Journal of Arid Environments 75 (2011) 416e423 Contents lists available at ScienceDirect Journal of Arid Environments journal homepage: www.elsevier.com/locate/jaridenv Effects of weak climatic variations on assemblages and life cycles of Orthoptera in North Algeria A. Guendouz-Benrima a,1, B. Doumandji Mitiche b, D. Petit c, * a Université Saad Dahleb, Faculté des Sciences AgroeVétérinaires, Département d’Agronomie, B.P. 270, route de Soumàa, Blida, Algeria Ecole National d’Agronomie, Département de zoologie agricole et forestière, Hassan Badi, El Harrach, Alger, Algeria c UMR 1061, INRA, Université de Limoges, 123 av. A. Thomas, 87060 Limoges Cedex, France b a r t i c l e i n f o a b s t r a c t Article history: Received 16 May 2010 Received in revised form 3 December 2010 Accepted 13 December 2010 Available online 7 January 2011 A study on orthopterologic diversity was carried out in two stations situated at 25 km (Soumàa) and 4 km (Koléa) from the Mediterranean Sea in the Mitidja plain (North Algeria) between 1991 and 1992. Mean temperatures are higher in Soumàa than in Koléa, the dry period begins earlier, at the end of spring, in Koléa. The two stations show a diversiﬁed entomofauna, as 28 species were listed in Koléa and 24 in Soumàa. Three seasonal assemblages were deﬁned, the summereautumn one signiﬁcantly differs between the two stations, especially for minority species. The life cycle of larvae was investigated for 6 dominant species in both stations. Four species present a precocious hatching in Koléa, but with a longer duration of larval life. The two species that accomplish their larval life earlier in Koléa than in Soumàa show the greatest lag in hatching date, suggesting an adaptation to the early onset of the dry period. The longer larval life of Ochrilidia harterti in Koléa is discussed in the light of a possible supernumerary larval stage. Ó 2010 Elsevier Ltd. All rights reserved. Keywords: Algeria Climatic parameters Larval life cycle Orthoptera assemblage 1. Introduction In various areas of Algeria, many works on the bioecology of Orthoptera have been carried out, especially on grasshoppers, whether gregarious or not (Allal-Benfekih, 2006; Benfekih et al., 2002; Bounechada et al., 2006; Benfekih and Petit, in press; Chopard, 1943; Chara, 1987; Doumandji and Doumandji-Mitiche, 1994; Fellaouine, 1984; Fellaouine and Louveaux, 1994; Guendouz-Benrima, 2005; Moussi et al., in press). These works focused more on relationships between insects and vegetation (structure) or ﬂora (diversity), less on the inﬂuence of climatic parameters on diversity or on the cycle of Orthoptera species (Petit and Benfekih, 2009), although this latter topic has been documented in other Mediterranean countries (Agabiti et al., 2006; Massa, 2009). The diversity and the cycle of species is an important issue, as this part of the Mediterranean region is a hot spot of biodiversity (Véla and Benhouhou, 2007), with a climate characterized by dry months in the hottest period and a high variability of the delay between rain events (Miranda et al., 2009). Climate- * Corresponding author. Tel.: þ33 (0)5 55 45 75 65; fax: þ33 (0)5 55 45 76 53. E-mail addresses: [email protected] (A. Guendouz-Benrima), [email protected] yahoo.fr (B. Doumandji Mitiche), [email protected] (D. Petit). 1 Tel./fax: þ213 25 43 39 38. 0140-1963/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.jaridenv.2010.12.006 change models are here somewhat original in the sense of a trend to reduced annual precipitations (Rind et al., 1989). Such abiotic factors as climate have complex consequences for the phenology and community structures of insects and spiders (Langlands et al., 2006). In the context of global changes largely documented in temperate countries and in mountain areas, it has been shown that numerous insects adapt by (i) moving northwards or reaching more elevated areas or (ii) by a shift in phenology into an earlier season (Parmesan and Yeho, 2003). When there is a close planteinsect relationship, predatoreprey or hosteparasitoid relationship, shifts in the phenology of one of the partners could affect the survival of the insect (Parmesan, 2006). Otherwise, local adaptations to favorable season involve ecotypes differing by numerous life traits, such as egg size, phenology, length of larval stages, and occurrence of supernumerary nymphal stages (Telfer and Hassall, 1999). The aim of this work is to address weak climatic effects on Orthoptera populations, by choosing two areas of North Algeria, more and less distant from the coast and quite comparable by their vegetation. Proximity to the sea should be associated with less extreme temperatures in winter and summer. In this context, the inﬂuence of climate on insect populations is not well documented, but a preliminary survey by Petit and Benfekih (2009) in 49 Algerian localities showed a weak positive correlation between minima means of winter temperatures and acridian richness. We A. Guendouz-Benrima et al. / Journal of Arid Environments 75 (2011) 416e423 Mean temperatures November December October September 4.3 18.25 12.1 21.9 35.5 28.0 588 64.7 July 7.9 12.3 10.1 23.4 30.2 26.8 486 74.8 August Q2 ¼ 3.43 (P/Mm) (Sauvage, 1963). Soumàa (Boufarik) June Hottest month Minima mean (m) Maxima mean Mean temperatures Minima mean Maxima mean (M) Mean temperatures Annual rainfall (P) Q2 Koléa (Staouali) May Table 1 Climate characteristics of the study sites in the 1988e1997 period. April The study was undertaken on waste lands in the plain of Mitidja (North of Algeria). It is the lartest sublittoral plain of this country, with a surface of approximately 140,000 ha, extended over a length of approximately 100 km, its width varying between 5 and 20 km. On the north side, it is separated from the sea by the Sahel wrinkle; on the south side, it is limited by the mountainous chain of the Blidean Atlas (Loucif and Bonafonte, 1977). Two stations were retained: the station of Soumàa, 25 km distant from the sea, is situated at the piedmont of the Blidean Atlas, at an altitude of 200 m A.S.L., with a southern exposure. The station of Koléa is only 4 km from the sea, established on a plane area on the southern slope of the Sahel at an altitude of 250 m A.S.L. The bioclimate, in the sense of Emberger-Sauvage (Sauvage, 1963), of both stations is Mediterranean at the limit of sub-humid and semi-arid stages with a mild winter. Climatic data for Soumàa and Koléa were taken from Boufarik and Staouali respectively, for the period 1988e1997 (around the years of study). The Soumàa station shows higher mean temperatures than the Koléa station (between 1.2 and 2 C), and a greater range between minima and maxima means (about 14 C versus 4.5e7 C), leading to colder minima means in January (Table 1). The mean temperatures between March and July were 1.6 C higher in Soumàa than in Koléa in 1991, but only 1.1 C in 1992. The rainfalls, generally observed from the end of autumn to the beginning of spring, are characterized by a great inter-annual and inter-monthly irregularity. The 2-year study (from January, 1991, to September,1992) were characterized by annual rainfalls of 806.2 mm in Soumàa and 764.4 mm in Koléa, exceeding by about 214 mm and 178 mm respectively the averages observed over 10 years. The relatively higher values of annual rainfall in Soumàa are mainly observed during the ﬁrst 5 months of the year. The dry months in the sense of Gaussen (1954), deduced from the ombrothermic diagram (Fig. 1), extend from the beginning of May in Koléa, (but June in Soumàa), until the beginning of September in both stations. March 2.1. Study stations Febuary January 2. Material and methods Coldest month Rainfall (mm) thus expect a richer fauna in the station closer to the Mediterranean coast. As there is a difference in dry month onset between both stations, a shift is expected in the phenology of species, in order to avoid the effects of aridity on shortage of plant supply, as most Orthoptera feed on plant species. The earlier the dry season, the more advanced the cycle. We conducted a two-year survey by monthly samplings, in order to deﬁne the different assemblages that occur during the seasons, and to compare their structures. In order to remove the effect of vegetation on insects, we veriﬁed the homogeneity of the vegetation between the two study sites, and carefully examined the phytosociological signiﬁcance. To have a better understanding of the differences observed, we focused on the phenology of topranked species, including larval life duration and L1 occurrence. 417 Fig. 1. Ombrothermic diagram. 2.2. Sampling 2.2.1. Plant sampling We chose two waste lands of identical aspect to avoid the effect of vegetation differences. Each waste land resulted from the natural plant dynamics over 4e5 years following a crop composed of a mixture of Vicia sp. and Avena sativa. These crops had been neither amended with nitrogen nor treated with pesticide. As for vegetation studies, a 50 m 1 m transect per station was carried out in May of the years 1991 and 1992. For each plant species, the number of individuals was counted in the sampled area, then reported to the total number of individuals, all species together, and total vegetation covering (Appendix A), giving the frequency (Fi): Fi ¼ % plant cover i* Number of plant individuals i/S Number of total plant individuals. All species were kept in the herbarium of Blida University, identiﬁed using Quézel and Santa (1962) and conﬁrmed by examination of herbarium specimens of the National Institute of Agronomy in El-Harrach and with the technical assistance of Mr. Beloued. The nomenclature was updated by the Tela Botanica electronic ﬂora, section North Africa, available at the web address http://www.tela-botanica.org/page:bdafn?langue¼fr. 2.2.2. Orthoptera sampling During the years 1991 and 1992, a monthly sampling of insects was undertaken. To sample the maximum number of Orthoptera species representative of each station, we delimited at random, open quadrates of 3 m 3 m (9 m2), separated from each other by a distance of at least 10 m, following Lamotte and Bourlière (1969). The problem of immigration and emigration of individuals from survey plots (Gardiner and Hill, 2006) was unimportant because samplings were carried out very early in the morning, between 6:30 and 9:00 in summer, and between 7:30 and 11:00 in winter, when the insects were still immobilized on the ground. This operation was repeated ﬁve times in each station using a sweeping net to collect almost all insect individuals by quadrat. For the majority of the species, individuals were released elsewhere in the vicinity after counting, so as to avoid counting them twice. For a small number of A. Guendouz-Benrima et al. / Journal of Arid Environments 75 (2011) 416e423 critical species, some individuals were put in plastic bags on which the date, place of capture, as well as the name of the station, were noted for a later determination. A reference collection of all the species (one male and female) was assembled during the study and kept at the laboratory of Zoology of the university Saad Dahleb in Blida. Systematic determination of Orthoptera species was carried out using the key of the Orthopteroids of North Africa (Chopard, 1943), corrected for a few genera, such as Pyrgomorpha (Hsiung and Kevan, 1975), Ochrilidia (Jago, 1977), Sphingonotus (Hochkirch and Husemann, 2008). Nomenclature was updated using the OSF2 website (http://Orthoptera.SpeciesFile.org). For larvae, the most difﬁcult specimens to determine were captured and then identiﬁed thanks to Mr. Pr. S.E. Doumandji (National Agronomic Institute in ElHarrach). The majority of the collected larvae were released so as not to affect the populations. 14 12 10 Abundance 418 8 L3 Koléa L3 Soumaa 6 4 2 0 1 2 3 4 2.3. Data analysis 5 6 7 Months 8 9 10 11 12 Fig. 2. Temporal shift in the abundance of larvae of stage 3 of Dociostaurus jagoi jagoi. We analyzed seasonal variations of the assemblages of sampled Orthoptera by a correspondence analysis followed by an ascending hierarchical analysis (CAH). This approach allowed projecting on a plane the line (species) and column (samples), in order to get the best association between both factors. As the percentage of variance (i.e., explanation) of the ﬁrst two axes is often less than 50%, it is useful to construct a distance tree, taking into account the exact position in three dimensions of both species and samplings. Brieﬂy, the scores obtained on the three ﬁrst axes were used to calculate Euclidean distances between taxa and samples. The species associated with samples in a given cluster allow deﬁning an assemblage. So this procedure makes it possible to examine the differences in composition of the samples (Martikainen et al., 2000). To compare the structure of the different assemblages, we constructed rankeabundance diagrams, following the procedure explained in Djazouli et al. (2009). The adjustment to the model of Motomura (Iganaki, 1967), where ln (abundance) ¼ A * S þ B, with S being the slope of the regression line, was assessed by Pearson coefﬁcients. The comparison between regression slopes was deduced from the F values of covariance analyses and the corresponding probabilities of Barlett’s test (Scherrer, 1984). We tested the overall similarity between the two sites for each seasonal assemblage by an ANOSIM (ANalysis Of Similarities), a non-parametric test of signiﬁcant difference based on any distance measure (Clarke, 1993). The BrayeCurtis index was here used as a similarity measure and the p-value calculated from 10,000 permutations. The signiﬁcance of plant diversity differences between the two stations was tested by resampling methods (bootstrap and permutations), according to the method described in Poole (1974). All the multivariate analyses were conducted with PAST vers. 2.03 (Hammer et al., 2001). The temporal barycenter of a single larval stage j was calculated by the formula: BSLj ¼ X X Ni*abundancej = abundancej ; with Ni ¼ number of the month, and abundancej ¼ abundance of larval stadium j in the corresponding month, for j ¼ 1 to 5. For a given larval or adult stage and a given species common to both stations, the temporal shift between the two populations was obtained by calculating the difference of the BSLj in both stations, estimated by the difference between the two means of normal distributions (Fig. 2). The signiﬁcance of the shift at the two stations for the different stages of a given species was tested with Wilcoxon tests using PAST vers. 2.03. The barycenter of total larval stages in May was calculated by the formula: BTL ¼ X X ðMi Þ*abundance= ðabundanceÞ; with Mi ¼ number of larval stage, abundance ¼ abundance of the corresponding larval stage. 3. Results 3.1. Comparison of the plant inventories We recorded 28 and 32 plant species in the stations of Koléa and Soumàa respectively (Appendix A). Nearly 78% of the species were found to be shared by both stations (Table 2). In addition, homogeneity of the ﬂora between both stations (taxonomic richness and the diversity, measured by the Shannon index) was supported by the bootstrap and permutation methods (p > 0.24). If we refer to the phytosociological index for French ﬂora (Julve, 1998), both stations (see appendix A) are characterized by the dominance of adventitious therophytes (Stellarietea medieae), Mediterranean and Medioeuropean xerophilic perennial species of fallow lands (Onopordetea acanthi) and European therophytes of fallow lands (Sisymbrietea ofﬁcinalis). 3.2. Species of Orthoptera recorded Total numbers of 1398 and 1112 insects were recorded in Koléa and Soumàa stations respectively. We listed 28 species in the station of Koléa, comprising 4 Ensifera and 24 Caelifera, the latter divided into four different families and ten subfamilies. In Soumàa on the other hand, 24 species were encountered, including 3 Ensifera and 21 Caelifera, this last group comprising 3 families and 8 subfamilies (Appendix B). The most abundant species in both stations were: Aiolopus strepens, Dociostaurus jagoi jagoi, Acrida turrita, Acrotylus patruelis, Ochrilidia harterti, Oedipoda caerulescens sulfurescens, Calliptamus wattenwylianus, Pezottetix giornai, and Aiolopus thalassinus. It appears that three species were linked to humid vegetation (Conocephalus conocephalus, Paratettix meridionalis and Tropidopola Table 2 Frequency of plant species at both study sites. Nb of species H0 Shannon % of shared species Koléa Soumaa Boot p(eq) Perm p(eq) 28 3.754 78.947 32 3.755 0.427 0.992 0.243 0.989 A. Guendouz-Benrima et al. / Journal of Arid Environments 75 (2011) 416e423 cylindrica) and not to fallow lands or to adventitious species. As a consequence, these species were excluded from the statistical analyses. Table 3 Comparison of regression slopes within the Motomura model. For the slope comparisons, only the p-values were given, according to the F values of covariance analyses and the corresponding probabilities of Barlett’s test. Ln WinterRank 3.3. Temporal variations of Orthoptera assemblages 3.3.1. Composition of assemblages In our case, the dataset (insect species in row and monthly sampling in column) was subjected to a Correspondence Analysis. The CAH (electronic supplementary data) showed that each group reacts differently to the seasonal characters of the zones of studies. We notice the existence of three seasonal groups: (i) a winter assemblage identiﬁed by a single characteristic species, A. strepens, (ii) a spring assemblage comprising O. harterti, Pyrgomorpha conica and both species in the genus Omocestus, (iii) a rich summereautumn assemblage, where the samples of both stations are gathered in two different clusters. Of course, a given seasonal group comprises more species than the characteristic ones cited above. As for example, the winter assemblage contains 8 species, including A. strepens, and the spring assemblage 21, etc. In addition to these 3 seasonal groups, there are two sets of species associated with Soumàa (Odontura microptera, Sphingonotus diadematus and S. rubescens) or with Koléa (Oedipoda miniata, Platycleis sp, Pyrgomorpha cognata and Tessellana tessellata). 3.3.2. Structure of the assemblages We considered for each seasonal assemblage the total number of recorded species, whether they were characteristic of a given season. Because of the distribution of both stations within the cluster corresponded to the summer-autumn group, the samples recorded in each station were considered as different assemblages. Thus, we compared the structure of the four retained assemblages (winter, spring, summer-autumn in Koléa, summer-autumn in Soumàa) through an adjustment to the abundance-rank model (log-transformed abundance) of Motomura. The calculation of Pearson coefﬁcients (Fig. 3) revealed a highly signiﬁcant adjustment (probabilities associated all lower than 104). Comparing the linear equations corresponding to the four assemblages (Table 3), we noticed highly signiﬁcant differences in the regression slopes between winter and other assemblages on the one hand (p < 106), and a moderate between the summer-autumn assemblages of Koléa and Soumàa on the other (p ¼ 0.031). 419 Regression slopes 0.6951 Ln Winter e Rank Ln Spring-Rank Ln Summer Koléa-Rank Ln Summer Soumàa - Rank e 2.4 107*** P ¼ 5.9 1011*** Ln SpringRank Ln Summer Ln Summer Koléa-Rank Soumàa-Rank 0.1759 0.151 0.1835 e P ¼ 0.65 N.S. e P ¼ 4.31 1016*** P ¼ 0.0128 * P ¼ 0.031* e N.S.- non-signiﬁcant, * signiﬁcant at 5%, ***signiﬁcant at 1&. We also tested the signiﬁcance of differences in the composition of the four assemblages by ANOSIM procedure. In a ﬁrst step, a twoway ANOSIM considering the season (three modalities) and the station (two modalities) as factors, revealed a signiﬁcant effect of season factor (p < 0.0001) but only a marginal one of site factor (p ¼ 0.081). In a second step, we compared the differences between both sites for each season, considered in one-way ANOSIM. Only the summer-autumn assemblages appeared to show signiﬁcantly different compositions between both stations (p ¼ 0.037). In conclusion, the composition of assemblages between the two study sites is not distinguishable in winter and spring, but differs in summereautumn, supporting our previous distinction between 4 assemblages. In order to have a better understanding of the signiﬁcance of this difference in summer-autumn, we calculated Pearson correlations for the majority and minority species recorded in the two stations at this period. We note that the most abundant species of Koléa and Soumàa are highly correlated (p ¼ 0.0011), meaning that the most abundant species in Koléa are the same ones in Soumàa (Fig. 4). As for the minority species, no correlation could be found (p ¼ 0.27), showing that the overall difference in the composition of both stations is mainly due to these less frequent species. 3.4. Lag between the larval cycle of dominant species in both stations The studies on larval phenology were conducted on the topranked species, in order to minimize statistical errors of sampling. Based on the presence of clear peaks in the abundance of larval stages, we can deﬁne four species with one generation per year (A. patruelis, A. strepens, D. jagoi, and C. wattenwilianus), whereas O. harterti presents two, and A. turrita two to three. Abundance in Soumàa 14 12 10 8 6 4 y = 0.588x + 2.251 . 2 0 p = 0.0011 0 5 10 15 R² = 0.599 20 Abundance in Koléa Fig. 3. Adjustment of the communities to the Motomura model (ranks and logarithm of species abundances). Fig. 4. Correlation of dominant species abundances between Koléa and Soumàa. 420 A. Guendouz-Benrima et al. / Journal of Arid Environments 75 (2011) 416e423 Table 4 Precocity of the life cycle. Species name Mean barycenter of larval stages in May Elapse time between L1-L5 (in month) Mean barycenter of L1 (in month) Koléa Soumàa Koléa Soumàa Koléa Soumàa Acrotylus patruelis Aiolopus strepens Dociostaurus jagoi Calliptamus wattenwilianus Ochrilidia harterti G1 Acrida turrita G1 2.81 2.43 2.26 2.29 2.39 3.38 2.28 2.11 2.14 2.2 3.04 3.33 3.09 3.24 3.14 2.52 2.67 2.72 2.87 2.95 2.74 2.25 3.33 3.38 3.91 3.93 4.00 4.54 4.14 3.50 4.13 4.33 4.20 4.75 3.25 4.17 A barycenter of 2.81 in May corresponds to a mean stage closer to L3 than to L2. A mean barycenter of L1 of 3.91 indicates a month mode closer to April than to March. 3.4.1. Precocity of the life-cycle As shown in Table 4, the less advanced species in their larval stage in May are A. strepens, D. jagoi and C. wattenwilianus, as their barycenter correspond to an early L2 stage in both stations. In contrast, A. turrita in its ﬁrst generation has the more precocious cycle, as most individuals are L3 in both stations. The two remaining species are intermediate: the population of A. patruelis is more advanced in Koléa but the contrary is true for O. harterti. If we compare the species in both stations, ﬁve are in advance (from less than a week to two weeks) in Koléa. O. harterti is an exception, as we observe a negative lag of 2e3 weeks in the same station. The situation in May can be attributed to different components of insect phenology, such as the speed of larval development and the date of hatching. In a ﬁrst step, we performed a regression analysis on the barycenters of dates versus the larval stages, in order to limit the uncertainty of L1 counting estimation. We also calculated the elapsed time between the barycenter of L1 and L5 for each station. As both methods gave comparable results, we show in Table 5 the times given by this last method, as being easier to interpret. The fastest larval development is observed in C. wattenwilianus, at about two months and a half, and the slowest in A. strepens, about three months. If we compare the populations in both stations, the insects are divided in two groups: four of which develop faster in Soumàa than in Koléa, whereas O. harterti and A. turrita take less time to accomplish their larval life in Koléa. Unfortunately, as we calculated these elapsed times using a two-year survey, we cannot assess the inter-annual variability. Moreover, as the barycenter of a given larval stage is calculated at the level of the population, no statistics can be given. In a second step, we calculated the barycenter of L1 for each station and each species (Table 4). Four species begin their larval life approximately at the same time, between the end of March to the beginning of April. It seems that C. wattenwilianus is the latest species to hatch, since L1 individuals are observed by the second or third week of April. More interestingly, all the species but O. harterti hatch about two weeks earlier in Koléa than in Soumàa. Table 5 Lag in the larval phenology in dominant species between Koléa and Soumàa. Species name Acrotylus patruelis Aiolopus strepens Dociostaurus jagoi Calliptamus wattenwilianus Ochrilidia harterti G1 Acrida turrita G1 Number of larvae recorded Lag p-value Koléa Soumàa 1991 1992 Wilcoxon 113 286 252 73 192 99 119 189 183 39 224 42 0.64 0.54 0.08 0.02 0.72 0.51 0.25 0.24 0.13 0.08 0.19 0.20 0.48 NS 0.016 * 0.19 NS 0.40 NS 0.028 * 0.067 A 0.40 mean lag indicates that the phenology of larva stages is 0.4 month later in Soumàa than in Koléa. 3.4.2. Lag in the larval phenology We calculated for each year (1991 and 1992) the lag in the larval development between both stations (Table 5). The Wilcoxon tests conducted with the data set of the two years taken together show that the larval cycle is about one to two weeks (A. strepens, ﬁrst generation of A. turrita) later in Soumàa than in Koléa. In contrast, there is an opposite shift in O. harterti phenology, the population of Soumàa developing 1e3 weeks in advance, relatively to the Koléa population. The life cycles of the three remaining studied species (A. patruelis, C. wattenwylianus and D. jagoi jagoi) show non-signiﬁcant lags. To summarize, simultaneous onset of the adult stage in two species can result from opposite strategies: early hatching and slow larval development or late hatching and fast development. However, even if the statistical support is weak, four species show a more or less advanced phenology in Koléa relative to Soumàa. O. harterti, in its ﬁrst generation, is a noticeable exception as it presents an opposite trend. 4. Discussion 4.1. Seasonal structured assemblages The inventory of the insect species in the two stations revealed a relatively rich orthopteran fauna as 28 species were recorded at the station of Koléa, 24 at the station of Soumàa. Samplings were done in two waste lands similar in their plant composition and covering (78% of shared plant species). As for insect inventories, both methods used (CAH and ANOSIM) show that three seasonal assemblages of Orthoptera can be deﬁned, the richest, developed in summer-autumn, being differentiated at the two studied stations. As to the possible factors driving these differences, several hypotheses can be brought: (i) vegetation composition or structure (Agabiti et al., 2006; Dufrêne and Legendre, 1997; Guido and Gianelle, 2001; and Vassiliki et al., 2003), (ii) historic reasons, such as a different interval since perturbation occured (ﬁre for example, see Langlands et al., 2006), (iii) more or less pronounced grazing pressure by goat and sheep (Louveaux et al., 1996; Feoli et al., 2002; Fadda et al., 2008), and (iv) climatic parameters. Of course, the diversity of the studied sites depends on the diversity of the areas surrounding them, particularly the existence of corridors, but such information is still lacking. As the history of both studied sites is, as far as we know, quite similar, we considered the climatic parameters as the main explanation of differences between summereautumn assemblages, especially for the less abundant species. Analysis of climatic data in both stations was revealed as complex by several considerations. First, the dry season appears in June in Koléa, but earlier in May in Soumàa. Second, the mean temperatures are one to two degrees higher in Soumàa than in Koléa. However, we recorded more extreme temperatures in Soumàa, due to the more signiﬁcant distance between this locality and the Mediterranean Sea. As a result, the minima temperatures recorded are lower in Soumàa than in Koléa, particularly in winter. Taken together, several more or less contradictory predictions about the studied insects can be advanced in such a situation. - At the life cycle level, one can expect two contrasting reactions of the species - A faster transition between larval stages in the station characterized by higher mean temperatures (Soumàa): a question of plasticity. - An earlier emergence of adults in the station where the dry period is recorded earlier (Koléa): a question of local adaptation. A. Guendouz-Benrima et al. / Journal of Arid Environments 75 (2011) 416e423 - At the community level, we can expect differences, as preliminary works would indicate an increase in Orthoptera diversity in areas with milder winter temperatures (Petit and Benfekih, 2009). 421 According to this, an insect species living in an area with a usually precocious dry season “should” accomplish its larval development before the same species living in an area that undergoes a later drought. This strategy is somewhat in contradiction to the previous one, as the insects living in Koléa are submitted to cooler mean temperatures, but also to an earlier onset of dry period. In any case, we observe that the larval phenology is shifted by approximately two weeks for A. strepens and A. turrita. In contrast, Ochlidia harterti, which accomplishes two generations per year, is in advance in the area of Soumàa. When we consider the hatching date, the duration and the lag of larval life, ﬁve species among the six studied show a late hatching in Soumàa, but compensated by a faster larval development resulting in a more or less pronounced lag. The key difference lies in the onset of L1. In the species hatching more than two weeks earlier in Koléa than in Soumàa, there is a signiﬁcant larval lag maintained throughout the larval existence, the Koléa population being in advance relative to the Soumàa one. It concerns A. strepens and A. turrita (ﬁrst generation). In contrast, in O. harterti, the hatching is later in Soumàa and the duration of larval life is also longer, resulting in a positive lag in Soumàa. The problem in interpreting these data is the determinism of the hatching lag. Is this lag resulting from plasticity, i.e., is it triggered for example by minima means lower in Soumàa? Or must we invoke a local adaptation, involving differentiation of ecotypes as shown by Telfer and Hassall (1999)? We point out that experiments in controlled conditions could bring some interesting light on this issue. If the cause of these differences in phenology was due to a genetic differentiation between populations, the hypothesis of an adaptation to accomplish larval life before the dry season would have some support. 4.2. Inﬂuence of climatic constraints on assemblages The greater diversity of Orthoptera recorded in Koléa station, where the winter minima temperatures are milder, ﬁt with the preliminary results of Petit and Benfekih (2009), but long- term studies of meteorological parameters and Orthoptera dynamics should be undertaken to arrive at sound conclusions (Carter et al., 1998; Cigliano et al., 2002; Hunter et al., 2001; Köhler et al., 1999). When the assemblages of Koléa and Soumàa stations are compared, the observed differences correspond to species recorded in summereautumn. We identiﬁed the main differences among the lower-ranked species, but it is difﬁcult to interpret this result: the sampling of rare species is obviously difﬁcult and leads to a statistical uncertainty. And in an opposite view, it could be advanced that rare species are more sensitive to moderate abiotic changes, such as higher mean temperatures (between one to two degrees) in Soumàa than in Koléa, or more extreme temperatures during winter and summer in Soumàa than in Koléa. This idea could be tested by the comparison of bioclimatic domains between top-ranked and lastranked species. We expect a wider range of these domains for topranked taxa. 4.3. Inﬂuence of climatic constraints on nymphal life-cycle traits 4.3.1. Mean temperature and development time When reared at different temperatures between 25 and 35 C, Chorthippus brunneus shows an increasing development rate, since the duration of nymphal stages is about 59 days at 25 C but around 23 days at 35 C (Willot and Hassal, 1998). Other British grasshoppers studied by these authors share the same response to increasing temperatures. So it was expected that the elapsed time between L1 and L5 would be shorter in the Algerian town, where mean temperatures are higher, i.e., Soumàa. The prediction is veriﬁed in four species among the six studied, but not in the case of O. harterti or A. turrita. It is true our empirical data were obtained from ﬁeld observations, where it is difﬁcult to obtain precise measures. However, other experiments conducted on C. mollis suggest that the inﬂuence of temperature on larval life is rather complex. Schädler and Witsack (1999) have shown that in females of this species, a higher supply of warmth leads to the more frequent insertion of an additional nymphal instar, and thus to a prolonged development time. C. brunneus can also exhibit this phenomenon (Grant et al., 1993). It would be interesting to test this idea in the case of O. harterti and A. turrita. Acknowledgements We thank Mr Pr. S.E. Doumandji for assistance in determination of Orthoptera and his cautions advice, Mr. Beloued for his expertise on determination of the plant species, Mr. G. Morris for English revision, and Mrs. F. Vallet of the University of Limoges for her technical assistance. This work received ﬁnancial support via the program Tassili n 08MDU726. Appendix. Supplementary material The following are the Supplementary data related to this article: Hierarchical classiﬁcation of the species of Orthoptera sampled in the two stations of study during the year 1991e1992. Abbreviations: K1, K2. and S1, S2..correspond to the samplings conducted on January, February. in Koléa and in Soumàa respectively. The codes of species are indicated in Appendix B. 4.3.2. Is the cycle adapted to avoid the dry season? We can hypothesize that the onset of the dry period, at the end of spring, is a driving force that inﬂuences the insect life cycle. Appendix A Frequency of plant species in both study sites. Families Plant names Asteraceae Asteraceae Scrophul. Apiaceae Sonchus oleraceus L. Glebionis segetum (L.) Four. Kickxia spuria (L.) Dumort. Ammi majus L. Frequencies of plant species Koléa Soumàa 2.87 0 0 1.88 0 4.08 3.02 2.07 Syntaxons Stellarietea mediae (Braun-Blanquet, 1921) Tüxen, Lohmeyer & Preising in Tüxen 1950 em. Schubert in Schubert, Hilbig and Klotz 1995 (continued on next page) 422 A. Guendouz-Benrima et al. / Journal of Arid Environments 75 (2011) 416e423 (continued ) Families Plant names Frequencies of plant species Syntaxons Koléa Soumàa Asteraceae Brassicaceae Apiaceae Boraginaceae Calendula arvensis L. Sinapis arvensis L. Torilis arvensis (Huds.) Link subsp. arvensis Heliotropium europaeum L. 0 2.86 1.87 0 3.11 3.42 1.35 2.07 Asteraceae Asteraceae Asteraceae Scrophul. Oxalidaceae Apiaceae Verbenaceae Convolvul. Centaurea calcitrapa L. Galactites elegans (All.) Soldano Scolymus hispanicus L. Verbascum sinuatum L. Oxalis pes-caprae L. Daucus carota L. Verbena ofﬁcinalis L. Convolvulus arvensis (L.) 1.72 2.04 1.69 0 2.14 2.04 1.54 1.01 0 0 2.63 3.93 3.33 2.67 2.12 2.58 Onopordetea acanthii subsp. acanthii Braun-Blanquet 1964 em. Julve 1993 Poaceae Asteraceae Poaceae Poaceae Poaceae Asteraceae Bromus hordeaceus L. Conyza canadensis (L.) Cronquist Lolium multiﬂorum Lam. Lolium rigidum (Gaudin) Trab. Avena barbata Pott ex Link. Anacyclus clavatus (Desf.) Pers. 2.96 0.78 2.34 1.27 0 3.11 2.34 1.73 2.32 1.42 4.07 4.19 Sisymbrietea ofﬁcinalis Gutte and Hilbig 1975 Poaceae Apiaceae Lamiaceae Cynodon dactylon (L.) Pers. Oenanthe ﬁstulosa L. Mentha pulegium L. 4.96 2.6 0 7.42 0 2.42 Agrostio stoloniferaeeArrhenatheretea elatioris subsp. elatioris (Tüxen, 1937 em. 1970) de Foucault 1984 Gentianaceae Cyperaceae Centaurium spicatum (L.) Fritsch Pycreus ﬂavescens (L.) P. Bov. ex Rchb. 0 1.34 2.02 1.02 Juncetea bufonii (Braun-Blanquet and Tüxen, 1943) de Foucault 1988 Isolepidetalia setacei de Foucault 1988 Asteraceae Poaceae Fabaceae Brassicaceae Poaceae Cyperaceae Poaceae Poaceae Plantaginaceae Asteraceae Aster squamatus (Spreng.) Hieron. Arundo donax L. Medicago polymorpha L. Lobularia maritima (L.) Desv. Avena sterilis L. Cyperus sp. Hordeum murinum L. Piptatherum miliaceum (L.) Cosson Plantago sp. Xanthium italicum Moretti % of vegetation cover on the ground 2.89 2.2 3.21 1.5 4.02 2.43 6.17 3.87 0 2.47 69.8 2.17 1.63 0.52 0 1.92 3.85 1.73 2.68 2.34 3.25 85.4 Appendix B Sampled Orthoptera in both study sites. Sub-Order Family Sub-family Species Code Nb Koléa Nb Soumàa Ensifera Tettigoniidae Caelifera Acrididae Conocephalinae Phaneropterinae Phaneropterinae Tettigoniinae Tettigoniinae Acridinae Acridinae Acridinae Calliptaminae Calliptaminae Catantopinae Eyprepocnemidinae Gomphocerinae Gomphocerinae Gomphocerinae Gomphocerinae Gomphocerinae Oedipodinae Oedipodinae Oedipodinae Oedipodinae Oedipodinae Oedipodinae Oedipodinae Oedipodinae Oedipodinae Tropidopolinae Pamphaginae Pyrgomorphinae Pyrgomorphinae Tetriginae Conocephalus conocephalus (Linnaeus, 1767) Odontura algerica (Brunner, 1878) Odontura microptera Chopard, 1943 Platycleis sp. Tessellana tessellata (Charpentier, 1825) Acrida turrita (Linnaeus, 1758) Truxalis annulata Thunberg, 1815 (¼ T. pharaonis (Klug, 1830)) Truxalis nasuta (Linnaeus, 1758) Calliptamus wattenwylianus Pantel, 1896 Calliptamus barbarus (Costa, 1836) Pezotettix giornae (Rossi, 1749) Eyprepocnemis plorans plorans (Charpentier, 1825) Dociostaurus jagoi jagoi Soltani, 1978 Ochrilidia harterti harterti (Bolívar, 1913) Omocestus lucasi (Brisout, 1850) Omocestus africanus Harz, 1970 Omocestus ventralis (Zetterstedt, 1821) Acrotylus patruelis (Herrich-Schäffer, 1838) Aiolopus strepens strepens (Latreille, 1804) Aiolopus thalassinus thalassinus (Fabricius, 1781) Locusta migratoria (Linnaeus, 1758) Oedipoda caerulescens sulfurescens Saussure, 1884 Oedipoda miniata mauritanica Lucas, 1849 Sphingonotus azurescens (Rambur, 1838) Sphingonotus diadematus Vosseler, 1902 Sphingonotus rubescens rubescens (Walker, 1870) Tropidopola cylindrica cylindrica (Marschall, 1835) Pamphagus elephas (Linnaeus, 1758) Pyrgomorpha cognata cognata Krauss, 1877 Pyrgomorpha conica conica (Olivier, 1791) Paratettix meridionalis (Rambur, 1838) Total Cocon Odalg Odmic Platy Tetes Actur Trann Trnas Cawat Cabar Pegio Eyplo Dojag Ochar Omluc Omafr Omven Acpat Aistr Aitha Lomig Oesul Oemin Spazu Spdia Sprub Trcyl Paele Pycog Pycon Pamer 12 31 0 20 11 122 21 17 80 15 76 21 153 96 55 25 27 99 234 71 5 88 20 28 0 0 8 2 19 8 34 1398 16 20 4 0 0 59 18 17 60 0 62 14 100 139 51 14 24 126 136 62 2 69 0 26 41 44 0 2 0 6 0 1112 Pamphagidae Pyrgomorphidae Tetrigidae A. 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