0 0 0 0 post May 2011 4 c 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post Aug. 2011 4 c 2 0 3 2 1 0 0 0 0 0 0 0 0 0 post May 2012 4 c 2 1 3 0 2 0 0 0 0 0 0 0 0 0 pre Sep. 2009 4 m 0 0 3 2 0 1 0 0 0 0 0 0 0 0 pre Apr. 2010 4 m 0 0 4 4 0 3 2 0 0 0 0 1 0 0 post Aug. 2010 4 m 0 3 6 3 1 1 0 0 1 1 0 2 2 0 post May 2011 4 m 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post Aug. 2011 4 m 0 2 5 3 0 3 2 0 0 0 0 0 0 0 post May 2012 4 m 0 0 4 2 4 2 0 0 1 0 0 0 0 0 pre Sep. 2009 5 c 0 0 3 0 0 0 0 0 0 0 0 0 0 0 pre Apr. 2010 5 c 2 3 5 3 0 3 0 0 0 0 0 0 0 0 post Aug. 2010 5 c 4 2 5 5 0 0 3 0 2 0 2 0 0 0 post May 2011 5 c 3 0 3 3 0 0 0 0 0 0 0 0 0 0 post Aug. 2011 5 c 0 0 3 2 0 0 0 0 0 0 0 0 0 0 post May 2012 5 c 0 0 3 0 3 0 1 0 0 0 2 0 0 0 pre Sep. 2009 5 m 0 0 3 0 0 0 0 0 0 0 0 0 0 0 pre Apr. 2010 5 m 2 2 4 2 2 2 0 0 3 0 0 0 0 0 post Aug. 2010 5 m 0 1 4 3 1 0 0 2 0 0 0 1 1 0 post May 2011 5 m 0 3 2 2 1 1 0 0 0 0 0 0 0 0 post Aug. 2011 5 m 2 2 3 0 2 0 2 0 0 0 0 0 0 0 post May 2012 5 m 0 0 3 0 2 0 0 0 0 0 2 0 0 0 pre Sep. 2009 6 c 0 0 2 0 0 1 0 0 1 1 0 0 0 0 pre Apr. 2010 6 c 2 2 3 2 3 2 0 0 0 1 0 0 0 0 post Aug. 2010 6 c 2 2 4 5 0 3 0 2 0 0 0 0 1 0 post May 2011 6 c 2 3 3 4 1 0 1 0 0 0 0 0 0 0 post Aug. 2011 6 c 0 2 3 0 0 0 0 0 0 0 0 0 0 0 post May 2012 6 c 2 2 2 0 0 0 0 0 0 0 0 0 0 0 pre Sep. 2009 6 m 0 0 2 0 0 0 0 0 0 0 0 0 0 0 pre Apr. 2010 6 m 2 1 2 0 0 2 0 0 0 0 0 1 1 0 post Aug. 2010 6 m 0 1 3 5 1 0 0 0 0 0 0 0 0 0 post May 2011 6 m 0 2 0 3 3 0 0 0 0 0 0 0 0 0 post Aug. 2011 6 m 0 0 2 0 0 0 1 0 0 0 0 0 0 0 post May 2012 6 m 1 2 0 0 0 1 0 0 0 0 0 0 0 0 pre Sep. 2009 7 c 2 2 3 0 0 0 0 0 1 0 0 0 0 0 pre Apr. 2010 7 c 4 3 3 3 3 3 0 0 0 0 0 0 0 0 post Aug. 2010 7 c 2 2 5 3 2 0 0 3 0 0 2 0 0 0 post May 2011 7 c 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post Aug. 2011 7 c 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post May 2012 7 c 2 2 3 2 1 0 1 0 0 0 2 0 0 0

92 pre Sep. 2009 7 m 0 0 4 0 0 0 0 0 0 0 0 1 0 0 pre Apr. 2010 7 m 2 2 4 0 3 0 0 0 0 1 0 0 0 0 post Aug. 2010 7 m 0 1 5 0 2 0 1 0 1 0 0 1 0 0 post May 2011 7 m 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post Aug. 2011 7 m 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post May 2012 7 m 2 1 3 0 2 0 1 0 0 0 0 0 0 0 pre Sep. 2009 8 c 0 0 3 0 1 0 0 0 0 0 0 0 0 0 pre Apr. 2010 8 c 2 0 0 0 0 0 0 2 1 0 2 0 0 0 post Aug. 2010 8 c 3 2 3 5 0 0 0 0 1 3 0 1 1 0 post May 2011 8 c 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post Aug. 2011 8 c 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post May 2012 8 c 0 0 3 0 1 0 0 0 0 0 0 0 0 0 pre Sep. 2009 8 m 2 0 2 2 0 0 0 0 0 0 0 1 0 0 pre Apr. 2010 8 m 2 2 0 0 0 0 0 0 0 0 0 0 0 0 post Aug. 2010 8 m 2 2 5 4 1 0 0 2 0 0 0 0 2 0 post May 2011 8 m 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post Aug. 2011 8 m 0 0 0 0 0 0 0 0 0 0 0 0 0 0 post May 2012 8 m 0 0 1 3 0 0 0 0 0 0 0 0 0 0 Average 1.06 1.01 2.64 1.60 0.88 0.55 0.35 0.59 0.28 0.23 0.25 0.15 0.17 0.02 Presence>1 44 50 77 49 45 27 21 21 19 13 12 12 10 1

C. Rodent new-captures data. Sex coding is F=female, M=male and '?'= unidentified, usually due to an escape before examination.

Species Gerbillus Gerbillus Gerbillus Gerbillus Meriones & sex andersoni gerbillus henelyi pyramidum sacramenti Total Year Season F M ? F M F M F M ? F M ? 2009 summer 6 10 1 17 2010 summer 30 13 1 2 6 52 winter 1 2 1 4 2011 summer 12 37 2 3 5 15 15 1 1 91 winter 28 35 1 4 9 3 3 19 21 1 1 125 2012 summer 12 8 1 4 1 7 8 1 42 Total 89 105 5 11 15 3 3 44 50 3 1 1 1 331

Appendix 3 Monitoring techniques:

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Monitoring dune surface toughness using penetrometer

Measuring erossion pin hight above surface

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Identifying beetle species collected in dry pitfalls (in this picture – most specimens are Blaps nitens)

Open pitfall for beetles near a bush-microhabitat

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Measuring body length of a nocturnal gecko caught in a pitfall

Common sand viper caught in a pitfall

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Identifying reptile activity levels on a track trail created with a toed tier.

Snake tracks crossing the track trail

97

Releasing a gerbil from a Sherman trap

Weighing a trapped gerbil

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Marking a gerbil for capture-recapture calculations.

Appendix 4 Evidence of Aeolian activity on dune crests

Aeolian activity expressed on the dune as ripples. December 2010. Plot 1C

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Buckets of reptile pitfalls exposed as the sand eroded around them. When initially buried, their lids were at the same level as the surrounding sand.

Beetle pitfall exposed by sand erosion.

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Another bucket exposed.

Two small nebkha's created by aeolian sand activity, covering bushes that block the wind

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תקציר בעידן המודרני אנו עדים לגידול אוכלוסין עולמי בקצב חסר תקדים המלווה בהתפתחות כלכלית גלובלית. דבר זה גורם ללחץ עצום על המערכות הטבעיות בעולמנו. הבט אחד משמעותי של לחץ זה, הוא משבר מגוון המינים. הקצב בו נכחדים מינים במהלך המאה ה12- גבוה עשרות מונים מהקצב הטבעי של ההכחדה בתקופה בה השפעת האדם היתה זניחה. לאור משבר סביבתי זה, הגישה השמרנית של שמירת הטבע אינה מספקת עוד. בעבר, הקצאת שטחים לשמורות טבע היה הפן העיקרי בו נקטו האמונים על שמירת הטבע, אולם כיום נדרשת פעולה וגישה אקטיביות יותר. גישה פרו-אקטיבית שכזו הינה שיקום אקולוגי, לפיה יש להתערב )לנקוט פעולה( במערכות אקולוגיות שמצבן התדרדר, באופן מבוקר ומוגדר היטב. התערבות זו נועדה לשקם תהליכי מפתח, תפקודים או מינים שמצבם חמור. הפעולה שיש לנקוט יכולה להתבטא בעצירת / הסרת הגורם המפריע שהכניס האדם למערכת, או כל תהליך מזיק אחר, כמו גם החזרת פעילות-אדם מסורתית שנפסקה לאחרונה, כגון רעיית צאן ובקר. כאשר החזרת פעילות-אדם אינה אפשרית מכל סיבה שהיא, ניתן להפעיל אמצעים מכניים שיחקו את הפעילות המסורתית שאבדה. כזה הוא המקרה בשמורת חולות עגור – חלק מרכזי במערכת החולית של צפון-מערב הנגב.

מערכת זו חווה תהליך מתמשך של התייצבות הדיונות במהלך שלושת העשורים האחרונים. לאחר שרעיית צאן בידי בדויים נפסקה, הדיונות מתייצבות באופן הדרגתי: פעילות חול איאולית מופחתת, כיסוי הצומח עולה, וקרומי קרקע ביולוגיים )קק"ב( מתהווים על-פני הדיונות. תהליך זה מלווה ככל הנראה בשינויים מסויימים של פאונת הדיונה. בעיקר נצפה לראות ירידה בצפיפות אוכלוסיותיהם של מינים פסמופיליים )חובבי חול( ועלייה מקבילה של מינים יותר ג'נרליסטיים. מבחינת שמירת- טבע, החשש הגדול ביותר הוא לגורלם של מינים נדירים וייחודיים למערכת זו, שאין למוצאם במקומות אחרים בישראל – כגון עכן החרטומים וצב-יבשה מדברי.

במטרה 'להחזיר את הגלגל לאחור' ולשפעל את הדיונות המיוצבות יחד עם הפאונה הייחודית להן, נקטתי בפעולה של שיקום אקולוגי על-פני 8 דיונות המצויות בשמורת חולות עגור. בכל אחת מהדיונות הללו ביצעתי מניפולציה שמהותה שבירת קרומי הקרקע לאורך רכס הדיונה, והסרה חלקית של כיסוי הצומח בהן. שבירת הקרומים נעשתה באמצעות משדדה יעודית שנגררה בידי טרקטורון. בכל דיונה רצועה של 122 מ' × 02 מ' עברה שידוד לאורך רכס הדיונה. שתי חלקות מחקר הוגדרו בכל דיונה: חלקת מניפולציה בתוך הרצועה המעובדת, וכמאה מ' ממנה, חלקה נוספת ששימשה כביקורת מזווגת. המניפולציה נערכה במהלך יוני 1222. כשנה לפניה ושנתיים לאחריה נאספו תצפיות באתר המחקר. נאספו נתונים הן של גורמים פיזיקליים והן של הפאונה על-פני הדיונה. המשתנים האביוטיים שנאספו כללו את תנועת החול )נמדדה בעזרת פיני ארוזיה( ואת כיסוי הקרומים )הערכה ויזואלית ובאמצעות פנטרומטר(. תגובת החברה הפאוניסטית למניפולציה הוערכה באמצעות ניטור שלוש חברות בע"ח: מכרסמים, זוחלים וחיפושיות קרקע. נמדד גם כיסוי הצומח הרב-שנתי בכל חלקה ששימש כמשתנה סביבתי מסביר.

איסוף הנתונים עבור הקבוצות השונות נעשה בעזרת מלכודות שרמן לאוכלוסייית המכרסמים, מלכודות נפילה יבשות עבור החיפושיות, ושילוב של מלכודות נפילה, חתכי פעילות ושביל טשטוש

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עבור הזוחלים. בנוסף, נערכו נסויי giving-up densities) GUD)במטרה לנטר שינויים בהתנהגות השיחור של הגרבילים על-פני הדיונה. ניסויים אלו בוצעו בשיטה המוכרת ומוכחת של אספקת תערובת של חול וגרעיני דוחן במגשים המדמים כתמי מזון בדיונה.

התוצאות העיקריות של מחקר זה נחלקות לפן הגיאומורפולוגי של הדיונה ולפן הפאוניסטי של תגובת שלוש קבוצות בעה"ח שנחקרו למניפולציה. ראשית כל, מצאתי כי פעילות החול האיאולית היתה גבוהה באופן משמעותי בחלקות המניפולציה ביחס לחלקות הביקורת לאורך כל תקופת המחקר )לאחר ביצוע המניפולציה(. עם זאת, ההפרש בין הטיפול לביקורת הלך ודעך לאורך הזמן וכמעט שנעלם לאחר 21 חודשים. באופן כללי, הפעילות האיאולית היתה גבוהה יותר במהלך החורף ונמוכה יותר בשאר העונות. שני המדדים האחרים לרמת המיוצבות של הדיונה: כיסוי קק"ב ומידת חדירות פני הקרקע, הושפעו אף הם מהמניפולציה. כאשר אחוז כיסוי הקק"ב ירד בחלקות המניפולציה בעקבות שבירתם על-ידי המשדדה, חדירות פני-הקרקע עלתה בהתאמה באותן החלקות. בחלקות המניפולציה נמדד גם כיסוי נמוך יותר של צומח מעוצה בעקבות עבודת המשדדה, אם כי לא בוצעו מדידות של טרום-מניפולציה לביסוס טענה זו. קבוצת חיפושיות הקרקע נשלטה בידי משפחות השחרוריתיים והרצניתיים לאורך כל תקופת המחקר. שפע החיפושיות הכולל השתנה מאוד בין עונות ובין שנים. בממוצע, היתה ירידה בשפע בחלקות מניפולציה בהשוואה לביקורת. הרכב המינים בחברה היה מעט שונה בין הביקורת למניפולציה, והבדל זה גבר ככל שחלף הזמן עבור חברת הסתיו אך לא עבור חברת האביב. שני מיני מחוון של חיפושיות שינו באופן מובהק את שכיחותם היחסית בחלקות בעקבות המניפולציה: Blaps nitens עם העדפה לחלקות הביקורת )מין ג'נרליסטי( ו- .Erodius spp )סוג פסמופילי( עם העדפה לחלקות שעברו מניפולציה. חברת הזוחלים הראתה את ההבדל הגדול ביותר בין הטיפול לביקורת )אנליזת PRC( מיד לאחר המניפולציה, אולם בשתי עונות המדידה הבאות החברות התכנסו למצב דומה, המרמז על השפעה דועכת של המניפולציה. היתה שונות גבוהה בין מיני הזוחלים ביחס לתגובתם למניפולציה. המכרסמים הראו שתי תגובות עיקריות: 2. היחס של GA/GP )שני מיני הגרבילים הנפוצים בדיונה( היה פי 4.3 גבוה יותר בחלקות הביקורת. משמעות נתון זה היא ששני המינים חוו את המניפולציה כשינוי בית הגידול עבורם; 1. כאשר גרביל דרומי (Gerbillus gerbillus), הידוע כחובב חול נייד, הופיע במערכת לאחר העדרות ממושכת, הוא הראה העדפה ברורה לחלקות המניפולציה. הממצאים העיקריים של ניסויי ה-GUD היו של-GA היו ערכי GUD נמוכים יותר בחלקות המניפולציה בשתיים מתוך שלוש עונות. בנוסף, נמצא כי GP העדיף בית גידול פתוח על-פני בית-גידול שיחי, אך רק בחלקות הביקורת )בהן הכיסוי הצמחי רב יותר(. הניתוח המרחבי העלה שלמרות שסביב החלקות הדרומיות ביותר )חלקות 2,1( אחוז הכיסוי של חול נודד היה הגבוה ביותר )כפי שניתן לצפות בעקבות הגרדיאנט המרחבי בסקלה גדולה יותר(, הרי שבשאר אתר המחקר לא נצפה גרדיאנט דרום-צפון של כיסוי חול נודד. כמו-כן הניתוח הראה שהמרחק מכל חלקה לכתם )בעל גודל משמעותי( של חול נודד הקרוב אליה ביותר הוא שונה ביותר מדיונה לדיונה, אפילו בקרב דיונות החולקות אותו קו-רוחב גיאוגרפי.

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לסיכום התוצאות ניתן להבחין בשני היבטים שונים של השפעת המניפולציה על הדיונה: 2. פעילות חול איאולית היתה גבוהה משמעותית בחלקות המניפולציה. שבירת הקק"ב על-פני הדיונה תוך הסרה חלקית של הצומח המעוצה עוררו את פעילות החול האיאולית; 1. השינויים בחברה הפאוניסטית כפי שבאו לידי ביטוי בשלוש קבוצות נפוצות ובעלות חשיבות אקולוגית על פני-הדיונות )מכרסמים, זוחלים וחיפושיות( היו חלקיים ומורכבים. כל שלוש הקבוצות הראו שינוי כלשהו בהרכב החברה בעקבות המניפולציה. שינוי זה היה בזהות המינים במאסף או בשכיחות היחסית של המינים הדומיננטיים בחברה )אשר במקרה של המכרסמים והחיפושיות מהווים גם מיני מחוון טובים(. שונות עתית גבוהה ושונות מרחבית בינונית בשכיחות המינים, עושרם, והרכב החברות, היוו גורם ממסך ותרמו לכך שהשפעות עדינות של המניפולציה היו קשות לאיתור.

מחקר זה היה יישומי מאוד מטבעו. אחד מיעדיו המוצהרים היה לנסח המלצות ממשק ארוכות- טווח לאנשי רשות הטבע והגנים, האמונים על ניהול שמורת חולות עגור ושמורות נוספות במרחב חולות צפון-מערב הנגב. בהנחה שאנו חולקים אותן מטרות של שמירת-טבע, להלן המלצות הממשק שהייתי מציג בפניהם: 2. הגדלת השטח הרציף העובר מניפולציה כך שיכלול מספר דיונות לכל אורכן )אך המשך העיבוד על-פני הרכסים בלבד(. באופן זה ייווצר שטח רציף גדול יותר של חול נודד עם כל היתרונות האקולוגיים הידועים ביחס לגודל ורציפות בית-גידול. לדוגמה צמצום השפעות שוליים, יכולת הפצה משופרת ועוד. 1. המשך ניטור של שינויים פאוניסטיים, תוך התמקדות במינים פסמופיליים ייחודיים ונדירים. מיקוד זה יאפשר לקבל הערכה משופרת של יחס עלות-תועלת של הפרויקט בכללותו. המטרה הסופית של ממשק שימור פעמים רבות מתמצה בשימור ועידוד אוכלוסיותיהם של אותם המינים. 4. יישום ממשק המניפולציה בתחום הביניים של קווי הרוחב הגיאוגרפיים ועד לצפונם )יחסית לשטחי המחקר שלי(. באזור הדרומי יותר נצפתה פעילות איאולית מוגברת גם בחלקות הביקורת בעטיה של הבצורת הממושכת הפוקדת את האזור. 3. ניטור השפעת המניפולציה על הצומח החד-שנתי המהווה רכיב מפתח במערכת החולית כספק עיקרי של זרעים לחברת הגרניבורים ושל רקמה צמחית יבשה לחברת הדטריבורים )למשל מרבית השחרוריתיים(.

ככלל, אני מאמין שלשבירת קק"ב על רכסי דיונה תוך הסרה חלקית של צומח מעוצה ישנה השפעה חיובית על חברות בעלי-החיים בדיונה באופן כללי, ועל המינים הפסמופיליים באופן מיוחד. עם זאת, אם הבצורת הממושכת באזור תמשך )ואולי יש להכיר בשינוי אקלימי לכיוון של היפר-ארידיות(, התניידות / שפעול טבעי של הדיונות עשוי להתרחש מעצמו, כך שפעולות ממשק עתירות משאבים עשויות להתייתר.

מושגי מפתח: נגב, מערכת )אקולוגית( חולית, התייצבות דיונה, שיקום אקולוגי, GUD, פעילות חול איאולית, קרומי-קרקע ביולוגיים, אקו-גיאומורפולוגיה, חברת מכרסמים, חברת זוחלים, חברת חיפושיות-קרקע

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