Wild Gazelles of the Southern Levant: Genetic Profiling Defines New Conservation Priorities

<div><p>The mountain gazelle (<i>Gazella gazelle</i>), Dorcas gazelle (<i>Gazella Dorcas</i>) and acacia gazelle (<i>Gazella arabica acacia</i>) were historically abundant in the southern Levant, and more specifically in Israel. Anthropogenic and natural changes have caused a rapid decline in gazelle populations, raising concerns about their conservation status and future survival. The genetic profile of 111 wild gazelles from Israel was determined based on three regions of mitochondrial DNA (control region, <i>Cytochrome b</i> and 12S ribosomal RNA) and nine nuclear microsatellite markers. Genetic analysis of the mountain gazelle population, the largest known population of this rare species, revealed adequate diversity levels and gene flow between subpopulations. Nevertheless, ongoing habitat degradation and other human effects, such as poaching, suggest the need for drastic measures to prevent species extinction. Dorcas gazelles in Israel displayed inbreeding within subpopulations while still maintaining considerable genetic diversity overall. This stable population, represented by a distinctive genetic profile, is fragmented and isolated from its relatives in neighboring localities. Based on the genetic profile of a newly sampled subpopulation in Israel, we provide an alternative hypothesis for the historic dispersal of Dorcas gazelle, from the Southern Levant to northern Africa. The small acacia gazelle population was closest to gazelles from the Farasan Islands of Saudi Arabia, based on mitochondrial markers. The two populations did not share haplotypes, suggesting that these two populations may be the last remnant wild gazelles of this species worldwide. Only a dozen acacia gazelles survive in Israel, and urgent steps are needed to ensure the survival of this genetically distinctive lineage. The genetic assessments of our study recognize new conservation priorities for each gazelle species in the Southern Levant.</p></div

Sampling sites of gazelles across the Southern Levant.

<p>The division by species and geographic regions is indicated by the different icons. Shaded icons represent mountain gazelles: triangles represent the Northern subpopulation, squares represent the Central subpopulation, diamonds represent the Coastal subpopulation and circles represent the Western Negev subpopulation. Dorcas gazelles are represented by unshaded icons: circles represent the Negev subpopulation and the triangles the Arava subpopulation. Acacia gazelles were sampled only from the Arava (shaded star).</p

Estimates of genetic diversity for the species of <i>Gazella</i> in Israel and their subpopulations.

<p>N number of samples; H number of haplotypes; π nucleotide diversity; Hd haplotype diversity; Na number of different alleles; Np number of alleles unique to a single population; Ho observed heterozygosity; He expected heterozygosity; F fixation index [(He—Ho) / He = 1—(Ho / He)].</p><p>^a Excluding Gd13.</p><p>Based on a 1286bp mitochondrial fragment and nine microsatellite loci.</p

Bayesian clustering analyses for the three gazelle species in Israel.

<p>The most probable number of genetic clusters across three gazelle species in Israel using the STRUCTURE program with the recessive alleles option. (A) Mean L(K)±SD over 5 runs per K as a function of K. (B) ∆K (Evanno et al. 2005) as a function of K. (C) Population assignments to inferred genetic clusters at K = 3.</p

Pairwise differences among populations of <i>Gazella</i> in Israel.

<p>Microsatellites F_st (bold) and Dest (in brackets) are given below the diagonal, mitochondrial F_st are given above the diagonal. All values are significant at α = 0.05</p><p>Pairwise differences among populations of <i>Gazella</i> in Israel.</p

Median-joining haplotype network showing the relationships among Dorcas gazelle populations across the species range.

<p>Range of Dorcas gazelle distribution is shown on map in light grey, based on IUCN and published literature [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116401#pone.0116401.ref037" target="_blank">37</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116401#pone.0116401.ref060" target="_blank">60</a>]. Triangles represent sampling locations, colors represent geographic grouping of samples (after [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116401#pone.0116401.ref037" target="_blank">37</a>]): Dark grey represents west, yellow represents south-central, pink represents south-east, dark blue represents Sinai and light blue represents Israel (our data). Haplotype network is based on concatenation of a 607bp fragment of CytB and a 200bp fragment of the CR, for a total of 70 individuals. Size of the circles is proportional to the frequency of the haplotype and the circle colors match geographic groupings.</p

Genetic relationships among gazelles from the Southern Levant and other localities.

<p>2a. Bayesian phylogenetic reconstruction. The phylogenetic analysis is based on sequences obtained from 230 individuals, 200bp of the control region, representing populations from the Southern Levant (this study, [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116401#pone.0116401.ref008" target="_blank">8</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116401#pone.0116401.ref037" target="_blank">37</a>]) and from neighboring localities [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116401#pone.0116401.ref008" target="_blank">8</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116401#pone.0116401.ref037" target="_blank">37</a>]. Numbers above the nodes represent node age in MYA while numbers below the nodes represent the posterior probability. Mountain gazelles are represented by the green color; Dorcas gazelles from Israel are represented by the light blue color; Dorcas gazelles from northern Africa are represented by the darker blue color; acacia gazelles are represented by the orange color and Arabian gazelles are represented by the red color. Gd13 is marked with an asterisk. Clades of the Arabian gazelles from the Farasan Islands are marked with an arrow at the node. 2b. Median-joining haplotype network. Size of the circle is proportional to the frequency of the haplotype. Color legend is the same as for the phylogenetic tree.</p

Higher differences in environmental parameters cause higher differences in community structure.

<p>Each point in the graph represents a comparison between two samples: the X axis depicts the difference between the two samples with respect to the following environmental parameters in soils: OM – organic matter; Clay – clay percentage; Saturation – water saturation; km – geographic distance between the samples in kilometers; the Y axis is the significance of the dissimilarity (MRPP tests' P-value) between bacterial communities from the two samples. Trend lines are R²>0.8 for all environmental parameters. Values under the ‘0.05 line’ signify two bacterial communities that are significantly different (P<0.05).</p

Mitigating temporal mismatches in forensic soil microbial profiles

<p>Forensic implementation of soil bacterial DNA profiling is limited by the potential for temporal mismatch of DNA profiles, e.g. after storage or seasonal changes. We compared profiles of samples retrieved at one location over 14 years after air-drying, freeze-drying and –80 °C freezing storage. Sample mismatch in freeze-dried and air-dried samples was significant after two years and continued to increase yearly, whereas profiles after –80 °C freezing remained unchanged for many years. In an attempt to mitigate inter-seasonal temporal mismatches, e.g. when months pass between crime and seizure of evidence, soils sampled in winter and summer were exposed to artificial ‘summer’ and ‘winter’ conditions, respectively, and their DNA profiles were compared. Differences were small between soil types, larger between seasons and largest between ‘natural’ and ‘artificial’ seasons. Understanding sources of temporal variations is critical for storage of forensics samples and for developing mitigation procedures that could help overcome these time-induced limitations.</p

Spatial and Temporal Biogeography of Soil Microbial Communities in Arid and Semiarid Regions

<div><p>Microbial communities in soils may change in accordance with distance, season, climate, soil texture and other environmental parameters. Microbial diversity patterns have been extensively surveyed in temperate regions, but few such studies attempted to address them with respect to spatial and temporal scales and their correlations to environmental factors, especially in arid ecosystems. In order to fill this gap on a regional scale, the molecular fingerprints and abundance of three taxonomic groups – Bacteria, α-Proteobacteria and Actinobacteria – were sampled from soils 0.5–100 km apart in arid, semi-arid, dry Mediterranean and shoreline Mediterranean regions in Israel. Additionally, on a local scale, the molecular fingerprints of three taxonomic groups – Bacteria, Archaea and Fungi – were sampled from soils 1 cm–500 m apart in the semi-arid region, in both summer and winter. Fingerprints of the Bacteria differentiated between all regions (P<0.02), while those of the α-Proteobacteria differentiated between some of the regions (0.010.05). Locally, fingerprints of archaea and fungi did not display distance-decay relationships (P>0.13), that is, the dissimilarity between communities did not increase with geographic distance. Neither was this phenomenon evident in bacterial samples in summer (P>0.24); in winter, however, differences between bacterial communities significantly increased as the geographic distances between them grew (P<0.01). Microbial community structures, as well as microbial abundance, were both significantly correlated to precipitation and soil characteristics: texture, organic matter and water content (R²>0.60, P<0.01). We conclude that on the whole, microbial biogeography in arid and semi-arid soils in Israel is determined more by specific environmental factors than geographic distances and spatial distribution patterns.</p></div