Article22

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
b
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
article info
Article history:
Received 16 May 2010
Received in revised form
3 December 2010
Accepted 13 December 2010
Available online 7 January 2011
Keywords:
Algeria
Climatic parameters
Larval life cycle
Orthoptera assemblage
abstract
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.
Ó2010 Elsevier Ltd. All rights reserved.
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 docu-
mented in other Mediterranean countries (Agabiti et al., 2006;
Massa, 2009). The diversity and the cycle of species is an impor-
tant issue, as this part of the Mediterranean region is a hot spot of
biodiversity (Véla and Benhouhou, 2007), with a climate charac-
terized by dry months in the hottest period and a high variability of
the delay between rain events (Miranda et al., 2009). Climate-
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 rela-
tionship, 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
*Corresponding author. Tel.: þ33 (0)5 55 45 75 65; fax: þ33 (0)5 55 45 76 53.
E-mail addresses: [e-mail] (A. Guendouz-Benrima), doumandjimitiche@
yahoo.fr (B. Doumandji Mitiche), [e-mail] (D. Petit).
1
Tel./fax: þ21325433938.
Contents lists available at ScienceDirect
Journal of Arid Environments
journal homepage: www.elsevier.com/locate/jaridenv
0140-1963/$ esee front matter Ó2010 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jaridenv.2010.12.006
Journal of Arid Environments 75 (2011) 416e423

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 top-
ranked species, including larval life duration and L1 occurrence.
2. Material and methods
2.1. Study stations
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 sit-
uated 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 Mediterra-
nean at the limit of sub-humid and semi-arid stages with a mild
winter. Climatic data for Soumàa and Koléa were taken from Bou-
farik 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 rela-
tively 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.
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 vegeta-
tion 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/SNumber of
total plant individuals.
All species were kept in the herbarium of Blida University,
identified using Quézel and Santa (1962) and confirmed by exam-
ination 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 m
2
), 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
Table 1
Climate characteristics of the study sites in the 1988e1997 period.
Koléa
(Staouali)
Soumàa
(Boufarik)
Coldest month Minima mean (m) 7.9 4.3
Maxima mean 12.3 18.25
Mean temperatures 10.1 12.1
Hottest month Minima mean 23.4 21.9
Maxima mean (M) 30.2 35.5
Mean temperatures 26.8 28.0
Annual rainfall (P) 486 588
Q2 74.8 64.7
Q2 ¼3.43 (P/Mm) (Sauvage, 1963).
Mean temperatures
Rainfall (mm)
January
Febuary
March
April
May
June
July
August
September
October
November
December
Fig. 1. Ombrothermic diagram.
A. Guendouz-Benrima et al. / Journal of Arid Environments 75 (2011) 416e423 417

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 El-
Harrach). The majority of the collected larvae were released so as
not to affect the populations.
2.3. Data analysis
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 vari-
ance (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 asso-
ciated with samples in a given cluster allow defining an assem-
blage. 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) ¼A*SþB, 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 corre-
sponding 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 jwas calculated
by the formula:
BSLj¼XNi*abundancej=Xabundancej;
with Ni ¼number of the month, and abundance
j
¼abundance of
larval stadium jin the corresponding month, for j¼1 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 BSL
j
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 ¼XðMiÞ*abundance=XðabundanceÞ;
with M
i
¼number of larval stage, abundance ¼abundance 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, homo-
geneity 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 (Ono-
pordetea acanthi) and European therophytes of fallow lands (Sisy-
mbrietea 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 and21
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,Cal-
liptamus wattenwylianus,Pezottetix giornai,andAiolopus thalassinus.
It appears that three species were linked to humid vegetation (Con-
ocephalus conocephalus,Paratettix meridionalis and Tropidopola
0
2
4
6
8
10
12
14
123456789101112
Months
Abundance
L3 Koléa
L3 Soumaa
Fig. 2. Temporal shift in the abundance of larvae of stage 3 of Dociostaurus jagoi jagoi.
Table 2
Frequency of plant species at both study sites.
Koléa Soumaa Boot p(eq) Perm p(eq)
Nb of species 28 32 0.427 0.243
H
0
Shannon 3.754 3.755 0.992 0.989
% of shared species 78.947
A. Guendouz-Benrima et al. / Journal of Arid Environments 75 (2011) 416e423418

cylindrica) and not to fallow lands or to adventitious species. As
a consequence, these species were excluded from the statistical
analyses.
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 summereau-
tumn assemblage, where the samples of both stations are gathered
in two different clusters. Of course, a given seasonal group com-
prises 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 Sou-
màa (Odontura microptera,Sphingonotus diadematus and S. rubes-
cens) 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 adjust-
ment (probabilities associated all lower than 10
4
). 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<10
6
),
and a moderate between the summer-autumn assemblages of
Koléa and Soumàa on the other (p¼0.031).
We also tested the significance of differences in the composition
of the four assemblages by ANOSIM procedure. In a first step, a two-
way 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
(p¼0.081). 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 (p¼0.037). 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 corre-
lations 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 (p¼0.0011), 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
(p¼0.27), 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 top-
ranked 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.
Fig. 3. Adjustment of the communities to the Motomura model (ranks and logarithm
of species abundances).
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 Winter-
Rank
Ln Spring-
Rank
Ln Summer
Koléa-Rank
Ln Summer
Soumàa-Rank
Regression slopes 0.6951 0.1759 0.151 0.1835
Ln Winter eRank e
Ln Spring-Rank 2.4 10
7
***
e
Ln Summer
Koléa-Rank
P¼5.9 10
11
*** P¼0.65 N.S. e
Ln Summer
Soumàa - Rank
P¼4.31 10
16
*** P¼0.0128 *P¼0.031*
e
N.S.- non-significant, *significant at 5%, ***significant at 1&.
y = 0.588x + 2.251.
p = 0.0011 R² = 0.599
0
2
4
6
8
10
12
14
0 5 10 15 20
Abundance in Soumàa
Abundance in Koléa
Fig. 4. Correlation of dominant species abundances between Koléa and Soumàa.
A. Guendouz-Benrima et al. / Journal of Arid Environments 75 (2011) 416e423 419

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.Ifwe
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 bary-
centers 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.
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 1e
3 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-signifi-
cant 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 sum-
mereautumn 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 Sou-
màa, 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 char-
acterized 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.
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 2.81 2.28 3.09 2.87 3.91 4.13
Aiolopus strepens 2.43 2.11 3.24 2.95 3.93 4.33
Dociostaurus jagoi 2.26 2.14 3.14 2.74 4.00 4.20
Calliptamus wattenwilianus 2.29 2.2 2.52 2.25 4.54 4.75
Ochrilidia harterti G1 2.39 3.04 2.67 3.33 4.14 3.25
Acrida turrita G1 3.38 3.33 2.72 3.38 3.50 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.
Table 5
Lag in the larval phenology in dominant species between Koléa and Soumàa.
Species name Number of
larvae recorded
Lag p-value
Koléa Soumàa 1991 1992 Wilcoxon
Acrotylus patruelis 113 119 0.64 0.25 0.48 NS
Aiolopus strepens 286 189 0.54 0.24 0.016 *
Dociostaurus jagoi 252 183 0.08 0.13 0.19 NS
Calliptamus wattenwilianus 73 39 0.02 0.08 0.40 NS
Ochrilidia harterti G1 192 224 0.72 0.19 0.028 *
Acrida turrita G1 99 42 0.51 0.20 0.067
A0.40 mean lag indicates that the phenology of larva stages is 0.4 month later in
Soumàa than in Koléa.
A. Guendouz-Benrima et al. / Journal of Arid Environments 75 (2011) 416e423420