Ecogeography and Demography of Cicer Judaicum Boiss., a Wild Annual Relative of Domesticated Chickpea

Published online April 25, 2006 Ecogeography and Demography of Cicer judaicum Boiss., a Wild Annual Relative of Domesticated Chickpea Roi Ben-David, Simcha Lev-Yadun, Canan Can, and Shahal Abbo* ABSTRACT domesticated chickpea compared with other cool season Chickpea (Cicer arietinum L.) is a major pulse crop in the Indian grain legumes (e.g., Abbo et al., 2003; Siddique et al., subcontinent and other world regions and is characterized by narrow 1999; Turner et al., 2001). Indeed, in their review of adaptation relative to other cool season food legumes. Comparative pulse crops adaptation in the Canadian and U.S. northern ecophysiology employing closely related wild species is a powerful Great Plains, Miller et al. (2002) noted that chickpea has tool to broaden the understanding of the genetic and physiological an “unusual response to growth season rainfall” and that basis of crop adaptation. However, meager data are available on the pea and lentils had broader adaptation compared with ecological preferences of annual wild Cicer species. Moreover, the chickpea. Miller et al. (2002) also stressed that “compar- geographic range, its size, shape, and boundaries as well as its in- ative adaptation among pulse crops remains poorly un- ternal structure have never been studied for any of the wild Cicer taxa, derstood.” Regardless of the evolutionary and agronomic thereby limiting our understanding of Cicer biology. Accordingly, this work focused on Israeli C. judaicum Boiss. a wild annual relative of reasons for the failure of chickpea to occupy a major chickpea. We defined the range of the species across the Mediterra- niche among the autumn sown crops of temperate lati- nean zone of Israel, characterized the ecogeographical profile of its tudes, understanding the genetic and physiological basis habitats and studied two populated sites at the macro- and microsite of adaptation is fundamental for future improvement of levels in terms of plant density, frequency, and niche physical char- chickpea and other crop plants (e.g., Evans, 1993). acteristics. Throughout the survey area the species is mostly confined The closely related wild relatives of crop plants pro- to stony and rocky niches where competition with more aggressive vide excellent material to study the potential adaptation annuals is small. This habitat preference dictates a patchy distribution spectrum of the respective crops (Evans, 1993). Eco- pattern at all levels, from local niche to the region and beyond. physiology and comparative physiology are key components in such an approach (therein), provided there HICKPEA is a grain legume associated with the ini- is a wide range of germplasm lines representing a suf- Ctiation of agriculture in the Neolithic Near East ficiently wide ecological spectrum. In the case of Cicer, (Lev-Yadun et al., 2000; Zohary and Hopf, 2000). An- however, the number of independent wild annual acces- nual world production of chickpea amounts to approx- sions found in genebanks is relatively small (Berger et al., imately 8 3 106 Mg, a lion’s share of it (94%) in devel- 2003). The data available from the annual Cicer world oping countries, mainly in the Indian subcontinent collection indicate that they provide incomplete coverage (FAO, 2006). Large population sectors in India and its of the geographical distribution of the taxa and thus prob- neighboring countries, many of them vegetarian, depend ably also of their genetic diversity (Berger et al., 2003). on chickpea as a main dietary protein source, while in As part of our ongoing project aimed at broadening developed countries it is considered a health food (e.g., the understanding of the genetic and physiological basis Abbo et al., 2005). of chickpea adaptation, we focused in this study on C. In a recent review on the evolution of domesticated judaicum, an annual wild taxon and a member of the chickpea (Abbo et al., 2003), the authors suggested that tertiary genepool of the cultigen (Ladizinsky and Adler, the restricted distribution of C. reticulatum Ladiz. (the 1976). This species is cross-compatible with C. bijugum immediate wild progenitor) poses severe limitations on Rech. f., which grows in higher latitudes (Ladizinsky and the adaptation of the crop. These authors hypothesized Adler, 1976), making both taxa suitable parents for seg- that the narrow adaptation of C. reticulatum (as deduced regating populations to study the genetic basis of adap- from its restricted natural distribution) represents (or tation (Abbo et al., 2003; Berger et al., 2003). The stems from) limited genetic variation in key adaptive loci specific aims of this work were as follows: first, to define (e.g., temperature and day-length response genes and the geographic range of C. judaicum across the Medi- edaphic requirements). Further, this narrow genetic vari- terranean zones of Israel and characterize this range by ation could partly account for the adaptive limitations of its size, shape, boundaries and internal structure; second, to identify ecogeographic patterns in the distribution of R. Ben-David and S. Abbo, The Robert H. Smith Institute of Plant C. judaicum by using Geographic Information Systems Science and Genetics in Agriculture, The Hebrew University of (GIS) and multivariate analyses; and third, to charac- Jerusalem, P.O. Box 12, Rehovot 76100, Israel; S. Lev-Yadun, terize the local spatial pattern of C. judaicum plants, Reproduced from Crop Science. Published by Crop Science Society of America. All copyrights reserved. Department of Biology, Faculty of Science and Science Education, their density, frequency, and preferred microhabitats by University of Haifa-Oranim, Tivon 36006, Israel; C. Can, Department focusing on two selected populations. of Biology, University of Gaziantep, 27310, Turkey. Received 12 Oct. 2005. *Corresponding author ([email protected]). Published in Crop Sci. 46:1360–1370 (2006). MATERIALS AND METHODS Plant Genetic Resources Survey Procedure doi:10.2135/cropsci2005.10-0351 ª Crop Science Society of America A field survey was held during the growth seasons 677 S. Segoe Rd., Madison, WI 53711 USA (November–April) of 2002, 2003, 2004, and 2005 searching 1360 BEN-DAVID ET AL.: ECOLOGY OF WILD CICER JUDAICUM 1361 for C. judaicum populations across 236 sites in central and PCA Analysis northern Israel, excluding most of the West Bank area. First, localities that were documented in the herbarium of the Hebrew Principal component analysis (PCA) of the continuous University of Jerusalem or in the “ROTEM” database (BioGis, ecogeographical variables was used to identify a smaller num- 2002) were visited. Second, typical “like-habitats” were sampled ber of principal components to account for most of the using the “search image” concept (Engels et al., 1995). To es- ecogeographical variance among 52 sites populated with C. tablish presence or absence patterns, ecogeographic data was judaicum. PCA was based on the correlation matrix and collected for each site irrespectively of whether C. judaicum was presented as biplot ordinations of populated sites (PC scores) found. In each site, latitude, longitude, and altitude were de- and ecogeographical variables (PC factor loading). Actual termined by GPS, and location descriptors (geographical region, populated sites were depicted in the ordination by plotting road or settlement name, proximity to prominent land marks) sites’ principal component scores using a unique symbol for and site physical characteristics (habitat type, slope, aspect, each cluster of sites. Three components were extracted by and precise location of target species plants at the site, if found) Eigenvales .1 to ensure meaningful implementation of the were recorded. Ecogeographical data were extracted from the data by each factor. PCA and hierarchical clustering was Geographic Information System (GIS) center of the Hebrew applied by SPSS v.12 (SPSS, 2002). University of Jerusalem and from maps of the Israel meteo- rological service (for annual and monthly rainfall, monthly Ecological Assay minimum and maximum temperature, soil type, lithology, associated species, vegetation cover, and distance to nearer The ecological assay, aimed at characterizing the local con- settlement, road, or reserve). To ensure independence between ditions at the populated site level, was preformed at Nahal observations and avoid autocorrelations, a minimal distance of A’naba and Nahal Mea’ra (Fig. 1) on four different dates 2 km between sites was kept (Legendre, 1993; Guisan and (March 2002 and three dates during 2003 season: early Jan- Zimmerman, 2000). On the basis of the presence–absence data, uary, end of February and early April). In addition, two long a “dot map” was constructed by the GIS software ArcView3.2 transects, extending from south to north and from west to east, (ESRI, 2002). were undertaken in each site during the 2003 season to obtain a rough estimate of the spatial size of the two populations. Multivariate Analysis The N. A’naba site is located southeast of Modii’n town and consists of four slopes: southeast, west, northwest and east The following 11 ecogeographical variables were used in facing slopes. The N. Mea’ra site is located at Judea foothills all multivariate techniques: longitude (Ln), latitude (Lt), alti- and consists of two contrasting, south and north facing slopes. tude (Al), annual rainfall (Rn-A), mean and minimum tem- Both sites are under seasonal grazing, cattle at N. A’naba and perature in January, representing peak winter conditions sheep at N. Mea’ra. (mean and minimum winter temperature- Tmean-W, Tmin- Demographic surveys in both sites were performed along W), mean and maximum temperature in August represent- random transects across the different slopes (2–4 transects per ing peak summer conditions (mean and maximum summer slope) aiming to maximize microsite topographic variability. temperature—Tmean-S, Tmax-S), slope direction relative to Transects position relative to slope direction was random. the north (S-D), slope rate in percentage (S-R), and distance to Each transect (50 3 0.5 m) consisted of 25 sampling units of sea (Dis-S). For the implementation of discriminant analysis 1m2 each.

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