Article22

Journal of Arid Environments 75 (2011) 416e423
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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), doumandjimitiche@
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. Guendouz-Benrima et al. / Journal of Arid Environments 75 (2011) 416e423
Appendix. Supplementary material
Supplementary data related to this article can be found online at
doi:10.1016/j.jaridenv.2010.12.006.
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